Department of Electronics and Communication Engineering was established in the year 2002, with an intake of 60. The department has dedicated, qualified faculty members with various specializations. All the faculty members are Post graduates with outstanding teaching and research experience. The department has maintained a student staff ratio of 15:1. The department has excellent infrastructure with state of the art equipment and software tools. The department is having computer centre with over 70 computers catering to student needs. The department has a strong R & D culture. The faculty interact closely with alumni in academia and industry in India and abroad in order to make the programmes to meet the aspirations of different stake holders. ECE department is equipped with state of the CAD tools and equipment’s. UG and PG students are highly innovative and have participated in national level Contest, Seminars, Conference, Workshop.
The focus of the department is to produce graduates with strong fundamentals in electronics and communication domain. The department is the most sought after branch of engineering by top CET (conducted by Karnataka examination authority) rank holders and other aspirants. ECE department has an excellent academic and placement record which has been consistently above 80% . Alumni of ECE Dept of MSEC occupy key positions in industry and are successful as entrepreneurs. ECE department has a strong PhD programme. It offers innovative approaches for teaching-learning and encourages virtual learning in order to tap the potential of its highly successful alumni spread all over the globe. The Department has been successfully carrying sponsored research projects since its inception.
Welcome to the Department of Electronics & Communication Engineering. Today, we are better positioned than ever to address the greater challenges of the coming century. At the Department of ECE, we are putting knowledge to practice with innovations in critical areas of Electronics and Communication Engineering. We are a place where innovation is expected and our work today will impact our future lives in ways we cannot imagine. As Head of the Department, I can assure you, if you're interested in exploring and applying technology, you've come to the right place. Here you'll learn to think logically, deal with uncertainty and change, work with technology in a socially and environmentally responsible manner, communicate effectively and collaborate with bright students and eminent faculty, all within a supportive community.
Every student in the Department of ECE receives personalized attention and is supported through effective student support services including mentorship, peer-tutoring, advising, academic learning, internships, job placement, etc. We are proud of our near perfect student placement with a diverse set of industries. We must continue to provide outstanding talent for companies engaged in fiercely competitive global markets.
Faculty in our college are our real strength. They are highly accomplished in their field with a majority having professional licensure/certifications and industrial experience. We are committed to further enhancing the research interests of our faculty and engaging in outreach activities to provide the best response to regional needs.
During the past five years, the Department has been engaged in several high impact research initiatives in collaboration with various agencies and institutions such as DST, AICTE, VTU etc. The dedicated R&D Center at M S Engineering College encourages undergraduate students, post graduate students, research scholars and faculties to pursue research in their area of interest and participate in undergoing research activities. The outcome of the research carried out will lead to publications, patents and product development. Some of the ongoing research addresses issues in brain-computer interface, visual information processing, pollution monitoring, wireless sensing and networking, bio-inspired autonomous navigation, Underwater Communication, Biodegradable Products, Biomedical Engineering, Nanotechnology, Health Care Systems Engineering, etc. Driven by interdisciplinary collaboration and entrepreneurial spirit, our students and faculty form ventures that keep society productive, healthy and entertained. We continue to successfully commercialize intellectual property through invention disclosures, patents, and ultimately, startup companies.
Our student experience is enhanced by an alumni network of 5600 worldwide. Alumni are viewed as major stakeholders in collaborating with faculty, students and staffs in helping the Department accomplish its mission. The ECE Department Alumni Association is engaged in several initiatives geared toward helping students succeed in their academic and professional mission.
I hope you will take the time to explore and discover the Department through our website. As one of the fastest rising engineering programs in the state, the Department of Electronics and Communication Engineering at M S Engineering College looks to the future with a tremendous sense of optimism and anticipation to advance even further.
Dr. Venkateshappa
Professor & Head
Department of Electronics & Communication Engineering
M S Engineering College, Bangalore
An electronic and communications engineer is responsible for the design of electronics that drive the transmitter and receiver functions of any system transporting wireless or wired communications. A person with this job may work in the fields of computer networking, digital TV, satellite, radio or Internet technology.
The electronics and communications engineer creates the electronic circuitries that convert a voice or Internet message into pulses to send them through communications lines. This person's expertise in electronic design sets the performance level of the system, such as the clarity of the connection and the reach of the communication.
Scope of electronics and communication engineering or EC engineering is huge because modern technology uses electronics, chips, transistors, fibre optics etc and you know that an EC engineer deals with all of these. Scope of EC engineering is vast that it is applied in every field. The development of the world that includes every area such as telecommunication, satellite, microelectronics, technology etc are all based on electronics engineering. Electronics has also helped in developing health care, automation, signal processing etc.
Few fields of Electronics :
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<h4>Programe Offered</h4>
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$viewFile = '/usr/www/users/tao1/hareesh/msec/app/View/Departments/view.ctp' $dataForView = array( 'department' => array( 'Department' => array( 'id' => '2', 'user_id' => '4', 'name' => 'ECE', 'title' => 'Electronics and Communication Engineering', 'blog_link' => 'https://msececeonline.wordpress.com/', 'email' => 'hod.ece@msec.ac.in', 'home' => '<p style="text-align: justify; "><span style="line-height: 1.42857143;">Year of Inception: 2002 with an intake of 60, In the year 2007 enhanced to 120.</span><br></p><p style="text-align: justify;">The focus of the department is to produce graduates with strong fundamentals in electronics and communication domain. The course is an outcome based structured to help students to achieve this goal. The department is the most sought after branch of engineering by top CET (conducted by Karnataka examination authority) rank holders and other aspirants.</p><p style="text-align: justify;">The department has a total of 22 faculty members with various specializations. All the faculty members are Post graduates with outstanding teaching experience. The department has maintained a student staff ratio of 15:1. The department has excellent infrastructure with state of the art equipment and software tools. The department is having computer centre with over 150 computers catering to student needs. The department has a strong R & D culture.</p><p></p>', 'about' => '<div style="text-align: justify; "><p>Department of Electronics and Communication Engineering was established in the year 2002, with an intake of 60. <span style="line-height: 1.42857143;">The department has dedicated, qualified faculty members with various specializations. All the faculty members are Post graduates with outstanding teaching and research experience. The department has maintained a student staff ratio of 15:1. The department has excellent infrastructure with state of the art equipment and software tools. The department is having computer centre with over 70 computers catering to student needs. The department has a strong R & D culture.</span><span style="line-height: 1.42857143;"> The faculty interact closely with alumni in academia and industry in India and abroad in order to make the programmes to meet the aspirations of different stake holders. ECE department is equipped with state of the CAD tools and equipment’s. UG and PG students are highly innovative and have participated in national level Contest, Seminars, Conference, Workshop.</span></p><p><span style="line-height: 1.42857143;">The focus of the department is to produce graduates with strong fundamentals in electronics and communication domain. The department is the most sought after branch of engineering by top CET (conducted by Karnataka examination authority) rank holders and other aspirants. </span><span style="line-height: 1.42857143;">ECE department has an excellent academic and placement record which has been consistently above 80% . Alumni of ECE Dept of MSEC occupy key positions in industry and are successful as entrepreneurs. ECE department has a strong PhD programme. It offers innovative approaches for teaching-learning and encourages virtual learning in order to tap the potential of its highly successful alumni spread all over the globe. The Department has been successfully carrying sponsored research projects since its inception. </span></p><p><a href="http://www.msec.ac.in/files/ECE_ADMISSIONS.pdf" target="_blank" style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); background-color: rgb(255, 255, 255);"><span style="font-size: 18px; text-decoration: underline; font-style: italic;">Why to choose ECE @ M S Engineering College</span></a></p><p><span style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); font-size: 18px; text-decoration: underline; font-style: italic; background-color: rgb(255, 255, 255);"><a href="http://www.msec.ac.in/files/ECE_ADMISSIONS.pdf" target="_blank" style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); background-color: rgb(255, 255, 255);"><br></a></span><br></p></div>', 'vision_mission' => '<br class="Apple-interchange-newline"><div><span style="font-weight: bold;">VISION</span> </div><div>To equip students with strong technical knowledge by logical and innovative thinking in Electronics and Communication Engineering domain to meet expectations of the industry as well as society.</div><div><br></div><div><span style="font-weight: bold;">MISSION</span> </div><ul><li><span style="line-height: 1.42857143;">To educate a new generation of Electronics and Communication Engineers by providing them with a strong theoretical foundation, good design experience and exposure to research and development to meet ever-changing and ever demanding needs of the Electronic Industry in particular, along with IT & other inter disciplinary fields in general.</span></li><li><span style="line-height: 1.42857143;">Provide ethical and value based education by promoting activities addressing the societal needs</span></li><li><span style="line-height: 1.42857143;">To build up knowledge and skills of students to face the challenges across the globe with confidence and ease.</span></li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Educational Objectives (PEOs) </span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will achieve successful professional career in IT industry with the approach of lifelong learning.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will possess technical competency to design develop and solve engineering problems related to IT industry.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will attain the qualities of professional leadership to deliver effectively in multidisciplinary global working environment with professionalism and ethical values</li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Outcomes (POs)</span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Engineering Knowledge</b> Apply the knowledge of mathematics, science, engineering Fundamentals, and an engineering specialization to the solution of complex engineering problems. </li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Problem Analysis</b>: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Design/ Development of Solutions</b>: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Conduct Investigations of Complex Problems</b>: Use research-based knowledge and research design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Modern Tool Usage</b>: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>The Engineer and Society</b>: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Environment and Sustainability</b>:Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Ethics</b>: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Individual and Team Work</b>: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Communication</b>: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Project Management and Finance</b>: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Life-long learning</b>: To recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.</li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Specific Outcomes (PSOs)</span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">. </li></ul><div><div><span style="font-weight: bold;">QUALITY POLICY </span></div><div>Our quality policy is to develop an effective source of technical man power with the ability to adapt to an intellectually and technologically changing environment to contribute to the growth of nation with the participative efforts of the management, staff, students and industry while keeping up ethical and moral standards required.</div></div><div><br></div>', 'hod_message' => '<div class="media"> <p> <img 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" data-filename="image.png" style="width: 220px;"></p> <div class="media-body"><p style="text-align: justify;"></p><p style="text-align: justify;">Welcome to the Department of Electronics & Communication Engineering. Today, we are better positioned than ever to address the greater challenges of the coming century. At the Department of ECE, we are putting knowledge to practice with innovations in critical areas of Electronics and Communication Engineering. We are a place where innovation is expected and our work today will impact our future lives in ways we cannot imagine. As Head of the Department, I can assure you, if you're interested in exploring and applying technology, you've come to the right place. Here you'll learn to think logically, deal with uncertainty and change, work with technology in a socially and environmentally responsible manner, communicate effectively and collaborate with bright students and eminent faculty, all within a supportive community.<br></p><p style="text-align: justify;">Every student in the Department of ECE receives personalized attention and is supported through effective student support services including mentorship, peer-tutoring, advising, academic learning, internships, job placement, etc. We are proud of our near perfect student placement with a diverse set of industries. We must continue to provide outstanding talent for companies engaged in fiercely competitive global markets. </p><p style="text-align: justify;">Faculty in our college are our real strength. They are highly accomplished in their field with a majority having professional licensure/certifications and industrial experience. We are committed to further enhancing the research interests of our faculty and engaging in outreach activities to provide the best response to regional needs.</p><p style="text-align: justify;">During the past five years, the Department has been engaged in several high impact research initiatives in collaboration with various agencies and institutions such as DST, AICTE, VTU etc. The dedicated R&D Center at M S Engineering College encourages undergraduate students, post graduate students, research scholars and faculties to pursue research in their area of interest and participate in undergoing research activities. The outcome of the research carried out will lead to publications, patents and product development. Some of the ongoing research addresses issues in brain-computer interface, visual information processing, pollution monitoring, wireless sensing and networking, bio-inspired autonomous navigation, Underwater Communication, Biodegradable Products, Biomedical Engineering, Nanotechnology, Health Care Systems Engineering, etc. Driven by interdisciplinary collaboration and entrepreneurial spirit, our students and faculty form ventures that keep society productive, healthy and entertained. We continue to successfully commercialize intellectual property through invention disclosures, patents, and ultimately, startup companies.</p><p style="text-align: justify;">Our student experience is enhanced by an alumni network of 5600 worldwide. Alumni are viewed as major stakeholders in collaborating with faculty, students and staffs in helping the Department accomplish its mission. The ECE Department Alumni Association is engaged in several initiatives geared toward helping students succeed in their academic and professional mission.</p><p style="text-align: justify;">I hope you will take the time to explore and discover the Department through our website. As one of the fastest rising engineering programs in the state, the Department of Electronics and Communication Engineering at M S Engineering College looks to the future with a tremendous sense of optimism and anticipation to advance even further.</p><p style="text-align: justify;"><br></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Dr. Venkateshappa</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Professor & Head</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Department of Electronics & Communication Engineering</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">M S Engineering College, Bangalore</span></p><div style="text-align: justify;"><br></div><p style="text-align: justify;"><br></p> </div></div>', 'why_dept' => '<p style="text-align: justify; ">An electronic and communications engineer is responsible for the design of electronics that drive the transmitter and receiver functions of any system transporting wireless or wired communications. A person with this job may work in the fields of computer networking, digital TV, satellite, radio or Internet technology.</p><p style="text-align: justify; ">The electronics and communications engineer creates the electronic circuitries that convert a voice or Internet message into pulses to send them through communications lines. This person's expertise in electronic design sets the performance level of the system, such as the clarity of the connection and the reach of the communication.</p><p style="text-align: justify; ">Scope of electronics and communication engineering or EC engineering is huge because modern technology uses electronics, chips, transistors, fibre optics etc and you know that an EC engineer deals with all of these. Scope of EC engineering is vast that it is applied in every field. The development of the world that includes every area such as telecommunication, satellite, microelectronics, technology etc are all based on electronics engineering. Electronics has also helped in developing health care, automation, signal processing etc.</p><p>Few fields of Electronics :</p><ul><li>In medical field- Almost all medical equipments are electronic and hence for the installation and maintenance of those equipments.</li><li>In automobile- The speed dial, air bag systems etc are all based on electronics.</li><li>In modern equipments- For the production, maintenance and repair of computers, laptops, tabs, mobiles etc.</li><li>In communication- Radio,telephones etc.</li><li>In government and private companies- Installation, operation and maintenance of electronics equipments and systems.</li><li>Defence- For design and development of complex devices and systems for signal processing and telecommunication.</li><li>Space and other research organisations- For design and development of complex devices and systems for signal processing and telecommunication.</li><li>Electronic industries- Design and fabrication of devices, embedded systems, electronic equipments etc. </li><li>Process industries- For instrumentation and control of electronic devices.</li><li>IT companies- Well preferred as IT professionals.</li><li>Manufacturing- PCB, IC etc.</li></ul><div><br></div>', 'swot' => '<div class="row"><div class="col-md-6"><h5>STRENGTH</h5><ul><li>Upgraded Lab Infrastructure</li><li>Centre of Excellence in Under Water Communication </li><li>Faculty with industrial <span style="line-height: 1.42857143;">experience</span></li><li>Highly qualified faculty (03 Ph.Ds 08 pursuing Ph.D)</li><li>Well established R&D Centre. </li><li>Periodic Student counselling and training</li><li>Industry certified Lab<span class="Apple-tab-span" style="white-space:pre"> </span></li></ul></div><div class="col-md-6"><h5>WEAKNESS</h5><ul><li>Placement – department Interface </li><li>Industry –faculty interface</li></ul></div></div><div class="row"><div class="col-md-6"><h5>OPPORTUNITIES</h5><ul><li>More collaboration with industry </li><li>Students Internship</li><li>External Sponsorship for Research Activities </li><li>Enhancement of Curriculum</li></ul></div><div class="col-md-6"><h5>CHALLENGES</h5><ul><li>Retention of Faculty</li><li>Competition from Autonomous colleges</li><li>Fast Changing Technology</li></ul></div></div>', 'faculty' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Name</th><th>Qualification</th><th>Specialization</th><th>Designation</th><th>Profile</th></tr> </thead> <tbody> <tr><td>1</td><td>Dr. Cyril Prasanna Raj P.</td><td>M.Tech, PhD</td><td>VLSI Design and Image Processing</td><td>Prof. Dean R & D</td><td><a href="/files/ece/faculty/Cyril.pdf" target="_blank">View</a></td></tr> <tr><td>2</td><td>Dr. Venkateshappa</td><td>M.Tech, Ph.D</td><td>Power Electronics</td><td>Professor</td><td><a href="/files/ece/faculty/Venkateshappa.pdf" target="_blank">View</a></td></tr> <tr><td>3</td><td>Mrs. Sunitha P. H.</td><td>M.Tech, (Ph.D)</td><td>Industrial Electronics</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Sunitha.pdf" target="_blank">View</a></td></tr> <tr><td>4</td><td>Mrs. Tejaswini C.</td><td>M.Tech, (Ph.D)</td><td>Biomedical instrumentation</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Tejaswini.pdf" target="_blank">View</a></td></tr> <tr><td>5</td><td>Mrs. Azra jeelani</td><td>M.Tech, (Ph.D)</td><td>Electronics</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Azra.pdf" target="_blank">View</a></td></tr><tr><td>6</td><td>Mrs. Savitha S. C.</td><td>M.Tech</td><td>Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Savitha.pdf" target="_blank">View</a></td></tr> <tr><td>7</td><td>Mr. Nagayya S. Hiremath</td><td>M.Tech</td><td>Power Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Nagayya.pdf" target="_blank">View</a></td></tr> <tr><td>8</td><td>Mrs. Mangalagowri</td><td>M.Tech, (Ph.D)</td><td>VLSI and Embedded system</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Mangalagowri.pdf" target="_blank">View</a></td></tr> <tr><td>9</td><td>Ms. Azarathamma S.</td><td>M.Tech, (Ph.D)</td><td>VLSI Design</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Azarathamma.pdf" target="_blank">View</a></td></tr> <tr><td>10</td><td>Ms. Natya S.</td><td>ME,(Ph.D)</td><td>Control System</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Natya.pdf" target="_blank">View</a></td></tr> <tr><td>11</td><td>Ms. Sushma G. Vasu</td><td>M.Tech</td><td>VLSI and Embedded System</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Sushma.pdf" target="_blank">View</a></td></tr> <tr><td>12</td><td>Ms. Pavithra S. G.</td><td>M.Tech</td><td>Power Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Pavithra.pdf" target="_blank">View</a></td></tr> <tr><td>13<br></td><td>Mrs. Divya S. Dechamma</td><td>M.Tech</td><td>VLSI Design and Embedded system</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Divya.pdf" target="_blank">View</a></td></tr> <tr><td>14</td><td>Mr. Chaluvaraj</td><td>M.Tech</td><td>VLSI Design and Embedded system</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Chaluvaraj.pdf" target="_blank">View</a></td></tr> <tr><td>15</td><td>Mrs. Asha Rani N.</td><td>M.Tech,(Ph.D) </td><td>Bio Medical Signal Processing</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Asha.pdf" target="_blank">View</a></td></tr><tr><td>16</td><td>Ms.Rekha N.</td><td>M.Tech,(Ph.D) </td><td>Digital Electronics</td><td>Asst. Professor</td><td>View</td></tr> </tbody> </table>', 'labs' => '<div class="tabbable tabs-left clearfix"> <ul class="nav nav-tabs" id="myTab1"> <li class="active"> <a data-toggle="tab" href="#tab1" aria-expanded="true">Analog Electronics Circuit</a> </li> <li class=""> <a data-toggle="tab" href="#tab2" aria-expanded="false">Logic design Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab3" aria-expanded="false">Microcontroller Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab4" aria-expanded="false">HDL Lab</a> </li> <li> <a data-toggle="tab" href="#tab5">Analog Communication Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab6" aria-expanded="false">DSP Lab</a> </li> <li> <a data-toggle="tab" href="#tab7">Advanced Communication Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab8" aria-expanded="false">Microprocessor Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab9">VLSI Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab10" aria-expanded="false">Power Electronics Lab</a> </li> </ul> <div class="tab-content" id="myTabContent"> <div class="tab-pane fade active in" id="tab1"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/1.jpg"></p> <h4>Analog Electronics Circuit</h4> <p class="text-justify">Analog Electronics lab provides basic knowledge of electronic devices like diodes, transistors, and elementary circuits. This lab includes various kits like characteristics of diode, transistor, TRIAC. DIAC, FET etc</p> </div> </div> <div class="tab-pane fade" id="tab2"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/2.jpg"></p> <h4>Logic design Lab</h4> <p class="text-justify">Logic design lab is very useful for the students for realising the logic circuits like counters, multiplexer ,adders , sequence generator etc. In this lab major equipment used are Digital IC trainer kit , Digital IC tester. The logic design lab helps students to understand basic digital components and its application</p> </div> </div> <div class="tab-pane fade" id="tab3"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/3.jpg" style="width: 530px; height: 385.877192982456px;"></p> <h4>Microcontroller Lab</h4> <p class="text-justify">The most widely used instruction set for 8-bit microcontrollers (MCUs), the 8051 core has a long history and a tremendous, widely used code base. This lab introduces students to the elementary programming techniques, interfacing and designingsimple applications using microcontroller 8051</p> </div> </div> <div class="tab-pane fade" id="tab4"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/4.jpg"></p> <h4>HDL Lab</h4> <p class="text-justify">Hardware Description language students will be able to analyze and evaluate VHDL & Verilog concepts. They are capable of designing and creating test with their complex system components. First implement an encryption algorithm using a standard hardware description language; then wrap the security module as a peripheral attached to bus; design an interface between peripheral and bus; apply an FPGA design flow for VLSI</p> </div> </div> <div class="tab-pane fade" id="tab5"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/5.jpg"></p> <h4>Analog Communication Lab</h4> <p class="text-justify">Advance Communication lab provides Basic knowledge on multiple duplexing ex, TDMA, FDMA and advance communication techniques. Modulation and Demodulation techniques for long distance channel with low power transmission.</p> </div> </div> <div class="tab-pane fade" id="tab6"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/6.jpg"></p> <h4><br></h4><h4>DSP Lab</h4> <p class="text-justify">To give students an introduction to real-time DSPrequirements by exposing them to the use of someeducational DSP kits with realtime capability, which will help them get acquainted with the programming of theses devices and some typical hardware and functions found in practical applications such as I/O interface cards (A/D, D/A, I/O filters), types of DSP processors and their different characteristics, interrupts, etc.</p> </div> </div> <div class="tab-pane fade" id="tab7"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/7.jpg"></p> <h4>Advanced Communication Lab</h4> <p class="text-justify">Digital Communication Lab provides practical knowledge on FSK, ASK, etc. The goal of this lab is to understand a simple modem, the Frequency Shift Keying (FSK) Modem, referred to by the International Telecommunications Union (I.T.U.)</p> </div> </div> <div class="tab-pane fade" id="tab8"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/8.jpg" style="width: 580px; height: 441.41592920354px;"></p> <h4>Microprocessor Lab</h4> <p class="text-justify">Microprocessor lab introduces the student with 8/16 bit microprocessor 8086. In this lab students will get exposed to basic instruction set, Architecture of 8086 , Addressing mode , Editing , Debugging the software programs like Data movement, Logical and arithmetic , Loop and branch , interrupt programming etc. The students get knowledge about interfacing the hardware kits like stepper motor, logic controller , display , Keyboard with 8086 Microprocessor.</p> </div> </div> <div class="tab-pane fade" id="tab9"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/9.jpg"></p> <h4>VLSI Lab</h4> <p class="text-justify">VlSI Lab provides the student basic VlSI design concepts using CAD tool called cadence. Creating Verilog code for digital system and verify by using test bench also how to design analog circuits and layout for it. Verifying layout using DRC and LVS check. The students will get expose to industry handled tool and real time projects.</p> </div> </div> <div class="tab-pane fade" id="tab10"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/10.jpg"></p> <h4>Power Electronics Lab</h4> <p class="text-justify">Power electronics lab gives the idea of characteristic features high power semiconductor devices like SCR,MOSFET and IGBT. This lab syllabus discuss about the converters, inverters and motors like DC motor, Universal motor and stepper motor. Experiments are conducted on triggering circuits like UJT and RC triggering circuits.</p> </div> </div> </div></div>', 'research' => '<div class="accordion"><div class="panel-group" id="accordion1"><div class="panel panel-default"><div class="panel-heading active"><h3 class="panel-title"><a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseOne1" aria-expanded="false">Performance Analysis of High Speed Low Power DWT Architectures for Image Fusion/ Registration/ Compression algorithms for Micro Air Vehicle Applications. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseOne1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Venkateshappa Guide : Dr. Cyril Prasanna Raj P.</h4><h4><img 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" data-filename="7.jpg" style="width: 260px; height: 204.347826086957px;"><br></h4> <p class="text-justify">Home land security, border security, remote sensing, surveillance and tracking are some of the primary application areas where micro air vehicles play a vital role. Due to geographical challenges, rough terrains and unpredictable environments and climatic conditions humans beings are finding it difficult to monitor and provide security across the border as well as within home land. Use of micro air vehicles are the only possible solutions in near future. </p> <p class="text-justify">Cameras that are mounted on micro air vehicles reduces payload and eliminates multiple sensors. However images/video sequences captured occupy huge bandwidth and hence need to be compressed and transmitted to base station for processing. As MAVs need to operate in day light and night conditions, IR cameras and thermal cameras along with visible light camera is used to acquire data. The acquired data is compressed and transmitted to the base station, at the base station the image registration and fusion is performed to extract information for monitoring and control.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseTwo1" aria-expanded="false"> Design, modeling and VLSI implementation of low power high speed wavelet based 3D architectures for image registration. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseTwo1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Sunitha P. H. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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" data-filename="8.jpg" style="width: 314px;"><br></h4> <p class="text-justify">With the growth in VLSI technology leading to nanometer transistors 3D VLSI IC technology is gaining momentum for high speed and low power signal and image processing applications. Medical imaging and aerial imaging are the major applications where 3D imaging plays an important role with image registration. In this research work, 3D architectures that are parallel, pipelined and systolic architectures are analyzed for their performances. Image registration algorithms that are used for 3D images are also analyzed for their performances, suitable algorithms for image registration based on Wavelet Transform approaches will be identified and implemented using 3D architectures optimizing for area, power and speed performances. </p> <p class="text-justify">Image registration helps physicians monitor the progress of cancerous tissue. Better registration techniques could give physicians new and more effective ways of monitoring and treating the millions of patients suffering from cancer. Also, image registration would be useful for more precise targeting of radiation therapy against tumors. Better image registration could also lead to improvements in image-guided surgery – a surgical procedure where the surgeon uses indirect visualization to operate. . Turning this data into information requires image registration to be accurate enough to consistently compare images across time and modalities.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseThree1" aria-expanded="false"> Design, Modeling and Performance Analysis of Novel Algorithms for EEG Based Brain Computer Interface for Paralytic Patients. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseThree1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Tejaswini C. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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" data-filename="9.jpg" style="width: 314px;"><br></h4> <p class="text-justify">Paralytic patients are also called as “locked-in” patients. Because of a stroke, traumatic brain injury, cerebral palsy or a degenerative neurological disease such as amyotrophic lateral sclerosis, their entire motor system is paralyzed. These patients are fully conscious and alert, but are unable to use their muscles; they are therefore unable to communicate their needs, wishes and emotions. In these patients a healthy brain is actually locked into a paralyzed body. There is no cure, and the cause of amyotrophic lateral sclerosis, one of the major causes of locked-in syndrome, is still unknown.</p> <p class="text-justify">This research aims to investigate intelligent systems which facilitate development of assistive robotic device for people with severe movement disability such as in locked-in patients. The project objective investigates a brain-computer interface (BCI) that allows a paralytic patient person to control robotic devices by thought alone. The research primarily involves developing advanced signal processing algorithms to extract information from BCI tasks-related electroencephalogram (EEG), commonly known as brain-waves, and requires investigations into signal pre-processing, feature extraction and classification aspects using innovative statistical methods and computational intelligence approaches. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseFour1" aria-expanded="false"> VLSI Implementation of Low Power MB-OFDM PHY Base band Modem for Wireless Sensor Network. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseFour1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Naveen H. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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data-filename="10.jpg" style="width: 314px;"><br></h4> <p class="text-justify">Efficient design and implementation of wireless sensor networks has become a hot area of research in recent years, due to the vast potential of sensor networks to enable applications that connect the physical world to the virtual world. WSNs are usually composed of small, low cost devices that communicate wirelessly and have the capabilities of processing, sensing and storing By networking large numbers of tiny sensor nodes, it is possible to obtain data about physical phenomena that was difficult or impossible to obtain in more conventional ways. In the coming years, as advances in micro-fabrication technology allow the cost of manufacturing sensor nodes to continue to drop, increasing deployments of wireless sensor networks are expected, with the networks eventually growing to large numbers of nodes. </p> <p class="text-justify">Wireless sensor networks are emerging as one of the most challenging technologies to meet the communication requirements and data monitoring requirements in several time critical applications. Recently ITU has proposed new set of protocols for wireless sensor networks and road map indicates that in another few years there will be high data rate and data transfer over wireless sensor networks. Software implementation and validation have been successfully accomplished by many of the researchers for demonstration of WSN capabilities. However, for real time implementation and practical purpose there is a need for hardware platforms. In this work, two major research activities are taken up:</p> <ol> <li>Design and modeling of MB-OFDM UWB physical layer for high data rate and development of novel algorithms for hardware implementation</li> <li>Design and implementation of novel architectures for the proposed MB-OFDM UWB on hardware platforms</li> </ol> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseFive1" aria-expanded="false"> Design, Modeling and FPGA Implementation of Robust Noise Filtering Algorithms for Under Water Imaging Applications. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseFive1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Azra Jeelani Guide : Dr. Veena M. B.</h4> <p class="text-justify"><img src="data:image/jpeg;base64,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" data-filename="11.jpg" style="width: 313px;"><br></p><p class="text-justify">A total 3, 90,884 accidental deaths were reported in the country during the year 2011. A total of 6, 94,390 cases of Un-Natural Accidents have caused 3, 67,194 deaths and rendered 5, 06,348 people injured during 2011. The major un-natural causes of accidental deaths were Road Accidents (37.3%), Railway Accidents and Rail-Road Accidents (7.6%), Poisoning (8.0%), Drowning (8.1%), Sudden Deaths (7.3%) and Fire Accidents (6.7%). 29708 deaths have occurred during the year 2011 due to drowning (boat capsize). Recovering the bodies from the deep water is a herculean task, as trained divers are required to dive deep into the water, identify the body, and carefully remove the body from the bottom. Currently there are very limited solutions to detect the body without diving into the waterfront. Divers need to swim underneath the water and with trial and error locates the bodies and recover them.</p> <p class="text-justify">In this research work, we propose a through water imaging equipment that can scan the water front in defined areas and generates images of the water bed indicating the location of drowned bodies. In order to achieve higher performance and reliability an array of sonar signals are transmitted and received. The received signals are processed to generate images, using which human bodies are detected. The received signals need to be preprocessed before information retrieval could happen. Noise plays an important role in distorting the underwater images. One of the major source of noise is the speckle noise, that need to be filtered from sonar images.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseSix1" aria-expanded="false"> Digital UWB Through Wall Imaging for Human Body Motion Detection on VLSI Platform. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseSix1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Vinod Kumar B. L. Guide : Dr. Cyril Prasanna Raj P.</h4> <p class="text-justify"><img 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data-filename="12.jpg" style="width: 287px;"><br></p><p class="text-justify">Through-the-Wall radar imaging (TWRI) is emerging as a viable technology for providing high quality imagery of enclosed structures. The ability to locate moving targets inside a building with a sensor situated at standoff range outside the building would greatly improve situational awareness on the urban battlefield.</p> <p class="text-justify">Through wall imaging technique is required for time critical applications such as disaster management, rescue operations and terrorist tracking behind walls. Micro air vehicles are found to be used as mobile surveillance unit to track terrorists hiding. Detection of human motion behind walls needs to be carried out within few microseconds or milliseconds. TWI techniques are mostly software oriented and hence there is a need for SoC that can process data and retrieve information in real time. In this work, novel algorithms will be developed to identify human motion behind walls and suitable architectures designed for high speed data processing. In the proposed research work, the architecture shown in Figure 2 is modified for human body detection in motion using digital UWB. The modified algorithm will be implemented on FPGA for time critical applications.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseSeven1" aria-expanded="false"> EEG Based Emotion Detection and Classification Using Multiwavelets and Neural Networks. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseSeven1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Mangalagowri S. G. Guide : Dr. Cyril Prasanna Raj P.</h4> <p class="text-justify"><img src="data:image/jpeg;base64,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" data-filename="14.jpg" style="width: 314px;"><br></p><p class="text-justify">The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.</p> <p class="text-justify">Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.</p> <p class="text-justify">It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseEight1" aria-expanded="false"> VLSI Implementation of Brain Computer Interface. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseEight1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Azarathamma S. <span style="line-height: 1.1;">Guide : Dr. Cyril Prasanna Raj P.</span></h4> <p class="text-justify"><img 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" data-filename="18.jpg" style="width: 235px;"><br></p><p class="text-justify">The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.</p> <p class="text-justify">Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.</p> <p class="text-justify">It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle" data-toggle="collapse" data-parent="#accordion1" href="#collapseNine1" aria-expanded="true"> Design and Analysis of Bioinspired Motion Detection and Velocity Estimation Algorithm and Architecture for Autonomous Navigation of Mavs. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseNine1" class="panel-collapse collapse in" aria-expanded="true"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div><div class="pull-left"> </div> <div class="media-body"> <h4></h4> <p class="text-justify"><br></p><p class="text-justify">Highly accurate real-time stabilization and navigation of UGVs, MAVs, humanoids and vehicles is a major research focus of robotics and automation. Research on autonomous navigation and guidance is influenced by the anatomy of insect’s eyes. A fly’s panoramic vision system comprises at its front end several thousand photoreceptors feeding into a 2D array of motion detecting neurons which the animal uses for dynamic visuo-motor pose and gaze stabilization and navigation. Insects such as fly possess a visual system that is fast, precise and reliable hence, they are able to execute flawless landing on the rim of a container, instantaneously avoid obstacles while flying.</p> <p class="text-justify">Insects have immobile eyes with fixed-focus optics, the eyes are also positioned very close hence possess inferior spatial acuity. The behavior of flying insects is dominated by visual control and hence insects use visual feedback to stabilize flight, control speed and measure self motion. Highly accurate real-time stabilization and navigation of UGVs of MAVs is major research interest as these systems are used for surveillance, security, search and rescue mission. Thus design, modeling and implementation of Bioinspired visual system on UGVs and MAVs could be an accessible methodology to replace the traditional image processing algorithms in controlling flying robots.</p> </div> </div> </div> </div> </div> </div><!--/#accordion1--> </div>', 'workshop_seminars' => '<p></p><p><br></p><thread></thread><table class="table table-bordered table-striped" style="line-height: 1.42857;"><tbody><tr><th><span style="font-family: Times New Roman;">Sl No</span></th><th><span style="font-family: Times New Roman;">Name</span></th><th><span style="font-family: Times New Roman;">Funding Agency</span></th><th><span style="font-family: Times New Roman;">Date</span></th></tr><tr><td><span style="font-family: Times New Roman;">1</span></td><td><span style="font-family: Times New Roman;">2nd National Conference on Emerging Trends in Engineering Technology and Applied Research</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 13th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">2</span></td><td><span style="font-family: Times New Roman;">Project Exhibition </span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 13th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">3</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest lecture on Advanced Microprocessor Programming </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 3rd 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">4</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Workshop on Microsoft Day –Future Technologies </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Apr 4th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">5</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Smart Ways of Cracking Competitive Examination </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"><span style="background-color: rgb(249, 249, 249);">Mar 30th 2016</span><br></span></td></tr><tr><td><span style="font-family: Times New Roman;">6</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Carrier Options in Electronic industries</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Mar 9th 2016<br></span></td></tr><tr><td><span style="font-family: Times New Roman;">7</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Industrial Visit to Keltron, Trivandrum, Kerala </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"><span style="background-color: rgb(249, 249, 249);">Mar 5th 2016</span><br></span></td></tr><tr><td><span style="font-family: Times New Roman;">8</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Workshop on Industrial Automation using PLC and SCADA</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Mar 2nd 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">9</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Optical Fiber Transmission System</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Feb 17th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">10</span></td><td><span style="font-family: Times New Roman;">Emerging Trends in Engineering Technology and Applied Research(NCETAR-15)</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">July 10th 2015</span></td></tr><tr><td><span style="font-family: Times New Roman;">11</span></td><td><span style="font-family: Times New Roman;">Embedded System Development using ARM Cortex M3MSET/SIMS</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">30 & 31 Oct, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">12</span></td><td><span style="font-family: Times New Roman;">Empower 10,000 VLSI Design Course VTU<br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Sept 2014 to Nov 2014 </span></td></tr><tr><td><span style="font-family: Times New Roman;">13</span></td><td><span style="font-family: Times New Roman;">Embedded System Design <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">9 April, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">14</span></td><td><span style="font-family: Times New Roman;">Research Process, Technical Paper Writing and Patenting <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">22 - 24 jan, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">15</span></td><td><span style="font-family: Times New Roman;">Empower 10,000 Embedded System Design Course <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">1 Dec, 2013 to 9 Mar</span></td></tr><tr><td><span style="font-family: Times New Roman;">16</span></td><td><span style="font-family: Times New Roman;">First State Level Project Competition cum Exhibition <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">10 May,2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">17</span></td><td><span style="font-family: Times New Roman;">FPGA for signal and image processing Applications <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">7 - 9, feb 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">18</span></td><td><span style="font-family: Times New Roman;">Recent Trends in Nano/MEMS Technologies DST</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">7 & 8, Oct 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">19</span></td><td><span style="font-family: Times New Roman;">VLSI Design Lab using Open Source EDA Tool <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"> 24 & 25, July 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">20<br></span></td><td><span style="font-family: Times New Roman;">VLSI System on Chip Design & Validation <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">10 - 13, July 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">21</span></td><td><span style="font-family: Times New Roman;">Towards VLSI <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"> 6 & 7, may 2009 </span></td></tr></tbody></table><p></p><p><br></p><p><br></p><p> </p><p></p>', 'placements' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Year</th><th>Name</th><th>Company</th></tr> </thead> <tbody> <tr><td>1</td><td>2011-12</td><td>Sunil kumar</td><td>L&T Infotech</td></tr> <tr><td>2</td><td>2011-12</td><td>V. S. Sudha</td><td>L&T Infotech</td></tr> <tr><td>3</td><td>2011-12</td><td>Praveena C. K.</td><td>Dell International</td></tr> <tr><td>4</td><td>2011-12</td><td>Karthika S.</td><td>Unisys Global services Ltd</td></tr> <tr><td>5</td><td>2013-14</td><td>Shruthi R.</td><td>24/7 Customer Ltd</td></tr> <tr><td>6</td><td>2013-14</td><td>Arun A. T.</td><td>HCL Technologies</td></tr> <tr><td>7</td><td>2014-15</td><td>Meghana Halkude</td><td>Good Through</td></tr> <tr><td>8</td><td>2014-15</td><td>Akash Roy</td><td>Microland</td></tr> <tr><td>9</td><td>2014-15</td><td>Akarshitha Shekar</td><td>Microland</td></tr> <tr><td>10</td><td>2014-15</td><td>Jane Karen</td><td>IBM</td></tr> </tbody> </table>', 'testimonials' => '<div class="media"> <div class="media-left"> <a href="#"> </a> <a href="#"><img class="media-object img-circle" src="/files/ece/testimonials/1.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Joshua James</h5><p>I am the student of the college ..i am truly fortunate enough to be a part of MSEC educational institute …the ECE department is brilliantly splendid the conceptual and teaching capability of faculty is unparalled….the labs of the institute provide first hand knowledge of the theoretical matters…the support and guidance of the teachers and the department is truly praise worthy….i recommend MSEC for all those who don’t comprise anything less than the Best</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/2.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Rahul G.</h5><p>I am the student of the college m s engineering college, it’s a great honour to be the student of msec.. this institution enhances the thinking out of the box capability.. we have a very good support from R&d to make a innovative project.. our faculties are supportive in every way to make us a better engineers…</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/3.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Latha A.</h5><p>I the student of M. S. Engineering College very glad to do my graduation here.As all the facilities provided by college is extremely good. And I am very impressed of the college’s environment provided with greenery. All the faculties in this college are very supportive towards the students.</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/4.jpg" alt="..."> </a> </div> <div class="media-body"><h5>J. Supraja</h5><p>Being proud of saying I am a student of M.S.ENGG coll I would like to say that studying in a environment like would surely bring success for future it has been my privilege to tell that the lectures of my department are the best of all creativity along with knowledge and dedication I think there is no difference between the teachers kids and us.</p> </div></div>', 'alumni' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Batch</th><th>Alumini List</th></tr> </thead> <tbody> <tr><td>1</td><td>2007-2011</td><td><a href="/files/ece/alumni/Alumni2010.pdf" target="_blank">View</a></td></tr> <tr><td>2</td><td>2008-2012</td><td><a href="/files/ece/alumni/Alumni2012.pdf" target="_blank">View</a></td></tr> <tr><td>3</td><td>2009-2013</td><td><a href="/files/ece/alumni/Alumni2013.pdf" target="_blank">View</a></td></tr> <tr><td>4</td><td>2010-2014</td><td><a href="/files/ece/alumni/Alumni2014.pdf" target="_blank">View</a></td></tr> <tr> </tr></tbody> </table>', 'contact' => '<address> <h5><span style="font-weight: bold; font-size: 14px;">Dr. Venkateshppa</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Professor & Head</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Department of Electronics & Communication Engineering</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">M S Engineering College, Bangalore</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Email: hod.ece@msec.ac.in</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Ph: +91-9980261535</span></h5> <div><br></div> </address>', 'created' => '2015-06-18 03:30:05', 'modified' => '2020-10-14 08:32:20' ), 'User' => array( 'password' => '*****', 'id' => null, 'username' => null, 'email' => null, 'role' => null, 'created' => null, 'modified' => null ) ), 'title_for_layout' => 'Electronics and Communication Engineering' ) $department = array( 'Department' => array( 'id' => '2', 'user_id' => '4', 'name' => 'ECE', 'title' => 'Electronics and Communication Engineering', 'blog_link' => 'https://msececeonline.wordpress.com/', 'email' => 'hod.ece@msec.ac.in', 'home' => '<p style="text-align: justify; "><span style="line-height: 1.42857143;">Year of Inception: 2002 with an intake of 60, In the year 2007 enhanced to 120.</span><br></p><p style="text-align: justify;">The focus of the department is to produce graduates with strong fundamentals in electronics and communication domain. The course is an outcome based structured to help students to achieve this goal. The department is the most sought after branch of engineering by top CET (conducted by Karnataka examination authority) rank holders and other aspirants.</p><p style="text-align: justify;">The department has a total of 22 faculty members with various specializations. All the faculty members are Post graduates with outstanding teaching experience. The department has maintained a student staff ratio of 15:1. The department has excellent infrastructure with state of the art equipment and software tools. The department is having computer centre with over 150 computers catering to student needs. The department has a strong R & D culture.</p><p></p>', 'about' => '<div style="text-align: justify; "><p>Department of Electronics and Communication Engineering was established in the year 2002, with an intake of 60. <span style="line-height: 1.42857143;">The department has dedicated, qualified faculty members with various specializations. All the faculty members are Post graduates with outstanding teaching and research experience. The department has maintained a student staff ratio of 15:1. The department has excellent infrastructure with state of the art equipment and software tools. The department is having computer centre with over 70 computers catering to student needs. The department has a strong R & D culture.</span><span style="line-height: 1.42857143;"> The faculty interact closely with alumni in academia and industry in India and abroad in order to make the programmes to meet the aspirations of different stake holders. ECE department is equipped with state of the CAD tools and equipment’s. UG and PG students are highly innovative and have participated in national level Contest, Seminars, Conference, Workshop.</span></p><p><span style="line-height: 1.42857143;">The focus of the department is to produce graduates with strong fundamentals in electronics and communication domain. The department is the most sought after branch of engineering by top CET (conducted by Karnataka examination authority) rank holders and other aspirants. </span><span style="line-height: 1.42857143;">ECE department has an excellent academic and placement record which has been consistently above 80% . Alumni of ECE Dept of MSEC occupy key positions in industry and are successful as entrepreneurs. ECE department has a strong PhD programme. It offers innovative approaches for teaching-learning and encourages virtual learning in order to tap the potential of its highly successful alumni spread all over the globe. The Department has been successfully carrying sponsored research projects since its inception. </span></p><p><a href="http://www.msec.ac.in/files/ECE_ADMISSIONS.pdf" target="_blank" style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); background-color: rgb(255, 255, 255);"><span style="font-size: 18px; text-decoration: underline; font-style: italic;">Why to choose ECE @ M S Engineering College</span></a></p><p><span style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); font-size: 18px; text-decoration: underline; font-style: italic; background-color: rgb(255, 255, 255);"><a href="http://www.msec.ac.in/files/ECE_ADMISSIONS.pdf" target="_blank" style="line-height: 1.42857; font-weight: bold; color: rgb(206, 0, 0); background-color: rgb(255, 255, 255);"><br></a></span><br></p></div>', 'vision_mission' => '<br class="Apple-interchange-newline"><div><span style="font-weight: bold;">VISION</span> </div><div>To equip students with strong technical knowledge by logical and innovative thinking in Electronics and Communication Engineering domain to meet expectations of the industry as well as society.</div><div><br></div><div><span style="font-weight: bold;">MISSION</span> </div><ul><li><span style="line-height: 1.42857143;">To educate a new generation of Electronics and Communication Engineers by providing them with a strong theoretical foundation, good design experience and exposure to research and development to meet ever-changing and ever demanding needs of the Electronic Industry in particular, along with IT & other inter disciplinary fields in general.</span></li><li><span style="line-height: 1.42857143;">Provide ethical and value based education by promoting activities addressing the societal needs</span></li><li><span style="line-height: 1.42857143;">To build up knowledge and skills of students to face the challenges across the globe with confidence and ease.</span></li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Educational Objectives (PEOs) </span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will achieve successful professional career in IT industry with the approach of lifelong learning.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will possess technical competency to design develop and solve engineering problems related to IT industry.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">Graduates will attain the qualities of professional leadership to deliver effectively in multidisciplinary global working environment with professionalism and ethical values</li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Outcomes (POs)</span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Engineering Knowledge</b> Apply the knowledge of mathematics, science, engineering Fundamentals, and an engineering specialization to the solution of complex engineering problems. </li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Problem Analysis</b>: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Design/ Development of Solutions</b>: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Conduct Investigations of Complex Problems</b>: Use research-based knowledge and research design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Modern Tool Usage</b>: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>The Engineer and Society</b>: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Environment and Sustainability</b>:Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Ethics</b>: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Individual and Team Work</b>: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Communication</b>: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"> <b>Project Management and Finance</b>: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.</li><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;"><b>Life-long learning</b>: To recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.</li></ul><h5><span style="font-size: 14px; font-weight: bold;">Program Specific Outcomes (PSOs)</span></h5><ul><li style="color: rgb(51, 51, 51);font-family: Calibri, sans-serif; font-size: 14px;">. </li></ul><div><div><span style="font-weight: bold;">QUALITY POLICY </span></div><div>Our quality policy is to develop an effective source of technical man power with the ability to adapt to an intellectually and technologically changing environment to contribute to the growth of nation with the participative efforts of the management, staff, students and industry while keeping up ethical and moral standards required.</div></div><div><br></div>', 'hod_message' => '<div class="media"> <p> <img 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" data-filename="image.png" style="width: 220px;"></p> <div class="media-body"><p style="text-align: justify;"></p><p style="text-align: justify;">Welcome to the Department of Electronics & Communication Engineering. Today, we are better positioned than ever to address the greater challenges of the coming century. At the Department of ECE, we are putting knowledge to practice with innovations in critical areas of Electronics and Communication Engineering. We are a place where innovation is expected and our work today will impact our future lives in ways we cannot imagine. As Head of the Department, I can assure you, if you're interested in exploring and applying technology, you've come to the right place. Here you'll learn to think logically, deal with uncertainty and change, work with technology in a socially and environmentally responsible manner, communicate effectively and collaborate with bright students and eminent faculty, all within a supportive community.<br></p><p style="text-align: justify;">Every student in the Department of ECE receives personalized attention and is supported through effective student support services including mentorship, peer-tutoring, advising, academic learning, internships, job placement, etc. We are proud of our near perfect student placement with a diverse set of industries. We must continue to provide outstanding talent for companies engaged in fiercely competitive global markets. </p><p style="text-align: justify;">Faculty in our college are our real strength. They are highly accomplished in their field with a majority having professional licensure/certifications and industrial experience. We are committed to further enhancing the research interests of our faculty and engaging in outreach activities to provide the best response to regional needs.</p><p style="text-align: justify;">During the past five years, the Department has been engaged in several high impact research initiatives in collaboration with various agencies and institutions such as DST, AICTE, VTU etc. The dedicated R&D Center at M S Engineering College encourages undergraduate students, post graduate students, research scholars and faculties to pursue research in their area of interest and participate in undergoing research activities. The outcome of the research carried out will lead to publications, patents and product development. Some of the ongoing research addresses issues in brain-computer interface, visual information processing, pollution monitoring, wireless sensing and networking, bio-inspired autonomous navigation, Underwater Communication, Biodegradable Products, Biomedical Engineering, Nanotechnology, Health Care Systems Engineering, etc. Driven by interdisciplinary collaboration and entrepreneurial spirit, our students and faculty form ventures that keep society productive, healthy and entertained. We continue to successfully commercialize intellectual property through invention disclosures, patents, and ultimately, startup companies.</p><p style="text-align: justify;">Our student experience is enhanced by an alumni network of 5600 worldwide. Alumni are viewed as major stakeholders in collaborating with faculty, students and staffs in helping the Department accomplish its mission. The ECE Department Alumni Association is engaged in several initiatives geared toward helping students succeed in their academic and professional mission.</p><p style="text-align: justify;">I hope you will take the time to explore and discover the Department through our website. As one of the fastest rising engineering programs in the state, the Department of Electronics and Communication Engineering at M S Engineering College looks to the future with a tremendous sense of optimism and anticipation to advance even further.</p><p style="text-align: justify;"><br></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Dr. Venkateshappa</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Professor & Head</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">Department of Electronics & Communication Engineering</span></p><p style="text-align: justify;"><span style="font-family: 'Times New Roman', serif; font-size: 16px; font-weight: bold; line-height: 18.4px;">M S Engineering College, Bangalore</span></p><div style="text-align: justify;"><br></div><p style="text-align: justify;"><br></p> </div></div>', 'why_dept' => '<p style="text-align: justify; ">An electronic and communications engineer is responsible for the design of electronics that drive the transmitter and receiver functions of any system transporting wireless or wired communications. A person with this job may work in the fields of computer networking, digital TV, satellite, radio or Internet technology.</p><p style="text-align: justify; ">The electronics and communications engineer creates the electronic circuitries that convert a voice or Internet message into pulses to send them through communications lines. This person's expertise in electronic design sets the performance level of the system, such as the clarity of the connection and the reach of the communication.</p><p style="text-align: justify; ">Scope of electronics and communication engineering or EC engineering is huge because modern technology uses electronics, chips, transistors, fibre optics etc and you know that an EC engineer deals with all of these. Scope of EC engineering is vast that it is applied in every field. The development of the world that includes every area such as telecommunication, satellite, microelectronics, technology etc are all based on electronics engineering. Electronics has also helped in developing health care, automation, signal processing etc.</p><p>Few fields of Electronics :</p><ul><li>In medical field- Almost all medical equipments are electronic and hence for the installation and maintenance of those equipments.</li><li>In automobile- The speed dial, air bag systems etc are all based on electronics.</li><li>In modern equipments- For the production, maintenance and repair of computers, laptops, tabs, mobiles etc.</li><li>In communication- Radio,telephones etc.</li><li>In government and private companies- Installation, operation and maintenance of electronics equipments and systems.</li><li>Defence- For design and development of complex devices and systems for signal processing and telecommunication.</li><li>Space and other research organisations- For design and development of complex devices and systems for signal processing and telecommunication.</li><li>Electronic industries- Design and fabrication of devices, embedded systems, electronic equipments etc. </li><li>Process industries- For instrumentation and control of electronic devices.</li><li>IT companies- Well preferred as IT professionals.</li><li>Manufacturing- PCB, IC etc.</li></ul><div><br></div>', 'swot' => '<div class="row"><div class="col-md-6"><h5>STRENGTH</h5><ul><li>Upgraded Lab Infrastructure</li><li>Centre of Excellence in Under Water Communication </li><li>Faculty with industrial <span style="line-height: 1.42857143;">experience</span></li><li>Highly qualified faculty (03 Ph.Ds 08 pursuing Ph.D)</li><li>Well established R&D Centre. </li><li>Periodic Student counselling and training</li><li>Industry certified Lab<span class="Apple-tab-span" style="white-space:pre"> </span></li></ul></div><div class="col-md-6"><h5>WEAKNESS</h5><ul><li>Placement – department Interface </li><li>Industry –faculty interface</li></ul></div></div><div class="row"><div class="col-md-6"><h5>OPPORTUNITIES</h5><ul><li>More collaboration with industry </li><li>Students Internship</li><li>External Sponsorship for Research Activities </li><li>Enhancement of Curriculum</li></ul></div><div class="col-md-6"><h5>CHALLENGES</h5><ul><li>Retention of Faculty</li><li>Competition from Autonomous colleges</li><li>Fast Changing Technology</li></ul></div></div>', 'faculty' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Name</th><th>Qualification</th><th>Specialization</th><th>Designation</th><th>Profile</th></tr> </thead> <tbody> <tr><td>1</td><td>Dr. Cyril Prasanna Raj P.</td><td>M.Tech, PhD</td><td>VLSI Design and Image Processing</td><td>Prof. Dean R & D</td><td><a href="/files/ece/faculty/Cyril.pdf" target="_blank">View</a></td></tr> <tr><td>2</td><td>Dr. Venkateshappa</td><td>M.Tech, Ph.D</td><td>Power Electronics</td><td>Professor</td><td><a href="/files/ece/faculty/Venkateshappa.pdf" target="_blank">View</a></td></tr> <tr><td>3</td><td>Mrs. Sunitha P. H.</td><td>M.Tech, (Ph.D)</td><td>Industrial Electronics</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Sunitha.pdf" target="_blank">View</a></td></tr> <tr><td>4</td><td>Mrs. Tejaswini C.</td><td>M.Tech, (Ph.D)</td><td>Biomedical instrumentation</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Tejaswini.pdf" target="_blank">View</a></td></tr> <tr><td>5</td><td>Mrs. Azra jeelani</td><td>M.Tech, (Ph.D)</td><td>Electronics</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Azra.pdf" target="_blank">View</a></td></tr><tr><td>6</td><td>Mrs. Savitha S. C.</td><td>M.Tech</td><td>Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Savitha.pdf" target="_blank">View</a></td></tr> <tr><td>7</td><td>Mr. Nagayya S. Hiremath</td><td>M.Tech</td><td>Power Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Nagayya.pdf" target="_blank">View</a></td></tr> <tr><td>8</td><td>Mrs. Mangalagowri</td><td>M.Tech, (Ph.D)</td><td>VLSI and Embedded system</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Mangalagowri.pdf" target="_blank">View</a></td></tr> <tr><td>9</td><td>Ms. Azarathamma S.</td><td>M.Tech, (Ph.D)</td><td>VLSI Design</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Azarathamma.pdf" target="_blank">View</a></td></tr> <tr><td>10</td><td>Ms. Natya S.</td><td>ME,(Ph.D)</td><td>Control System</td><td>Asso. Professor</td><td><a href="/files/ece/faculty/Natya.pdf" target="_blank">View</a></td></tr> <tr><td>11</td><td>Ms. Sushma G. Vasu</td><td>M.Tech</td><td>VLSI and Embedded System</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Sushma.pdf" target="_blank">View</a></td></tr> <tr><td>12</td><td>Ms. Pavithra S. G.</td><td>M.Tech</td><td>Power Electronics</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Pavithra.pdf" target="_blank">View</a></td></tr> <tr><td>13<br></td><td>Mrs. Divya S. Dechamma</td><td>M.Tech</td><td>VLSI Design and Embedded system</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Divya.pdf" target="_blank">View</a></td></tr> <tr><td>14</td><td>Mr. Chaluvaraj</td><td>M.Tech</td><td>VLSI Design and Embedded system</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Chaluvaraj.pdf" target="_blank">View</a></td></tr> <tr><td>15</td><td>Mrs. Asha Rani N.</td><td>M.Tech,(Ph.D) </td><td>Bio Medical Signal Processing</td><td>Asst. Professor</td><td><a href="/files/ece/faculty/Asha.pdf" target="_blank">View</a></td></tr><tr><td>16</td><td>Ms.Rekha N.</td><td>M.Tech,(Ph.D) </td><td>Digital Electronics</td><td>Asst. Professor</td><td>View</td></tr> </tbody> </table>', 'labs' => '<div class="tabbable tabs-left clearfix"> <ul class="nav nav-tabs" id="myTab1"> <li class="active"> <a data-toggle="tab" href="#tab1" aria-expanded="true">Analog Electronics Circuit</a> </li> <li class=""> <a data-toggle="tab" href="#tab2" aria-expanded="false">Logic design Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab3" aria-expanded="false">Microcontroller Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab4" aria-expanded="false">HDL Lab</a> </li> <li> <a data-toggle="tab" href="#tab5">Analog Communication Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab6" aria-expanded="false">DSP Lab</a> </li> <li> <a data-toggle="tab" href="#tab7">Advanced Communication Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab8" aria-expanded="false">Microprocessor Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab9">VLSI Lab</a> </li> <li class=""> <a data-toggle="tab" href="#tab10" aria-expanded="false">Power Electronics Lab</a> </li> </ul> <div class="tab-content" id="myTabContent"> <div class="tab-pane fade active in" id="tab1"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/1.jpg"></p> <h4>Analog Electronics Circuit</h4> <p class="text-justify">Analog Electronics lab provides basic knowledge of electronic devices like diodes, transistors, and elementary circuits. This lab includes various kits like characteristics of diode, transistor, TRIAC. DIAC, FET etc</p> </div> </div> <div class="tab-pane fade" id="tab2"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/2.jpg"></p> <h4>Logic design Lab</h4> <p class="text-justify">Logic design lab is very useful for the students for realising the logic circuits like counters, multiplexer ,adders , sequence generator etc. In this lab major equipment used are Digital IC trainer kit , Digital IC tester. The logic design lab helps students to understand basic digital components and its application</p> </div> </div> <div class="tab-pane fade" id="tab3"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/3.jpg" style="width: 530px; height: 385.877192982456px;"></p> <h4>Microcontroller Lab</h4> <p class="text-justify">The most widely used instruction set for 8-bit microcontrollers (MCUs), the 8051 core has a long history and a tremendous, widely used code base. This lab introduces students to the elementary programming techniques, interfacing and designingsimple applications using microcontroller 8051</p> </div> </div> <div class="tab-pane fade" id="tab4"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/4.jpg"></p> <h4>HDL Lab</h4> <p class="text-justify">Hardware Description language students will be able to analyze and evaluate VHDL & Verilog concepts. They are capable of designing and creating test with their complex system components. First implement an encryption algorithm using a standard hardware description language; then wrap the security module as a peripheral attached to bus; design an interface between peripheral and bus; apply an FPGA design flow for VLSI</p> </div> </div> <div class="tab-pane fade" id="tab5"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/5.jpg"></p> <h4>Analog Communication Lab</h4> <p class="text-justify">Advance Communication lab provides Basic knowledge on multiple duplexing ex, TDMA, FDMA and advance communication techniques. Modulation and Demodulation techniques for long distance channel with low power transmission.</p> </div> </div> <div class="tab-pane fade" id="tab6"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/6.jpg"></p> <h4><br></h4><h4>DSP Lab</h4> <p class="text-justify">To give students an introduction to real-time DSPrequirements by exposing them to the use of someeducational DSP kits with realtime capability, which will help them get acquainted with the programming of theses devices and some typical hardware and functions found in practical applications such as I/O interface cards (A/D, D/A, I/O filters), types of DSP processors and their different characteristics, interrupts, etc.</p> </div> </div> <div class="tab-pane fade" id="tab7"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/7.jpg"></p> <h4>Advanced Communication Lab</h4> <p class="text-justify">Digital Communication Lab provides practical knowledge on FSK, ASK, etc. The goal of this lab is to understand a simple modem, the Frequency Shift Keying (FSK) Modem, referred to by the International Telecommunications Union (I.T.U.)</p> </div> </div> <div class="tab-pane fade" id="tab8"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/8.jpg" style="width: 580px; height: 441.41592920354px;"></p> <h4>Microprocessor Lab</h4> <p class="text-justify">Microprocessor lab introduces the student with 8/16 bit microprocessor 8086. In this lab students will get exposed to basic instruction set, Architecture of 8086 , Addressing mode , Editing , Debugging the software programs like Data movement, Logical and arithmetic , Loop and branch , interrupt programming etc. The students get knowledge about interfacing the hardware kits like stepper motor, logic controller , display , Keyboard with 8086 Microprocessor.</p> </div> </div> <div class="tab-pane fade" id="tab9"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/9.jpg"></p> <h4>VLSI Lab</h4> <p class="text-justify">VlSI Lab provides the student basic VlSI design concepts using CAD tool called cadence. Creating Verilog code for digital system and verify by using test bench also how to design analog circuits and layout for it. Verifying layout using DRC and LVS check. The students will get expose to industry handled tool and real time projects.</p> </div> </div> <div class="tab-pane fade" id="tab10"> <div class="media"> <p><img class="img-responsive" src="/files/ece/lab/10.jpg"></p> <h4>Power Electronics Lab</h4> <p class="text-justify">Power electronics lab gives the idea of characteristic features high power semiconductor devices like SCR,MOSFET and IGBT. This lab syllabus discuss about the converters, inverters and motors like DC motor, Universal motor and stepper motor. Experiments are conducted on triggering circuits like UJT and RC triggering circuits.</p> </div> </div> </div></div>', 'research' => '<div class="accordion"><div class="panel-group" id="accordion1"><div class="panel panel-default"><div class="panel-heading active"><h3 class="panel-title"><a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseOne1" aria-expanded="false">Performance Analysis of High Speed Low Power DWT Architectures for Image Fusion/ Registration/ Compression algorithms for Micro Air Vehicle Applications. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseOne1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Venkateshappa Guide : Dr. Cyril Prasanna Raj P.</h4><h4><img 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" data-filename="7.jpg" style="width: 260px; height: 204.347826086957px;"><br></h4> <p class="text-justify">Home land security, border security, remote sensing, surveillance and tracking are some of the primary application areas where micro air vehicles play a vital role. Due to geographical challenges, rough terrains and unpredictable environments and climatic conditions humans beings are finding it difficult to monitor and provide security across the border as well as within home land. Use of micro air vehicles are the only possible solutions in near future. </p> <p class="text-justify">Cameras that are mounted on micro air vehicles reduces payload and eliminates multiple sensors. However images/video sequences captured occupy huge bandwidth and hence need to be compressed and transmitted to base station for processing. As MAVs need to operate in day light and night conditions, IR cameras and thermal cameras along with visible light camera is used to acquire data. The acquired data is compressed and transmitted to the base station, at the base station the image registration and fusion is performed to extract information for monitoring and control.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseTwo1" aria-expanded="false"> Design, modeling and VLSI implementation of low power high speed wavelet based 3D architectures for image registration. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseTwo1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Sunitha P. H. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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dBoXhxb+Jr7UpzZ6avHmkfNKf7qDuffoKp6DpX9ramsTkrbxgyTuP4UHX/Cu/wBK0h/E94LuVRBp8HyW8Sj5VUf/AFqAK+mNNC3k+G9MS0AGHuHBeVx7k9Pw21fh8LajqUryXk7PICR+9bP8iK7OG2tdNZrO2hHmsM8c8ep96v2+kajdESiNLdScjPXHvn1oA4SHwJHNO8fmKpRRllBHPp1qP/hG9Y0Z/tGnahKkiqGBHTmvRJtH1RGVo4Ed92cqevGOaozWt7KEhuj9njAI8tOrfn2oA4yRbXxir6X4jtIbLWGXNrqMY2B2HQN2IPvzXleqaZd6Pqdxp99EYrmB9rqfX/CvaPEOjiaJkjKxyRNmMfxH3rlvGFuPEfhaLVwv/Ez0rbb3igcvF0Vz9OBQB5qOor6PtP8Ajyg/65r/ACr5wHUV9H2n/HlB/wBc1/lQB4V4nXd4z1Yet7L/AOhmvTvDaQ2dvD5qA+YFCgjkDJ5/LH5V5t4hjLeMtZbptvJTnH+2a7TTEu51SbY7x+WHAGTgdOKAPoCxt2ks0OflI/T3rauE861QuSi9MDpXk2keL7vSbLy5nVRGvAYkHFS/8LLil/dO+FfgEvxQB6nFbMyFYpWjAPK9MVDLdXOmSIJnEsLnapPUH61y2heJpYr2O2uonVJkzG5bIPOOa6jxBiTTlZWG4OGGMZoAL+WbzlGyMZ759s1j6lHHLZTebh8oAdvHanG9uPKjeZCUCYJB5rM1TUQ1qsKOcPhQv+NAHBeJrdZfCc1q+WdEUZPoWYA/yrx3wwhj1+VD/Da3Q/8AIL17P4wnjSyvIowCY44Ys577wT+ufyryHRRjxZc46fZrn/0Q9AGJpVubvVrS3Az5kyr+ZFep2TpP4iu5YgCEYKoHoMf4V5p4dk8rX7Nsf8tAPpXXWUt14c1e4SdMF23ZboQaAPR7S3FzeRpJ9xGz14Nb2qXV1aTLaWO2MMmWlxkk+grgrTxfbooklTBBxlG5FWj4vS/MnktmSJSw3HGaAOlTQtTA8+51y/EjchImAAra0W+nMc9tqNwkojUbHIwzfUdKxPDPiuXVHls57fbJGAQx/iFZ2t2tzJr5aBzHGU5HrzQBqXcqTzvbwrtiB5wO1Z2u2UFzYOqIw28KSP6023lmtvlcdOMiq2pXsXlhS5yx5OcUAec+OoTNpOj37/64K1vIfXacD+VYNj/yKOr/APXe3/8AZ66bxtKH8J6Wx/5b3U0q+67iM1zNj/yKOr/9d7f/ANnoAt+BI1PiUTsARbQSzc9MhSB+pFei+ET5emvPEuFklbLlc8Z9a868IwSXcWsWduM3M1mQgHUgEEj9K3/BviZtGs2065tyCpLKXHBz2NAHrfhuyiuNQklnbEy/cz0C+oqW7vNb1G7mtNPl+xxxuUUooLkDuSen4CuSTx3aWMAkk8mMsuVIamWPjiS7k+3WAScq+2ZAcNt9cf1oA6UaXrtnmVvEt3LKvO10UofaulimF5oMc9/FGZGViyKcrkZ5Hp0rO07Wo9d0j7Qbfy2y0bgHOCPfuK5ELqcVzchrlmhEp2rkjI/CgDaUw6hdqzYjt4c7UPUmub8W2r2ph1ayz59uwbp2rcs5baWLacwydAp5xWR4mu0tNNug8jFBG3BHU/8A66APJfG1rFbeKbloBiK4C3CD0DjNQ6n/AMizoX+7P/6Mq/8AEFGh8Rx27jEkNpDG49GC81Q1P/kWdC/3Z/8A0ZQBq+GClt4V1u4fAaV4oVJ44+Zj/IV6bpBkttJggiXZmIYUp9449fWvK4LS4v8AwEfsiFhbXZaYL15Awf0rr9C8cRrpsNtNbqrxgIRIvBPtQB6joNvBb6VPdpueZVLSKT8zMO3tWe3/AAkWtIWh1A2KdT9nTAX6k8k1zc/xEsrGAoGjSTOCFOal0/xrcWq/a4IUubORNxMb4UNnnPpxmgDcjg1vSZI5hrUt+AwDw3Sjaw74I5Bro9ce0hthLNEJHQDbzyuaz9RuF1LRTPCjRGWHzEOPmGRkZHrXI2z36W8bXjmdSoym4j/9dAG/bxR3XnXkzKHfAVR/CPpXHX9r9i8TJCBmz1NGtpgRwdwIH64P4V1cRtZ4gySuj4JOBmuf1KcT61pVrktK12jKvcKuWJ/IGgDxG4hNveSwHrHIUP4HFfRVp/x5Qf8AXNf5V8+6tIJdbvZF6NcOR/30a+grT/jyg/65r/KgDxnVrKW78aasseM/bpSMn/aPNeh6UkkdnGyBy0aYKrxx0rh5pfK8d62xIwbqXgtj+Mmu40++aG3VhO5jVN204yCegzigCvfp51ttVVV+7M5Ukf1rBm0kRyRnb1b5nDYxxXUG3E8m+3gCsc52ksf1qteafczRKCmE3DL859qANbT5N1nbP5pMkBzG7t1UjkGu8tfENrqmihmzvhwpDDHI4615taTNbwFHdSYxxx+dVIdQfTpzIpLJISCinjPagD1Z9ahaJLcoS2Mrg8cCssxNLfw7wGLOANp5Gf8A61c1Yai9xPF8+APvADJrpdEaS613zGUxwWx3MxIz1/yfoKAOE8f3aW10NLhflC13dP7jhFrzbw2/neIJ5PW1ufy8lq6P4h35N7dtgBp5WOQeo6D9M1y/hP8A5Dbf9elz/wCiXoAm8NWPmTC4IHyHcd3tW/cbtSuWlkZi543A5AHoKoaFdp9n2Wqxh921ixGea1wsyxPvdAI8nKHGaAM6TTDzll46Ybn8qo2drPFfuYZd5PWMt/StsJNOmQrEdMtiqMmnXUFyt1Ay4B+Zc8igDqLLV5NN1D7avHyBZIs8ke1dNZ+LLLUpA8UbeYDtywxXE3EsXkxysBvboxPSsuO7ksJt8ABL8Y7UAepXl/bOu0H5+5Ark2s5/E+sJpVg4G84lnPRV9B71Tb7TN5ZluiFKb2SLj8Ca6rw9ND4f8OavrOwB0hMcJ/2j3FAHmnxM1CCfxEunWXFjp0Yt4F7YUYz+OM/jWLY/wDIoax/13t//Z6yrq4e6upZ5CS0jFiTWrY/8ihq/wD13t//AGegDU8K2MlpZyavkhnPlRAcH3P6YrQa087e5imZzyWzWfpl7Jc3cNjp80EUMcIbMp5JxyOnXNa85dJGR5UeQEfKuQTnvigDKn0qN1JMn7wqQCTR4UstR0zXIb61kjcQv+8RWB3rjkEVsi1umh5eKMHoGYk/yqnZaTc2WrNfedA6SHDKgKlfzAwaAOy0TxbDpCTQ3jN9nklLIyLkox6qR1rqLbUrO5LvEodZFDsx6civMdUWG4kMIXE8vJPTj/OKdpetT2yrpvlky5wr5wpGe/50Ad3qr2aI0scgQKCWJ7VheFdJfXNSk17UGb+yNNBuRE//AC2deVz7ZxxWVL5k8rrdz+aofGxThB7n1rpfFV6fD3whSOMbJtTlP3eu0YAH6k0AeMeIdSfV9evL6RtzSyk5PcVY1P8A5FnQv92f/wBGViV0c5gXRvDhuQTCDLvx6eZQBt6XYzaRoyRhzvu18yUKeQMcDFRvpqtH8iSovZ85waj0i4vdUuJ5Y7mBIon2BDySDnH4ce1Wt7SSqiHzGYkEI2MfWgDKvNEjeGQxzqrn5iXb0rT8LrfaRY3wLLJa3UQRtvzhTuBB9unP1qzNZXPl4Lwrxzu3Nj64FM0Kxn0rzI5JIZEfLK0WR9R9KAO20XxlaLZ21heSMJgojRsbg46A5/nW9Fc2b2xUoPJUkAnqfpXk15Ek0zC1UIYSS3PU/StO0124vYWgiQQyRqdzOfl49KAOg8QXcFlaTTxSHGMKF+8Se1QWGnv4d8Fap4y1Rma+uYzaWEfXyg33j9SBjPvWVawNcTwec7TztjaX6An0Har3xx1H7ImjeG4SRHa26vIAeCxGTn8xQB46WLPuY5JOSa+jrT/jyg/65r/KvnAdRX0faf8AHlB/1zX+VAHiurybPHuqDGQ15KpH/AjXVWEheKXynwAA7ZIHTiuJ8UOY/GerOvVb2Uj/AL6NTWOuSxKQF4yCefegD0RdVutpaFsqp6DoBRDqc0sbZyTj9K5C015IuVhILEkgcjFTLr4j+5G3PWgDpJp87fl+V1O89eazDKZk8tzhl5BAxt5rMbXlyMxt1xUEuuHzidhwRzwKAO+0aYW0Uca4ZM7i2ODx/OtQauyWd5FG/wB9lJbPXBHNed2fiFoJAAr4GCBUjeJAryqImwRQBi+ObtJ9X8qM5CD/AD/WqPhP/kNN/wBelz/6Jes3Ubk3l7JMQQT61peE/wDkNt/16XP/AKJegCro1ytveLv+6xAI9a6o3qLcZ7Ywi44J9a4RWKsGBwR0rbhv3lhRnGWXjNAHQ/brjJDNnPGKlt7osxVmJHvWKbssmNvzZ4amLdOG55PrQBu3hL23y4OxulY4lMk6LKAuWwDimLfSea4z8rL0qg10Y7lQMke9AHaRzbIvKxjHc9zVvxNqxg8C/ZkIHmvziuOXVJRgcn6mq+s6lLdWUcD5wrZFAGDW3Y/8ihrH/Xe3/wDZ6xK27H/kUdX/AOu9v/7PQBB4fuEttYieQ4ByoPoTXTmdoLy4YOolmOVY/wAS47GuFBKkEHBHINb7aoJba3aRGJjYHPrQBvfbp2Pzsdo6c81LBdM5Kk5bsTWOl4sgWRUIyucU+K6KOWxnmgC9qc0kaR3SKCwG0giqtq3n6grFcSMNwUHnio5L/wA+zmG08McZ/OqlpctHcqwJzjFAHXGQFANuDnrUvxX1dJdE0HTE/wCWcRc/if8A9VYS35LBfmIFZfi+/a+msiwxsh2/rQBzVbep/wDIs6F/uz/+jKxK29T/AORZ0L/dn/8ARlAFnwrcKn2mENskcAq1acF3NbQC3iKq8f8ArFHBJ9c1x9pO1vdRyKTkHtW8+qI14szRHJTb1oA2RfStzI53Y4IqaK7Z4ty8lTzWN9qXnapBNPjvfJhbKk5B6UAWL6eS0vSFRWWY5NP0raZ5GHJXggds1n3l4bi1hcAqx5zRY3RiaQZbBbPFAHa6ZIBrNpkAYcZFcx8WNVXVvH17IvSICL/vkYqe01Z0u0mIJZWB61yviK4N14gvJyOXkyfyoAzB1FfR9p/x5Qf9c1/lXzgOor6PtP8Ajyg/65r/ACoA/9k=" data-filename="8.jpg" style="width: 314px;"><br></h4> <p class="text-justify">With the growth in VLSI technology leading to nanometer transistors 3D VLSI IC technology is gaining momentum for high speed and low power signal and image processing applications. Medical imaging and aerial imaging are the major applications where 3D imaging plays an important role with image registration. In this research work, 3D architectures that are parallel, pipelined and systolic architectures are analyzed for their performances. Image registration algorithms that are used for 3D images are also analyzed for their performances, suitable algorithms for image registration based on Wavelet Transform approaches will be identified and implemented using 3D architectures optimizing for area, power and speed performances. </p> <p class="text-justify">Image registration helps physicians monitor the progress of cancerous tissue. Better registration techniques could give physicians new and more effective ways of monitoring and treating the millions of patients suffering from cancer. Also, image registration would be useful for more precise targeting of radiation therapy against tumors. Better image registration could also lead to improvements in image-guided surgery – a surgical procedure where the surgeon uses indirect visualization to operate. . Turning this data into information requires image registration to be accurate enough to consistently compare images across time and modalities.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseThree1" aria-expanded="false"> Design, Modeling and Performance Analysis of Novel Algorithms for EEG Based Brain Computer Interface for Paralytic Patients. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseThree1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Tejaswini C. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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" data-filename="9.jpg" style="width: 314px;"><br></h4> <p class="text-justify">Paralytic patients are also called as “locked-in” patients. Because of a stroke, traumatic brain injury, cerebral palsy or a degenerative neurological disease such as amyotrophic lateral sclerosis, their entire motor system is paralyzed. These patients are fully conscious and alert, but are unable to use their muscles; they are therefore unable to communicate their needs, wishes and emotions. In these patients a healthy brain is actually locked into a paralyzed body. There is no cure, and the cause of amyotrophic lateral sclerosis, one of the major causes of locked-in syndrome, is still unknown.</p> <p class="text-justify">This research aims to investigate intelligent systems which facilitate development of assistive robotic device for people with severe movement disability such as in locked-in patients. The project objective investigates a brain-computer interface (BCI) that allows a paralytic patient person to control robotic devices by thought alone. The research primarily involves developing advanced signal processing algorithms to extract information from BCI tasks-related electroencephalogram (EEG), commonly known as brain-waves, and requires investigations into signal pre-processing, feature extraction and classification aspects using innovative statistical methods and computational intelligence approaches. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseFour1" aria-expanded="false"> VLSI Implementation of Low Power MB-OFDM PHY Base band Modem for Wireless Sensor Network. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseFour1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Naveen H. Guide : Dr. Sreerama Reddy G. M.</h4><h4><img 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data-filename="10.jpg" style="width: 314px;"><br></h4> <p class="text-justify">Efficient design and implementation of wireless sensor networks has become a hot area of research in recent years, due to the vast potential of sensor networks to enable applications that connect the physical world to the virtual world. WSNs are usually composed of small, low cost devices that communicate wirelessly and have the capabilities of processing, sensing and storing By networking large numbers of tiny sensor nodes, it is possible to obtain data about physical phenomena that was difficult or impossible to obtain in more conventional ways. In the coming years, as advances in micro-fabrication technology allow the cost of manufacturing sensor nodes to continue to drop, increasing deployments of wireless sensor networks are expected, with the networks eventually growing to large numbers of nodes. </p> <p class="text-justify">Wireless sensor networks are emerging as one of the most challenging technologies to meet the communication requirements and data monitoring requirements in several time critical applications. Recently ITU has proposed new set of protocols for wireless sensor networks and road map indicates that in another few years there will be high data rate and data transfer over wireless sensor networks. Software implementation and validation have been successfully accomplished by many of the researchers for demonstration of WSN capabilities. However, for real time implementation and practical purpose there is a need for hardware platforms. In this work, two major research activities are taken up:</p> <ol> <li>Design and modeling of MB-OFDM UWB physical layer for high data rate and development of novel algorithms for hardware implementation</li> <li>Design and implementation of novel architectures for the proposed MB-OFDM UWB on hardware platforms</li> </ol> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseFive1" aria-expanded="false"> Design, Modeling and FPGA Implementation of Robust Noise Filtering Algorithms for Under Water Imaging Applications. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseFive1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Azra Jeelani Guide : Dr. Veena M. B.</h4> <p class="text-justify"><img src="data:image/jpeg;base64,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" data-filename="11.jpg" style="width: 313px;"><br></p><p class="text-justify">A total 3, 90,884 accidental deaths were reported in the country during the year 2011. A total of 6, 94,390 cases of Un-Natural Accidents have caused 3, 67,194 deaths and rendered 5, 06,348 people injured during 2011. The major un-natural causes of accidental deaths were Road Accidents (37.3%), Railway Accidents and Rail-Road Accidents (7.6%), Poisoning (8.0%), Drowning (8.1%), Sudden Deaths (7.3%) and Fire Accidents (6.7%). 29708 deaths have occurred during the year 2011 due to drowning (boat capsize). Recovering the bodies from the deep water is a herculean task, as trained divers are required to dive deep into the water, identify the body, and carefully remove the body from the bottom. Currently there are very limited solutions to detect the body without diving into the waterfront. Divers need to swim underneath the water and with trial and error locates the bodies and recover them.</p> <p class="text-justify">In this research work, we propose a through water imaging equipment that can scan the water front in defined areas and generates images of the water bed indicating the location of drowned bodies. In order to achieve higher performance and reliability an array of sonar signals are transmitted and received. The received signals are processed to generate images, using which human bodies are detected. The received signals need to be preprocessed before information retrieval could happen. Noise plays an important role in distorting the underwater images. One of the major source of noise is the speckle noise, that need to be filtered from sonar images.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseSix1" aria-expanded="false"> Digital UWB Through Wall Imaging for Human Body Motion Detection on VLSI Platform. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseSix1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Vinod Kumar B. L. Guide : Dr. Cyril Prasanna Raj P.</h4> <p class="text-justify"><img 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data-filename="12.jpg" style="width: 287px;"><br></p><p class="text-justify">Through-the-Wall radar imaging (TWRI) is emerging as a viable technology for providing high quality imagery of enclosed structures. The ability to locate moving targets inside a building with a sensor situated at standoff range outside the building would greatly improve situational awareness on the urban battlefield.</p> <p class="text-justify">Through wall imaging technique is required for time critical applications such as disaster management, rescue operations and terrorist tracking behind walls. Micro air vehicles are found to be used as mobile surveillance unit to track terrorists hiding. Detection of human motion behind walls needs to be carried out within few microseconds or milliseconds. TWI techniques are mostly software oriented and hence there is a need for SoC that can process data and retrieve information in real time. In this work, novel algorithms will be developed to identify human motion behind walls and suitable architectures designed for high speed data processing. In the proposed research work, the architecture shown in Figure 2 is modified for human body detection in motion using digital UWB. The modified algorithm will be implemented on FPGA for time critical applications.</p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseSeven1" aria-expanded="false"> EEG Based Emotion Detection and Classification Using Multiwavelets and Neural Networks. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseSeven1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Mangalagowri S. G. Guide : Dr. Cyril Prasanna Raj P.</h4> <p class="text-justify"><img src="data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDABALDA4MChAODQ4SERATGCgaGBYWGDEjJR0oOjM9PDkzODdASFxOQERXRTc4UG1RV19iZ2hnPk1xeXBkeFxlZ2P/2wBDARESEhgVGC8aGi9jQjhCY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2P/wAARCADrAToDASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwDUptONNNZgIaaacaYaAGOeDTBxTnNNFXHYmQAU8U0U4VRI4UDrQKWgYopaBRSGOFOFMpw6UCHCikFKOtAxe1FFAoAMUoFFApDFFFFKaBAOa5t9ak82RI7V5AjbSVrpF61yWnnM94D/AM92qZaFRLn9q3B/5c5KUapc/wDPm9OApRU8xdhv9qXP/Pk/6UDVLjvZSfpUopQKdxWI/wC1Lj/nxk/SmtqNw4INlKOMdRVgCii6CxDHqc8QwthKoxjinjWLkjH2KbH1FSYoFGgrDP7XuM5+xTevUUf2tPn/AI856koxRoBH/a8v/Ppc0v8Aa0n/AD63I79KkApcUaDI/wC1nxg210B/u0v9rn/n3usf7lSYoxTEM/tvH/LO6zn/AJ51XPiaNSQfN44+5VsDmuVu0P2ybgf6xv50WA7c0049aRmqB2osIkZwKhecDoKYxqJ6dgJVl8x8Y6VIKrW/3mNWR1q0iGxacKaKWmSLThTacKRQtLSCnCgBQKWkFKKQC0opKdQMKXFAoFAC0UUCkAtFFLTAF61yOmqzXF6VGcTsT+ddevUVyujcXOof9dW/rUyKiXcZpdtEdSYrE1G4pQKcBSgUANxSgU7FAFMQmKMU7FAFFxCAUuKXFKBxTTAbilApaWmITFGKXcucFh+dLjPSmAgFc7dR/wClzf77fzrpKybiLNxIf9s/zpoDZaoWqZqhamQRtULmpmqF6YD7fox96mFQwDCn61LVmb3HiikFKKBCinU2nUDHA06oxThSGOFOptLQMcKWmilpAOoHWkFLQMWlpKWgBQaWm06kAq9RXLaP/r78/wDTZv611K9RXK6L/rr/AP67t/WlLYqJfTg1MBUQHNTpyKwZqJtpQKdilAoAbijFPxSYFADcUU/A65wPU9qwtTv7o3UcVmMqV3Ag9cHk/TiqSuTexss6Rrudgo9zWdd6qmxkhBOer9gM4rKla5uRmeTKqPvZ4NQ3UkKwRRQs53LmXd0LZOMe1aKImx0moXZuGYzsik/dVuKje8cNnzC31NV2YEU3ZxVWJJXuiSDnkd80qX8qElZGAPYGq+zAqMqaLAaUesXCnm4l/wC+qcdULEkliTyeR/hWSVam80BqekvUJqZ6hNIRG1QtU7VA9AEsX+rFPFNj+4KdWqMmOFKKaBTwKYBS0lLSAcBS0gpwpDuKKRJEZmCsCVOCPSlFQrb4maTeSDn5aB3LGaXtTcYpQKQx1KDSdqAaQx2aXNNzR3oAeKWkHSlFADl61ymij97ff9d2/rXVA/NXLaJnzL3/AK7t/OplsVE0ttPSkxThWBsSAUoFC0/FIBuKMU7FGKAI3BKMAM54rKstPiKuZy4eIGMof51qTXa2hX5Nzt09hWPLqa6gLhIQYpcZAP8AGO+K6qcHYwnUSZn3kjSPKkGGIzwO1Z042svHDKCPyqxasiXqGYfuy2H9cGn6hHlWxy0LYOPQ8j+da2vEz5rSKSZ9KexbHSoVY9u9G8g9azNCQ9OnFM43e1Lg8F8jvimMQrHByO1Jgh5UYpm0U3dwaSlYq53Z1Oxf7t1F+JpRc27/AHbiI/8AAxWS/hXUV6IT/wABNRHw1qI+9EB9c/4Vv7CRz+3p9zb3K3R0P/AhTWRj0Un6VgvoV/H/AMsc/wC7Uf8AZ+oJwI3H0b/69T7CfYft6fc3mmmTgwPx7GojqBXrHisYxaih/wCW/wCDE0CTUl6G5/Imq9nPsHNB7M2DqmP4RTf7Wx/CKyTe36cOW/4En/1qaNSnH3khY+8YpNSXQdo9zXOr+iik/tk/3RWUdRZvvW8B+ikUgvYj96zX8JGFKzKsjVOtMOij8qQ61J6fpWb9rtT1tpF/3ZP8RSi4sSOUuQfZlP8ASkHKaH9tS+n6Un9tTf5FUDJZHpJOv1QH+tOX7GT/AMfjD6xH/GjQLFz+2p/f8qP7Zn9/yqssVqx4vYx9QR/SnfZIj928hP8AwP8AxpaDsTHWZ8d/ypP7ZuPVvyqP7AzfdkRvo6n+tV2WFGKtKcjg8UroLMuHWLk92pP7YuvVqp4tyeZSP+A1CZFBOASKNBmoNYuT/EwqRdSnbrOF+prKcBYxIo3J3I7fWovNX+6fzpWGbsd7cyShEuAxOT16VDpDiNb526Cdsmsy2ujFNujGGx160kF1JHBOA3EkjFh65pMDplvrL/nqv508X1l/z1X865QXYH8ApRef7AqeVDuzqxqFmOky/nThqVn3nWuT+1j+4KPtf/TMUciC7OuGpWP/AD2U/iakivrOVwkcgZm6AE1xwu/+mYrf8Pxq6G4ZQGOQo9BT5UguX9TsvPt2ZHKOqnBAzXMW0W791cME8tSsMoGMHPBNdwVzGQe4rmdWtPJk44UnNdEWc0zLkGZmkkQCSMEtjlW9/wA8VVMrH73OeDUtyfKjYA/fYcewqKCVA2HO1T1OKqQ4J7EeyP8Au4prRd0YD61JLsEjBG3Lng1GzYXrUOOhfNrYRoLtl3geYPUckVWKsD81SrIyHKsVPqDT2umdcSBX/wB4c/nWRZWPFJmpyI2HAK/Q5pvkr/z0H5GgZ6onjLRm6yyL/vRmpR4q0Mjm8H/ftv8ACvKM0bjVaEnrSeJNEkOBexD/AHgR/MVZXU9LccXdqf8Aga145uPrSh26ZpBZdj2LztLlPEtox/3lNP8AstjJ91IW+mK8fjDMR6VfhtZpB+7BPvmqu11F7OL6Hp50uxbrCtNOi2Df8sP1rzhrO6jx976hqes2pQD5Lm4TH92Q0/aT7k+wh/KjvZPDWnSHmKoG8JaaekQH/ARXBvrerRcjULn/AL+GlTxVrMf3b6Q/72DT9rPuT7Gn2O0k8GWDHjj8KhbwRaHpJj8/8a5YeMdbH/L5/wCQ1/wqaLxxq6fekik/3ox/Sn7WYKjFbX+9m1J4FU/cnxULeBXA+WbP4/8A1qqL4+1AD5oLc/8AAT/jUqfEG6B+ezhYezEUe1l2Q/Z9mxj+CLwfdcH8qiHgnUGbBcL7kcfzq8vxD4+bTh+Ev/1q1/D/AIqXW702wtDEQhct5memPb3pOp5IcabX2mee6rp0ulXrW0rKXUA5XpyM/wBaRYXKg7h0rW8dH/io5v8AdX/0EVVVflX6Cs2zVFXyG/vCk+zv/eFXNtG2lcLFeJJYX3Kw9wehHvTriz3L5sBwndf7h/wqXbSoSjZU4NK47FDyXj+bIOKWSMhtgONyq35ir0m1gTswfY8VGwBlbjoEH/jgoAqC0OPvUv2Q/wB6rgXijbSGU/sp/v8A6Uv2U/3qt7aXb7UxFT7K479faul8NgfZ/Lc4KHg56g81ReUysZdioDkhRzirFnbyz3CxrnaU3sRxjnA/lWlo9zNuT6HTMyKvLL+dYmusjxrsIYjPAqY6QcfM5/OsjWLT7MBtlbn3qkybGNdwSv8AMEbI9qjWxuzH5ghJXOPr9Kv6bYSXcm93fywfWtZYjDrljGoHk7SAD7Ak0mxpHJElDhlIPoaa75HWtzxFBGGW5VBw2HHrXPck8flSch8q3FzR15ppBBwaBUli7T2OaXL03dS7/egCTNGaKKCQqSJd7c9KjxV/TIfNuFU+oovYpK+hdsNMknZewrrNP0ragXb9as6dZgDLIF9AK2oECisW3I3soopDS4in3RnFUrvSSEyoGPauiAGKZIoK1fLoRzXep51q2mBVLKvI61y8i7HI9K9O1ewMoLR8N6V53q0PkXbJjB7iiMujFOKWxRzRmg0lWZi5pc02igQ6us+HY/4nkp/6d2/9CWuSHWuv+HQzrMx9ID/NaYyp45OfEk3+6v8A6CKrhuB8h6VP42OfEtx9F/8AQRTO1SxoZuP9xv0pN3+w1SYoxmkMj3H+41G4/wBxqkxRigCLOT9xqit5RNGHwdygIwx1IGM/pVsCqWmD91L/ANdDQBN5n+w35UeZ/wBM3/KpsUmKBkXmf9M3/Kl8zH8D/lUmKMUATWTC4kSHy5N2eDt4xXW2cKQQqoHOBk/Suc0e4jtp3Mg+8mAa6CGXfAjDgEU0RLYsO4FY+rWsd4u3JBB7VoknZk1UYZc5q7kJJEdpaLBbqgOKikgZr9FTOYCJC/Ye3vUl3MY047U1RdXN8H87ZbWq+XsX/lpJj5ifpnH4UkN6Mwddkxp4DdZZSR9AK53ocVr65Kbm92g/LH8qj0qgYQoyetTc25WVW602nvwaZQQFFHeigCxRRRTEKASQAMk9q6Hw1YXC6kTJGVEXLhhisrR1D6raKehlX+dei29useo3LHBLBR/Opka049R63DkZLJEo7tUY1O4zmCWKVc84FTS6WJjJySsg2sPamHS0toiIgVPBJHfH/wCusktC27s1bS78+38xlwR1xVKbVpRLtSBCnqzYpbFStnInfBqtHp4mys2XjYbdvbnr/KqjK5LjYsm5aVAzRgBu6sGH6V594vhMWrM2OHUNx2rvV0o2yhbV/LTfu2gY/D6VleKbYDS758ceWvPuDx/OqskxPVHnJpKDRVmQlKKM0UAKOtdl8OBnVLk+kP8A7MK5BmjaOMKhVxnc2c554rsfhwP+JhdH/piP5igDM8an/iprn22/+gijFN8YnPia6/3l/kKeetIaDFJilpaBiYoxS0tIBoFUtLGYZf8Aroav44qlpI/cS/8AXQ0AW8UYp4FGKBjMUu2nYpaAC3h82UJuC57mupjQLGqgcAYFcxEAZFBOAT1rp0P7tcHPHWmiJiynCYFUmODnNTzvxiqMzkZpkohupkWVC4LKGBIHcZqidVNnYNFGM3M7NLIfQtzTrklkfPYfz4qn9nEjAnrU30saqPUzwhLF25Y8mh1OOlbK2SquTg1SuogmcVJoncw5RhqjzVm4XLGq5GKtGTG5ozRS4piLFFFFBJJBM0EySpwyMGH4V6ZZzecIrjdnz13Y/CvL66DwtfSjU4YZJXaMqQqk8Dvx+VRJXNqcrOx6RA2aW7IWJj7VXhYDmn3MyFdjHrWTehbXvEdlE5RyT1qey6Mp6g1RitMbjHcFY3+/zVqyWG3TbHJuHuc01oEru5ambArjvGd48WltEDxPIE/Acn+ldXJICTzXlniK9ku9UuAzkxpIQq54GOOKtasnZGQetJmlpK0MgozRRQIUda7b4bj/AE28/wCuY/nXEiu4+GwzdXp9I1H6mgDG8XHPia6/3x/IVKetV/FRz4mu/wDrpS+aKLATiioPNFL5tFh3JqUGoPM96BJSsFyfNUtJP7iT/rof5CrCyDvVPTHCwSDP/LQ/yFFh3NPNFQeYPWl8wetFguTUVEJR60eYD3osFyYV0ZPlRIh6hQK5cSYPWrMuqu6gHOQOTQJq5rSyjnms2e4G481Ra7dj1NKqGUjB5JxU3Go2HzS/IBjljn/CpLOFpHB7UyKLzrnr8vQZ9K2reFYlwBRa7HzaFO5XyxWTcDeTWxfCsuRSTUSZrFaGZPAcZrPlQg1typVGWDceKcZEyiZwUnpU4tZCAdp59quWdvsmLEDAFX811U6TmrnNOai7MxKKACTgDNKVYHBBB96yKuJViyuDa3cU46owNJa2VxdsVt4mkIGTgdBUZjZGKsMEdqGgjJXtc9RtbtJrdJUbKsoIrPvo7q4n3Cby4vQdaoeGBK2ksck7ZCAp9OK3bdk3fOPzrmlo7HXGXUrRxQImDcXBB6hR/wDWoWxYTebDcSKq87W71uxvAF4AqrdOvOwcn0qxudynqGoCw02W4c8qvA9T2rzB2LuzE5LHJNdR4yeZZLeAudhXeV981y+0iritDCctRhFGKdSVRA3FHanGmmgQgruvhr/x8X59Ej/m1cN3rufhp/rtQ/3I/wCbUwMLxQM+J7oesuKf9nT0P50zxCd3ii5/67/1q2F5pgV/s6e9Atl9TVoLShaVwsVfsq+po+yD1NXNtOC0rjsUxaDsTVXTIEa2YkHPmMK2FXBzVHRkBsif+mjfzouOwv2ZD2NL9lU+tXQgpwjFTcdih9kT/ao+yL6tWj5YpRGKOYfKZn2Rf7zUG0H941p+WKPLFHMKyMs2n+0akhtmQlgxJI2qPc1f2D0ojTDBsd6LiaHW9sYnDGtFBmo0ORyKsoPlqjNbmdepk1nMmK2Z49xqhLHg9KxkdUTOkjyKrNFhq1DEaq3IEY569qUIuUlFDlJRVyt0OBS0zNG6vaUVFJI8pvmbbOlt9JsoLqJ0gXJXdg84NMbS7SeWaWSIEjJ/Gqc+v+XKHjVWCjAHtVQeJJAzYiXDDGK5Lo8qNHETd1c6Gxtba1lLW6gAx/NiszUbGNQB5Kln53DqaraZrVxPfJBFEmZfl56AdTXTR22Qoc7tvSonUSR1UMFWcrydivoVuYLTymXBznFarWokXpz7cVHEm1sgVfiPA4rl3dz3IrkVkUvsOP4n/wC+qkS3WPnBrRwCvSq0/C8U7WHcxdStLa5nVp4Q+3gsewqodKs47bzDZowD+nJFbJTcTkdajljaKPKu4jQ7yoxg46jmtYVEtGeficG5y54yscncaXE8jNHbbVJ4HpVKTStrYWHnrjvWsLySa2uEkkYB4eBvGd+4dD9M1YmvlePchZPkUENKC5+fJ+b121vZGUKM47yOUnsJEBPlMPwqotvI77FQ5rqLi5jkQB5nRAZPl8zLc42gnv0P51UsbqAHMpjOI8EMCQzYqeVHSm4owzauIhJkbd23PbNdp8NBiTUvYRD/ANDrnkkWPQWtpQok8zcvHOCBXR/DUc6kf+uf/s9KSSWhcJN3uc7rPzeKLgf9PGP1rSCc1maoc+Kp/wDr5P8AOtYHismaIQLSheaO9OFIYBaeEFIKeKljALz0qhoaZ01T6u/860hVHQv+QTCfUsf/AB40AXRH7U4RinCnLUjGhB6U7yx6U5cZqQfSgCLyx6UGH0FSnilTJOMUAZ9xA5u4CsojVSd4J+8CKuBozgB1/OmywRzsWdcgcCojp1uexFO4i2gBPBBFW1XCVn2dsltu2E8nnNacKmReOnrTc1FXZPK29CHYDkmojZtIoaNTnPO8YGK1UiWMcD8TQxPYVw1MV/KjphT7mQdOIfc8mMcgLxXNajIkl2/l/cBwOc5rq9YuBa6fI24B2G1frXFseSa9HLYymnUkc2MklaKAmmZpC3NN3V6jOJI7Q+C9JUZa6uAPcj/CnJ4N0gjK3NwR/vD/AArjvterH+K5/WmGXUz1+0frXBaHc3SqeR3Vt4b0mwuo7hJp96HjJ/D0rYKWijktXlZ/tA9RL+JppjvD13D6sKLUxr2vdHq0bWbHgn8eKkaa1jH314/2q8j8i5/vqPrIv+NAhlDDdLFjPI81f8am0Og17S2rPXjdWyqCZUAP+0Krvf6fu2tNH/32P8a80MkOT8sQ/wC22f61TkUFyRcRKCeBuJx+lL3RtT6M9UbUNKQZM8P/AH8H+NQy6vpHlkNLCyuMEbx0ry7ane7i/Jv8Kbti73aH/gLf4U1ydgSn1Z6FBc+GiWH2a2QL3bHNPa98MIP9TaH6R/8A1q872wd7kfhGaUC1HW4k/CP/AOvVc0OxPJLuejfbvCqjJW0/785/pR/a3hVOgtR/27//AFq85H2PP/HxMf8AtkP8aUmz5/eznP8A0zA/rUNroaHft4k0BH2pFCVz18r/AOtTf+Ey06HIhRVB/upjNcEZLQnP749uwpDNaYH7qVsdP3gH9KfMuxDg31C/umn1Ga6BwzuXGO3NR/2jdj/lu1Olmt5Qx8iTe3O4yA8/TFVSuCVI5FRuaLQsjVLwf8tj+Qpy6veA/NLkf7oqnjFFAGgNXvB1kA/4CKf/AGzeAZ8xf++RVS32P+7l4Dfdb+6f8KiYYyO/SgC+ddvcfeT/AL5qtFfXUUYSKd1UdADVfHFAGKANRdRvFgjY3D7myfw/zmgavqGcJMWP0FV5uDEB08pTTmTy9ML/APPaTb+CjOPzP6VNh3L1jqV7dXUcJvUXd3CA4/Stj7PqQORqUWB6xCuOX5GypIIPBFSvcTSDDyuw9CxosCNSHWtQkvDB9oTG4gNsHNazNq1shkmubcovJAXk4rkQSDkcH2rWmttQMMcLGWaWcA7clto64/lQ7IaGjxNfAAAR491qRPEt87BRHEzE4Hymrth4KvJ8Ndutup7dWrptN8N6dprCRIzLKP435/IVzzr04lxi3uVtGtr6dBLfokeeka9fxrcCbQO1OLADgVG5Jrz6tZzZvGNthHkH1qrLLKRheBU7cVXmlCIWbhVGTWCTkzXRI5nXbh2nWFjkIMn6mshmqW6mae4klbqzE1Ax4r7GhTVKkonh1Zc82xjHmm5oY03NNsqJWLMf4j+dNxW4vhq6PWSMfnTh4YuD1uIx+BrzPaROrlZgkUmPaugPheUdbpPwU0o8M8c3P5JS9pEOVnPYoxitC705be4eLzC23HOOvGar/Zx6mtCbiT+U1tbhFw6q3mH1O44/Sq+KupbpuUybioPOOuKRIrc3hVjiE8ruOOKTYIp4oxV4xRNIVSMlefmBJxyf8/hS/Z0gKPPE7RE45BWlzFWKG32pdvtWtFDazSmU28iW+3CkKeT3NXYbHTJDhSpb0LkGodRIfKc9HC8jbUAJ+uKd9ml3bcDP1rqV0e1xxEPqGNN/sS3zkbh9GNT7ZD9mznHs5uBHGxHqe9MNlcDrE1dONFhH8cv/AH3T10eAHJLt7MxNHtoj9mzlI7WVydsbHHXFKbO5JyYX/KuxSwhQYVBj2p32OLP3f1pe3QezZx4tJxBIPJfJK9vrTTZygZeJyT2Arr57eKGF5BEzlRkKp5NZqXKyrwIYSf8Ano7U1UuS4M58W04/5YyAfQ1JDas5+Y7fbGT+VdPDp4lG6W4aUekZwP05qzFY28fEcZX6Gh1kh8jOU+zwqDujuGP0AqItbCNh5Em8/dYv0/Cu0NnGwIO4g+9Z11okcVu5tlJO08HnI9KSrJhyMx5pLY2sMv2U4OYwfNPBH4e9I2JNA3YA2XWB9Cn/ANauisYra7tQwiCkEhkIHBqz/Z8Hl7fLAXOcYGKbrRQcjOF49afEkbuFYsM9CBnn6V2v9mWx6xL/AN8ir2n6VawuJzEgYfd+Uce9S68bD9mzH0PwirIs+ok4PIiH9T/Suwjjji/1cYX6CkDr2NDOOgrgqVZSerNowJC/FML00nIqMsQa5ZM1UR5k9qiacCmSOccVWkcioRaiSSXHoayNavNlmUHWT5fwqyxLHNc9q05kuimchOK9PL6PtKqb2RzYmfJApMaiY05jTGNfTSPJihhNNzSsaZmsGzZI6463ZdpS3+6pNNOtQH7qTn/tkas4jHRAPwo3qOi15XIux08zKbasT9y2uG/4BimnUbph8tjJ/wACYCrjSKB8wPPoKrmRzxn9KtUrkuoZeoK0l0XZdrMiEj0+UVXEeO1bE7I5VmjLNtAJ/OoVJZsLAPXlgK2aITRneV7UktkqxjaI3A65yCa0ZHMQJdYV+sgrMe/j34ILA90GamxV7DoVuoMiHOw9eQf1p/2SSeUfaJOv8O7OB9aqi4IkPyEIOoPBqQX0eflhkP4ik4j5jpIjFHGqhwqgYAyKimazcYldG+q5rEivEcnFuTj1cUp1KNSQLYcdfmNR7Hrcr2hpBbMN/o9xKjf7G4/pTvNnQ7RfLj/prER+tZf9pLIQqxCMkfKwJzVGSeSRmLSMdvPJNP2XmL2h0huJwpIvbU/RCaaJLlxk3Zx/0zh/xrn1kmjCgSsqkbxg1eg1y6j2iQo49xzUOl2LU+5o7j/Ff3P/AHxj+lKCCeNQuR9cf4U2PxHAQPMhcepU5rXs5or2ATRMSp7HqPrWck47lLUzN86/6vUAf+uiLTx9rk6raz/pWx5C45ANRS2MRG+ILHKOjgfzqedDszFfTbuR90UUNs2fvIx/lWl9pt7eFVuLmPeowxyOT9KxNa1a8WZrZSIQvDFDkn8aw9uTknJNaKHMtSXKx2seqafI21bpM+/FXVRWAKnIPQg1wkSwkfP96tjTdQSyv4oFk3W0uAR/dJ7/AJ1MqVtUCn3OjSBEB2KFycnHc0/ZxU2wCl2Cue5oQonzDPSp92447CopCF4HWnx/KtSxEq8ZOelQNcbSSOtLcSeXFjuapRks2e1Yy3sbQWly/HdHb83NS71lTchqiThSKpJcNBKSDx6VEoX2KizVL9QarSOM4o84S4dPxqrLJh+tQol3FuZxBbSS4+6OPrXKOxZiSckmtXWLncqQg/7RrINfS5dR5KXM92eRip80+XsNaoyacTTCa7mYRGnmm4pSabXNJ6myO6kVIl3SOqD1Y4qtcXVvDt3Sr83QjpWTLPLcNBFM5dCoBBqhgJcyoBlQCADzj865lDqU5a2Nt9StkkKF+R37VGmoxyA5HltjK7+A30rBiYlGQn5euKeyhrCNzywcjJPbFaJEMvvqcr7kCKko9TwaoSyG4zPwWXhkOSMetOHMyN0IXtxTrdQ9vcu3LAZzn3oGMjZIWLiPekgwMgcfzqMIzB4uy5YEc1Ngf2cHwNytwcc1HLLIDHIGIbb19aGgvcbsYqJQMdmx0pxiC9/kbpzxUYYnPJ+br71MhKqFB+XPTtUlWsILc+WxI+7yD601oRG2Sfl7sOaYZGEm0HAyRgUEDbk85qWxoaWIYYzgdKdJtLAjGMd6jYncR2oHSp5irDuowTnFKcEitHRbSC5lxMm8e5NdXBp9nCAY7aMH125rGdblNFTucTDa3ExxDBI/0U11nh+xlsrVxMuGkbdj04rVAAXjinCueVVz0NYxsFBHtRS1mO5TuNMs7g5lt0Y+uKoS+G7F/uBkPsa3KTFUpNdQaRzD+FDu/d3RA91qay8Mrb3CSyzeZsOQNuK6IClIp+0k9Lk8qE7UZwM06mS/6s1JRAPmfNTLknAqGP71TJ3+lSZlK9l3S4B6cUkRwtQSnMlTL90VzLVnZsrDy3FZ85Abnoaunoao3XetCIj7e5aElQRg1FcS/MWJqqpJI5pL4kRHBrenTU5JGcp2uZs8pkmZj3qEmlbrTT0r6dJRVkeQ9XdjSaYTTjTDWci0J3oo70Vzs1R//9k=" data-filename="14.jpg" style="width: 314px;"><br></p><p class="text-justify">The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.</p> <p class="text-justify">Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.</p> <p class="text-justify">It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle collapsed" data-toggle="collapse" data-parent="#accordion1" href="#collapseEight1" aria-expanded="false"> VLSI Implementation of Brain Computer Interface. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseEight1" class="panel-collapse collapse" aria-expanded="false" style="height: 0px;"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div> <div class="media-body"> <h4>By : Azarathamma S. <span style="line-height: 1.1;">Guide : Dr. Cyril Prasanna Raj P.</span></h4> <p class="text-justify"><img 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9uuPoKMFJnkzdjp38S6rflo9G0GZOP8Aj51XNtGPomDIx+qqPekOl67eMTqHie5jVhzDpsCW6D2DMHk/HcD9OlWdLgWz0y3tlvLi7VEG2e4kDu49S2Bn61Je6hHp0KySh3LuI44o1y8jnPyqPXgnsAASSACa64qK0Q+Rbsz28HaPN81w+pzN/em1W5c/rJWdLpXg7TdQhJa6ku7WYSrHFc3Nw0br0ygZsHk8EdCaZcahrF4SDOoM0giigsg5jTBxIZZwucqc8LsztI5JJEkKTfalt1g8zS3VRbPA4KqAhJL85IPQdR07k1fMTyo0rnxnYRBI7aC/u7pwStutu0T4HUky7FUe5I9s0Wfi2G9jZo9Nvsg8bTE6t9HWQr+ZzVOSCzsr+0kVVheUNAiqv+sY5kyT7BG9qrteajDrwimsZ5bJoGYXFvE8gDBhtUqASpwW56NgY9AXHa25e1LxnHpzxCTSryQSSJH+6lgLKzMFUEGQdSevSrH/AAk0afNf6ffWEX/PWVUeMdskxs20epOAO5qDUJ5bXTXvIojIIlErRuCpKDlsD+9joPUAcZyKOsW9nJfWJnRomuT5MV/bybJY5PvIuccq2G4ORkAEHdSuG2zOojvLeZiIZ4pWHOEcHH5Vlajo5luxqmmz/wBn6xGuEukXIkH9yVejp9eR1BBrGHh9hHcC7t9LuMZe3khsNkiPyckZIJ6HIwc59Rirp3iGXTfLW8kmmtiyJMrrI0ts7ttU/Oodo2OMFhxzhm6Beg7p6SO98OeIxrCz2d5ALTVrPAubbduBB6SIf4o25weoOQcEVuHpXA38DX/2TVtGu4o9QtxutLkfNHKhwTG+D80bAD6cEdK6bw9r8Wv6aZ/Ka2u4W8q7tXOWglGMqT3HIIYcEEHvQ3dXMZQ5GapqNqeaYaxkESM9aZTzTKwkajD0qM9aeaYaxkXEY3WmGnnrTDWMjVDDUZp7Uw1jI0iRnpTDTz0pjdawkaRGGozT6YaykaIjbrTKe3WmViy0bWoW9zd2MsNpfyWE7D5LiONHKH/dcEEev8xXnWkCGPxSNM8SStqmvwZeG4ebz4gvqsa8QNx0Kg56Ma9FvbKHUbKS0nMoikGG8qZ4m/BlII/OuXt/CF/4chZPDN1C9pnP9n3qBQT3xKg3A/7wf69x9PQmkrNnkPSV2bF3ewWNlNd3D7YoULse/HYepPQDuaw4Quo65bST3zm+tI23W1sitDEHK5VmKn5sbR1ViASAoJFU4NdtdcvNPM6fZoYo5Ll45mGFlSTylO8EqQG3455IVh92ujtxZRGe1Eiw/KZZdrbCN5bLZ9chue1dGyKnK+2xDevpRI0zUpUgE4yqTHYkyggkA9CvQEf7WCPmGY9YvzoUR1O7kgfRAAJJo0Zmhz91sqTvQnC8AEEjtnDZPDLaRrUWrWmnz63atEYpbW5ujPNbnOTJAZmOc4AZcgnC49D0V9YabrWgRJCiPYyGK4RBHsVgrrIAVIGOV5BH1HatFTVjmdR3OGuIZBr1xc26TT6lcxD7LFPIxis4sAGVlP3Nzdh8zbccfPjb0FJNS1aFbcym1tEZZL8nb5r8DYv98fxMfu5UAZI+WG/t7fVJbxraSa2vbrTxFJuUhowxfYSOgZWMo9c5zUtjc3N5oYgtJG0y7hPlfulDCB14wFbhkPYHqpB44NSpWNHdx0E8XNLfa5B4WtpWtY7qzkubm6RQX8oMqbI88bjuyTg4HI5wRYbwxpsmkR6XLbmS1j27VeVywKng787sjHXNRWHhCwuprfU9cto9S1ryUSW5uRvAIHOxD8qDJJGADzzzk1m3Wq65Y+FdQ1yfMWqahKlrp+miMsYWDso2r1kkILOeBnaOMDmuXm2M1Ll3Jr62bU9Qb+xrtYNU0pxFK1xE7pIjx7vLYhhkfMrdcgr055kgVNYgsNS8sRMUeOaJ+TtIIePPs6jnp8vvWviw8PXGmaMsbqt55oSdyW3yqAx3t3dxubJOTtNY/iC8Syjaxjf7BctIlzC+QFnxOrSKD/eOcFcc+Zxnmpaa0Rakc3pGqvaGa6BYrDqlzY3oz/rhHkrMFHJcALuI5I3E5wMbl7cnQb+LxPatuhWMJqKIeJrfr5gA6tHksMdV3AdRV+HTLeGCeARfu2uWuQM8l2fzN3t85OOawtAv0kH2QR+XBLGZYYH+9AQcSwEHpsYjA9HwOBSb6o2guZcj6npdzfW9tp0t+7g20cJmLpzlAN2R68VlWviayvZrONIruNrxpFh8+3aPdsQOT83bB4PfB9KwPDiS3XhTW/CwcedYrJaW7SMf9RIhMJPsoJTj/nmfoK6eCdQOnWdrGLWyaJblJHiuJJSTJCqBhuAI5HIGBgcdazko9SIxXXc7dLu3lgeWOeJ40JDMrggY65PtVKfW7CCeyhadWN4zLC6MCp2gk856cfnxXInwpNZ6PdtcDT7VswFo2nHkTLG24rJiNQAemcE+tW20H+17bTLuCz0m3SNppFFsdyMrxEKwbYOd209OwPtWTjHuaKKvudT9stTsxcRESNtQ7x8x9B6n2qtf6raaaoa4kwxKgIuC3zMFBx6ZPWuSufBl3/Z8NtFbadMTpq2Z84lRbSclpIxtIJJOegOVHNPvPCd+9zNtisLjzLiCcXk7EToECAqPlP8AcOOR941k4x6stRXc6/7RC07QLKhlUZZAw3AepFKelcppXhe5stc+1T+S6pNLKtwsgEj7ycBhsz0bByxHA44FdUa56iSejLsNbvUZp5NRk1zSLQ09KjbqakNRnvWMjRDajPWnmoz1rGRohjd6bTj0ptZMtHQ1l+J9TfR/DOoXsWfPSIrAB3lYhIx/32y1pg5rk/FM/wBt1zSdHQ/LC/8AaF0O21MiIfjId2P+mVfQ0VeSPLkm9CrYafa6RHbW7MjJDbW1uhZfvMjMA2PUsw57EircckcOp3b2rwXd+xUtBLOEaGMKBhRgnBOW6DJbrTL+1+0ojLGkjJlSh43ocblz26Ag8cqOR1rL2SaxaxbJFkliIksr7yirxTITmOUDpnkHG3ILLheM96fMgqxcXY6zTvFBudUfTV067guYsNKLho1Coc4YYYlhnj5QQCcHGKr+JtcsfD+jXcUEwjvbsSGztY2zJLM5OPLX3c5PHUkmo1/0uGKe5hNvOisp2v8AMgJG4K45CnAOeDjB4I457W5NF1PwZfz6bHZXDzwtFbSRKu5piSiEHru34wfxpqTehg4WNpHh0GG6kv72CG1a5aSFpXVFVWwSmSB/Fu9ex9hy2ma/p1np0emm31VLh5zHbypaSlruUNlZVcrgs2N/zceuQMm/4M8PPYWS32sRPNr0hP2i6uJBK/BO3a3ZcY4GPet681D7G0NxNa7rVck3a7XEAx95h1Ckd1zgcnA5o0TsVql2GJB4pt/DbXV7rsC6oFXyoYbaMQtISAsb7gSdzELlSvXitbyvEcmpWM91oukXT2ySCOdNQdERmAy+xoiVJAKjBbG4jPOalS6nVhl0IB6EVLfzveadPYyzS2xuYniEseAy7gRlWGcHnNXGaMZ030Iy99q16LbU9AEFlFGXkNw0UqvMHQxmPaxOBhySyqQduK5fxHpMGteLbO/vrmL+x9HVpXVjtVbrdgZcEdMLkdsKOdxx1F1Cbjw/dWep3EH2eSN45JEUwqISMEHk7flyCQeOCAOlef8Aim6sBPo1mtg8WhxJI0KAGOGdwBsG1edgPO7GCGJGRmiT7FU43dmal34u0eTZFb6jav5snkszSbQmQfm5xkduM8lR0JIi1qBLTVtP1MS4EdwWmjBGWVkEO73Cloyfb8M8nq4EplTTrlPsWmwfaHuFbcrSk/IYzk7NzZIVTsAAGMkGr+q6TPcaVPqVxNPeSQ2MrAzOCFdodwKgfLhWUDgdSM5xU8vLodEWmuZG5pOtxQeOHfT0l1A3WnmIx2pBBeOQFSWJC4AkbJzxx3Iz1gTxFfgGSa20qI9VhHnzf99MAi/98tWDp6Z8daUsfCxWN4xA7LugGPpkj8q7gmuabtYc7c7sY8HhnTY5FnuY3vrlTkTXrmZl9NoPC/8AAQK1TSk0wmsJO+4lcaaaxpTTD61i2WkIaYacTUZNYSZohpphpxphrGTNEhrHrUZp7VGaykaJCGoz0NOamN0rGTLQw9KSlNRk81kzRI6EGuK1Jbmx8bXjNGjLqVqj2zhs/wCpwroR25lUjscmuzB/GvPxfDVNYv8AXhgwjNlYkHho1b536/xSA/gi/j9Dh92zzl8aLqan82JIyvY7T/SkksIriZr2wuXtLtx88sGMSH/poh4b69R2IrO5Jyepq5p6Fpy+SAo7d63jJpm+ktGLcNr7bEKW77elzazmFwT/ANM3R1P4sfwrPg1KeeSJdSaB2s3eedhbgSqI1bG5Tu67kZWQ/MOgHOejz71k6pblZri4MU0kFza/Z7j7MuZUClirqO/32yOT93APNbwqXdmZVaCSvE34XfYjOuxupTOdp9M1V0lHt9Ht7WVH3Qx+SfMxk7Ttzx2IGR7EVQ0bxFDrGQsMqNuZchSyZXqCcAqeRw4U9cA4q/C13FqU8c0TvbSDzIZFxtQYUFCOuSctnkc/nbRjdPUv7yRxk/hUoljgjJu2VY0BY7mAAzjrXPX97rdhMgSO1mtppPLFwsbA2xP3S6AneuepBXGecDJEuq6TPq0ljayzF9PDM13EOGlwPkBPBxkZIHXjtmlYl9kWLuCHW9Tuorqdy1hKht7cSFVDbEdZWUH5zuJAzkDZxzk1JrmmLrOnrayKshDBgTwwI7qR90++D6Yp2o6Vp2pIsmo2FtcCLOHniDbPxI4rl3ihWQ29j4Y0W+hZchoUVEB7AnbyTg9M474HINWSk07om0/whptpczO093NBFOZGiuHUo0hUNvIA+Y4OMn0rn9fstRt4v7R0yOW1s7+EebYsDneyyM4MZ4UbVGffdWvaaqNOtjptjHGk2c5e7e6YMWOWx0xw2eQB1IFP0u+c22oapq0zs1rLKoZwAkcQAb5VAA6Ec4ycdccAckkdUIzspPYyPDXjqC18R/2lq8L/APHp9lQ265Ay4YsQT3wvT0r1nTNe0vWovM069iuBjJCn5lz6qeR+Irx/WPA2oR+G7fxAkZ82dWnu7RV5gV2LLgDsqlQR2wT06cdFLJDKssMjxyKQVdGwyn1BHSs5QjPYr2cKnvRPp8mmGvFNG+Jet6eVjvGW/gHUTcOB7OP6g13+kfELQtVVVkn+xTn+C5IUfg3T88H2rlnSnEzdKUTqSe1NJoDqyhlYEMMgg9aaTxXLJjSEJphpSaYTzWUmUkIelMNKTTDWMmaoaabSk0w1k2aIa3WmN1pxNRk1jJlpCHpUdOY0lZMtFXxXqshjXQtPl26hfId8i9baDo0nsf4V/wBr6GsVhFFHFbW6BLeBBHEg6ADistb6DRZ9QXUHe3uZ7ubfd3asDcIJGEZ3twQE2gY44q1b3dvdx+ZbTxTJ/ejcMP0r6hR5I2R50Gt+pYrT09Ntvu7sc1lZqeK7lhwAxKj+E9KEbKSvc2aKjjlEsYdehp2aZpchuLG0uzuuLeORsbdxUZx6Z9Kg/sm1gmFxYxRWVwvHmQRKu4f3WA6r+o7EHmruaM01JoTjF9CncXOvRB/s6afcYUlQQ8ZY44UDJxn1zXP3MusazLBcRz291aOocadNEY4m4BDMQST/ALpyMnoMcdZ1GK5qSz1HQrn7TZxve2Sl/wBwpzJGrHOACeQBuxjnGARxuGsZt7kxhTV+ZGaPD2oI9u82l+H4pCQqs5YoJCM5wI+MnjlvQCuiudKaBD9uvJLwlhJDaxSiDnuoBb5/+BMRgAYGKrDxNcNpwRdLv/tYGCq2sqh/TDFRt+p6H86gH9qT2XkjSZLoB2aF9VaJfLUjGGKF2J69hwSBgVV31M5XbWugrwxwl7eCyEcCKpKspGGPYDAQ4HJIbr1qHQLI67eRacEzZ3M51G853AwqQsSEnqJTGGx/dDVpJoguoY11Sdp8DBhiZkh+hGcsMcfMSD6DpW74Ft0Ok3Gr4Bk1K4eVX24PkqSkS/TYoI/3j61nKajFtFYio3FQR1RIK15J498DfYjJq+kwn7MTuuIFH+r/ANpR/d9R2+nT1nNNPII7GuWNVwd0Ywbi7o+ZKASDkEivQPHXgY2DSarpMJNoSWmgQf6n/aX/AGfbt9Onn9d8JqaujsUlJXRr6T4k1TRmH2K9kiT/AJ5k7o/++Tx+I5rvNK+J0cgCarZmMkj99bfMv1KnkfgTXllOV2U8GpqUYT3QnBM+hLDVrDVYvNsLuKdB12Nyv1HUfjVkmvny3u2jmWWOR4pl5WWNirKfYjmuu0vx5q9mFW42X8SjpIdkn/fQGD+Iya4auCktYO5HLY9TJqMmsDTfGmj6kfLMzWs55MdyNp/A9D+dbuc8ivNqQlB2krFJAajanGmH1rBstIRqjpTTSaxky0hp60UUVBZrSTLBDJLISI0Us/BPA5PArzPTZftoudUMYjOoTG4CDHypgCMcd9gXPuTXpgNeeXVh/YviG50+EMLO4j+2Wy4+WMbsSIPYMVYDt5mO3PvYWS1XU86StJMlopKWukov6c5w6enIq/WZYf69v93/AArRpo0i9B1FNqtBn7TcZJ6jr+NA7luk4pKKAuLmsbVfEEWnytbxx+fcInmOu8Isa5ABYn3I4A/KtiuGh8P6rrWsazc2UlsV+0PbSCd2UkBgR93/AHVp6JXY1ruWH8Y3qkD+zkBYDBV2OcjI6D05qxpHjbUdC0ex0oaSHFrAkQZmYFgPlBIxx0P61G/gnxLIiLJNp7KkflAeZIBsxjbwP16+9M/4QTxCuFD6YqgEFQ78jDLjp0w7DtS9rTas2hOMHuan/CytS2b/AOx027tv32688dP9k/TFInxMvnR2GmW42EhgZyCCATjGM5wDx7VnN4F8RMBvfTSQeW8yQEjnA4A4+Y+namJ4B8TIk6Jc2ISZiZAJX5yCMfd96m9LyDkgan/CxdRdSP7FQ5O0gu3PXtj/AGT+VcBqEKXF5LcwWxtIXbIiXLKp7hTgccHjtXYf8IN4k8yWTzdO3SIykmWTjKspPTjh29qQ+BfEpaNjLpxKZxmR8YIORjGO5qoVIQ+Gw0orY4ltPlXqH56HYf8APek+wOPN3OF8o7X3cYPPH14P5V28fgPxCs6SyPp0myLydvmNgrgAfw89B9f5Mb4fa8WuNrWIWcguGnkJzgjrjnqetaLEruirrucZ/Z0+cbJcjAI8o8ZOB+tOS1uEAI34JAGYz1PT+Y/Metdm3gLxA8qSONLZkbcu53bnPOcjnPvn8Kpazo2q6ZHClzLYveSMTDbwNJJNMAqDCqBnH7tcsfzFONdydlYTlFatnPFZzA7uqmNMBt8ZAB7de/NaGm6rrOkDNleYhBGYP9Yp6nG0kkZwemOlaY8GeIryyUyraQs6BdskrF0UHIXIyP1P1qZfBniCM5WSwHGD+9k5GCMe3BPTFVNOSs0mLnh3LaeO9TZPm0tGZR8xXcOhweMevGKa/j6+VNzaYgUdTubjnHPFVf8AhDdf8xZC2nl1IOTI5zhtw7dj/wDXzUL+Btckt1hd7AhAQh3vlcnJxx3rn+pUm/hX4j549zQPjq9+X/iXwlmVXCiUlsNjbxjPOR+dIfHF/nnS19PvN3GfT0qGDwl4ghiSHzLAwqQ23e/JBB7ggZxzgc+hpv8Awh+uCZ3Q6fsaPyyju5GOOnHHI49OMdqj6jSvbkX4j9pHuaNr42bcv27TniibkyxktsGSORj1VvyrrEdHRXR1ZWGVI6EV59ceENeNvIZXsGRYyMeY5wAWOeRgn5m5NdX4OJl8J2DOckKyg57BiB+gFcGNwcacVOKt95cZ32OrBrjfFcwn8T6ZbIcPbW000px/C5RVX8ShP/ABXXg+tcZ4lBsvEy3lxhLO8tordZ2OFSVHkIUntuEnGe647jN4SzqHLVWhDRSlWHBBH1FJj5c9hXcIsWkqxTFnOFK4q99sg/vj8jXPy6lYQHE99axH/ppMq/zNPt7y0u8/ZbqC4x18mVX/AJGnZgpI25b2JUJRgzdgKbZA+W0rHLOc1Qij82VUB69fpWuqhQABwOBQVdjs0ZpKKB3F71V8Fcy69/2EpKs1ydv4nufCtprV8mk/brc6pIkj/aPL8onoSNp4J4odKVaLhDdilNRi2z08CsCC21uFpJWDOxu5mCl+PKxLsHLlT1jxhVx3zyav6FqcmqaZBNdRRW15JGJZLVZd7RK33d3QjI55Hr6VXTT9XiEwFyrq0zlFaRujTSPnjByEMajnjBx78cabg3GW5k5XV0Nkk1tgmI5UHnRE7VQkxeau7OT97ZnoPfAJwFjk11YV82Eb90e8IV2qhA345OXDbgB0wAec06S01s2duiX0JvFiP2gZ+XeSNpAAB2/fzyDyOoGKqxaV4gSNomuIQhuppiElfOxpXkCg46jcg6cAHnBxWvKvIhst6SdXNy0V/CUiwShJXJGFxkg8NuLjAyMAdO+3isSK11tpRJ9sikiLhhgnaykk5A/3dv8AEQMH5T1Ohqur6fo1us1/OIhI2yNApZ5W/uooyzH2ANZyhzPT8ClKy1LeKiuJ4LSB57iWOGFBl5JGCqo9STwKwDfeJNXwbS1i0S1YEeZdqJbg+4jU7FP+8zeu2lj8K2JnS51OWfVboHKy3zbwp/2YwAi+xCg+9axwjfxOxDq9iGXX77W28nw5GEt+Q2q3MZ8of9clODIf9rhfc9Km0vSbDSp5lhczX8iq9xcTvvnkHIBY9hwQAMDg4Arc2GsDU5J9GvPtqvB9iubiITvIdrRdE6ngqQB6EHPXPHdRpRjpFWM5Sd7s0zNEtwsBb966l1X1AIB/mKXncQVwB0OetU4ke51b7bIjxQrF5MAkXa0hJDMcHkD5QMEA/K3GME6OMVb0GmQke1U572OC4MbEBY4/NmkY4WJOQCfqQfyP43pYxLEyEsAwwSrFT+BHIrntW0O8kQXVre+ZewEPGbhRhwGDBG27QVyOCQSDyCDknSnyt6sbbWxq2ssk9usksfls5LKpzkLn5c55BIwcds4qfvWCup7b6G78uWRb+xSS1hA+YMvJX2yHXngfKc9BV3TrG5hS3kvZ1kuIrcQ4T7o+7uOTyxJUcnHTpyapwtqxp3LV0MWVxyT+7br9DWT4K/5FCw+j/wDobVr3f/Hlcf8AXNv5GsjwV/yKFh9H/wDQ2ryszf7pev8AmdmH6nTZpk0ENzA8E8UcsMgw8cihlYehB60oalBrx1LU0aMQeDdFVQsS38CAYCQ6lcIqj0Ch8Aew4p0fgzw+CDPYm9YdGvpnuMfQSEgfhW1mnA1v9YqveTMvZR7Fa10fS7IYtNNs7fP/ADygVP5CszxRpWjNod/f3mnQs9tbSSrNEgWZNqkjY45ByPWt3dSSKksTxyKrI6lWVhkEHqCD1FOFaSle4nTTRxeheabKFrhg1x5CeYw7tj5v1zWtWTfadN4SU3VoJLnQxxNDy0lmv95T1aMd1PKjkZAwNRZFkQOjKysMqynII9civTUlJc0diIvox1FJmkzQVccOtVfBlvDdr4jguIklhk1CRXjdQVYHqCO4p13eW9jbNcXU8cEK9XkYKP1o+HcqXCa3PHu2SX7Mu5SpwR6HkfjSnfkbE2mmjpX0izN++pR20MeomIxC6EY3YOOvr0HX6VnjUbjRbKztNdu2uLm7mNul3bWrKmScIX2n5SeOmOTgdCa6HFLtz1FYxl0lqv66mTXY5W58P6l5YQ3s1zCUANuGCg4EvBJ+XBMgyQuR5Y4J5FuTQb43Vu8OqyLFGqB0KklmUg78k8ZAIx1564GCtzv8Lw6hqbzapqVtNOshtgBJ9mDHDsn8W0ZzjJxj6mjXvEY063S3slEmoTx70WRSFhU/xyDgj2XgkgjoGI6OWcmlHW5ldJajE1C28N6dp2hJ5+oalBYqiW1rHl5BGmM45Cg7TjJ7Hrg4yNNlgsb+LUfEIuYdb1GRbdGuLSZI4yx+WCFiu0D3z8x59Kk8MLa+HrO88W65Kzu+4QNIR5lw2MFuw7bRjgDPQAVx2o3V14v1hNc1yRYLLf5dpG7ERxZAZSx52jBDZIOQVcq0YYV3Qw0YLXc53Vbemx66qpvKgrvAyQDzipPL9q53wze/2heS2l+pttWs3Ms1q8exiGBG8HJ3IeRwTggDJABPWhOOlZQUmnzKxpKS6Mo3FuZrWaJZGiaRCiyIfmQkYyPcVzsT3d7cxadNEJ7yzufNvXZ9sY43JsYAnnchAIyNjZOcE9DqkUk8lrZpIYkmkPnOjFX2KpOFYHIJOBkchdxGDgizDZQ2cCW9vEkMUYwscahVH0Arde6iOa7MGz0Zred7i6nFxMZHkQrGEVC3cDJ5wAuSc7VHTnN1lwavuntVd1rGV2aRZTkZYxliAD0rJ1+6ZdJ8q1kUXF6wtrduuGfjd/wFct/wGtiWLLxurlHjJZWGOOMd/rXNwomp+K8xvvtdGjMYweDcPw2fdU4PoXx2NFHm9o2/hWpo7cum7LNtpl3aWoiW7hExwr3K2/zlRnsWIyMnH8I7Ljin6daPZNcxsmU3hknJBeRcD756kg5GT2xyTmtRhUMmcDGcZGcHBx7cGtJVHyt2HGKuRXf/AB5T/wDXJv5VkeCv+RQsPo//AKG1atwSNPlDH5vJOeep21leCv8AkULD6P8A+htXmZm70Y+v+Z2YfdnQg0oNRZpwNeGpG1iUGlzUQNOzVKQrEmaXNR7qXdVXCw4hW+VgCrcEMMg157oOr6dY+GrI3eo20CbWMQmnVSItx8scnJwm2vQOCMHvxVOy0fStObdY6bZWzesECof0FdVDERppqSvcynTbaaOYTxFa3Q/4ltve6iwOP9EtmZf++yAn/j1WUsvEmoHAitdJgP8AHK32if8A75UhAf8AgTfSur49KWrljX9lWJVJ9WYth4V060uVu7jzdQvVOVubxg7If9hcBU/4CBR4JybvxF/2FZK2s1jeB+brxH/2FJKvD1JVObmd9vzCcVGOh1wFOpQKp3810phtbBEN3csVjeXPlxgDJZscnA6KOSeMgZYdEIOTsjllKyuypq2qyWziysESXUHUNhvuQIcjzH9uDherEcYAZl5yHTraGOS5vppDbq3mXM7kGSd/TPHJAHoFGAMAAV0h0+20u1lzKcH99cXM2N8jd3Y8DOFwOgAAAwBiuD1a+j125ijnb7Jpe4x23mOQsr+r8cA88nkHazKUOD61KlGlHzOKU3UfkU9Rv38T38d3qRS20dT5NmjcQg44DAcquBnnBOQ+GjBrRhtLqS+nt4rNF1WKLN7pFxhYNRgB+/Efuqd3PHAcknbubMVlHOt3NbRWIN3BEv8AaWhuoVbmAfdltyeBtPRc7QeAV4z1mgaJA9pbKs32vTLdxNp0khZbm0IODET1wMFeSCBlGBxTbuNKwvhzQYXgtJleaSytjvsGnyl1Z84e3Y/xIMEYPYYOcKR17lIYHlc4SNSzH2HNOjUAAdMVZWMMMEZzxRa4m7HF+JtRkTTI9YgiljfR5o72SJsfvYWVkcZBPOxnIz3UfWuljeO5t4riB1khlQOjr0ZSMgj2xWN47trfTvh/rC20MUImhEHyKAP3jLH/AOzVD8PrpbrwRYRhvntN9o6/3fLYquf+A7T+NVGnNUE56tMl1YOpyxNqRMg+tczrviHRdLDWV9cmW5ZQwtoFLyn04X7v1OBTfFXiaWO4Oh6Ewl1d8CR1wRag9z2Lnsv4njAPn8OnSwIzLBKxdg0kjAszs3dj3Y+9a0cKp+9M83MM2jhPdguaX4I1dW8XahqUTQaZbtp8DDBnlYGfHfaBkKfckn2B5rV8DWaWvhK1ZR807yTMepJZjjJ7naFH4VzEdvPKdscMjk44VST0z/LmtTw3q50cRaRqKPBbTuXsrl1IVtxyUJ7HJOD0OcdRztiKCjR5aa8zlyjNZ4jEtV3a607HVam06WLNbZ80PH0Xcdu9d3H+7mssXesJbsfJDsGIXdC2WAGe3TPbIHQ5wa3zg1GfSvMR9WjJke7lW48+FBEqOFO05/1anOc46lhjH8NVvBX/ACKFh9H/APQ2rXu/+PK4/wCubfyNZHgr/kULD6P/AOhtXnZp/CXr/mdmG6m1upwNMor5651WJM0uajyaXIpqQrEu6o2uoI3KvPGrDqGYA1h+KdVbTNKHlOVlnbywwOCoxkkfy/GuDXVAowpCjOcCvSwmBdeHO3ZGcnZnq/2y2/5+Yf8AvsUfbbb/AJ+Yf++xXmUN75tu0rT7fm2AcYz75YHH0Bp3mzA4MqAevzdMAk/QA5/PtzXT/Z0L29p+BPM+x6X9ttv+fmH/AL+Cj7bbf8/MP/fwV5qJJmbAnhOBuJ3nhefmz0xx9ajkuzHA0hnRirhCq5PXdznp/D2z1oWXQe1T8A5n2PTvttt/z8w/99iqPgMh5/ETKQQdUkII6GvNm1fapYvgAZJJ6frWz4P+I2laPBdLdWl84nmDrJFGhXG0DJBYN+QNdFLAukm4u9zKrK8bHsgFcbdaww+IUVwzTDTtKBt5BDE0m+WWJnPyqCTtAhAwOPMNat94v0u20KDU7SUX32v5bKGA/PcP/dAPTH8Wfu4OelYumRpoelh9TuYhd3UzTXMmcCWeQ7mC55PXAHXAFdFCDi+Zo4ZLm0KniXVpda1KPT8tZ2zYa2WdWQ3Dg5Bfj5RnG0EMMqA6/Miti21u9w1xGll5rxKqanoUg2llP3ZIDngjnaN2APlDfKtaiSp4ih1ex1LSbqN4ZFNnLISPO3BhlUIBTaOCf9rPBrX03SZkaEajILqazY/Zb5WIldCBlZMdeMA9mwDgEcXDEOcpJq1glQUFox2iaQk9raGe4+22tqyy6bduWS5RT1R+BkAfKc/eBwy5GTt6cL3zYGm87cUP2gSNld3GNo7e2OMVLEwIGDnFW42pShzyUr2sJS5U1YvRmrIkRF3MwVfUnFUUfFSOsc8XlyKrIcZBGQa6kzmaOd+Js4PhaG0PW7vreLA77XEh/SM1xVppM0XmG1vLy087HnC1naMSYGOcd8dxg+9dP4xm/tDxBpGlABltg9/Nx0JBjiH47pD/AMA+tXLOwBxxn+td9OXLTR4WOjKWIXI7NI5vT9CWyKJZ24GScJgncT1J9Tz1NbDWzoVE17bpIjhsKrucjbnJBAOSozz1z36brwC0g3LxNIMLjqB3P9PxrP8As3HXn60c7epz/V1HfVnK6nb3GlBLyFre5tAVjwocbCNhUMDyM+WOc84PtXPX9wdSjKXMcbqc7hjg5VV6fRB+tekmACOSN40kikXa6OOGH+e9cpr3h2K2ga+sN4hTiWBzkx9ACD3XPHqOOvbWE1fU83FYapFc9N6dUVfC2sTwXqaNdyNLFIpNnI5yy7eTGT3GOQfQEHtXQ3OoKLTUngBMtmrA5XI3iMOMAcnhh/KvPrjzVRJ7fBuLeRZogehZTnB9iMj6E12sMUOrWDXun3Ci11GLM0UiblfK7T0IKvgBTzjjp3rkxVGMZc/c+pyLHSxOH5ZO8o6f5E0N19q0mZs8CI7d7Zcrt4ZgB8pPJx6enIFTwV/yKFh9H/8AQ2qHT7WaXRpI76RGezkkA8kgpIwU/OTgEsdx3Hj5t3HapvBX/IoWH0f/ANDavCzZJU1bv/mfTYR3TNmiiivmjtCiiigDivHcJuNR0SBt4jleRTtODyU9j/I1yMumgW7zq00YRiCjAs3Tr91SB15wMZHFd/420iTVdD3QIXntm8xUAyWXGCB+h/CvKOnFfRZdLmopRdmjN7mw1tPaQTKl5dx7Wy6qhVSAG5HPOSvB6e4pLoXltcD/AEu7w0xUnJ5wxXg9GPHt2rIPIwelH+Oa71B31YjoIra7urqK3hu7lFADKd7MeSQTghT69cHHHPGYjZXU6Qwm9uXjYg7SCyqxCtkjPT95yfr61jLLIjFldgWGCQeo9/yH5U0kksScljkk96lU5LqBZ1OxddJluFZ3j37CpGM9eAe/3T0Faem6joK+Fb2CexMuoynNvcKOAO2D2xWH1rptE0LSb/wyzS2UUmoXOqwW8T852fLJJxnB/dq5yR39xVSp80VGT6mNWTguZF/wFYyhWuJZjbfbN62c/lhnaMfeWNmJVeQ7EbctncMhePQ7XT7W0laaOLMzDDTOxeQjsCzZOPbOOaLm1guLYwyLiMY27TtKEdCpHQjjGKoaZqdy13c2F1a3LNaFE+3eWBFOWGVwf7394AYB9sCrlJJXZxqOvqbo6U9TWVBeNbXd1bXkvyRp9ojmcY/dktkHHBKkfkV75NX4pldYyco0i7gjja2O/HXjIqZRsTe5diYDoMVZRqoK2KnV6lMlovhwRzjB65rJ1vxXp+gKsLlp711zDZw8yN6E9lX/AGm464yeKNW1eLRdIudQm+YQIWVAeXboqj3JwB9a8qshIkhuLl/NvJ28y4lPV3PX8PQdhXfhaPtPeeyPHzTMFg4KyvJ7f5naaFFcSz3F9fMsl/eSeZMVHC8YVF/2VGAPXknk120eLRNpAab+72X6/wCFcz4YIME10OXQqicdCc8/kP1ro7ePJ+bnuSe9dFTc87DSlNe0e7MvWvEFvo8sazqZ7mYbwG6Kuep+uOB7Vg6h44uGTbZbY29o1x+oro/EHhJPEBinScwXUabMldysuSQD0IPJ5/SqGmfDeKCZZdRu/tCg58mNNqn6nOSPypxdNK73MMRSx86jjT0i+pq2TPe6TaXjxKjzxK7BemT3Hsev41T1ZVh0fUZJPu/ZZF59WGF/8eIrppYgq8bVCj1wAB/SvNPF/iGK+f8As+xfdao26SQdJW7Y/wBkfqfwpQTk9DXGzjh6V5vW1vU5SrvhjSb27ea9ivrix02RziKFhmdgcM/Odg4xxgnGciqVbngzUF8qfRpSBJbs0sI/vxM2fx2sSPoVrXEuSpPlOThr2bxLUnrbQ6KSGO30uSGFAkaQsFA+lZngr/kULD6P/wChtWtdACxnA6eU38jWT4K/5FCw+j/+htXy2Zt+yXr/AJn6Lhups0UUV84dgUUUUAFUpdI0yeUyTafaSSMclmhUk/U4q7RTUnHZgZ/9haR/0C7L/vwv+FH9haR/0C7L/vwv+FaFFV7Wfd/eBn/2FpH/AEC7L/vwv+FH9haR/wBAuy/78L/hWhRR7Wfd/eBn/wBhaR/0C7L/AL8L/hWD4V0uH+39YvD0truWK3hAwkWT8zAepAUfQe5rrq5/wt/x+6//ANhKSvWymcpTld9DnxC9w6TqMGqtzcW9jslmUrGW+aXHyIQOGb0HbPTnkirVHWvbsnujju1sc7cLHc+XZo91LqFrK0sYIOPL8zcodjwUOxB13EpxnaauJqcj6kWmsrtDaR7HWJRInmPtbqOThQMcD7/NW2lNo7RwadK6ld2YdgDH05YHNSadBJb22JmBmkdpJNp4BY5wPUDgZx26DpWkpK17GXKyrP4iFsAx0jVpFPeO1LfpnP6VjSfEayaV4bXTb1rqM8xzlIdv1G4sP++a6mAzAozu5LKTIrBcK+eNuOoxnrTbzTbDUVC3tjbXIHTz4lfH5is6FWlJc04P7ya9OqlaErP0PP8AUNSvtdnjmv3jWGJt0NrDkojc/MxP32wTgkADJwOai+lXfEemWOi6rZR6cghW4SRpoEJ2jGNrgfw8kjjGfwqlkV7lFxdNOCsj87ziFaGJca0uZm/4d13+zJmjlUvBIMOoODx0I9xz+dd3aa3pUqjZfKCR0dGBH6EfrXkjMERpGbCKMljxj61YsW1S+UNpun3FzF2mbEUZ9wzY3D3ANRUhHduxrl1fFNezpw5kex/8JDpUJOboOcdERj/SqF544tolItrdnIHBdgB+Qrgv7I8R7Nxj0tBj7pu3P5kRVnXlpr1tua5015Ihz5lpKJh+XDH/AL5rGMaTfxHr1nmUYXVO3pY1Nd8UahqoaKSfETdY4/lU/X1/HNYumaTqmsxrParDbWb52XE4LNIPVUGOPckeuCKzLiRL2wkSCUHziIA3dSxC8jqCM969SijjghSGJdscahFX0A4FViKroxSjuzHJ8AsbOdXFXdnazORPgq92nOtjf/16Db+W7+tZV/4b16x2Xtg8F5LbNvSSMGOQEdRsJIYEcY3c+lei0fhXJHGVVvqfSLKsJFqUIWa6oxdM1uPXdBnuAjRXEavFcwP96KUD5lP+f14pngr/AJFCw+j/APobU26Nnb+IboJNDHPc6eTNHvALlThGx64Zh+XpTvBWP+EQsPo//obV4+bJezTXf/M9jCXs7mzRRRXzJ2hRRRQAUUUUAFFFFABRRRQAVydvfp4Z8Q38Oo5js9Ql+0Q3GPlDH7yn8/0966yop4IbmF4p4o5YzjKOoYH8DXVhMU8PPmtdMicFJWZTbxForKV/ta0X3Ey5pR4j0T/oLWf/AH+Wo/8AhHtG/wCgVZ/9+F/wo/4R7Rv+gVZ/9+V/wr1f7Vh/KzD6su5J/wAJHomMf2rZ/wDf5aX/AISTRP8AoK2f/f5ai/4R7Rv+gVZ/9+V/wo/4R7Rv+gVZ/wDflf8ACj+1YfysPqy7k/8Awkuif9Baz/7/AC1l65460/TbZVsGS/u5TtjSNxsHu7dAP1+nWrv/AAj2jf8AQKs/+/K/4Uq+H9HKk/2XZ8f9MV/wprNqad3C5Lwqtozi7WwjvriS+1rxbYJdzEbxblWIUdFDMcAD0C/ietag0zwwFwPFdxn1+0Qfy8vFb3/CP6MeTpdn/wB+V/wpf+Ee0b/oFWf/AH5X/Ctnn8nok19xyvJsNJ80opt91cx7Wy8GwTJLPqkN86HK/a7pXUH12DC/pXQ/8JPofT+1rP8A7/L/AI1W/wCEe0b/AKBVn/35X/Cl/wCEe0b/AKBVn/35X/CsZZzGbvJNm9PA06StBWXkTt4l0Nhg6rZkY/57LSf8JLomMDVrMDp/rlqH/hHtG/6BVn/35X/Ck/4R7Rv+gVZ/9+V/wqf7Vp/ys0+rLuc94oOi3y/2lpuo2K6nE6SlROqi52sG2t78cH8M4PHQW/inRbi3jmOo28RdQTHJKoZfY89aX/hHtG/6BVn/AN+V/wAKP+Ee0b/oFWf/AH5X/CtJZzGUVFxehKwcIvmXUf8A8JHouQf7Ws8enmrSP4i0Zo2CavZK2OCZVOD9M03/AIR7Rv8AoFWf/flf8KP+Ee0b/oFWf/flf8Kj+1oL7LL+rJ9Tmv7Zj07T2gtr6K+v5laELAvmeexztkLdiu4g5yWwOAOnVaBZPpehWllICZI0+fHOGJJI/M1LZ6Vp9mxe1sreFiOWjjCn8xVquLHZg8TZJaI0pUlTVkf/2Q==" data-filename="18.jpg" style="width: 235px;"><br></p><p class="text-justify">The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.</p> <p class="text-justify">Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.</p> <p class="text-justify">It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients. </p> </div> </div> </div> </div> </div> <div class="panel panel-default"> <div class="panel-heading"> <h3 class="panel-title"> <a class="accordion-toggle" data-toggle="collapse" data-parent="#accordion1" href="#collapseNine1" aria-expanded="true"> Design and Analysis of Bioinspired Motion Detection and Velocity Estimation Algorithm and Architecture for Autonomous Navigation of Mavs. <i class="fa fa-angle-right pull-right"></i> </a> </h3> </div> <div id="collapseNine1" class="panel-collapse collapse in" aria-expanded="true"> <div class="panel-body"> <div class="media accordion-inner"> <div class="pull-left"> </div><div class="pull-left"> </div> <div class="media-body"> <h4></h4> <p class="text-justify"><br></p><p class="text-justify">Highly accurate real-time stabilization and navigation of UGVs, MAVs, humanoids and vehicles is a major research focus of robotics and automation. Research on autonomous navigation and guidance is influenced by the anatomy of insect’s eyes. A fly’s panoramic vision system comprises at its front end several thousand photoreceptors feeding into a 2D array of motion detecting neurons which the animal uses for dynamic visuo-motor pose and gaze stabilization and navigation. Insects such as fly possess a visual system that is fast, precise and reliable hence, they are able to execute flawless landing on the rim of a container, instantaneously avoid obstacles while flying.</p> <p class="text-justify">Insects have immobile eyes with fixed-focus optics, the eyes are also positioned very close hence possess inferior spatial acuity. The behavior of flying insects is dominated by visual control and hence insects use visual feedback to stabilize flight, control speed and measure self motion. Highly accurate real-time stabilization and navigation of UGVs of MAVs is major research interest as these systems are used for surveillance, security, search and rescue mission. Thus design, modeling and implementation of Bioinspired visual system on UGVs and MAVs could be an accessible methodology to replace the traditional image processing algorithms in controlling flying robots.</p> </div> </div> </div> </div> </div> </div><!--/#accordion1--> </div>', 'workshop_seminars' => '<p></p><p><br></p><thread></thread><table class="table table-bordered table-striped" style="line-height: 1.42857;"><tbody><tr><th><span style="font-family: Times New Roman;">Sl No</span></th><th><span style="font-family: Times New Roman;">Name</span></th><th><span style="font-family: Times New Roman;">Funding Agency</span></th><th><span style="font-family: Times New Roman;">Date</span></th></tr><tr><td><span style="font-family: Times New Roman;">1</span></td><td><span style="font-family: Times New Roman;">2nd National Conference on Emerging Trends in Engineering Technology and Applied Research</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 13th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">2</span></td><td><span style="font-family: Times New Roman;">Project Exhibition </span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 13th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">3</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest lecture on Advanced Microprocessor Programming </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">May 3rd 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">4</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Workshop on Microsoft Day –Future Technologies </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Apr 4th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">5</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Smart Ways of Cracking Competitive Examination </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"><span style="background-color: rgb(249, 249, 249);">Mar 30th 2016</span><br></span></td></tr><tr><td><span style="font-family: Times New Roman;">6</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Carrier Options in Electronic industries</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Mar 9th 2016<br></span></td></tr><tr><td><span style="font-family: Times New Roman;">7</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Industrial Visit to Keltron, Trivandrum, Kerala </span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"><span style="background-color: rgb(249, 249, 249);">Mar 5th 2016</span><br></span></td></tr><tr><td><span style="font-family: Times New Roman;">8</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Workshop on Industrial Automation using PLC and SCADA</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Mar 2nd 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">9</span></td><td><span style="font-family: Times New Roman;"><span style="font-size: 12pt; line-height: 115%;">Guest Lecture on Optical Fiber Transmission System</span><br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Feb 17th 2016</span></td></tr><tr><td><span style="font-family: Times New Roman;">10</span></td><td><span style="font-family: Times New Roman;">Emerging Trends in Engineering Technology and Applied Research(NCETAR-15)</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">July 10th 2015</span></td></tr><tr><td><span style="font-family: Times New Roman;">11</span></td><td><span style="font-family: Times New Roman;">Embedded System Development using ARM Cortex M3MSET/SIMS</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">30 & 31 Oct, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">12</span></td><td><span style="font-family: Times New Roman;">Empower 10,000 VLSI Design Course VTU<br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">Sept 2014 to Nov 2014 </span></td></tr><tr><td><span style="font-family: Times New Roman;">13</span></td><td><span style="font-family: Times New Roman;">Embedded System Design <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">9 April, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">14</span></td><td><span style="font-family: Times New Roman;">Research Process, Technical Paper Writing and Patenting <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">22 - 24 jan, 2014</span></td></tr><tr><td><span style="font-family: Times New Roman;">15</span></td><td><span style="font-family: Times New Roman;">Empower 10,000 Embedded System Design Course <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">1 Dec, 2013 to 9 Mar</span></td></tr><tr><td><span style="font-family: Times New Roman;">16</span></td><td><span style="font-family: Times New Roman;">First State Level Project Competition cum Exhibition <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">10 May,2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">17</span></td><td><span style="font-family: Times New Roman;">FPGA for signal and image processing Applications <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">7 - 9, feb 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">18</span></td><td><span style="font-family: Times New Roman;">Recent Trends in Nano/MEMS Technologies DST</span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">7 & 8, Oct 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">19</span></td><td><span style="font-family: Times New Roman;">VLSI Design Lab using Open Source EDA Tool <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"> 24 & 25, July 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">20<br></span></td><td><span style="font-family: Times New Roman;">VLSI System on Chip Design & Validation <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;">10 - 13, July 2013</span></td></tr><tr><td><span style="font-family: Times New Roman;">21</span></td><td><span style="font-family: Times New Roman;">Towards VLSI <br></span></td><td><span style="font-family: Times New Roman;">MSEC</span></td><td><span style="font-family: Times New Roman;"> 6 & 7, may 2009 </span></td></tr></tbody></table><p></p><p><br></p><p><br></p><p> </p><p></p>', 'placements' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Year</th><th>Name</th><th>Company</th></tr> </thead> <tbody> <tr><td>1</td><td>2011-12</td><td>Sunil kumar</td><td>L&T Infotech</td></tr> <tr><td>2</td><td>2011-12</td><td>V. S. Sudha</td><td>L&T Infotech</td></tr> <tr><td>3</td><td>2011-12</td><td>Praveena C. K.</td><td>Dell International</td></tr> <tr><td>4</td><td>2011-12</td><td>Karthika S.</td><td>Unisys Global services Ltd</td></tr> <tr><td>5</td><td>2013-14</td><td>Shruthi R.</td><td>24/7 Customer Ltd</td></tr> <tr><td>6</td><td>2013-14</td><td>Arun A. T.</td><td>HCL Technologies</td></tr> <tr><td>7</td><td>2014-15</td><td>Meghana Halkude</td><td>Good Through</td></tr> <tr><td>8</td><td>2014-15</td><td>Akash Roy</td><td>Microland</td></tr> <tr><td>9</td><td>2014-15</td><td>Akarshitha Shekar</td><td>Microland</td></tr> <tr><td>10</td><td>2014-15</td><td>Jane Karen</td><td>IBM</td></tr> </tbody> </table>', 'testimonials' => '<div class="media"> <div class="media-left"> <a href="#"> </a> <a href="#"><img class="media-object img-circle" src="/files/ece/testimonials/1.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Joshua James</h5><p>I am the student of the college ..i am truly fortunate enough to be a part of MSEC educational institute …the ECE department is brilliantly splendid the conceptual and teaching capability of faculty is unparalled….the labs of the institute provide first hand knowledge of the theoretical matters…the support and guidance of the teachers and the department is truly praise worthy….i recommend MSEC for all those who don’t comprise anything less than the Best</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/2.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Rahul G.</h5><p>I am the student of the college m s engineering college, it’s a great honour to be the student of msec.. this institution enhances the thinking out of the box capability.. we have a very good support from R&d to make a innovative project.. our faculties are supportive in every way to make us a better engineers…</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/3.jpg" alt="..."> </a> </div> <div class="media-body"><h5>Latha A.</h5><p>I the student of M. S. Engineering College very glad to do my graduation here.As all the facilities provided by college is extremely good. And I am very impressed of the college’s environment provided with greenery. All the faculties in this college are very supportive towards the students.</p> </div></div><div class="media"> <div class="media-left"> <a href="#"> <img class="media-object img-circle" src="/files/ece/testimonials/4.jpg" alt="..."> </a> </div> <div class="media-body"><h5>J. Supraja</h5><p>Being proud of saying I am a student of M.S.ENGG coll I would like to say that studying in a environment like would surely bring success for future it has been my privilege to tell that the lectures of my department are the best of all creativity along with knowledge and dedication I think there is no difference between the teachers kids and us.</p> </div></div>', 'alumni' => '<table class="table table-bordered table-striped"> <thead> <tr><th>Sl No</th><th>Batch</th><th>Alumini List</th></tr> </thead> <tbody> <tr><td>1</td><td>2007-2011</td><td><a href="/files/ece/alumni/Alumni2010.pdf" target="_blank">View</a></td></tr> <tr><td>2</td><td>2008-2012</td><td><a href="/files/ece/alumni/Alumni2012.pdf" target="_blank">View</a></td></tr> <tr><td>3</td><td>2009-2013</td><td><a href="/files/ece/alumni/Alumni2013.pdf" target="_blank">View</a></td></tr> <tr><td>4</td><td>2010-2014</td><td><a href="/files/ece/alumni/Alumni2014.pdf" target="_blank">View</a></td></tr> <tr> </tr></tbody> </table>', 'contact' => '<address> <h5><span style="font-weight: bold; font-size: 14px;">Dr. Venkateshppa</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Professor & Head</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Department of Electronics & Communication Engineering</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">M S Engineering College, Bangalore</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Email: hod.ece@msec.ac.in</span></h5> <h5><span style="font-weight: bold; font-size: 12px;">Ph: +91-9980261535</span></h5> <div><br></div> </address>', 'created' => '2015-06-18 03:30:05', 'modified' => '2020-10-14 08:32:20' ), 'User' => array( 'password' => '*****', 'id' => null, 'username' => null, 'email' => null, 'role' => null, 'created' => null, 'modified' => null ) ) $title_for_layout = 'Electronics and Communication Engineering'include - APP/View/Departments/view.ctp, line 51 View::_evaluate() - CORE/Cake/View/View.php, line 971 View::_render() - CORE/Cake/View/View.php, line 933 View::render() - CORE/Cake/View/View.php, line 473 Controller::render() - CORE/Cake/Controller/Controller.php, line 963 Dispatcher::_invoke() - CORE/Cake/Routing/Dispatcher.php, line 200 Dispatcher::dispatch() - CORE/Cake/Routing/Dispatcher.php, line 167 [main] - APP/webroot/index.php, line 118
Sl No | Name | Qualification | Specialization | Designation | Profile |
---|---|---|---|---|---|
1 | Dr. Cyril Prasanna Raj P. | M.Tech, PhD | VLSI Design and Image Processing | Prof. Dean R & D | View |
2 | Dr. Venkateshappa | M.Tech, Ph.D | Power Electronics | Professor | View |
3 | Mrs. Sunitha P. H. | M.Tech, (Ph.D) | Industrial Electronics | Asso. Professor | View |
4 | Mrs. Tejaswini C. | M.Tech, (Ph.D) | Biomedical instrumentation | Asso. Professor | View |
5 | Mrs. Azra jeelani | M.Tech, (Ph.D) | Electronics | Asso. Professor | View |
6 | Mrs. Savitha S. C. | M.Tech | Electronics | Asst. Professor | View |
7 | Mr. Nagayya S. Hiremath | M.Tech | Power Electronics | Asst. Professor | View |
8 | Mrs. Mangalagowri | M.Tech, (Ph.D) | VLSI and Embedded system | Asso. Professor | View |
9 | Ms. Azarathamma S. | M.Tech, (Ph.D) | VLSI Design | Asst. Professor | View |
10 | Ms. Natya S. | ME,(Ph.D) | Control System | Asso. Professor | View |
11 | Ms. Sushma G. Vasu | M.Tech | VLSI and Embedded System | Asst. Professor | View |
12 | Ms. Pavithra S. G. | M.Tech | Power Electronics | Asst. Professor | View |
13 | Mrs. Divya S. Dechamma | M.Tech | VLSI Design and Embedded system | Asst. Professor | View |
14 | Mr. Chaluvaraj | M.Tech | VLSI Design and Embedded system | Asst. Professor | View |
15 | Mrs. Asha Rani N. | M.Tech,(Ph.D) | Bio Medical Signal Processing | Asst. Professor | View |
16 | Ms.Rekha N. | M.Tech,(Ph.D) | Digital Electronics | Asst. Professor | View |
Analog Electronics lab provides basic knowledge of electronic devices like diodes, transistors, and elementary circuits. This lab includes various kits like characteristics of diode, transistor, TRIAC. DIAC, FET etc
Logic design lab is very useful for the students for realising the logic circuits like counters, multiplexer ,adders , sequence generator etc. In this lab major equipment used are Digital IC trainer kit , Digital IC tester. The logic design lab helps students to understand basic digital components and its application
The most widely used instruction set for 8-bit microcontrollers (MCUs), the 8051 core has a long history and a tremendous, widely used code base. This lab introduces students to the elementary programming techniques, interfacing and designingsimple applications using microcontroller 8051
Hardware Description language students will be able to analyze and evaluate VHDL & Verilog concepts. They are capable of designing and creating test with their complex system components. First implement an encryption algorithm using a standard hardware description language; then wrap the security module as a peripheral attached to bus; design an interface between peripheral and bus; apply an FPGA design flow for VLSI
Advance Communication lab provides Basic knowledge on multiple duplexing ex, TDMA, FDMA and advance communication techniques. Modulation and Demodulation techniques for long distance channel with low power transmission.
To give students an introduction to real-time DSPrequirements by exposing them to the use of someeducational DSP kits with realtime capability, which will help them get acquainted with the programming of theses devices and some typical hardware and functions found in practical applications such as I/O interface cards (A/D, D/A, I/O filters), types of DSP processors and their different characteristics, interrupts, etc.
Digital Communication Lab provides practical knowledge on FSK, ASK, etc. The goal of this lab is to understand a simple modem, the Frequency Shift Keying (FSK) Modem, referred to by the International Telecommunications Union (I.T.U.)
Microprocessor lab introduces the student with 8/16 bit microprocessor 8086. In this lab students will get exposed to basic instruction set, Architecture of 8086 , Addressing mode , Editing , Debugging the software programs like Data movement, Logical and arithmetic , Loop and branch , interrupt programming etc. The students get knowledge about interfacing the hardware kits like stepper motor, logic controller , display , Keyboard with 8086 Microprocessor.
VlSI Lab provides the student basic VlSI design concepts using CAD tool called cadence. Creating Verilog code for digital system and verify by using test bench also how to design analog circuits and layout for it. Verifying layout using DRC and LVS check. The students will get expose to industry handled tool and real time projects.
Power electronics lab gives the idea of characteristic features high power semiconductor devices like SCR,MOSFET and IGBT. This lab syllabus discuss about the converters, inverters and motors like DC motor, Universal motor and stepper motor. Experiments are conducted on triggering circuits like UJT and RC triggering circuits.
Home land security, border security, remote sensing, surveillance and tracking are some of the primary application areas where micro air vehicles play a vital role. Due to geographical challenges, rough terrains and unpredictable environments and climatic conditions humans beings are finding it difficult to monitor and provide security across the border as well as within home land. Use of micro air vehicles are the only possible solutions in near future.
Cameras that are mounted on micro air vehicles reduces payload and eliminates multiple sensors. However images/video sequences captured occupy huge bandwidth and hence need to be compressed and transmitted to base station for processing. As MAVs need to operate in day light and night conditions, IR cameras and thermal cameras along with visible light camera is used to acquire data. The acquired data is compressed and transmitted to the base station, at the base station the image registration and fusion is performed to extract information for monitoring and control.
With the growth in VLSI technology leading to nanometer transistors 3D VLSI IC technology is gaining momentum for high speed and low power signal and image processing applications. Medical imaging and aerial imaging are the major applications where 3D imaging plays an important role with image registration. In this research work, 3D architectures that are parallel, pipelined and systolic architectures are analyzed for their performances. Image registration algorithms that are used for 3D images are also analyzed for their performances, suitable algorithms for image registration based on Wavelet Transform approaches will be identified and implemented using 3D architectures optimizing for area, power and speed performances.
Image registration helps physicians monitor the progress of cancerous tissue. Better registration techniques could give physicians new and more effective ways of monitoring and treating the millions of patients suffering from cancer. Also, image registration would be useful for more precise targeting of radiation therapy against tumors. Better image registration could also lead to improvements in image-guided surgery – a surgical procedure where the surgeon uses indirect visualization to operate. . Turning this data into information requires image registration to be accurate enough to consistently compare images across time and modalities.
Paralytic patients are also called as “locked-in” patients. Because of a stroke, traumatic brain injury, cerebral palsy or a degenerative neurological disease such as amyotrophic lateral sclerosis, their entire motor system is paralyzed. These patients are fully conscious and alert, but are unable to use their muscles; they are therefore unable to communicate their needs, wishes and emotions. In these patients a healthy brain is actually locked into a paralyzed body. There is no cure, and the cause of amyotrophic lateral sclerosis, one of the major causes of locked-in syndrome, is still unknown.
This research aims to investigate intelligent systems which facilitate development of assistive robotic device for people with severe movement disability such as in locked-in patients. The project objective investigates a brain-computer interface (BCI) that allows a paralytic patient person to control robotic devices by thought alone. The research primarily involves developing advanced signal processing algorithms to extract information from BCI tasks-related electroencephalogram (EEG), commonly known as brain-waves, and requires investigations into signal pre-processing, feature extraction and classification aspects using innovative statistical methods and computational intelligence approaches.
Efficient design and implementation of wireless sensor networks has become a hot area of research in recent years, due to the vast potential of sensor networks to enable applications that connect the physical world to the virtual world. WSNs are usually composed of small, low cost devices that communicate wirelessly and have the capabilities of processing, sensing and storing By networking large numbers of tiny sensor nodes, it is possible to obtain data about physical phenomena that was difficult or impossible to obtain in more conventional ways. In the coming years, as advances in micro-fabrication technology allow the cost of manufacturing sensor nodes to continue to drop, increasing deployments of wireless sensor networks are expected, with the networks eventually growing to large numbers of nodes.
Wireless sensor networks are emerging as one of the most challenging technologies to meet the communication requirements and data monitoring requirements in several time critical applications. Recently ITU has proposed new set of protocols for wireless sensor networks and road map indicates that in another few years there will be high data rate and data transfer over wireless sensor networks. Software implementation and validation have been successfully accomplished by many of the researchers for demonstration of WSN capabilities. However, for real time implementation and practical purpose there is a need for hardware platforms. In this work, two major research activities are taken up:
A total 3, 90,884 accidental deaths were reported in the country during the year 2011. A total of 6, 94,390 cases of Un-Natural Accidents have caused 3, 67,194 deaths and rendered 5, 06,348 people injured during 2011. The major un-natural causes of accidental deaths were Road Accidents (37.3%), Railway Accidents and Rail-Road Accidents (7.6%), Poisoning (8.0%), Drowning (8.1%), Sudden Deaths (7.3%) and Fire Accidents (6.7%). 29708 deaths have occurred during the year 2011 due to drowning (boat capsize). Recovering the bodies from the deep water is a herculean task, as trained divers are required to dive deep into the water, identify the body, and carefully remove the body from the bottom. Currently there are very limited solutions to detect the body without diving into the waterfront. Divers need to swim underneath the water and with trial and error locates the bodies and recover them.
In this research work, we propose a through water imaging equipment that can scan the water front in defined areas and generates images of the water bed indicating the location of drowned bodies. In order to achieve higher performance and reliability an array of sonar signals are transmitted and received. The received signals are processed to generate images, using which human bodies are detected. The received signals need to be preprocessed before information retrieval could happen. Noise plays an important role in distorting the underwater images. One of the major source of noise is the speckle noise, that need to be filtered from sonar images.
Through-the-Wall radar imaging (TWRI) is emerging as a viable technology for providing high quality imagery of enclosed structures. The ability to locate moving targets inside a building with a sensor situated at standoff range outside the building would greatly improve situational awareness on the urban battlefield.
Through wall imaging technique is required for time critical applications such as disaster management, rescue operations and terrorist tracking behind walls. Micro air vehicles are found to be used as mobile surveillance unit to track terrorists hiding. Detection of human motion behind walls needs to be carried out within few microseconds or milliseconds. TWI techniques are mostly software oriented and hence there is a need for SoC that can process data and retrieve information in real time. In this work, novel algorithms will be developed to identify human motion behind walls and suitable architectures designed for high speed data processing. In the proposed research work, the architecture shown in Figure 2 is modified for human body detection in motion using digital UWB. The modified algorithm will be implemented on FPGA for time critical applications.
The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.
Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.
It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients.
The field of Brain-Computer Interfaces (BCIs) has gained enormous popularity during the last few years. The Brain Computer Interface (BCI) systems enable people suffering from severe neuromuscular disorders to operate devices and applications through their mental activities . Bio-signals can be acquired from an organ or a nervous system. The Brain Computer Interface (BCI) system involves recording and analyzing the Electro-Encephalogram signals from brain using electrodes.
Monitoring of the user's brain activity results in brain signals (e.g. electric or hemodynamic brain activity indicators), which are processed to obtain features that can be grouped into a feature vector. The latter is translated into a command to execute an action on the BCI application (e.g. wheelchair, cursor on the screen, spelling device).The result of such an action can be perceived by the user who can modulate her/his brain activity to accomplish her/his intents.
It is identified that there is a need for novel algorithms for emotion classification that can achieve more than 70% accuracy. Also it is required to classify emotions in abnormal patients those who suffer from neurological disorders. In this proposed research work, novel algorithms that combine neural network approaches and frequency domain approaches will be developed for emotion classification in abnormal patients.
Highly accurate real-time stabilization and navigation of UGVs, MAVs, humanoids and vehicles is a major research focus of robotics and automation. Research on autonomous navigation and guidance is influenced by the anatomy of insect’s eyes. A fly’s panoramic vision system comprises at its front end several thousand photoreceptors feeding into a 2D array of motion detecting neurons which the animal uses for dynamic visuo-motor pose and gaze stabilization and navigation. Insects such as fly possess a visual system that is fast, precise and reliable hence, they are able to execute flawless landing on the rim of a container, instantaneously avoid obstacles while flying.
Insects have immobile eyes with fixed-focus optics, the eyes are also positioned very close hence possess inferior spatial acuity. The behavior of flying insects is dominated by visual control and hence insects use visual feedback to stabilize flight, control speed and measure self motion. Highly accurate real-time stabilization and navigation of UGVs of MAVs is major research interest as these systems are used for surveillance, security, search and rescue mission. Thus design, modeling and implementation of Bioinspired visual system on UGVs and MAVs could be an accessible methodology to replace the traditional image processing algorithms in controlling flying robots.
Sl No | Name | Funding Agency | Date |
---|---|---|---|
1 | 2nd National Conference on Emerging Trends in Engineering Technology and Applied Research | MSEC | May 13th 2016 |
2 | Project Exhibition | MSEC | May 13th 2016 |
3 | Guest lecture on Advanced Microprocessor Programming | MSEC | May 3rd 2016 |
4 | Workshop on Microsoft Day –Future Technologies | MSEC | Apr 4th 2016 |
5 | Guest Lecture on Smart Ways of Cracking Competitive Examination | MSEC | Mar 30th 2016 |
6 | Guest Lecture on Carrier Options in Electronic industries | MSEC | Mar 9th 2016 |
7 | Industrial Visit to Keltron, Trivandrum, Kerala | MSEC | Mar 5th 2016 |
8 | Workshop on Industrial Automation using PLC and SCADA | MSEC | Mar 2nd 2016 |
9 | Guest Lecture on Optical Fiber Transmission System | MSEC | Feb 17th 2016 |
10 | Emerging Trends in Engineering Technology and Applied Research(NCETAR-15) | MSEC | July 10th 2015 |
11 | Embedded System Development using ARM Cortex M3MSET/SIMS | MSEC | 30 & 31 Oct, 2014 |
12 | Empower 10,000 VLSI Design Course VTU | MSEC | Sept 2014 to Nov 2014 |
13 | Embedded System Design | MSEC | 9 April, 2014 |
14 | Research Process, Technical Paper Writing and Patenting | MSEC | 22 - 24 jan, 2014 |
15 | Empower 10,000 Embedded System Design Course | MSEC | 1 Dec, 2013 to 9 Mar |
16 | First State Level Project Competition cum Exhibition | MSEC | 10 May,2013 |
17 | FPGA for signal and image processing Applications | MSEC | 7 - 9, feb 2013 |
18 | Recent Trends in Nano/MEMS Technologies DST | MSEC | 7 & 8, Oct 2013 |
19 | VLSI Design Lab using Open Source EDA Tool | MSEC | 24 & 25, July 2013 |
20 | VLSI System on Chip Design & Validation | MSEC | 10 - 13, July 2013 |
21 | Towards VLSI | MSEC | 6 & 7, may 2009 |
Sl No | Year | Name | Company |
---|---|---|---|
1 | 2011-12 | Sunil kumar | L&T Infotech |
2 | 2011-12 | V. S. Sudha | L&T Infotech |
3 | 2011-12 | Praveena C. K. | Dell International |
4 | 2011-12 | Karthika S. | Unisys Global services Ltd |
5 | 2013-14 | Shruthi R. | 24/7 Customer Ltd |
6 | 2013-14 | Arun A. T. | HCL Technologies |
7 | 2014-15 | Meghana Halkude | Good Through |
8 | 2014-15 | Akash Roy | Microland |
9 | 2014-15 | Akarshitha Shekar | Microland |
10 | 2014-15 | Jane Karen | IBM |
I am the student of the college ..i am truly fortunate enough to be a part of MSEC educational institute …the ECE department is brilliantly splendid the conceptual and teaching capability of faculty is unparalled….the labs of the institute provide first hand knowledge of the theoretical matters…the support and guidance of the teachers and the department is truly praise worthy….i recommend MSEC for all those who don’t comprise anything less than the Best
I am the student of the college m s engineering college, it’s a great honour to be the student of msec.. this institution enhances the thinking out of the box capability.. we have a very good support from R&d to make a innovative project.. our faculties are supportive in every way to make us a better engineers…
I the student of M. S. Engineering College very glad to do my graduation here.As all the facilities provided by college is extremely good. And I am very impressed of the college’s environment provided with greenery. All the faculties in this college are very supportive towards the students.
Being proud of saying I am a student of M.S.ENGG coll I would like to say that studying in a environment like would surely bring success for future it has been my privilege to tell that the lectures of my department are the best of all creativity along with knowledge and dedication I think there is no difference between the teachers kids and us.