<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0" xmlns:media="http://search.yahoo.com/mrss/"><channel><title><![CDATA[GAUGE NEWSLETTER]]></title><description><![CDATA[Engineering Students' Publication Society | Gauge]]></description><link>https://gauge.fly.dev/</link><image><url>https://gauge.fly.dev/favicon.png</url><title>GAUGE NEWSLETTER</title><link>https://gauge.fly.dev/</link></image><generator>Ghost 5.17</generator><lastBuildDate>Thu, 23 Apr 2026 08:50:29 GMT</lastBuildDate><atom:link href="https://gauge.fly.dev/rss/" rel="self" type="application/rss+xml"/><ttl>60</ttl><item><title><![CDATA[ESCAL: Pioneering the Future of Computer Engineering at Peradeniya]]></title><description><![CDATA[<p>The University of Peradeniya is the oldest and most highly acclaimed university in Sri Lanka. The Faculty of Engineering is one of the faculties which engages in extensive research while training highly qualified engineers. To add more value to the Faculty, the Department of Computer Engineering had formed a group</p>]]></description><link>https://gauge.fly.dev/escal/</link><guid isPermaLink="false">652cdcb16304750107fa66af</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Mon, 16 Oct 2023 08:37:46 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/10/image9.png" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/10/image9.png" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya"><p>The University of Peradeniya is the oldest and most highly acclaimed university in Sri Lanka. The Faculty of Engineering is one of the faculties which engages in extensive research while training highly qualified engineers. To add more value to the Faculty, the Department of Computer Engineering had formed a group and built a lab for students to engage in research and development activities in Computer Architecture and Embedded systems. &#xA0;This is introduced as &#x201C;ESCAL (Embedded Systems and Computer Architecture Laboratory) - one of the greatest research and development centres in Sri Lanka, at the University of Peradeniya.</p><p>The ESCAL group has been in effect for over 15 years at the University of Peradeniya with the aim of enhancing our country&apos;s capacity to produce engineering graduates equipped with advanced knowledge in upcoming tech and computer architecture-related advancements. Since its establishment over 15 years ago, the ESCAL group at the University of Peradeniya has remained committed to fostering the development of our country by nurturing engineering graduates with in-depth expertise in emerging technologies and computer architecture-related advancements.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/8vpYVAM6DQSbumnuidMZ39RHxorWXWBMzT8QF_rnc-sTL6N3DHP0QwEFpNBOunwMX9KKr_ieYevF6T00rcfacYRmsJx_1006YwtQGIep9FC_ZfsgDA5VeDrsxprV8KM1GAsQmqZTvatCdAJxGzU0XQ" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="597" height="267"></figure><p><br>The group&apos;s inception can be traced back to a defining moment in October 2006, when a passionate PhD graduate named Roshan Ragel, brimming with dreams, dedication, and enthusiasm, embarked on a journey. This individual, one of the three lecturers in the Department of Computer Engineering at the time, was determined to provide unparalleled service to the Department, Faculty, University, and the entire nation. Fueled by unwavering confidence, the goal of delivering excellence was at the core of his mission.</p><p>He was travelling through the A9 route by bus from Kandy on a Saturday morning. The traveller had just finished his PhD in Sydney and was full of dreams, dedication, incredibly high expectations, and enthusiasm. That morning, his mind was focused on research and publications. He thought of establishing a lab that would be distinctively recognised as the only one of its calibre in Sri Lanka. It would also assist in moulding the department&apos;s students into specialists. His best decision was to concentrate on the systems element of computer engineering and establish a specialised laboratory dedicated to conducting research and development projects focused on systems, specifically Embedded Systems, as he is a graduate of the same Department and is familiar with the atmosphere, its vision, and aspirations.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/QhZ28tyJviNZ26OSpHVa74W0rwfDs_yKwtZRd8KcqNYxrnMzxmh9KUMS83O3YOH5eEaU0osa-eP6Lfg7LTJ_1pubsH00gh_-onu7pcsl8hIzwLRqSjSqCcGsiPq1NqeZmcBly7N-4oOcha8jMudNqA" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="372" height="265"></figure><p>As an initiative, he began writing several acronym permutations and combinations on paper while riding on the bus. He was looking for a unique name that represented expansion and had significance for the targeted area. After substantial thoughts and thousands of trials and errors, he decided on the acronym &#x201C;ESCAL&#x201D;, which stands for Embedded Systems and Computer Architecture Laboratory, which also depicts the meaning &#x201C;escalate, escalator, or other words with ascending connotations&#x201D;.</p><p>The ESCAL group, with its rich history and remarkable accomplishments, continues to make ground-breaking strides in research and development. Its primary focus lies in the micro-architectural design aspects of embedded microprocessors, with a keen emphasis on addressing security and reliability concerns. Moreover, the ESCAL group&apos;s pioneering efforts extend beyond the realm of micro-architectural design in embedded microprocessors. They actively explore cutting-edge research avenues related to Cyber-Physical systems, fostering advancements in various domains such as side-channel attacks and countermeasures, application-specific CPU and memory hierarchy design, robotics, hardware acceleration, and high-performance computing. They further expanded into application areas such as robotics, biomedical engineering, and computational biology, where systems research can help.</p><p>By delving into these critical areas, the ESCAL group not only expands the boundaries of knowledge but also contributes to practical applications and solutions that have the potential to shape industries and drive technological progress. Their dedication to advancing the field ensures that they remain at the forefront of innovation, making significant contributions to the ever-evolving landscape of computer engineering and its impact on society.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/KciQLpK7o3YfWru4GsmUD1p5wlRlutMAzoyk_vUgGSNblCFnjEBptAMQKFEB9apFWTZIqdmg9LN6chMwAgtssuHTIHqeXvc2Sh3lVpfHosOCg_LNHranFQhyNbb0QI-2NxCd_oqe6-S9zs1B8cCLFQ" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="607" height="272"></figure><p>Prof. Roshan Ragel, the present Head of the Department of Computer Engineering, leads the group with support from Dr. Isuru Nawinne. The group consists of the academic staff<em> </em>members of the Department of Computer Engineering, the Postgraduate (PhD, M.Phil., M.Eng., and M.Sc.) students from both the Faculty of Engineering and the Postgraduate Institute of Science (PGIS), and the Undergraduate students from the Department of Computer Engineering and the Department of Statistics and Computer Science. The group also collaborates with academic staff members, postdoctoral researchers and postgraduate students from the School of Computer Science and Engineering, UNSW. Prof. Roshan Ragel regularly visits UNSW, Sydney, as a visiting research fellow and Queensland University of Technology (QUT), Brisbane.</p><p>At present, the group works on the following themes:</p><ul><li>Embedded and Cyber -Physical Systems Design</li><li>Security and Reliability of Embedded Systems</li><li>Side-Channel Attacks and Countermeasures</li><li>Application-Specific CPU and Memory Hierarchy Design</li><li>FPGA and GPU based acceleration</li><li>High-Performance Computing</li><li>Biomedical Engineering</li><li>Intelligent Robotics</li></ul><p>While concentrating on research projects, the ESCAL group made some better changes, which will indefinitely help undergraduate students shine worldwide even in the future. One of those developments is the ESCAL Makerspace, which was solemnly built for students interested in innovations.</p><p>The ESCAL Makerspace, too, has its own history. Computer Engineering students at Peradeniya must design and develop cyber-physical systems and embedded systems-based tech products as part of the core curriculum. In these projects, they build hardware and network, security, and software components. Being closely guided by the academic staff, some students go above and beyond the requirements of the course to take their projects to even higher standards.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/92JLft6P-1xUZ1sp4ehZgsO1rPpQzJlnBsMtgV6pn7OJqO7uRp5aPEn48nrkBxbQ84-8KNWjThoZTfaRRKc-YBlrojaK8DOAjy7shvVathjmP1eOypsaB50rG-XSd0GHIfXNSYwHGET8nzabeNHxqw" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="610" height="367"></figure><p>Since the inception of the cyber physical systems design project course, one of the main obstacles hindering undergraduates from creating innovative solutions for several years was the absence of current design and production tools necessary to build high-quality components and items effectively. Dr Isuru Nawinne, who himself was a former student in ESCAL, and the mind behind the Cyber-Physical Systems Design project course, stepped up and proposed a creation of a fully functional Makerspace with funding secured from the University as well as external collaborations. Dr Nawinne, who firmly believes in project-based experiential learning, planned this laboratory as a place where students could walk in and use their creativity and curiosity to engage in practical engineering projects.</p><p>Aligned with Dr Nawinne&apos;s vision of project-based experiential learning, establishing of ESCAL MakerSpace was a crucial step towards fostering an environment where students could unleash their creativity and curiosity. Under this vision, Mr Nuwan Jaliyagoda from the E15 class of Computer Engineering embarked on developing the Makerspace in August 2020. Phase one was successfully finished in August 2022 after the necessary space and resources were secured in late 2021.</p><p>With dedication and tireless efforts, Makerspace has become a reality, providing a space where students can come together, explore their ideas, and engage in hands-on engineering projects. This transformative initiative empowers students to apply their theoretical knowledge and nurtures a culture of innovation and entrepreneurship, ultimately preparing them to thrive in the practical world of engineering. The Makerspace is also structured so that students can easily work on different stations and subdivided areas based on the requirements of their projects. As Dr Isuru Nawinne predicted, the students are now showing more enthusiasm and dedication in building items with new ideas and creativity, making our students shine worldwide. This is one of the most significant improvements at the University of Peradeniya, especially in the Faculty of Engineering.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/QNs-7n3xAdRb1N_j0HWs9PXo790pRQDW5CzPO0op6nHdkxmOpX3WH09710LaMtpcLbmHejv649PIEZXsKyE3exkD9r4SurLvfni6aE8aqauseIxrrJNjky1gVQdp7TcLRsvl6AGQvmQ1HkxdSGzvtg" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="339" height="254"></figure><p>Another important inclusion within ESCAL is the NVIDIA GPU Research Centre at the University of Peradeniya. The primary focus of this research centre is investigating the High-Performance (and Accelerated) Computing (HPC) aspect of GPU in various domains, including bio-computing, computer security, machine learning and data mining, and physics. To this end, ESCAL is in possession of several high-performance and mobile GPU computing resources including NVIDIA RTX A6000, Kepler, Tesla and portable Jetson platforms.</p><p>ESCAL also contains extensive expertise and resources on FPGA based prototyping and acceleration. The lab is well equipped with Intel Altera Stratix V, Cyclone and AMD Xilinx Vertex FPGA resources for undergraduate and postgraduate students to conduct cutting edge research with.</p><p>The Cambio wearable computing laboratory is another important segment within ESCAL, which was setup in partnership with Cambio Software Engineering. Through this partnership, the lab has acquired modern equipment for capturing biometrics such as EEG, ECG and EMG signals for biomedical applications. ESCAL researchers conduct highly acclaimed biomedical engineering research work on topics such as emotion recognition with biometrics, brain-computer interface, non-invasive monitoring, and hyper-spectral imaging.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/XI7uWFUmS9MaUmNWl1X9TOWHa7UL7ZJL2YeWcNCMXi_e8oNmuUzszlzxw6PF9GgljLHV1h8Gl8wz9eXnESKPEz5xMi8Vm45ZLNNXGmLUS0ElhMMMEFvv2CCuoa7hyaWgnS5UHr2r2sDDw8CsIzZZfg" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="361" height="240"></figure><p>One of the latest additions to ESCAL is the new robotics laboratory (ESCAL Robotics). Currently it focuses on intelligent swarm robotics design, along with an in-house developed mixed-reality simulation framework for robotic swarms containing seamlessly integrated physical and virtual robots. Additionally, the lab provides many other resources including robot arms and programmable robot development kits.</p><p>Over the years, under the leadership of Prof. Ragel, many undergraduate students who worked in ESCAL research projects have embarked on research careers pursuing PhD qualifications at top-ranked universities around the world. With Dr. Nawinne&apos;s recent efforts, there&apos;s a significant rise in enthusiasm on computer architecture which has led passionate PeraCom undergrads to be directly recruited by world leading CPU design organisations such as ARM and SiFive. The fact that ESCAL alumni are gaining recognition and making a difference all over the world excelling at the cutting edge of science and technology is a testament to the quality of work done at ESCAL and the untiring efforts of the team.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/Jug93MlodsP0zEVSX40hUwQEDp1LW1yELGZ0TEaUsuJnhiP9ooL-3k1iGTY0wttQt3C31TBKjx_k5C8XdO9Ypi-ww3nyVgRPf86WuQPPiIyVFO_k7Z6VSUubrTGUkuluKnAb9vBwc-52V73RlH84Bw" class="kg-image" alt="ESCAL: Pioneering the Future of Computer Engineering at Peradeniya" loading="lazy" width="305" height="231"></figure><p><br>At UoP, the ESCAL group is creating a new practical world for ambitious undergraduate and postgraduate students. This initiative aims to shape future innovators by significantly enhancing various aspects of the university, thereby making a profound impact on its overall development, and contributing to the country&apos;s advancement.</p><!--kg-card-begin: html--><pre>By-Hamshica Mohanathas</pre><!--kg-card-end: html--><p><br></p>]]></content:encoded></item><item><title><![CDATA[Empower Future Tech Leaders: Department of Computer Engineering is Hosting Successful Portfolio Building Awareness Events]]></title><description><![CDATA[<p></p><p>A portfolio can showcase the unique strengths, talents, and skills of someone and help them stand out in a competitive job market. A series of programs related to Portfolio-building awareness were introduced to the Department of Computer Engineering starting from 2015. The industry demands not only technical expertise but also</p>]]></description><link>https://gauge.fly.dev/portofolio_awareness/</link><guid isPermaLink="false">64e59b7519602c010724c884</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 05:43:15 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/portofolio_awareness.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/portofolio_awareness.jpg" alt="Empower Future Tech Leaders: Department of Computer Engineering is Hosting Successful Portfolio Building Awareness Events"><p></p><p>A portfolio can showcase the unique strengths, talents, and skills of someone and help them stand out in a competitive job market. A series of programs related to Portfolio-building awareness were introduced to the Department of Computer Engineering starting from 2015. The industry demands not only technical expertise but also emphasizes the significance of soft skills. Fresh graduates and interns lacked awareness regarding this aspect, resulting in insufficient soft skill proficiency. And also they overlooked and missed out on valuable opportunities to develop their soft skills.</p><p>The industry feedback regarding their expectations of the quality of the fresh graduates and interns highlighted that there&#x2019;s a significant deficiency in soft skills. Therefore, the Department rekindled the Softskill Development Workshop, which had been introduced in 2004 to the department by the Head of the Department, Prof. K. Walgama. This workshop was aimed to support students by not only making them understand the importance of soft skills but also identifying the opportunities to develop them.</p><p>While the soft-skill development workshop was intended to provide a bottom-up approach to student development, the top-down approach was also expected through the senior-junior knowledge transfer, especially in terms of industry experience after their training. However, the Department faced difficulties there, as only a few students were readily providing feedback on their training experience. Also, their perspectives on the industry varied, making it challenging to provide a holistic idea of the industry. As a solution, the department organised a &quot;Mid-Training Reflection Workshop,&quot; aimed at all the undergraduates in their internship period. It aimed not only to provide a clear idea about the industry to junior batches but also to get updates on the ongoing training programs.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/VuwI6ciJsLxvOmOfmUXhN1gpmggFh31zxkMW9r2Q7oSKoQDrQdJwso5CI2F9PL5dgvdwzrph-kX5z2Ghz8kpSPgB2i2BhSt_tzo-F8yAlVrxv8FdqMrXKYNQMB_3LGGY8Av6BC7gqdpfSZMMZv8y8Ps" class="kg-image" alt="Empower Future Tech Leaders: Department of Computer Engineering is Hosting Successful Portfolio Building Awareness Events" loading="lazy" width="470" height="352"></figure><p>In addition, students were provided with soft skills development programs as a part of their orientation program. Then, CV writing and interview preparation workshops were organised for 3rd-year undergraduates, and a career fair was organised for final-year undergraduates by the Department. Since discussing skills with artefacts is more effective, the department provided opportunities for students to participate in various projects, such as the Third Year Project, aka 3YP and the Sixth Semester Project, aka 6SP. Through them, students could develop their presentation skills, time management skills, writing skills, innovation, creativity etc. With this structured approach, students could manage their workload effectively, develop essential skills, and create a polished portfolio that showcases their unique strengths and achievements.</p><p>The workshop series evolves yearly, adapting to the times, but the main idea and objective remain the same. The last year&#x2019;s workshop, aimed at the E18 and E19 batches, was successfully held on the 16th of October 2022 from 8 a.m. to 5 p.m. It offered diverse programs to foster team spirit, leadership skills, logical thinking, and public speaking abilities. Attendees engaged in lively idea-sharing sessions focused on their interests, life goals, and discussions about interview preparation and industry expectations. Also, students could participate in exciting activities such as debates, treasure hunts, etc. The support and guidance received from staff facilitators for every event were immense. This workshop was a great success, sparking hope for offering similar programs in the upcoming years.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/qKImfZBdK54hbyBjbOQTWyGW836bPn8G5Z1Bs-EFKvXB6wKo7ln5uJ3Wlyhq3bgI2hZ-UuIy0J7mTSG1eljUR5QX29KbuGJ1A127xU2iOpagi2PAhoQJWOF7vzuGJKkUMbMhbsqD9UuCtmZW2oP5rPs" class="kg-image" alt="Empower Future Tech Leaders: Department of Computer Engineering is Hosting Successful Portfolio Building Awareness Events" loading="lazy" width="469" height="352"></figure><p>This initiative has proven to be a resounding success, with remarkable student performance improvements. Now they&#x2019;re leaving a lasting impression on potential employers and securing better career prospects.</p><!--kg-card-begin: html--><pre>Piyumali Sandunika
Third year,
Department of Computer Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html--><p></p>]]></content:encoded></item><item><title><![CDATA[Mechanical Engineering Society's Annual General Meeting Sets the Stage for a Successful Year Ahead!]]></title><description><![CDATA[<p></p><p><strong>Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!</strong></p><p>The Mechanical Engineering Society of the University of Peradeniya recently held its Annual General &#xA0;Meeting in physical and online settings in the New Mechanical Building seminar room on 8th December 2022 at 6.</p>]]></description><link>https://gauge.fly.dev/mes-agm-2022/</link><guid isPermaLink="false">64e599ef9e9ab50107f6eaba</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 05:37:43 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image.2.png" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image.2.png" alt="Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!"><p></p><p><strong>Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!</strong></p><p>The Mechanical Engineering Society of the University of Peradeniya recently held its Annual General &#xA0;Meeting in physical and online settings in the New Mechanical Building seminar room on 8th December 2022 at 6.30 PM, with the participation of professors, office bearers and undergraduates of the Mechanical Engineering Department. Several staff members, including The Head of the Department, Prof. Asanga Ratnaweera, Dr Ubaya Higgoda, Dr Primal Fernando, Dr I. W. Kulathunga, and Dr Lekha Bakmeedeniya, were among the attendees.</p><p>This meeting was held to appoint the new office bearers for the new term and to plan new initiatives to enhance the quality of Education and Research. The AGM provided members with an opportunity to discuss the society&apos;s plans for the coming year and to voice their opinions on the society&apos;s activities, policies and the direction in which it should be heading.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/ydOl4juT8wP8QideU0CKcfMCmO-rm4F_dwnbDhlEsy-tBzLEC8ayYTA-dzPnDc5QpG6754CuTv6ElQwr2W-yh0sULVLdrGuGJH7HM5zXdzLniNyG5oIxWhZrfsaXQdJXn7BJSkZD4zN4-fcGEuM6TiQ" class="kg-image" alt="Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!" loading="lazy" width="349" height="232"></figure><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/uXbu6FHQaVKE-Sqk7z09jZo-SzzroSzXJiJYz9CnGa8oqUfboUXMtPSMj34uAaaR0LQraWvdkMb_aS2_EqjEScsbdnr3INTsZZftzUm0Qn8IyWCo7uyXZvFA6M96rp02LY5FD0T3Z-zhyN7HnDQMq6A" class="kg-image" alt="Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!" loading="lazy" width="349" height="233"></figure><p>The meeting began with a welcome speech by the President, Mr Tharana Wasalaarachchi of the previous term and an overview of the department&#x2019;s accomplishments over the past years was delivered by the Senior President of the society, Prof. Asanga Ratnaweera. The minutes of the previous AGM were presented by Mr G.G.A.D. Madushanka on behalf of the Secretary Mr Nadeera Ukwatta. The Vice President for the term 2021/22, Mr K.K. Wagachchi presented the summary of work carried out by MES throughout the term. He mentioned all the hands-on experience workshops and webinars carried out by the society for the betterment and self-improvement of the undergraduates.</p><p>New office bearers were selected, and Prof. Asanga Ratnaweera was elected as the Senior President for the new term 2022/23, and Dr Primal Fernando was elected as the Senior Treasurer. Mr C.H. Kannangara &#xA0;was elected as the President of the society for the new term 2022/23, and Ms W.S.N. Herath, Mr G.G.A.D. &#xA0;Madushanka, Mr N.T. Dedigamuwa and Mr W.A.H.M. Perera were respectively elected as the Secretary, &#xA0;Vice President, Junior Treasurer and Editor for the new term. Two committee members were also selected from each batch.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/3AqqBEPnvu4bNyDB891OPNgcP-iXGaDYMmVvcbJNWJRDLR62QmBOP-uwz9gzItoLv_pk-Dlj1xRDrFH2V7ENvxZ-VQCP3agw0XCtUo_7aJaRE_lc7DCPKGqYch1j7BZ_kGsmcA2b3NleAYnTEVyxg2E" class="kg-image" alt="Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!" loading="lazy" width="242" height="161"></figure><p>The society is open to all Mechanical Engineering students, &#xA0;regardless of their specialisation, so the AGM was an excellent opportunity to learn from each other&apos;s experiences. Undergraduates from E16 and E17 batches spoke about their experiences in the previous years and how Covid affected the society-activities. They shared their thoughts on the field visits and project activities organized by the society, where they were able to expand their knowledge of industry and research activities.</p><p>The newly elected President, Mr C.H. Kannangara expressed some ideas and plans for the upcoming year. He focused on providing members with resources to help them gain the skills necessary for success in the industry, as well as organizing events that would allow members to gain practical experience.</p><p>Dr Primal Fernando, Dr Ubaya Higgoda, Dr Indrani and other lecturers expressed their views on the various initiatives to be implemented, such as a project symposium, field visits, competitions etc. Overall, the meeting was a success, with a productive exchange of ideas between the staff members and the students.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/FdhOs0cdE87m4Jh4nV9i6nLgbc2fDu5SaUnnHq6n4_91znjvkz-azRjOT0Sxi2hr4cQDzMbxJHf63nKQOA_huK3hmS_8wXiGJtXoTTvm2knkAceMkCt4rB7A5qgf1M_6e5vl5lVtZ6lN5aQZOb2gK40" class="kg-image" alt="Mechanical Engineering Society&apos;s Annual General Meeting Sets the Stage for a Successful Year Ahead!" loading="lazy" width="479" height="319"></figure><p>The AGM concluded with votes of thanks, presented by the newly appointed Secretary for the board members, stating the commitment to continue the society&apos;s efforts to support its members. The event proved highly successful, allowing members to network, exchange ideas, and enhance their professional development.</p><p><br>Written by: W.S. Nethmini Herath</p>]]></content:encoded></item><item><title><![CDATA[“How IEEE WIE can lead you to a successful career”]]></title><description><![CDATA[<p></p><h2 id="about-ieee-wie">About IEEE WIE</h2><p></p><p>IEEE Women in Engineering (WIE) is a global network of IEEE members and volunteers dedicated to promoting women engineers and inspiring young females around the world to follow their academic interests in a career in Engineering.</p><h2 id="about-ieee-wie-sb-ag-of-uop">About IEEE WIE SB AG of UoP</h2><p></p><p>The IEEE Women in</p>]]></description><link>https://gauge.fly.dev/ieee-wie/</link><guid isPermaLink="false">64e5907dd81b1d0107dd8f59</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:53:39 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image2-2.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image2-2.jpg" alt="&#x201C;How IEEE WIE can lead you to a successful career&#x201D;"><p></p><h2 id="about-ieee-wie">About IEEE WIE</h2><p></p><p>IEEE Women in Engineering (WIE) is a global network of IEEE members and volunteers dedicated to promoting women engineers and inspiring young females around the world to follow their academic interests in a career in Engineering.</p><h2 id="about-ieee-wie-sb-ag-of-uop">About IEEE WIE SB AG of UoP</h2><p></p><p>The IEEE Women in Engineering (WIE) Student Branch Affinity Group of the University of Peradeniya is one of the pre-eminent student branch affinity groups among universities in Sri Lanka. It dedicates to inspiring and empowering young females to use their diverse talents, in achieving technical eminence with the proper maintenance of work-life balance, and to innovate for the betterment of humanity.</p><p>IEEE WIE Student Branch Affinity Group of UoP has inspired young females in leadership roles. Career advancement for women in the profession has been advocated throughout the journey of IEEE WIE Student Branch Affinity Group of UoP</p><p>Furthermore, while inspiring young females WIE has encouraged many undergraduates by conducting percipient events. Also, these events absolutely stimulated the development of the social and professional skills of the participants.</p><h2 id="what-have-we-done-so-far">What have we done so far</h2><p><br>IEEE WIE Student Branch Affinity Group of UoP has been able to guide not only undergraduates but also the people in the community recently through many initiatives, such as TRIERVIEW and Herself which help them to build their soft skills while bridging the gap between academia and industry.</p><p>IEEE WIE SB AG of UoP has elevated its excellency by winning the award for Best Affinity Group Project Award for the project Trierview, in the special activities awards category at the IEEE Sri Lanka Section Awards Ceremony in 2022.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/8sP-YUwCCgK1bC7OWKnIfIWtLnfoEDYeuYU8kMQU9z1rWyEkCF5OKDN4zBfSMQeeBKTfc8YncF1Zy-JcdvFARO_pVZwIYoVcistKDPaA_ZTzh2fIQ17WiV2bm5teVHh2mL0KlMmDEljspLCTJvtrQw" class="kg-image" alt="&#x201C;How IEEE WIE can lead you to a successful career&#x201D;" loading="lazy" width="444" height="444"></figure><h2 id="what%E2%80%99s-new-with-the-occasion">What&#x2019;s new with the occasion</h2><p><br>Throughout the endeavour of the WIE SB AG of UoP, the strength and energy of the society have to be purveyed to the future generation in order to dignify the society with its supremacy. The transfusion of the experience and the knowledge gained from the expedition was held on the 10th of November 2022. Though this event is conventionally famous as the introductory session of WIE, the session was far way beyond that of an introductory session. The theme title of this session &#x201C;How IEEE WIE can lead you to a successful career&#x201D; depicts that this is not an ordinary introductory session.</p><p>The session commenced at the DEEE Seminar room, Faculty of Engineering, University of Peradeniya from 3.00 p.m. with about 30 young enthusiastic female undergraduates from E19 and E18 batches who are interested in achieving their aspirations with IEEE WIE and who are eager to pull out all the stops for humanity.</p><p>The IEEE WIE was privileged to have Prof. Maheshi B. Dissanayake, a senior lecturer at the Faculty of Engineering, University of Peradeniya as the event&#x2019;s guest speaker. It is with great honour to mention that she was the founder, first and interim Chairperson of IEEE WIE Sri Lanka, Chairperson of IEEE Sri Lanka Section for the year 2021/22 as well as the advisor of IEEE WIE SB AG of UoP since 2011. Her experiences with IEEE WIE make her the ideal personage to precede an introductory session for female undergraduates who need proper guidance to enter the competitive world as female engineers.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/4kcZKii-SZDgkMOF7_-PfVv1xdwdx9ZlCHdx_tqRx6iNuvyYRz9cHy9tqglIGbkJZ4aKMquPa0526Zum0x-AiTfO9YAj11mxQvmcni7DjB6plJgJ7DjHLDXH8GVQ8N5LXw-1XiLzS2a5_-oiTV_NFg" class="kg-image" alt="&#x201C;How IEEE WIE can lead you to a successful career&#x201D;" loading="lazy" width="789" height="526"></figure><p></p><h2 id="insights-of-the-guest-speaker">Insights of the Guest Speaker</h2><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/hysTBHrhQRh-InKEdRx75s0erjZ5ySPxMsYSkqe7wRMlcHIT0TRM5y_TxhbV6iEmYGFHOd1caAeOPLximkxcgibS_-hvc1p4M_Dcd-9QB3LSnbEpx7fjxi7UuJ1RIWopYlh2lS3cicqi5LiaxWF9LQ" class="kg-image" alt="&#x201C;How IEEE WIE can lead you to a successful career&#x201D;" loading="lazy" width="785" height="524"></figure><p>Over the length and breadth of Prof. Maheshi B. Dissanayake&#x2019;s speech, she focused on the skills a young undergraduate should gain before approaching the community as an engineer, and the new windows of opportunities with WIE to enhance their proficiency and discover their potential. She also precisely mentioned the significance of work-life balance and how to maintain it appropriately. Furthermore, she encouraged the gathering to cultivate confidence and to overcome the challenges faced as females in the industry.</p><h2 id="the-fruitful-conclusion-of-the-event">The fruitful conclusion of the event</h2><p>The event was concluded successfully, motivating the young female undergraduates to identify their expertise and to hold hands with WIE. The event was a massive success thanks to the committee and all the contributors who gave their maximum. Undoubtedly, the session had given all the participants a memorable opportunity to develop their point of view on society and industry as female engineering undergraduates. Heretofore, another milestone in the grandiose journey of IEEE WIE SB AG of UoP! Through this gratification, we expect to write the name &#x201C;IEEE WIE SB AG of UoP&#x201D; in a glorious style and to achieve more accomplishments while serving the community.</p><p>Written by: N.B. Ashini Senara and Isuri Liyanage</p>]]></content:encoded></item><item><title><![CDATA[IEEE MTTS Student Division's SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs]]></title><description><![CDATA[<p></p><p>Over the years, the University of Peradeniya&apos;s Department of Electrical and Electronic Engineering has grown to the point where it now offers one of Sri Lanka&apos;s most prestigious Engineering Degree Programmes. IEEE MTT-S University of Peradeniya is a Student Branch Chapter under the IEEE Microwave Theory</p>]]></description><link>https://gauge.fly.dev/satcap2022/</link><guid isPermaLink="false">64e58f054b9a220107e1b7bf</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:50:53 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/PLACEHOLDER_image2.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/PLACEHOLDER_image2.jpg" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs"><p></p><p>Over the years, the University of Peradeniya&apos;s Department of Electrical and Electronic Engineering has grown to the point where it now offers one of Sri Lanka&apos;s most prestigious Engineering Degree Programmes. IEEE MTT-S University of Peradeniya is a Student Branch Chapter under the IEEE Microwave Theory &amp; Techniques Society (MTT-S) which is one of the major technical sub-societies belonging to the IEEE organization.</p><p>Over the past few years, the MTTS student branch chapter has organized numerous events that have helped undergraduate students develop their soft skills and close the knowledge gap between academia and industry. The SATCAP 2022 Webinar and Workshop, part of a series of activities by the IEEE MTTS student division, witnessed two outstanding programs reach key milestones.</p><p>SATCAP 2022 webinar session was held on the 26th of April 2022 using the Zoom online platform with the participation of Prof. Aruna Gunawardana, Senior Advisor of the IEEE MTT-S Student Branch Chapter of the University of Peradeniya. Eng Tharindu Dayarathne, a graduate of the Electrical and Electronic Engineering Department of the Faculty of Engineering, University of Peradeniya, Sri Lanka, and the designer of the country&apos;s first satellite, RAVANA 1, in 2019, conducted the session successfully.</p><p>During the webinar, he clearly outlined the KITSUNE satellite&#x2019;s construction, the technologies employed, and antenna concepts. A vivid explanation was given by Eng Tharindu Dayarathne on QHF antennas and their structure to conduct the SATCAP workshop on QHF antennas.</p><p>What should and what not to do while building a QHF antenna?</p><p>This was clarified by this experienced professional on that day. Finally, he outlined how to capture signals of kitsune satellites using a home-built QHF antenna.</p><p>The webinar&apos;s purpose was fully addressed during the session, which was highly effective in getting everyone ready for the physical workshop that followed.</p><p>The second phase of the big event, SATCAP 2022, was conducted next weekend (30th of April 2022) &#xA0;at the Engineering Faculty premises. The workshop was led by Eng Tharindu Dayaratne, the same brilliant expert who led the webinar.</p><figure class="kg-card kg-image-card kg-width-wide"><img src="https://lh6.googleusercontent.com/avu1pYzdRK5dhsJEVWfzmDVi7ALhRa3OG6AvIVjsCd22AaITrtSTuUG9w2-rm21Z_BghGJvnZWRTjTsI77DWgywLxlw1f2AGrWZ-QOU73JDfjeCY4L1sVKekSTpA2WbZGB-UQgm_yvwF" class="kg-image" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs" loading="lazy" width="565" height="318"></figure><figure class="kg-card kg-image-card kg-width-wide"><img src="https://lh4.googleusercontent.com/YFfWJr_QsUnTy_aUdqx5MOLoAoHBWU9nEDEceGgcFLEE7Pwj0vT9OUNbk2xthhhGdMfNeGLsCpbe44zvXhj7Y5kSisx4qfKovgdohyB6aB89QhwWirUONUY3WPv3m1c8zDrDHQh7r4ub" class="kg-image" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs" loading="lazy" width="569" height="320"></figure><p>The main objective of the workshop was to capture the signals from the KITSUNE satellite. Participants were divided into four groups and provided with the task of building a QHF antenna. All the guidance was given to make the antenna step by step, and at the end of the workshop, four QHF antennas were built and were able to capture radio signals by all the antennas successfully. Some participants even waited to catch satellite signals at around 11.45 p.m., which is truly incredible, and they were successful in receiving the signals.</p><p>The event was indeed a tremendous success. A souvenir was given out to Eng Tharindu Dayarathne to appreciate his enormous support and dedication throughout the event. The event was completed successfully, giving all the participants a memorable chance to take part in a creative and exciting antenna workshop session. Another accomplishment in the illustrious success tale ended just like that. With this accomplishment, we anticipate achieving greater heights in the future.</p><p><strong>ProCB Altium 2022</strong></p><figure class="kg-card kg-image-card kg-width-wide"><img src="https://lh5.googleusercontent.com/UYWSD0NbfniRbhwiF88bghvwlmLNxJaHYu1k5a-rQpSMVnqMkf5q8xmo959yP1dN07dPoipEcKUfXxJyuvTyES9848FxNX4jBd7eKoS-Ejo1DRaF8AQ_Q1VKqct0NR9ORn9FSujOyHy3" class="kg-image" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs" loading="lazy" width="355" height="237"></figure><p>The second hands-on workshop organized by the IEEE MTT-s student branch chapter of the &#xA0;University of Peradeniya was on PCB designing and implementation. It was held on the 4th of December 2022 at the faculty premises.</p><figure class="kg-card kg-image-card kg-width-wide"><img src="https://lh6.googleusercontent.com/wPI_5uJBo03veOd1lfFi-cgD3IYHepKCKA36g7iJatA4YC7UJofyt8l7a9G42FmWq08OpCQGX0fS3pT7vEPXUyTcxshVqvHR_Gi_hTKGYHhDdWCSuCy4njCh2vv4IKfX7n8TPcpO9Kxd" class="kg-image" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs" loading="lazy" width="299" height="199"></figure><p>The PCB designing workshop was conducted by research scientist Mr Thilina Wijebandara from Arthur C. Clerk Institute for Modern Technologies. It was successfully concluded with 50+ participants. Designing the PCB was done during the morning session using Altium software. Every single step was fully described by the resource person so that anyone could understand and design their own PCB.</p><p>Most of the participants were fresh undergraduates of the Faculty of Engineering who are new to this PCB designing field. At the evening session, the participants were assigned to five groups and guided to practically implement the PCB. The necessary components and tools were provided for every group. The participants had a valuable chance to see the process of printing a PCB at the Microwave Lab of the Department.</p><p>Though it was a one-day workshop, participants were able to understand and have a fresh start with PCB design. The workshop successfully continued for 9+ hours continuously and ended with the hope of having a PCB designing workshop using Microwave Technology in the near future.</p><figure class="kg-card kg-image-card kg-width-wide"><img src="https://lh4.googleusercontent.com/cKkd7CMCHkpwfWnhSNu9MZFvDAp4YggMWRvYzH7JT83D-X8GmgJMghbTJfwCEA-u0jFELQPl-UPkrhcOy2QU2I8MaEJvh41sE_vIPxNBmGOtNeABb8fgGUanlCSaS61ImVmR0AuhdS8C" class="kg-image" alt="IEEE MTTS Student Division&apos;s SATCAP 2022 Webinar and Workshop Celebrates Milestones with Outstanding Programs" loading="lazy" width="293" height="195"></figure><p></p><p>Written by : Chathumi Wijayapala and Chalani Munasinghe</p>]]></content:encoded></item><item><title><![CDATA[Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!]]></title><description><![CDATA[<p>The Engonitez 2022 sports meet, which was organized by the sports subcommittee of the Engineering Students&apos; Union to promote brotherhood through the essence of sport and align our brothers and sisters towards sports, bringing out their hidden talents, continued throughout a couple of weeks. The speciality is that it&</p>]]></description><link>https://gauge.fly.dev/engonitez2020/</link><guid isPermaLink="false">64e58de068352b0107228b97</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:45:05 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image2-1.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image2-1.jpg" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!"><p>The Engonitez 2022 sports meet, which was organized by the sports subcommittee of the Engineering Students&apos; Union to promote brotherhood through the essence of sport and align our brothers and sisters towards sports, bringing out their hidden talents, continued throughout a couple of weeks. The speciality is that it&apos;s been 12 years since such an event was last organized.</p><p>The opening ceremony was held magnificently at the University indoor gymnasium with the participation of the Dean of the Faculty of Engineering, Academic staff members, members of the students&apos; Union and the University sports Council on the 26th of October 2022. The President of the Sports Council presented the sports charter, and as a special event, the trophies were exhibited. The event began with volleyball, and nearly 16 sports were held successfully, including netball, basketball, elle, table tennis, chess, baseball, badminton, weightlifting, carrom, kabaddi, tennis, hockey, and rugby. The above events were held in both men&apos;s and women&apos;s categories. The sports meet concluded with a cricket tournament in which separate trophies were presented.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/N8QSdhVQ_0pHT3-W--vTgQTKzSYkYGs-Xl8NwqRGyOitdhyfOASKscYuz61Kdda6S7VrqnUWJbiQpB1Tswjlr40t3O-sCW3Bjjx4KRXchZaMVT52XlbTXNH5Sws-NVR57T4vA8_hntlaClBMfeoEuA" class="kg-image" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!" loading="lazy" width="522" height="220"></figure><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/YvtR9xVpk21YzIIazIIns3XlfbEMbHlapcRKeAZeAN65DGnQtzEb6yy44-9ThrVlVMcN3QWNPQkZtmNmESFOjnXxID5st51J6nnO4TYF8laEPgaKUo7322nXakXafVvdljazQucve48Ljrh2HeE9fA" class="kg-image" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!" loading="lazy" width="562" height="316"></figure><p>Each event was held according to the knockout method, and every position was assigned a score, and the total score of each team was calculated. The rules and regulations of the freshers&#x2019; meet were followed.</p><p>Not only the players of each batch but also all the brothers and sisters were abundantly seen to cheer their fellow mates. Accordingly, the E/16 batch held blue, the E/17 batch held grey, the E/18 batch held yellow, the E/19 batch held green, and the E/20 batch held purple flags and headbands to cheer their batchmates, respectively.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/tJ-hKzlrWLFTMuAkb5dKBiAIrSXlPYr-5f9fgfID1wSA0ETltmY52Lbwj7ya9vC_-tiu2sK3MU9BCcPAjriYAyH6ttyd_SU2p-MFyomabRtA5r7Rj5AMbw_4zlXHo8GXGRBbnfgrsNvdDGDYZCiqcg" class="kg-image" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!" loading="lazy" width="591" height="332"></figure><p><br>The overall winner of this sports meet held to develop the brotherhood with the participation of batches E/16, E/17, E/18, E/19, and E/20 that are currently studying in the Faculty was the E/16 batch and the E/17 batch became runners up while the E/19 batch became the second runners up.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/ZZOk9B41rw1xYU0zW6alSQlvxRr190jv7z69twLAJyJMp-f2vSj_wsz4C4U7J9lB-pTg6zsHAUWLvEPIz3H640zPQ-AQybDqKru1JHLMrhAa2rsvD3fc5FWb2EhLDRvAtzbmJytBhHX2_PuDFvTBeg" class="kg-image" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!" loading="lazy" width="624" height="351"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/D4qFmwDy-XgyIChE76XVyKOFWrENGax7fhFOikLajKIUV11QuK_8HhYLU-EJUcKDk_lIn94pFrjUO6-p8LShGiCeLo0WtBAts9ALRag4zlGiaFEFYHGP52Zi_TXiA5XcK3y9yDADx6O00KNZUgM7tA" class="kg-image" alt="Engonitez 2022: Unleashing the Thrill of Sports for Engineering Undergrads!" loading="lazy"></figure><p>To conclude the sports meet, the Engineering Students&apos; Union organized the Faculty Night, and the trophies and certificates were presented during this event. The best male player award was presented to Osanda Galgoda of the E/16 batch, and the best female player award was presented to Nisansala Nilmini of the E/16 batch. Thus came to an end, the glamorous event Engonitez came with the hope of having an even more successful and elegant sports meet next year.</p><p>In conclusion, Engonitez was an excellent opportunity for students to come together and engage in friendly competition while relieving themselves from the academic pressure that comes with being engineering students. The event not only provided a chance for students to bond with each other but also showcased the importance of maintaining a healthy balance between academic and extracurricular activities. By participating in the sports meet, students could cultivate a sense of community and camaraderie and develop essential life skills such as teamwork, leadership, and sportsmanship. Overall, the Engineering faculty sports meet was a resounding success, and we hope to see more events like this in the future that foster a positive and supportive academic environment.</p><!--kg-card-begin: html--><pre>Irushi Layanga
Second year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[Cheers to 10 years of the Calistus Trophy—a year to remember!]]></title><description><![CDATA[<p>The University of Peradeniya is a world-class institution of higher education that offers its students a demanding academic program, a thriving research environment, and an excellent student life experience connecting with people from various other cultures. The Mahaweli River flows nearby, and the campus is surrounded by lush greenery, providing</p>]]></description><link>https://gauge.fly.dev/calistus-trophy-2022/</link><guid isPermaLink="false">64e58ad4fc765a01076a6d80</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:37:13 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image12.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image12.jpg" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!"><p>The University of Peradeniya is a world-class institution of higher education that offers its students a demanding academic program, a thriving research environment, and an excellent student life experience connecting with people from various other cultures. The Mahaweli River flows nearby, and the campus is surrounded by lush greenery, providing students with the peace and quiet they need to study, chill, and enjoy their university experience. Considering the vibrant student life, the university has a wide variety of extracurricular activities, including sports, music, drama, and debating.</p><p>Concerning sports, some are held annually for Tamil Engineering undergraduates of the University of Peradeniya, such as the Calistus Memorial Cricket Trophy, Sujeevan Memorial Volleyball Trophy, Jeyanthan Trophy, and Clash of Brotherhood Football Championship, which contribute to the promotion of mental and physical health, socialising, and personal development, as well as to the enjoyment and entertainment of both individuals and communities.</p><p><strong>Digging deeper into The Calistus Trophy</strong></p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/8wkF9R2lOe4_4XgJS-JTXoFIYQVSP1DsP6DHeAIRbjBCUHUN9wzoC485fpoOrtPxACKsgUG8nOac37L-Wwlkelpbd8okJeyaL79h5-BkkxqLX-Jle5KwpYIBg4sVto-wJRnuSU_PHGi5PD2Bk_XOyA" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="371"></figure><p>The Calistus Trophy is one of the yearly cricket tournaments for Tamil undergraduates from the Faculty of Engineering, University of Peradeniya, founded by E08 students in memory of Mr Anton Yogaraja Calistus Kajendran from batch E07, who passed away in 2010 during his university life. Although he left early, his university brothers and sisters will always remember him in this way every year.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/9bosmcidlAUu6dNBfCzLUi7IPeMf0BgQe244zJ31YScF01mduCon93FIv7KlCgZcd7IAcBNQb13cUIF-oU3x3zNnvJqpldZBOOH0U3vHAxHyUytf-8e55_aVqAdUwk2BfNa9U1AiJTKad4eZBts0yA" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="267"></figure><p>Let&#x2019;s explore history! Although the first competition was held during the day, <a href="https://people.ce.pdn.ac.lk/staff/academic/roshan-ragel/">Prof. Roshan G. Ragel</a>, the Head of Computer Engineering at the Faculty of Engineering, University of Peradeniya, was the driving force behind moving the competition under lights for the second and subsequent rounds. He has since made every effort, together with <a href="https://eng.pdn.ac.lk/civil/people/drSKNavaratnarajah.php">Dr S.K. Navaratnarajah</a>, a Senior Lecturer of the Department of Civil Engineering of the University of Peradeniya, to ensure the tournament&apos;s continuation.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/GdpxclGs11gfvEeQG0qo5iziw-T-Z2b7R0kpgY7g5-XFW54-xbbIPAgYLQNYPdsbvMcvneE2p0GSoBX2sviIfafH8f81poXOK0199MLzskHOqGS-lRtwdMEFhv4wnFXHzJTAJ0RzQyHitxAWdXVc-w" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p>In the first tournament held in the year 2011, teams 08A and 08B advanced to the finals. As every first is special, this is the only instance in which two teams from the same batch have reached the final. The playoffs and lighting wickets were first introduced by the E13 batch in 2019, and the E16 batch followed them in 2022. E16 broke the first-year curse in 2019 by becoming the first team to win the trophy as first-years. Nonetheless, the Calistus Memorial Trophy has yet to be won by a final-year squad. Unfortunately, a pause in the progression was caused by the COVID-19 pandemic and other circumstances, and the 9th Memorial Trophy, which was organised by E14, only reached the league stages.</p><p><strong>Where are we now?</strong></p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/GfJtkIfeOKlnn9nKHG1_Nmsf64wCW19kURmNN2ZF9lD7Pwglh7BfNv8WlXN-THGUckE62yHtsA8DBsTFzgw0rgYZn0GweirIKZ4nUKncJwaHeil3j5lp_c2nLdglm5c6SqYDndPQ8XV_3QghXead9w" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p>Following a three-year hiatus, the commemoration of the 10th anniversary of the Calistus Memorial Cricket Trophy happened in 2022, with the assistance and encouragement of the E16 brothers and sisters, who were the only ones present when the last Calistus Trophy match took place before the break. Despite several ups and downs, challenges, and difficulties, marking a decade is a huge success.</p><p>The tournament kicked off on the 7th of December, 2022, with two teams from each of the four batches (E16, E17, E18, and E19) and was whittled down to four teams for the final battle following B-League and Super Six League matches at the Peradeniya Campus ground. This time, every A team from each of the four batches made it to the final day with the expectation of winning the crown.</p><p>It&#x2019;s time to rewrite history! The grand finale of the 10th Calistus Trophy arrived on the 21st of January, 2023 starting with the opening ceremony. The captain of the defending champions, team 16 A, handed the Calistus Trophy on behalf of the players and the audience. Everyone&apos;s attention was drawn to the trophy, and they expressed how seriously and eagerly they wanted to win it and proclaim themselves the Calistus 2022 champions.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/HBJ9fXVvTpE9Hy1KrKBs10FOdsnyV7AhRn56BPJubJpe536fnNvwRXC5sYCeE3rFy3cP6r2s2zRKcG4lPxEawFVRYW_gor_eME98QgP4A-RYt4y0zeIoPlVATrGwvVvk6Tjl5ltL0ov2AKpkWNPhgQ" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p>The chief guest, Dr S.K. Navaratnarajah, expressed his happiness at the occasion and his thoughts on the event, including how it has continued without coming to an end. &quot;The assistance given by the senior batch students can be witnessed over the years, and this should continue in the future as well for the continuity of the event,&quot; he added.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/OKyCfVR6aOjqQl4JKxGqFlvvv8obw9hxlDGAvnDBFCtP4kzwz0XEuR7lzXpIh6HWQSVW7bbKMgIBGBNJx_HptoFn9Xasanyl8kiX_SchZ1rVSzzQ6G6IiQoPvve7n1mNXJD1afS47S7DwRD2XW-xAw" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/Glut5FmPsRc5nCaHM4OgDgjY5JmRHTeLjhBI7vpY4rmD6J7z7ZvOBPgfxwZxA9D5jrFiWu-Qm-TuJhctHoRfmKiFbe3kOGtcUNX98Z2cqI0YKPa63AlDxWygVL42rvyC0bsZiXm8j3toM3U6khoO5A" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>Furthermore, the Calistus Memorial Coin was launched to celebrate the tenth anniversary on behalf of the special guests, Mr Calistus&apos; parents, and this is the first-ever Calistus tournament in which participants have used their own coin. Moreover this time, E16 introduced an LED scoreboard that showcases their innovative and creative thoughts. During the play, teams 17A and 18A advanced to the final battle after competing in Qualifier 1, Eliminator, and Qualifier 2 matches.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/vc_basNyN7Z1jTBwalG4NVeAs6Kcib4EFJlrzMU4SXwa0b4qXrQ9BotrCSa6kP-kPVqeKqOUSobL8644Gy1FfLlqunMhlv-lN0oxAQ27qY-j4wiaxcf3GX4uTUaOzl-7ze361c0M9RqpzPEOHAjPkg" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="375"></figure><p>Athletes must understand and practice sportsmanship if they want to maximise their sporting endeavours. Overall, the players&apos; sportsmanship was quite noticeable when they were battling, which promotes respect, develops character, fosters a positive environment, and improves performance, making it substantially better than before.</p><p>In the most recent Calistus Memorial Trophy results, 10, 12, 14, and 16 are the patterns of champions. Will the trend continue with 18 A&apos;s victory, or can 17 A break the odd-year curse and win the Calistus Trophy as it has been almost ten years since an odd-year batch did? The one question on everyone&apos;s mind is, &#x201C;Which team will claim the throne?&#x201D;</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/tmoom2jDBrMZEal2m0EG-r5Hfb-v5L_ZzFwRTNgd9m-uDYkotsixgdsqt-0QcCq48DGjdEMjHGHb9_ihwHPJrcqkKCsBS-6mWN4gT34VYc7ljGdwRmakrg3dL7ZBQycHu9eKSqGIe2AAUquoy0vrzA" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>&quot;The strength of the team is each individual member. The strength of each member is the team,&quot; according to the American former professional basketball player, Phil Jackson. From the start of the event to the end, players received great team support in an effort to foster unity, promote collaboration, and achieve success as a team. Finally, the trend of even-year champions for the Calistus Memorial Cricket Trophy was preserved in 2022 as well. The 18 A ultimately won the 10th Calistus Trophy, and the 17 A ended as runners-up.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/RlwsKTRU8muRomZUnJ4XuorK4vmzBzbmpgGQACN4RheBKNjAO3SkxANmputpTySh0dzNDfcAocgVyWw-cj4b325-pyEun6ENs1oXCLK_TilI4kFl70p0SWG8zZHzv53VWR0c8obLJK7VWMKrmVsomg" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>The night match lasted until the following morning and was concluded by the award ceremony. By the time it was all through, each and every one of them had expressed various emotions. Yet, everyone who participated adhered to the motto &quot;Win or lose, be a good sport&quot; and joined forces once more as brothers and sisters. No matter what challenges arose throughout the tournament, the players, teams, and supporters remained focused on their objectives. Despite the rain, cold, and trying conditions, they showed their commitment throughout the play.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/S_ALhMGrbzxXkbBM3yOpBOlAv3Df-zqFXl9QaHG988LQyrxBRAeh1xx85yW_V9LJm-kDMI502rvwI8-rtDEcI5CHAE8-NnvBtQMWZVgsUbTLdaP7NeJxHP29KDQ9P5oG_rls7UwybnLeui8fZ6_ZXg" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>The chief guest, Prof. Roshan G. Ragel, expressed his delight and satisfaction with the event at the gathering. He further emphasised the need for publicising the success of such events since it is crucial to remove the misconception that the University of Peradeniya is recognised for unpleasant events. &quot;Even when we do good deeds like this, they don&apos;t really reach out to the outer world, so we should start working on them right away,&quot; added Prof. Ragel.</p><p>And yet, this is just one of many tournaments to showcase the good sportsmanship of the Tamil Engineering undergraduates of the University of Peradeniya. The Sujeevan Memorial Volleyball Trophy, which was established in 2010, continued this year as well. While participating and playing aggressively, all four batches maintained their sportsmanship, which was encouraging to see. Team E18 won the volleyball match and displayed a variety of motivation and dedication.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/_JKQOAjVvAFTPftnvp9SPXKsv9DtqUPQh4tqaBTHDQiJoh3RfoeHZ7GduQOoVB0uI8piSAHgUmkG4lbckglUuW5tcnxs-SD0YoPo7FRbNwVXeO6qziS5G1uRnyWeOLDoeODjlQsHVRTXOJol4WzzGQ" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="416"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/Mz5ErrMK2whQucm_rc6_KcasHxvsaN-pFTcu8kPvlKyUSqXdNcqnPXdKaeLD9oFWK6viJHLdc5cPU4UjFpPMfQ8dKeWniLbX-TH8DhEJOGYw28XrGC8Av4lh6N34BKwjDFHKhpomRChudJTM_-Ds2A" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>The Clash of Brotherhood Football Championship, a competitive inter-batch football tournament that began in 2017, was also a tremendous success this year. This time, Team E16 won after dedicating a great deal of work and effort, and it paid off in the end.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/b0k-5l7b6JRDpQjvaN6mf0DHGKID6ZHWHFeiOf9yUhyl8oWRQH_LhMOAW4YkZkHryQlYMjaPJTTSUkHC88tLYCPWEYaTPun5f157KndgdNPsG3qoywXpX-gO4unjlTqaQbdtTVHLZB4nnAtigdblnw" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="416"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/kzDQtcpBwbLGdVg9qFV7Ejf7a1BNkjDoxn1dHxMjh9iUb1yGpCeh3x6cj6eJhk8XA2QAOxIhZ70dHZWMjvU4ueWJnn7KM-8UScLT5cSj2QCc3K9-u8f8BumQ3kAY7F1QAsONIC8T2BxCMmxACoKPng" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>Furthermore, the first-ever women&apos;s badminton competition was also staged this year in an effort to inspire girls to play sports and foster a sense of community among female participants.</p><p>Even though it was their first time, the girls&apos; fair play and teamwork were admirable to observe. A new chapter in history was begun as Team E18 established itself as the first-ever champions. Since the foundation was strengthened this year, the effort will be a genuine success, and any mistakes made this time around will be successfully fixed in the future.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/so0Yu7T6R8w1_IPnqp0rnBbUdiTfaRjiRwy3QUsFS0vUpAexn1uJO6j3PAVzWM2rWkios37MOC5nkrZkpxuHa_oJ0rdOmbll8bUqkcWyO6bF32daqQTo2c8kKwMw_Kks3baY2Vx8CT9yvYy4Ku-PuQ" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy" width="624" height="416"></figure><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/9koM04yvbdMj_foQDMeata5VXZCL57UGhEaSwgOBGGir4wfdGje8vKd5WWEoIG8DxkqblPCALAnHngClDgv1VJTbufZNwnFgrQQx_lcT1eOrtzOiJDgqXvSYYLfML_uBCYU0sY9Bf8SVvCZ6OG4aCw" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br>It takes a lot of effort, time, and attention to arrange a tournament. It is crucial to have a committed team that can work together, communicate well, and adjust to changing conditions. The organising committee kept the slogan &quot;ItzE16&apos;sEndGame,&quot; worked much harder than anticipated, and despite the fact that we are aware of how difficult it is to organise all of the tournaments mentioned above, the team gained knowledge from the experience of proper planning and execution to make it memorable. Moreover, the committee handed the subsequent batch the responsibility to carry on from where it left off and advance to higher levels.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/AGH7KwPgFSBD4O5qAbOaRphuuP8TYVz-gDlO5kyLNtkaGAA47Cs5kfe-1KFQFjLiyZJDEQQkoYz9fkBmV_Adtjd0jRZmSBKgDtjY4v80w9qymMYYLbuDNypQkLWfKHxsjW75TxzHUbnRTfxVnxIRPw" class="kg-image" alt="Cheers to 10 years of the Calistus Trophy&#x2014;a year to remember!" loading="lazy"></figure><p><br><br>&quot;Success is not final; failure is not fatal: It is the courage to continue that counts,&quot; said Winston S. Churchill. Another achievement in the glorious success tale and anticipating expanding the tournament to include many matches in the future in order to achieve even greater heights and achievements while highlighting the athletic prowess of the undergraduates.</p><!--kg-card-begin: html--><pre>Vithurshini Subramanieam
Third year,
Department of Computer Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[“Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting”]]></title><description><![CDATA[<p></p><h2 id="about-ieee-wie-sb-ag-of-uop">About IEEE WIE SB AG of UoP</h2><p></p><p>The IEEE Women in Engineering (WIE) Affinity Group Chapter of the University of Peradeniya (UoP) is a student-run organisation that operates under the global IEEE WIE organisation. It is focused on promoting women&apos;s participation and advancement in engineering, providing a supportive</p>]]></description><link>https://gauge.fly.dev/ieee_wie/</link><guid isPermaLink="false">64e588aeb14b750107f88ae6</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:21:55 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image2.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image2.jpg" alt="&#x201C;Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting&#x201D;"><p></p><h2 id="about-ieee-wie-sb-ag-of-uop">About IEEE WIE SB AG of UoP</h2><p></p><p>The IEEE Women in Engineering (WIE) Affinity Group Chapter of the University of Peradeniya (UoP) is a student-run organisation that operates under the global IEEE WIE organisation. It is focused on promoting women&apos;s participation and advancement in engineering, providing a supportive community for undergraduates, and organising activities that promote their professional and personal growth. This organisation aims to inspire, support, and empower women in the engineering field.</p><h2></h2><h2 id="agm-its-importance">AGM &amp; its importance</h2><p><br>The Annual General Meeting (AGM) of a society is an essential event that enables members to gather, discuss, and make decisions on the future of the organisation. It brings together members from different backgrounds and experiences to discuss the progress of society and its future direction. Moreover, the AGM is an opportunity for members to voice their opinions, share their ideas, and contribute to the decision-making process of the organisation. One such organisation that holds a crucial AGM is the IEEE Women in Engineering (WIE) Affinity Group Chapter of the University of Peradeniya.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/6XF_IsnpyCs3kl8LYopkIYq5WREg83WqtiNqIfsFO0qimbYOY8f-6Fre6unoGcXuC5SVvvSaihCyCPjTV1_BG7OjUKRA59B82qsQSTOi60HXRnN_YM7vU1JtP8aMBrpZep6wE_5VAF0vCYoY9xQApw" class="kg-image" alt="&#x201C;Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting&#x201D;" loading="lazy" width="785" height="523"></figure><p><br>One of the key objectives of the IEEE WIE AGM is to elect new members to the committee and discuss the goals and objectives of the organisation. The recruitment process is conducted in accordance with IEEE WIE&apos;s bylaws, which outline the nomination procedures.</p><p><br>Another significant aspect of the IEEE WIE AGM is the opportunity for members to engage with each other and build their networks. The AGM typically attracts a diverse group of attendees from different batches in the Faculty of Engineering. This provides a unique platform for members to connect with their peers, share best practices, and learn from each other&apos;s experiences. Moreover, members can gain a deeper understanding of the IEEE organisation, especially of IEEE Women in Engineering.</p><h2 id="the-speciality-of-the-occasion"><br>The speciality of the occasion</h2><p><br>The AGM of the IEEE WIE Affinity Group Chapter of the University of Peradeniya for the term 2023/24 was held on the 17th of January, 2023. It was lead-off at 12.30 p.m. at the DEEE Seminar Room of the Faculty of Engineering, University of Peradeniya, with the welcome speech of Ms Sachini Senevirathne, the President of IEEE WIE UoP for the term 2022/23. Following that, the meeting minutes of the last AGM were presented by Ms Aveesha Gunasekara, the secretary of IEEE WIE UOP for the term 2022/23.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/iux7D3QgrAAgkesX2sJU3xjQk2jO8xZfofJIsZu3C8TOaLRyHX2hO7q8R4CkeDtFzmPieucTzwxu-RjfYv0EsDekjODJMr-gW5Y40jaARlJpgCSNa5QyAgowqljX_rW_xN_zVUxHW5tjFUpI_eJNyg" class="kg-image" alt="&#x201C;Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting&#x201D;" loading="lazy" width="783" height="522"></figure><p>Moving further, the budget report for the past year was presented by the junior treasurer, Ms Sasini Jayawardana. The headway in the AGM is electing a new president and secretary for the organisation. Accordingly, the former president and secretary resigned from their posts, and Ms Bhashini Jayathunga was appointed as the new president. Following that, Ms Ashini Senara was appointed as the secretary. Subsequently, the newly appointed president addressed the gathering, and the other committee members were designated.</p><h2 id="insights-of-the-senior-advisor"><br>Insights of the Senior Advisor</h2><p><br>The IEEE WIE was honoured to have Prof. Maheshi B. Dissanayake, a professor at the Faculty of Engineering, University of Peradeniya, guiding IEEE WIE as its Senior Advisor. She was the founder, first and interim Chairperson of IEEE WIE Sri Lanka, Chairwoman of the IEEE Sri Lanka Section for 2021/22, and adviser of IEEE WIE SB AG of UOP since 2011.</p><p>Prof. Maheshi B. Dissanayake&apos;s address focused on the skills a young undergraduate should acquire before entering the community as an engineer, as well as the new windows of opportunity with WIE to develop their proficiency and uncover their potential. She also specifically addressed the need for work-life balance and how to keep it properly. Over and beyond that, she urged the attendees to develop confidence and conquer the hurdles they experience as ladies in the profession.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/i-xSYZgGg-fwoJJcYLhs9qg1DOSUR5LxxO2eN7odVqxzWH9D-F8WsrktYAJxGWeDqFMPK2ofFJL3if6EUYLmp5qbusGupFQ61dvssnkekBbbatTWBFaqVDunPnnOdndXs4qn5wZn-marWv47mTRqZQ" class="kg-image" alt="&#x201C;Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting&#x201D;" loading="lazy"></figure><h2 id="the-successful-adjourning-of-the-meeting">The successful adjourning of the meeting</h2><p><br>In conclusion, the AGM of the IEEE WIE Affinity Group Chapter of the University of Peradeniya for the term 2023/24 has been a momentous event that promoted the involvement and engagement of its members, highlighting the past achievements of the society.</p><p><br>The event was completed successfully, motivating the young female undergraduates to join WIE and discover their capabilities. Furthermore, the IEEE WIE Student Branch Affinity Group of UOP is not only for encouraging the social and professional skills of female undergraduates and inspiring them for leadership roles but also to put forth every effort of them for the betterment of humanity. To do so, we hope to bring out several community service projects and an Electrical safety program for non-electrical students in collaboration with &#x201C;Kelani cables&#x201D; and a Communication Service Provider (CSP) lecture series as a technological society in the near future.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/uDXTus_y4NdIk36t80aUbx8-AO16KtbpdjxsY6ysxFfLWupVc8Mh1VMRHfS1jFxxRD7P0MckOcCTt2FAw_uyW0hWt3ERXW69jS4XThRx_cNtbrmLoXSnr997i5_DEEn4crLHxskujUGwe1w2YSCVJg" class="kg-image" alt="&#x201C;Breaking Barriers and Building Bridges: Insights from the
IEEE WIE UOP Annual General Meeting&#x201D;" loading="lazy"></figure><p><br>The social impact of the organisation is significant, and by empowering women in engineering, society is promoting gender equality and contributing to the development of new technologies and services that can benefit the organisation as a whole.</p><!--kg-card-begin: html--><pre>Prannavi Sivaneson
Third year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event “TuneIT” - a Radio Design Workshop & Competition]]></title><description><![CDATA[<p></p><p>IEEE ComSoc (Institute of Electrical and Electronic Engineers Communication Society) Student Branch Chapter of the University of Peradeniya is a leading society in the Faculty mainly focused on the Telecommunication discipline and modern telecommunication trends. The telecommunications industry encompasses a wide range of technologies and services, including wired and wireless</p>]]></description><link>https://gauge.fly.dev/ieee_comsoc/</link><guid isPermaLink="false">64e5860442fb5f010742f058</guid><category><![CDATA[events]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Wed, 23 Aug 2023 04:12:47 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/08/image11.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/08/image11.jpg" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition"><p></p><p>IEEE ComSoc (Institute of Electrical and Electronic Engineers Communication Society) Student Branch Chapter of the University of Peradeniya is a leading society in the Faculty mainly focused on the Telecommunication discipline and modern telecommunication trends. The telecommunications industry encompasses a wide range of technologies and services, including wired and wireless communications networks, internet services, satellite communications, broadcasting, and more. These technologies have enabled the rise of a truly global society, allowing people from all corners of the world to connect and share information and ideas in real time.</p><p>As the Communication Society in the Faculty, ComSoc UoP has announced an event called &#x201C;TuneIT&#x201D;, which is a radio designing workshop and a competition. A radio designing workshop can be a rewarding and educational experience for the enthusiastic participants and can help foster a deeper understanding and appreciation for the principles of radio design. Though the world has evolved in the telecommunication industry it may be handy for undergraduates of Electrical and Electronic Engineering, to be in touch with the basic fundamentals behind those fabulous engineering innovations.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/fxVTUedVN1HD-bBIXKwm9IBHoDJ1d8-neXNvgqVrag47YAN5tK9hMKHmYJHFMwSIrHd-nR0K5pVhCSIbsRlWU0EAbeM_ITWXBSFi9v1X456S7ycuqY3J-Xj-huP85Q3RMBVRi6R5XoZRQWsib4or8w" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="288" height="192"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/B7-EW-J9arhCchX5KrZunjcGXo8wzpj9_jBPn8J1baEFDIOmRWR7tpUD49Iz24xnp9w30gv5t-IBAslyRM9UDmUtywaMZAD1NdxGgptWFiDkxRTVUu8m4Cdj59Sm5KbhzgpLUuRdMN9BKKyJi2lNiA" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="284" height="189"></figure><p><br></p><p>&#x201C;TuneIT&#x201D; was a one-day program, and it was held on the 7th of December 2022 at the Engineering Faculty premises of the University of Peradeniya. The event was fully organized by the committee members of the IEEE ComSoc Student Branch Chapter of the University of Peradeniya, which is led by its Chairperson, Miss Malsha Koswaththa, and Vice Chairperson, Mr Tharika Liyanage. The event was effectively carried by the guests of the Radio Society of Sri Lanka who are very capable of conducting such an event, talented and humble engineers with a ton of experiences in their professional career as telecommunication engineers.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/qAwQuZIsujiyI8cadBaFk-d0rQWJJ-Vl-P_-9bhzMHNCoBKajEvtR9hEu4CHIU4uSIIfUDbpkhfZWRonD0tz0MwWrdJ3o9yQ2g-FcnYU9k3wPA_yipclW9otCRdO3k9QXBxWzWgUimDps4OLjNxUog" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="301" height="201"></figure><p><br></p><p>The main goal of the Society for organizing and holding up such an event was to give undergraduate students a basic idea about Radio Technology, give them an opportunity to practically engage with Radio signals, and let them have hands-on experience with Radio Technology Equipment. &#xA0;&#x201C;TuneIT&#x201D; wasn&#x2019;t an event where all the participants were asked to sit and listen to the keynote speaker for the whole day, but it was an interactive session where all the participants were supposed to follow up a lecture to some point and after that, use the learned theories in practice building a simple Radio Design which the experts from the Radio Society of Sri Lanka guided. All enthusiastic students from inside the University, as well as outside, were warmly welcomed to join the Workshop and gain some knowledge and memorable experiences.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/l2SVOaYAXS1ZZ9-N84R7qBjQOoCYxjdy--k67qRdVeWFApH3L8n2GwSh1OPKV5n6I-rmR8wnBlun_rg0BBbsByqwCyzH8IeP_W4-RJFznEZ6myCuJvqI4WNMDgnbgX2tAog8SCBpVLwPiyiJPZN6_w" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="294" height="196"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/_s6b8HvSmcqRZRn12sGYHrqmP3RtnA9PRQbLWVWmIXFsbsm3xKAReDgbjamuClhXjHomOl8jBBEKFizqs4gAcOTtj1hrX197RnWPoRMhn6PFXhUti6LDKgibGJoKXZ5AX07Re8FAMdeRaSgyfXi2ZQ" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="290" height="194"></figure><p><br></p><p>Since the event was planned with some team events, all the participants were asked to register as a group, including five enthusiastic undergraduates and an interesting name for their team. The registrations of the teams were taken before the event due to the limited number of available seats. Each of those teams was provided with the necessary equipment to implement the Radio with their team members. After the registration deadline, there were fourteen groups registered for the event which was a huge encouragement for us, to see that there are many students who are willing to gain some experience and knowledge in telecommunication disciplines.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/xm9hJzkVhHvCSp9Vnz5N-EGD7L4oVDi4mPzHfAlYl1lMR3qhoTyY8W6GPtLkHmxaGH4XD94QCs3jfl_LbHUT4FYEuUY8vNUvzQ8rn0LLFk9SdKDecEmJ6cDMdATvjfDzwqxmekBCULpsr9QhdqBeLw" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="283" height="189"></figure><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/phmoJgjrvQ3ktsHfNNKGfooHP0gEmYNg5_xkfU5atxh97IOltW8HLMqJ6QI8j0ULA13STQDk_UxcNWIa4XhfLoIoKhY6tirnm00IT1hOXZxc0ia4h8Yw1CpU6AwepW6tMR4Pe2gw3v2yQ2gA3m1usA" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="288" height="192"></figure><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/CPW6RWjv9boPRe-Gw4lZkp5o1PhcAzYgmpx_nH7V0VJPJjMlJkfP-czUoeq7DA2Pf4RxT_2G6gByzdzjE-Ix_VV_I6S4lSdwE18aZ4s4e3nT-AmPxnk9roEr6KtzsBVgFG5q7NhHpU2PcpTjtkn1jQ" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="286" height="191"></figure><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/Y_8vlwn7iSA1TmKLPbCkPI5_GtSncUT8k_YKryjg_MPOin1WuuzUgB6A1gr_n4OoMJiOHQBAPgrPJS6Xr_MSvjpgkwz0KLs9nKMJKyU-A0XH_1OsazDxmoOPdxnJrHFzllDvcSAyjuxepIHEjEVNlQ" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="285" height="190"></figure><p><br><br></p><p>At the start of the event, all participants were educated with a lecture series on the Basics of Radio Technology, its working principles, and applications in day-to-day life. This simple yet very informative series was carried out by Mr. Tharanga Premathilake of the Radio Society of Sri Lanka. After enlightening the students with such valuable knowledge, the students were then asked to be engaged in a practical session based on Radio signals which was a fresh experience for all the attendees of the event. In this part of the event, students were given the chance to communicate in real-time with some other members of the Radio Society of Sri Lanka working on other Radio Stations from all over the country via a Radio Setup which was implemented by the engineers of the Radio Society of Sri Lanka. All the participants were entirely delighted to experience this real-time communication via the Radio Setup since it was a rare and valuable experience that many would not get in their lifetime. The event was more delighted by allowing the participants to practically use the setup and talk with an unknown person on the other side of the Radio Station. It was a pleasing experience for us all to have a word with another enthusiastic engineer in a faraway station. They provided some valuable advice and clarified all the doubts of the participants.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/fBetL1W6-UqL52IYDOuDoFU4eOPFlDK_h8PplRYvcpJguU2E3gsdMUOWBipD2Idbp2oSURFsi5JrwL0Y1-9zL15Wts6C5hReXs6sfsZbZ9c_gKoN_tlWSEo_WXFkDpjzhLlauzs4RbA7CLkwH7NYQw" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="323" height="216"></figure><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/J2nNqwFM7frk5nS1yrE_CnjuYvoXNnmOyzPr94s1EueglGES4-Wkvw-F8BjW1Y0OXIj3F6clyVt82mvO2d6hc4nBnvUuwzZwjenqJ3OShLfbu4ASxKVRoQSPvZhRU9FH4qN6ppEUG8aXqzdFR488MA" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="321" height="214"></figure><p><br></p><p>After the interactive session with the radio setup, it was time to have a break and be refreshed for the next part of the event. In the second session, Engineers from the Radio Society of Sri Lanka provided another short and very informative session about the modern aspects of receivers and antennas used for telecommunication purposes. Participants were allowed to get hands-on experience with the devices that they brought to the event which was an interesting experience to see the functionality of each piece of equipment.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/MdwOBzHhgQCuJ8mt8Pzml87RP-WgYOIa_5U188dzM8tCZTNKe_yabAiciAorCR6CWZnyjlxRP-UV5Nl99vxycrn5MlkiS-qqJ0N3UQOGv2GYvjKBtc1BQFq4BJNTGYMDmSgQKykr5NpuVDMcPh-V4A" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="204" height="306"></figure><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/QI2pR0aZeMk5Jkm316yL1ibcZK-z4scdhWebBhe9x890QosVBC-Wm5vtPA4pMrUgXul_jjGazPHwgLpzXsSoohGl3_jS4V1fRmxXnz0bMIWwNvXrZFqyEfRJClWM1jQ9AzwL1pmyJIjmRpbXE43n6Q" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="467" height="311"></figure><p><br><br></p><p>Concluding that valuable lecture, it was time to commence the most awaited and thrilling part of the event, the &#x2018;Radio Design and Competition&#x2019;. In this part of the session, participants were asked to build a Radio Signal Receiver with the aid of knowledge they were provided at the prior part of the event. All the necessary equipment and instructions were provided to the groups and all participants were guided by professionals from RSSL and aided by the members of the ComSoc society. Participants were so busy implementing the Radio Signal Receiver. Yet, they were delighted to compete with each other using their abilities in handling electronic components and assembling them in their unique designs. Each team had to use the Radio Signal Receiver to follow up and find the emitter which was hidden in the Faculty premises. So, all the teams were hurrying to implement the receiver first and get in the fox hunt challenge. After all the groups were done constructing the receiver of their respective groups, the competition began!</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/svaKWyDGGQD1sUz6U_Cpy4LZBH9zBDfVD3W3yych07iNoOmVc59Rtswfc6Ivg0R2-UMhkwF0Oq0zlSa1yODe_H2oyiQkQ1A_5DitOmJBY-t6kTnGUlrzKmbgV8a9cvTHFPTqG3--wT5HKoTaUIyIsQ" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="286" height="191"></figure><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/JCTmbyeGIvFzt-_CfzDvM6UDSMby3tPPbKTSRbJ7XkXRaBphHkHS-gfhCubxmRg3cIHksqbZ450EqWhhlLl2t_mTxFlx7x1eVOpxAIJxQi-26M76VwhGZCI7Fi7_71wvVODvL6crVNxKrXuRy9dUXg" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="285" height="190"></figure><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/yLpNUFAWtuXon71BTrYcDIMIJ16rvj1wbG7MuKcbL-bFOIgq7YbOT0qyYfOOtweh_1KvACYJ2t-s_jvgdZ_enAhD0MInpInLlu4CYk9pU7CVa3gFOT74hV_ZGF5v5Wu6Q2qGtaMB0g4GsenHsB0WqA" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="534" height="304"></figure><p><br></p><p>It was amazing to watch the designs by each team using the fundamentals that they were taught, improving it further with their own abilities and visions. Many teams were able to finish implementing their Radio Signal Receiver and went outside to participate in the fox hunt challenge. They were not given a slight hint about the whereabouts of the transmitter, and they were supposed to find it with the aid of the receiver they built.</p><p>After some time, one team named &#x201C;Falcons&#x201D; was able to find the hidden emitter and complete the foxhunt challenge successfully. For the second and third places, it was considered the design of the receiver that each team made, inspecting the soldering skills, assembling skills, and finishing of the receiver. Only the first place was awarded a valuable prize along with valuable certificates for each member of the team &#x201C;Falcons&#x201D;. All the participants were happy to be a part of the interactive and educative event for all of them. Each participant was appreciated with a certificate for their encouragement and active participation in the whole event.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/vosbKNdjlI8gncGfoBXWfcTO-Y610jdBQN2FF3EPovNAagUyRUDsc9bc_JQalWjG7LPQAluMcHyjIMQZEzqYeZxal72zk2hBSbWVcrOhTDT63sohEyZD0b8AADpka72r7A78lRJRTPVjVbqlziXpJA" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="399" height="266"></figure><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/Aj5gQjtknQnorpO-6P4lJwdSAxALNE1IkrD89jz58Cqxth_HJ6_1UXXte4ibr3dj07qKYxKWJmv8kdu0FgBv-Ph0tvhpt9QaFvDqZy5RREn3cn_e4lnRkc39YvD707sqrTJDwviFJVww-FoDjWm4kg" class="kg-image" alt="IEEE ComSoc SBC UoP collaborated with the Radio Society of Sri Lanka for the event &#x201C;TuneIT&#x201D; - a Radio Design Workshop &amp; Competition" loading="lazy" width="306" height="397"></figure><p><br></p><p>Finally, it was time to wind up the session, thanking the members of the Radio Society of Sri Lanka and appreciating their service and contribution with a token of appreciation. While the final part of the event was taking place, some little refreshment was provided for each participant since they were all exhausted with the fox hunt challenge.</p><p>The event was indeed a tremendous success, with all the support received from the engineers of the Radio Society of Sri Lanka and from the enthusiasts who participated in the event with passion and willingness to add something new to their engineering careers.</p><p><br></p><p></p><!--kg-card-begin: html--><pre>Shanon Gunawardana
Third year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[Deep learning]]></title><description><![CDATA[<h3 id="what-is-deep-learning">What is deep learning</h3><p>Deep learning is a type of machine learning in which a model learns to perform classification tasks directly from images, text, or sound. Simply it teaches computers to do what comes naturally to humans by learning from examples. It is the key technology behind every single</p>]]></description><link>https://gauge.fly.dev/deep-learning-2/</link><guid isPermaLink="false">646d2efb91afcc0210cf398a</guid><category><![CDATA[articles]]></category><category><![CDATA[general_articles]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Tue, 23 May 2023 21:37:57 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/05/deep.png" medium="image"/><content:encoded><![CDATA[<h3 id="what-is-deep-learning">What is deep learning</h3><img src="https://gauge.fly.dev/content/images/2023/05/deep.png" alt="Deep learning"><p>Deep learning is a type of machine learning in which a model learns to perform classification tasks directly from images, text, or sound. Simply it teaches computers to do what comes naturally to humans by learning from examples. It is the key technology behind every single marvellous invention in the world of AI. Like driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost, virtual assistants ranging from Alexa, and Siri to Google Assistant which provide the opportunity to learn more about your voice and accent, thereby providing you with a secondary human interaction experience. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. While deep learning was first theorized in the 1980s, it is getting lots of attention lately for two main reasons. Also, it&#x2019;s achieving results that were not possible before.</p><ol><li>Deep learning requires large amounts of labelled data. For example, driverless car development requires millions of images and thousands of hours of video.</li><li>Deep learning requires substantial computing power. High-performance GPUs have a parallel architecture that is efficient for deep learning. When combined with clusters or cloud computing, this enables development teams to reduce training time for a deep learning network from weeks to hours or less.</li></ol><p>In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound. Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance. Models are trained by using a large set of labelled data and neural network architectures that contain many layers.</p><h3 id="deep-learning-as-a-state-of-the-art">Deep Learning as a State-of-the-Art</h3><ul><li>It is because the following three technological enablers make this degree of accuracy possible.</li><li>It is easy to access massive sets of labelled data</li><li>Increase of computing power &#x2013; High-performance GPUs accelerate the training of the massive amounts of data needed for deep learning, reducing training time from weeks to hours</li><li>Pretrained models built by experts.</li></ul><h3 id="day-to-day-applications-of-deep-learning">Day-to-day applications of deep learning</h3><ul><li>Deep learning applications are used in industries from automated driving to medical devices.</li><li>Automated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.</li><li>Aerospace and Defense: Deep learning is used to identify objects from satellites that locate areas of interest, and identify safe or unsafe zones for troops.</li><li>Medical Research: Cancer researchers are using deep learning to automatically detect cancer cells. Teams at UCLA built an advanced microscope that yields a high-dimensional data set used to train a deep learning application to accurately identify cancer cells.</li><li>Industrial Automation: Deep learning is helping to improve worker safety around heavy machinery by automatically detecting when people or objects are within an unsafe distance of machines.</li><li>Electronics: Deep learning is being used in automated hearing and speech translation. For example, home assistance devices that respond to your voice and know your preferences are powered by deep learning applications.</li><li>An ATM rejects a counterfeit bank note.</li><li>A smartphone app gives an instant translation of a foreign street sign.</li></ul><h3 id="how-does-it-work">How does it work?</h3><p>First of all, let us dive deep and figure out the way how it processes.</p><p>Most deep learning methods use <a href="https://www.mathworks.com/discovery/neural-network.html">neural network</a> architectures, which is why deep learning models are often referred to as deep neural networks.</p><p><br></p><figure class="kg-card kg-image-card"><img src="data:image/png;base64,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" class="kg-image" alt="Deep learning" loading="lazy" width="346" height="134"></figure><p><br></p><p>A deep neural network combines multiple nonlinear processing layers, using simple elements operating in parallel and inspired by biological nervous systems. It consists of an input layer, several hidden layers, and an output layer. The layers are interconnected via nodes, or neurons, with each hidden layer using the output of the previous layer as its input.</p><p>Let&#x2019;s say we have a set of images where each image contains one of four different categories of object, and we want the deep learning network to automatically recognize which object is in each image. We label the images in order to have training data for the network.</p><p>Using this training data, the network can then start to understand the object&#x2019;s specific features and associate them with the corresponding category. Each layer in the network takes in data from the previous layer, transforms it, and passes it on. The network increases the complexity and detail of what it is learning from layer to layer. Notice that the network learns directly from the data&#x2014;we have no influence over what features are being learned.</p><figure class="kg-card kg-image-card"><img src="data:image/png;base64,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" class="kg-image" alt="Deep learning" loading="lazy" width="438" height="258"></figure><p></p><p>Deep learning models are trained by using large sets of labelled data and neural network architectures that learn features directly from the data without the need for manual feature extraction. A convolutional neural network (CNN, or ConvNet) is one of the most popular algorithms for deep learning with images and video. Like other neural networks, a CNN is composed of an input layer, an output layer, and many hidden layers in between. The internal process in a CNN is extracted below using a flow diagram descriptively.</p><figure class="kg-card kg-image-card"><img src="data:image/png;base64,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" class="kg-image" alt="Deep learning" loading="lazy" width="672" height="243"></figure><p>Deep learning can be extracted as an AI function that mimics the workings of the human brain in processing data for use in detecting objects, recognizing speech, translating languages, and making decisions.</p><p><br><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br></p><p><br><br></p>]]></content:encoded></item><item><title><![CDATA[Still only one-fifth of the Earth’s ocean floor is mapped]]></title><description><![CDATA[<p><em>A research ship using sonar for higher-resolution seafloor mapping.</em></p><p><em><a href="http://www.ausseabed.gov.au/about/mapping">http://www.ausseabed.gov.au/about/mapping</a></em></p><p>Also known as seabed imaging, ocean floor mapping is the measurement of the depth of the sea bed at a certain point. After obtaining a set of data for such depths, &#xA0;mapping can</p>]]></description><link>https://gauge.fly.dev/still-only-one-fifth-of-the-earths-ocean-floor-is-mapped/</link><guid isPermaLink="false">643a4a617c076c021060eae4</guid><category><![CDATA[articles]]></category><category><![CDATA[general_articles]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Tue, 23 May 2023 21:22:22 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/04/image8.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/04/image8.jpg" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped"><p><em>A research ship using sonar for higher-resolution seafloor mapping.</em></p><p><em><a href="http://www.ausseabed.gov.au/about/mapping">http://www.ausseabed.gov.au/about/mapping</a></em></p><p>Also known as seabed imaging, ocean floor mapping is the measurement of the depth of the sea bed at a certain point. After obtaining a set of data for such depths, &#xA0;mapping can be done. These maps are known as bathymetric charts and can be used to perform bathymetric studies.</p><p>While the history of seafloor mapping goes about 3000 years back, with the first evidence of water depth measurements in historical records from ancient Egypt, its first large-scale scientific application was not until 1870, during the HMS <em>Challenger</em> oceanographic expedition. With the developments of underwater acoustic techniques, the echo-sounding era begins at the beginning of the 20th century[1].</p><p>In 2017, when the Nippon Foundation-GEBCO Seabed 2030 Project was initiated, only 6% of the global ocean bottom had been surveyed with modern measurements at a reasonable resolution. Today is number stands at 19% level with more than 80% of this vast underwater realm remaining unmapped, unobserved and unexplored. The GEBCO Seabed 2030 Project&#x2019;s mission is to bring this to 100% by the year 2030. [2]</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/u4_gZPfAuj6NIVj5W1QblzEkZ9laSN5p_0VdnjUe0naZxXOXjXPXhCJS3nJ9IEznQTV_Sib4y52uiqIl8i9_Sg3BwRcigvPOH8tMYb9tIXXWVu-SIcNzwa7YO-cu91_UaGcw3PYLKtHNJPmcg7fWLw" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="376" height="246"></figure><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/Dgw-w6ZLICrs96kmG43yGUMrpRGBzgKKp-LRVkBFT_jw894YZ80ZRqzP3aRnVWI8W0wJOg9xYrs_qgroIG2YHIbQmmVrYRN_fHrfr08Zg3fBGABNmb6zrJnGCer3JC1Wao--ON7FRuWS1woKkk5NVg" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="624" height="300"></figure><p><em>Map showing the areas(black) which are yet to be mapped with reasonable resolution.</em></p><p><em><a href="https://seabed2030.org">https://seabed2030.org</a></em></p><p>About 71% of the Earth&#x2019;s surface is covered with water and nearly 97% of that water is from our oceans. That is nearly 70% of the Earth&#x2019;s surface is covered with seawater and underwater. Getting a detailed knowledge of the shape of the seafloor is critical for the safety of navigation and many other offshore applications such as mineral exploration and extraction, offshore wind turbines and deep water research activities. High-resolution seafloor maps provide vital information in tracking and protecting marine life, allowing us to establish solid and sustainable conservation measures. In other words, it&apos;s crucial for the safety of marine natural resources as well as humans.<br><br></p><p>The first measuring devices of depth were sounding poles and lines with weights attached to them. Most of the time, weights made out of lead were used. Sometime later, similar systems using wires and a winch were used for measuring higher depths but these methods were very inefficient and time-consuming.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/AI90fZJna7e4wamKVEJQvCOBrDttEUHWjRn2rwDXTV50PBp1dAR8y-vG4uOY1f81LmPSvZTeEvUCIVItbr4YjiY43HEr2rAjaTS-RFyec7xXJMotBlG4LCPULG8pj8vAhXtoNwHO3oWwQzIOkQXA-w" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="174" height="266"></figure><p><em>Using sounding pole to measure depths in 1934, Louisiana</em></p><p><em>NOAA photo library</em><br></p><p>In order to increase the efficiency and the need to detect underwater objects, exemplified by the search for the Titanic that sank in 1912, as well as submarine warfare during World War I, mapping methods using sound waves started to merge. The development of Single Beam Echo-Sounders (SBES) constituted a significant improvement in terms of accuracy and efficiency over earlier equipment. SBESs are configured with piezoelectric crystal- or ceramic-based transducers that can generate and receive acoustic signals. The depth of the seafloor is determined by measuring the two-way travel time of a sound wave that is sent and reflected back from the sea floor.&#x2003;&#x2003;<em>NOAA OCS</em></p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/hjx9utib--SfyX1SzIT848ZlfEDcLJF8gtS28XxObm82eSQYkgm0X22RlL97HMSVzqfz0XOWPK6TZBaJD850kN5pUoaIzYirO1RORe5jpc8kbo6krTJaxTd5Jkc8mukHkkQKLL7RiS8kgkKQPbDu6Q" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="395" height="263"></figure><p>In the 1970s with the development of the satellite-based navigation system global positioning system (GPS), Multibeam echo-sounder systems became popular. Multibeam systems radiate a fan of the sound and listen to the returning echoes of the emitted signals in narrow sectors perpendicular to that fan, resulting in the mapping of a swath of seafloor instead of just a line. Compared to SBESs, they have the advantage of collecting higher-resolution bathymetric data and mapping an area in a much shorter time.</p><p>One of the drawbacks of these acoustic methods is that the resolution decreases with increasing water depth. This is due to the expansion of the acoustic beam as it travels through the water column [3]. This challenge could be overcome by using vehicles operated near the seafloor as underwater robots in deep waters.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/7XkvSCkGdc1crj_tANTxO4c8hzXNpiuaN7he46rqH18MXZdKyNm8uDwmxfrYFrJqbsicG4Y5DhP1QKL-M95dMSXO3JqDv3gGGrpgo9oDwfyHeYBE2aK-1FPJINn5L5EBTPYVfrr2DJB-vodMd9DGmw" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="304" height="208"></figure><p><em>Animated picture of a UAV mapping the ocean floor</em></p><p><em>GEOMAR</em></p><p>With the development of the satellite industry and more and more satellites being put into orbit enabling high spatial accuracy for environmental measurements globally, &#xA0;Satellite-Derived Bathymetry was used for seafloor mapping in coastal environments. But this method is restricted to a shallow area with high water clarity. Satellite platforms collect data in multiple spectral bands, spanning the visible through infrared portions of the electromagnetic spectrum. Water depth estimations are based on the attenuation of radiance as a function of depth and wavelength in the water column.[4] With the launch of altimetric satellites, satellite-altimetry-derived digital terrain models were developed. These are used to reveal large geomorphological features of the ocean floor.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/NcwxttJMq0pLGHbmczbeT__o9xV9yh3XJobvEjZY-6-kNpoiXcxz9x759tFwmqSaf_olRVmONtZhhgJuwDwYkUIEb0316dVHSs-XLT-JDKKD4VB8uGd4fd7rg876rKztZbIQpAkFJ_X_1QUcHP4ttw" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="255" height="204"></figure><p><br></p><p><em>Seabed mapping using satellites</em></p><p><em>NASA JPL</em></p><p><em>Using satellite radar altimeter to map the ocean floor</em></p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/qozh-hoZIJAWliHWJqOD06pzjpFaZFSw9zbUtOmPCNv3ExhhHFVpx64fJn3NGq3FLozIVgtFXOJ7VTB8f75ptuM5xx_eoZQWyYpFvzlCoguhAe1LXsNT3bXSJZL8dQsOXrvKqr-FuFd-3xgwbjxhTg" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="302" height="332"></figure><p><br></p><p>Another option to map shallow areas is the use of bathymetric LIDAR (Light Detection and Ranging), a technique that transmits laser pulses from an airborne platform and measures their return. The water depth is calculated from the time difference between the reflection from the water surface and the reflection from the seafloor [5]</p><p>The newest &#xA0;technology of Photoacoustic Airborne Sonar brings about a revolutionary change in the advancement of seabed mapping techniques. This is a &#xA0;hybrid optical-acoustic system. Engineers at Stanford University have developed an airborne method for imaging underwater objects by combining light and sound to break through the seemingly impassable barrier at the interface of air and water.[6] In this method, the Photoacoustic Airborne Sonar System first fires a laser from the air that gets absorbed at the water&apos;s surface. When the laser is absorbed, it generates ultrasound waves that propagate down through the water column and reflect off underwater objects before racing back toward the surface. This allows it to image even through turbid water and carry out large-scale aerial searches of sunken ships and planes and map the ocean depths with a similar speed and level of detail as Earth&#x2019;s landscapes. &#xA0;This makes it possible to scan the ocean floor rapidly, from a helicopter, rather than relying on a slow-moving ship or submarine.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/uvPNj3C4RIM4p4OVcDhASkHCtJvr7rYw4IZqwJolIzqm-mh-wO2EmUqrRRKqOmErNTeLPXmfvHLI0avoqLthAxtPHzl76n0gymyPpjNCsLYEDNHACVE-TOkxMnJ8M28AORF84YkfgP4QVTfO1h776w" class="kg-image" alt="Still only one-fifth of the Earth&#x2019;s ocean floor is mapped" loading="lazy" width="578" height="526"></figure><p><em>Schematic of Photoacoustic Airborne Sonar System</em></p><p><em><a href="https://www.inceptivemind.com/photoacoustic-airborne-sonar-system-aerial-underwater-surveys/16484/">https://www.inceptivemind.com/photoacoustic-airborne-sonar-system-aerial-underwater-surveys/16484/</a></em><br></p><p>With these developments in ocean mapping techniques, it is possible to map the seabed faster and with high resolution. But using these methods to properly map the whole ocean takes some effort. Some of these will come from a great crowdsourcing effort - from ships, big and small, routinely operating their echo-sounding equipment as they transit the globe. Even small vessels - fishing boats and yachts - can play their part by attaching data loggers to their sonar and navigation equipment. And projects should be implemented and carried out in every corner of the world. GEBCO stands for General Bathymetric Chart of the Oceans. It is the only intergovernmental organization with a mandate to map the entire ocean floor. The latest status of its Seabed 2030 project was announced to coincide with World Hydrography Day. Combining all these efforts carried out, it is safe enough to say that we have just become a little more curious about Planet Earth.</p><p>REFERENCE</p><p>1. <a href="https://www.frontiersin.org/articles/10.3389/fmars.2019.00283/full">https://www.frontiersin.org/articles/10.3389/fmars.2019.00283/full</a></p><p>2. <a href="https://www.bbc.com/news/science-environment-53119686">https://www.bbc.com/news/science-environment-53119686</a></p><p>3. Lurton, X. (2002). <em>An Introduction to Underwater Acoustics, Principles and Applications.</em> Cham: Springer.</p><p>4. Pe&#x2019;eri, S., Parrish, C., Azuike, C., Alexander, L., and Armstrong, A. (2014). Satellite remote sensing as reconnaissance tool for assessing nautical chart adequacy and completeness. <em>Mar. Geod.</em> 37, 293&#x2013;314.</p><p>5. Irish, J. L., and White, T. E. (1998). Coastal engineering applications of high-resolution lidar bathymetry. <em>Coast. Eng.</em> 35, 47&#x2013;71.</p><p>6. An Airborne Sonar System for Underwater Remote Sensing and Imaging</p>]]></content:encoded></item><item><title><![CDATA[Starshade  - From Japan to space]]></title><description><![CDATA[<p>Can you recall the sweet memories of childhood when we used to float paper boats on rainwater? Can you remember the excitement of throwing paper rockets to see which one moves the farthest? Do you believe the techniques we used to turn paper into a rocket are being used in</p>]]></description><link>https://gauge.fly.dev/starshade-from-japan-to-space/</link><guid isPermaLink="false">643a4760a3b7d5021058e0c7</guid><category><![CDATA[articles]]></category><category><![CDATA[general_articles]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Sat, 15 Apr 2023 06:44:43 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/04/image1.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/04/image1.jpg" alt="Starshade  - From Japan to space"><p>Can you recall the sweet memories of childhood when we used to float paper boats on rainwater? Can you remember the excitement of throwing paper rockets to see which one moves the farthest? Do you believe the techniques we used to turn paper into a rocket are being used in mainstream projects all around the world?</p><p>With the big commotion out there for colonizing Mars, space exploration also getting high attention not only from organizations like NASA but also from astronomy enthusiasts and local communities. One of the main targets of space exploration is to discover new exoplanets which are highly likely to sustain life.</p><p>But the problem is these exoplanets are extremely dim when compared with their host stars and they are located very close to the host stars making it more difficult to observe. Currently, the method used by satellite telescopes to capture them is known as the transit method. Even though the transit method is widely used, this is not very effective.</p><p>When we want to observe a bird around noon, we usually cover the Sun with our hands to see it clearly, right? In a bright environment, if we can block the direct light emitted from the light sources, other objects become more detailed and easier to observe. Starshade is a proposed spacecraft that can utilize the above method to create an artificial eclipse effect, so the exoplanets will be exposed to the telescopes.</p><p>The star shade is an enormous sunflower-like structure that can shield the telescope from the direct light of the host star. This structure is supposed to be 36m in diameter. A structure of this size is too huge to be transported in a rocket. If you are wondering what is the connection between a small paper boat and a giant sun shield, here is the big secret. Both of them are applications of origami. Since the structure is as large as a baseball ground the scientists and engineers of the Jet Propulsion Laboratory (JPL) of NASA are using techniques of origami to compact the massive shield to fit in a modern rocket.</p><figure class="kg-card kg-image-card"><img src="https://lh6.googleusercontent.com/_0r3UJ449G-GUlm2JJK9QA25NHtvA2vkF3uxDHig1teJEL_rzr0O_TqLrwMkOBBD1itYRGCq_27tVm-ZFOl0k_xt6-_WXegVGlUq80F7u7XnzYFFbEJFExFVwjxtDWZXrjpHeXtxN469_s8infHjig" class="kg-image" alt="Starshade  - From Japan to space" loading="lazy" width="368" height="207"></figure><p>The Starshade model has two major parts. The middle part of the sunflower is like a shield. It can be folded into a small hexagonal-shaped object. The outer petals are rolled over it. Although the design looks simple, these parts should be unfolded in the space at millimetre accuracy. The biggest challenge for JPL scientists is to implement the theoretical model on a large scale with higher precision. They have already built smaller versions of the model and currently enlarging it to the required size. The project has been under discussion since 2005 and yet it was not been able to implement successfully. But there are signs that this will be realistic within the next few years.</p><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/u2aaBGv6ceptKP7bhZUU75ydybqbj8PxBPId_Wiv2b5iglYUj1I9X0LKfjSiwVgpVhMYg-NuJfdwP5hg_BFxit48vM8ajhj9GnjLGEJgyM5xUIaMRiRDWC1RniG1RlM8R0itJR1-IfoGtnM4pom4Fw" class="kg-image" alt="Starshade  - From Japan to space" loading="lazy" width="334" height="188"></figure><p>Starshade is not the first spacecraft that uses origami techniques. &#x2018;Mars phoenix lander&#x2019; had a fan-folded solar array named &#x2018;Ultraflex&#x2019;. It was a solar array wing with Z folding pattern. Miura folding pattern, which is a very famous technique to fold a thin surface layer into a small area of space has used in the &#x2018;SPROUT&#x2019; satellite and the space flyer unit in 1995. Apart from space technologies origami is extensively used in designing airbags, stents for heart patients, foldable gadgets etc.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/ibWoEKt1_j3YZUXrb_050pnwJfl-YCCnho9Zl4UnqVqGuYfKJrECZMUACRcXTzXhMM-wAg5m6jKO_lbtAYOjiAGLVHcoZsMs7AKqI7TkZ8Umzj1b5G9N7lsjVyk1ekOObKhtaTLRQOYh82_VKR0a5g" class="kg-image" alt="Starshade  - From Japan to space" loading="lazy" width="294" height="161"></figure><figure class="kg-card kg-image-card"><img src="https://lh4.googleusercontent.com/HdLQHYrV-jBAST7n6MoXKt_SyjQJFiBwIZmt-hGqQp8K6HRxr0hAtmVmHXzxq3s_M7tq53dZ1LJYWAiJTjUwZ1VuEI70lJdtMMoUwe9V9_aa94NwGwNSZSjMFj-k4VY2iad6GfkQZR9QMbcH4Da2nA" class="kg-image" alt="Starshade  - From Japan to space" loading="lazy" width="294" height="161"></figure><p>Although origami is mostly observed as a compacting method in most science applications, there are various aspects of this ancient art that are yet to be discovered. One such great potential can be found in structural engineering. By implementing origami techniques, it is possible to produce higher quality, strong structures with unique aesthetic appeal. There are research being conducted exploring new dimensions of applications. But the practical implementations are still comparatively very low. Origami can be sighted as one of the major fields to which engineers should pay more attention in near future.</p><p>Origami is the art of paper folding which is one of the stunning ways of expressing oneself creatively. Even though we often use the term origami for all folding practices irrespective of the origin, these techniques are believed to be emerged and developed in ancient Japan. One time it was just a method used for home decorations. Now origami has become the major building block of a giant space project. From Japan to space it has evolved and will emerge as a cutting-edge technology in future.</p><h3 id="references">References</h3><p>1. &#xA0;Starshade Would Take Formation Flying to Extremes</p><p><a href="https://www.jpl.nasa.gov/news/starshade-would-take-formation-flying-to-extremes">https://www.jpl.nasa.gov/news/starshade-would-take-formation-flying-to-extremes</a></p><p>2. Science within the art of origami</p><p><a href="https://assamtribune.com/science-within-the-art-of-origami/">https://assamtribune.com/science-within-the-art-of-origami/</a></p><p>3. Incredible Technology: Giant Starshade Could Help Find an Alien Earth</p><p><a href="https://www.space.com/25172-starshade-alien-earth-exoplanets-incredible-tech.html">https://www.space.com/25172-starshade-alien-earth-exoplanets-incredible-tech.html</a></p><p>4. Space Origami: Make Your Own Starshade</p><p><a href="https://www.jpl.nasa.gov/edu/learn/project/space-origami-make-your-own-starshade/">https://www.jpl.nasa.gov/edu/learn/project/space-origami-make-your-own-starshade/</a></p><!--kg-card-begin: html--><pre>Thilanka Pathum Weerasekara
Third year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[DIGITAL SIGNAL PROCESSING]]></title><description><![CDATA[<p></p><p>Digital Signal Processing is the process of analysing and modifying a signal to optimise or improve its efficiency or performance. It involves applying various mathematical and computational algorithms to analogue and digital signals to produce a signal that&#x2019;s of higher quality than the original signal. Digital Signal Processing</p>]]></description><link>https://gauge.fly.dev/digital-signal-processing/</link><guid isPermaLink="false">643a46bca3b7d5021058e0b5</guid><category><![CDATA[articles]]></category><category><![CDATA[general_articles]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Sat, 15 Apr 2023 06:41:18 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2023/04/USASIC---DSP-1920w--1-.png" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2023/04/USASIC---DSP-1920w--1-.png" alt="DIGITAL SIGNAL PROCESSING"><p></p><p>Digital Signal Processing is the process of analysing and modifying a signal to optimise or improve its efficiency or performance. It involves applying various mathematical and computational algorithms to analogue and digital signals to produce a signal that&#x2019;s of higher quality than the original signal. Digital Signal Processing is an area of science and engineering that has developed rapidly over the past thirty years. As a result of significant advances in digital computer technology and integrated-circuit fabrication, this rapid development of digital signal processing occurred. Three decades ago, digital computers and associated digital hardware were relatively large and expensive, considering today, and as a consequence, their usage was limited to general purposes. Hence, many of the signal processing tasks that were conventionally performed by analogue means are realised today by less expensive and often more reliable digital hardware.<br></p><p>Digital signal processing is not the best and proper solution for all signal processing problems. Indeed, for many signals with extremely wide bandwidths, real-time processing is a requirement for such signals, analog perhaps signal processing is the only possible solution. For signal processing, digital circuits are not the only ones that yield a more reliable system. They have other advantages as well. In particular, digital processing hardware allows programmable operations. When talking about digital signal processing, there are some keywords that we should know, like signal, systems and process. A signal is defined as any physical quantity that varies with time, space or any other independent variable or variables. A system may also be defined as a physical device that performs an operation on a signal. When we pass a signal through a system, as in filtering, we say that we have processed the signal. Most of the signals encountered in science and engineering are analogue in nature. Digital signal processing provides an alternative method for processing analogue signals. <br></p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/PUFQ0qBaxQt4q7acW0pEDTBNxfPftcNGuA_VctWUAbkyr-uvjIP43Eh1SlqiFUHXDwgNwFRAcjt885OMop_ij2kOhHZXWUuoJK5B3zPaxwFrBL8FqbU6vIsx9VUKEsHmZ6QuAukTZzgWGMVLmaQ2WA" class="kg-image" alt="DIGITAL SIGNAL PROCESSING" loading="lazy" width="565" height="116"></figure><p>The digital signal processor may be a large programmable computer or a small microprocessor programmed to perform desired operations on the input signal. On the other hand, it might be a hard-wired digital processor configured to perform a specified set of operations on the input signal. When we are referring to why we use digital signal processing, there are some reasonable thoughts to be considered. To understand how digital signal processing, or DSP, compares with analogue circuitry, one would compare the two systems with any filter function. While capacitors, inductors, or resistors would be used for analogue filters and be affordable and easy to assemble, it would be rather difficult to calibrate or modify the filter order. However, the DSP system is just easier and more active to do both calibrating and modifying.</p><p>There are numerous variants of digital signal processing that can execute different operations, depending on the application being performed. Audio signal processing, audio and video compression, speech processing and recognition, computer graphics, photo manipulation, and digital image processing are some of the variants that can be done by using DSP. The difference between each of those applications depends on how the digital signal processor deals with and filters each input signal. Clock frequency, RAM size, and input-output/voltages are some aspects that vary between DSP systems. All of these components are going to affect the arithmetic format, speed, memory organisation, and data width of the processor. One major application is sampling, which is the reduction of a continuous-time signal to a discrete-time signal. Audio sampling and the conversion of a sound wave use digital signals and pulse-code modulation for the reproduction of sound. Using different filters with DSP software, samples of audio can be reproduced through this technique.<br></p><p>Digital Signal Processing is important because it significantly increases the overall value of hearing protection. In fact, this is a very valuable aspect of protecting user hearing, especially when users are immersed in an industrial work environment. DSP systems protect users from unhealthy noise exposure without compromising communication. There are so many advantages to using DSP over ASP (Analog Signal Processing). Digital processors are more impactful and lightweight than analogue systems. Analog systems are less accurate because of component tolerance. It is fair enough that digital components are less sensitive to environmental changes, noise, and disturbances. As well as DSP systems are the most flexible as software and control programs can be easily modified. Apart from a series of advantages, the DSPs have to deal with a few limitations as follows. Additional complexity and limit in frequency loss of information through aliasing are some of them. In high-frequency applications, DSP systems are not suitable.<br></p><p>Digital Signal Processing has evolved so much, right from the mid-70&#x2019;s. It is heavily used in day-to-day operations, and is essential in converting analogue signals to digital signals for many purposes. The quality of the signal can be improved through digital signal processing by removing unwanted parts of the signal. The DSP has a wide range of applicability. They are cost-effective, easy to market, easily configurable, and flexible. Cell phones, which play a key role in present voice communication, is the main area of this technology. The present DSP market is near the $4 billion mark, and it is expected to play an enormous role in next-world applications.</p><!--kg-card-begin: html--><pre>Thilanka Pathum Weerasekara
Third year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[Deep learning]]></title><description><![CDATA[<h3 id="what-is-deep-learning">What is deep learning</h3><p>Deep learning is a type of machine learning in which a model learns to perform classification tasks directly from images, text, or sound. Simply it teaches computers to do what comes naturally to humans by learning from examples. It is the key technology behind every single</p>]]></description><link>https://gauge.fly.dev/deep-learning/</link><guid isPermaLink="false">643a45aea3b7d5021058e091</guid><category><![CDATA[articles]]></category><category><![CDATA[general_articles]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Sat, 15 Apr 2023 06:38:57 GMT</pubDate><content:encoded><![CDATA[<h3 id="what-is-deep-learning">What is deep learning</h3><p>Deep learning is a type of machine learning in which a model learns to perform classification tasks directly from images, text, or sound. Simply it teaches computers to do what comes naturally to humans by learning from examples. It is the key technology behind every single marvellous invention in the world of AI. Like driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost, virtual assistants ranging from Alexa, and Siri to Google Assistant which provide the opportunity to learn more about your voice and accent, thereby providing you with a secondary human interaction experience. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. While deep learning was first theorized in the 1980s, it is getting lots of attention lately for two main reasons. Also, it&#x2019;s achieving results that were not possible before.</p><ol><li>Deep learning requires large amounts of labelled data. For example, driverless car development requires millions of images and thousands of hours of video.</li><li>Deep learning requires substantial computing power. High-performance GPUs have a parallel architecture that is efficient for deep learning. When combined with clusters or cloud computing, this enables development teams to reduce training time for a deep learning network from weeks to hours or less.</li></ol><p><br></p><p>In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound. Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance. Models are trained by using a large set of labelled data and neural network architectures that contain many layers.</p><p><strong>Deep Learning as a State-of-the-Art</strong></p><ul><li>It is because the following three technological enablers make this degree of accuracy possible.</li><li>It is easy to access massive sets of labelled data</li><li>Increase of computing power &#x2013; High-performance GPUs accelerate the training of the massive amounts of data needed for deep learning, reducing training time from weeks to hours</li><li>Pretrained models built by experts.</li></ul><p><strong>Day-to-day applications of deep learning</strong></p><ul><li>Deep learning applications are used in industries from automated driving to medical devices.</li><li>Automated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.</li><li>Aerospace and Defense: Deep learning is used to identify objects from satellites that locate areas of interest, and identify safe or unsafe zones for troops.</li><li>Medical Research: Cancer researchers are using deep learning to automatically detect cancer cells. Teams at UCLA built an advanced microscope that yields a high-dimensional data set used to train a deep learning application to accurately identify cancer cells.</li><li>Industrial Automation: Deep learning is helping to improve worker safety around heavy machinery by automatically detecting when people or objects are within an unsafe distance of machines.</li><li>Electronics: Deep learning is being used in automated hearing and speech translation. For example, home assistance devices that respond to your voice and know your preferences are powered by deep learning applications.</li><li>An ATM rejects a counterfeit bank note.</li><li>A smartphone app gives an instant translation of a foreign street sign.<br><br><br></li></ul><h3 id="how-does-it-work"><strong>How does it work?</strong></h3><p>First of all, let us dive deep and figure out the way how it processes.</p><p>Most deep learning methods use <a href="https://www.mathworks.com/discovery/neural-network.html">neural network</a> architectures, which is why deep learning models are often referred to as deep neural networks.</p><p><br></p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/0IW7WQnYyq1LmVINREIn4ZlKaM966IbFNF11Rv4qys4rClpXs7TKWIK4_NmxcYWyfidyDZSabZBcuJwFdIfv9iKsV-L939LtiE_RqgnznIOzOZ_WAPKVwJaSlnpffghXSNd2TrAAOcgXTUlDNAuX5Q" class="kg-image" alt loading="lazy" width="346" height="134"></figure><p><br></p><p>A deep neural network combines multiple nonlinear processing layers, using simple elements operating in parallel and inspired by biological nervous systems. It consists of an input layer, several hidden layers, and an output layer. The layers are interconnected via nodes, or neurons, with each hidden layer using the output of the previous layer as its input.</p><p>Let&#x2019;s say we have a set of images where each image contains one of four different categories of object, and we want the deep learning network to automatically recognize which object is in each image. We label the images in order to have training data for the network.</p><p><br></p><p>Using this training data, the network can then start to understand the object&#x2019;s specific features and associate them with the corresponding category. Each layer in the network takes in data from the previous layer, transforms it, and passes it on. The network increases the complexity and detail of what it is learning from layer to layer. Notice that the network learns directly from the data&#x2014;we have no influence over what features are being learned.</p><figure class="kg-card kg-image-card"><img src="https://lh3.googleusercontent.com/AYXHNliFF7DIhTT3EdinrcDKvrGKOuGCZzgp7hyy2UaKYy3K-FWDBJvDddFiQCRJ4YSIpfYrhN-2rltK-bXz5xixAU7qOg-ND1Ew74Ln0H0QyjyXCK9wYUhDwqr_c3vbssOip8_WIFcfQR-i6xZHQw" class="kg-image" alt loading="lazy" width="438" height="258"></figure><p><br></p><p><br></p><p><br></p><p><br></p><p>Deep learning models are trained by using large sets of labelled data and neural network architectures that learn features directly from the data without the need for manual feature extraction. A convolutional neural network (CNN, or ConvNet) is one of the most popular algorithms for deep learning with images and video. Like other neural networks, a CNN is composed of an input layer, an output layer, and many hidden layers in between. The internal process in a CNN is extracted below using a flow diagram descriptively.</p><figure class="kg-card kg-image-card"><img src="https://lh5.googleusercontent.com/PQxjvZvhJPesJKCg1ZJ8aNIz7F1FusU6KdPnRjiiCgk0xWza02jXNeC2wTPXtdWvjsRshE4wZkO4nQRFwjumUQunrmSXYvc-uWJ65rWVHitIRr6Ya4H0EvSF_1T-dYVO1U5SAmpiRow5UhgwFe1qhw" class="kg-image" alt loading="lazy" width="672" height="243"></figure><p>Deep learning can be extracted as an AI function that mimics the workings of the human brain in processing data for use in detecting objects, recognizing speech, translating languages, and making decisions<br></p><!--kg-card-begin: html--><pre>Thilanka Pathum Weerasekara
Third year,
Department of Electrical &amp; Electronic Engineering, Faculty of Engineering, 
University of Peradeniya.</pre><!--kg-card-end: html-->]]></content:encoded></item><item><title><![CDATA[Departmental Welcome Party for E19 Computer Engineering Students]]></title><description><![CDATA[<p>With much delight, on October 28, 2022, the departmental welcome party for E19 computer engineering students was held physically from 6 p.m. at the faculty premises. The event was successfully conducted by E18s with the collaboration of the association of computer engineering students, accompanied by the academic staff members</p>]]></description><link>https://gauge.fly.dev/untitled-3/</link><guid isPermaLink="false">639befe0b44a90021136c8ec</guid><category><![CDATA[events]]></category><category><![CDATA[Department Welcome]]></category><dc:creator><![CDATA[Engineering Students' Publication Society]]></dc:creator><pubDate>Mon, 07 Nov 2022 05:37:25 GMT</pubDate><media:content url="https://gauge.fly.dev/content/images/2022/11/314401110_549841187149441_1355660822206334990_n.jpg" medium="image"/><content:encoded><![CDATA[<img src="https://gauge.fly.dev/content/images/2022/11/314401110_549841187149441_1355660822206334990_n.jpg" alt="Departmental Welcome Party for E19 Computer Engineering Students"><p>With much delight, on October 28, 2022, the departmental welcome party for E19 computer engineering students was held physically from 6 p.m. at the faculty premises. The event was successfully conducted by E18s with the collaboration of the association of computer engineering students, accompanied by the academic staff members of the department. The day was made more memorable by some energizing events presented by E18 students and staff.</p><p>Photographed by: Dylan Ramanan, Nimnad Mihiranga</p><p>Edited by: Nimnad Mihiranga, Dylan Ramanan</p><p>Reported by: Aarah Jahufar</p><figure class="kg-card kg-gallery-card kg-width-wide"><div class="kg-gallery-container"><div class="kg-gallery-row"><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314445260_549841487149411_4196605388872205165_n.jpg" width="2000" height="1333" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314445260_549841487149411_4196605388872205165_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314445260_549841487149411_4196605388872205165_n.jpg 1000w, https://gauge.fly.dev/content/images/size/w1600/2022/11/314445260_549841487149411_4196605388872205165_n.jpg 1600w, https://gauge.fly.dev/content/images/2022/11/314445260_549841487149411_4196605388872205165_n.jpg 2048w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314472537_549842337149326_5931410468503982480_n.jpg" width="1365" height="2048" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314472537_549842337149326_5931410468503982480_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314472537_549842337149326_5931410468503982480_n.jpg 1000w, https://gauge.fly.dev/content/images/2022/11/314472537_549842337149326_5931410468503982480_n.jpg 1365w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314406302_549841153816111_3990329063886951916_n.jpg" width="2000" height="1655" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314406302_549841153816111_3990329063886951916_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314406302_549841153816111_3990329063886951916_n.jpg 1000w, https://gauge.fly.dev/content/images/size/w1600/2022/11/314406302_549841153816111_3990329063886951916_n.jpg 1600w, https://gauge.fly.dev/content/images/2022/11/314406302_549841153816111_3990329063886951916_n.jpg 2048w" sizes="(min-width: 720px) 720px"></div></div><div class="kg-gallery-row"><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314327495_549841017149458_4730742524557518498_n.jpg" width="2000" height="1333" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314327495_549841017149458_4730742524557518498_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314327495_549841017149458_4730742524557518498_n.jpg 1000w, https://gauge.fly.dev/content/images/size/w1600/2022/11/314327495_549841017149458_4730742524557518498_n.jpg 1600w, https://gauge.fly.dev/content/images/2022/11/314327495_549841017149458_4730742524557518498_n.jpg 2048w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314474828_549841133816113_5298969112084651885_n.jpg" width="2000" height="953" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314474828_549841133816113_5298969112084651885_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314474828_549841133816113_5298969112084651885_n.jpg 1000w, https://gauge.fly.dev/content/images/size/w1600/2022/11/314474828_549841133816113_5298969112084651885_n.jpg 1600w, https://gauge.fly.dev/content/images/size/w2400/2022/11/314474828_549841133816113_5298969112084651885_n.jpg 2400w" sizes="(min-width: 720px) 720px"></div><div class="kg-gallery-image"><img src="https://gauge.fly.dev/content/images/2022/11/314482910_549841940482699_195849033261384842_n.jpg" width="2000" height="1333" loading="lazy" alt="Departmental Welcome Party for E19 Computer Engineering Students" srcset="https://gauge.fly.dev/content/images/size/w600/2022/11/314482910_549841940482699_195849033261384842_n.jpg 600w, https://gauge.fly.dev/content/images/size/w1000/2022/11/314482910_549841940482699_195849033261384842_n.jpg 1000w, https://gauge.fly.dev/content/images/size/w1600/2022/11/314482910_549841940482699_195849033261384842_n.jpg 1600w, https://gauge.fly.dev/content/images/2022/11/314482910_549841940482699_195849033261384842_n.jpg 2048w" sizes="(min-width: 720px) 720px"></div></div></div></figure>]]></content:encoded></item></channel></rss>