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<!doctype html> <html> <head> <meta charset="UTF-8"> <title>IEICE English Webinar | IEICE The Institute of Electronics,Information and Communication Engineers</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <meta name="keywords" content="IEICE,EiC,IE,The Institute of Electronics,Information and Communication Engineers,電子情報通信学会"> <meta name="description" content="Official homepage of the Institute of Electronics, Information and Communication Engineers.This homepage guides a summary, an events, the publications of the society. 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class="fas fa-chevron-right"></i></a></p> </li> <li> <p><a href="/eng_r/faq/index.html">Faq<i class="fas fa-chevron-right"></i></a></p> </li> <li> <p class="toggle">Representative page<i class="fas fa-plus"></i></p> <ul> <li><a href="http://www.ieice.org/ieice-osr/" target="_blank">International Section Representative page</a></li> </ul> </li> </ul> </div> </div> </div> </nav> </header> <section id="main"> <div class="breadcrumb"> <ul class="clearfix"> <li><a href="/eng_r/index.html">TOP</a></li> <li>Activities</li> <li class="current">IEICE English Webinar</li> </ul> </div> <section class="index webinar"> <h2>IEICE English Webinar</h2> <!-- IEICE Livestream English webinar ここから --> <!--<div class="info_box"> <h5>IEICE Livestream English webinar</h5> <p class="date">coming up on April 13, Wednesday 1:30 p.m. start</p> <div class="clearfix"> <figure><img src="../../assets/img/activities/webinar/Ken-ichi_Sato.jpg" alt="Ken-ichi Sato"/></figure> <div class="txt"> <p class="ttl">Title: How optical technologies can innovate future data center networks<br> Lecturer: Prof. Ken-ichi Sato</p> <p class="btn"><a href="https://us02web.zoom.us/webinar/register/WN_6uHHBug-RN-n3iWcy8_NnA" target="_blank">Registration<i class="fas fa-arrow-circle-right"></i></a></p> </div> </div></div>--> <!-- IEICE Livestream English webinar ここまで --> <div class="inner"> <section class="about"> <h3>About IEICE English Webinar</h3> <p> As a part of overseas activities, IEICE has been dispatching Distinguished Lecturers since 2010. The purpose of this program is to share knowledge, expertise, and insights on the future direction of electronics, information, and communication technologies at events held by IEICE international sections. In the current situation where overseas travel is restricted, IEICE offers livestream and on-demand webinars by Distinguished Lecturers.<br> <br>  Please contact our Membership Section <span class="nsm">member</span> for details. If the international section is involved in the event you are planning to dispatch the lecturer, please contact to the section representative instead.</p> </section> <section> <h3>Distinguished Lecturer Program Series</h3> <ul class="clearfix"> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Murata.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Intermediate</span> <span class="time">Livestream: Friday, November 1, 15:00 PM JST/KST (GMT+9)</span></div> <h4>Basis of Advanced Electro-Optic Sensor for Microwave/Millimeter-Wave Field Measurement</br> - Applications for Precise Field Measurement and Signal Processing - </h4> <p class="name">Hiroshi Murata (Mie University)</p> <p class="contents">DAn electro-optic (EO) sensor is promising for the precise field measurement of electromagnetic wave wireless signals in the quasi-millimeter-wave (10-30 GHz) and millimeter-wave (30-300 GHz) bands owing to negligible field distortion and good linearity. By combing an EO sensor with optical fiber links, remote field measurements are also obtainable, which is attracting a lot of interest in many applications, such as antenna measurement, mobile communication base stations, non-contact imaging for security inspection, molecular fingerprint, environmental sensing, etc. Especially, the photonic-based electromagnetic field measurement (PEM) technology is rather important in precise antenna measurements for the 5G and Beyond-5G/6G mobile systems owing to its extremely low field distortion characteristics compared with the conventional antenna measurement using a metal probe and coaxial cable. The author has developed advanced antenna-coupled electrode EO modulators/sensors using the integration technique of planar antennas on a substrate of high-speed EO LiNbO3 modulators, which is effective for wireless-optical signal conversion with extremely low-signal distortion and reasonable signal-to-noise ratio for precise antenna measurements. The key technical point is the coupled structure of the precisely designed planar patch antenna and standing-wave resonant modulation electrode (operational frequency, input impedance, and Q-factor), which enables to improve high-efficiency conversion from wireless to optical signals compared to conventional EO sensors. In this lecture, the fundamentals of EO modulator/sensor (Pockels effect, optical modulation, etc.) and recent advanced EO sensors operating in quasi-millimeter-wave/millimeter-wave frequency bands are discussed. The high-speed wireless signal detection and signal processing for auto-correlation are also reported. Further applications for the Beyond-5G/6G wireless systems are also to be presented. </p> <p class="btn"><a href="https://us02web.zoom.us/webinar/register/WN_8QwGVvNXR2C3xNci6mpZDg">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Uyematsu.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Intermediate</span> <span class="time">Livestream: Wednesday, September 25, 15:00 PM JST/KST (GMT+9)</span></div> <h4>Data Compression: Principles and Applications</h4> <p class="name">Tomohiko Uyematsu (Tokyo Institute of Technology)</p> <p class="contents">Data compression is a technique that is widely used in data storage and communication. In this presentation, we focus on the lossless data compression, which allows the original data to be completely restored, and explain the basic principles of data compression in information theory as well as practical coding algorithms. Specifically, we explain information sources such as memoryless sources and stationary ergodic sources, types of source codes, prefix codes, Kraft's inequality, and entropy. Then, we prove that the performance limit of data compression, determined by the average code length, is the entropy of the source. Further, we clarify how to construct prefix codes whose average code length differs from the entropy within 1 bit. We also explain practical coding algorithms, including Huffman codes that minimize the average code length, and Lempel-Ziv 77 and Lempel-Ziv 78 codes, which are universal codes whose average code length converges to the entropy as the length of input data becomes long, even if the statistical properties of the source are unknown. Finally, we investigate the actual performance of these codes by compressing test data. </p> <p class="btn"><a href="https://youtu.be/Iw1OaEEmZLc">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-tsaito.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Intermediate</span> <span class="time">Livestream: Friday, August 30, 15:00 PM JST/KST (GMT+9)</span></div> <h4>An introduction to multiobjective optimization problems in nonlinear circuits and systems</h4> <p class="name">Toshimichi Saito (Electrical and Electronics Engineering Department, Hosei University)</p> <p class="contents">LMultiobjective optimization problems require simultaneous optimization of multiple objectives (e.g., cost and performance). In the problem, we often encounter trade-offs: an improvement in one objective causes deterioration in other objectives. The trade-off is characterized by the Pareto front. Efficient evolutionary algorithms have been presented to calculate the Pareto front. The problems have been studied intensively in benchmarks (e.g., the multiobjective 0–1 knapsack problem). However, the studies in nonlinear circuits and systems are not sufficient. The reasons include huge parameter space and complicated calculation of the objectives. For simplicity, we introduce two example problems. (1) Biobjective optimization problems in switching power converters with photovoltaic inputs. The circuits play important roles in renewable energy supply in carbon neutral technology. The first objective evaluates power efficiency and the second objective evaluates circuit stability. Applying piecewise linear modeling, the two objectives are described theoretically and the Pareto front is obtained exactly. The Pareto front guarantees existence of a trade-off between the two objectives (2) Biobjectve optimization problems in discrete-time recurrent neural networks as associative memories. The first objective evaluates memory stability and the second objective evaluates connection sparsity. In order to realize precise calculation, we consider the case where the networks are characterized by the signum activation function and ternary connection parameters. Performing precise numerical analysis in typical examples, the Pareto-fronts are obtained. Based on the two examples, several research directions/themes are suggested. This lecturer is grateful if the suggestions give some hint to studies in young researchers/students. </p> <p class="btn"><a href="https://youtu.be/9lbB_wS3wH8">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Akakura.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">Youtube:Uploaded in July 20, 2024</span><span class="time">45mins</span></div> <h4>ICT in Education -Past Practices and Current Online Education-</h4> <p class="name">Takako Akakura (Tokyo University of Science)</p> <p class="contents">In 2021, the Central Council for Education issued a report titled "Towards Building the Japanese-Style School Education in REIWA". The report calls for "individualized learning and collaborative learning," and ICT is expected to be used. The spread of COVID-19 infection in 2020 forced the introduction of online education at the school level. Since then, ways of effectively achieving individualized, optimal, and collaborative learning in online education have been a topic of discussion. However, the use of ICT in education is not just recent, but has been around for 100 years. Although it was not called ICT, the idea that it is an "educational equipment, i.e., a "teaching machine," that enables education tailored to individual learner rather than simultaneous classes, has been studied primarily by behavioral psychologists. The performance of today's computers is far beyond that of the educational equipment of that time. Attempts have been made in the past 100 years of existence of the teaching machine to use increasingly advanced equipment for achieving individualized and optimal learning. In more recent years, with the rapid advancements in ICT equipment, it has also become possible to achieve collaborative learning remotely (online). In addition, online sequential authentication systems have been developed to prevent students from performing remote test spoofing. In this lecture, based on our past practices and experiences, we will discuss about how the latest ICT methods can achieve "individualized and collaborative learning," including spoofing prevention technologies in online testing.</p> <p class="btn"><a href="https://youtu.be/vopQBbQL6iY">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Noda.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Intermediate</span> <span class="time">Livestream: Tuesday, June 25, 14:00 PM JST/KST (GMT+9)</span></div> <h4>Photonic-Crystal Surface-Emitting Lasers (PCSELs) for Paradigm Shift Towards Smart Society (Society 5.0)</h4> <p class="name">Susumu Noda (Department of Electronic Science and Engineering, Kyoto University)</p> <p class="contents">Laser technology is one of the keys to realize a smart society (Society 5.0), represented by smart mobility and smart manufacturing. However, existing lasers have individual issues that hinder their use in such emerging fields: For example, conventional semiconductor lasers have issues of low brightness and low functionality even though they have merits of compactness and high efficiency. These issues result in systems that are large and complicated, and whose application to direct material processing is difficult. Photonic-crystal surface-emitting lasers (PCSELs) show promise to give solutions to the issues of existing laser technologies, based on their broad-area coherent two-dimensional (2D) resonance at a singularity (Γ) point of their 2D photonic band structure. In this webinar, recent progresses in PCSEL development, including the formulation of a design guideline for realizing 100-W-to-kW-class single-mode operation, the experimental demonstration of a brightness of 1 GW/cm2/sr, which rivals to bulky lasers such as gas and solid-state lasers, and various functionalities such as 2D beam steering and emissions of arbitrary beam patterns are discussed. In addition, future research directions of PCSELs as well as the recent establishment of the center of excellence for PCSELs are described. </p> <p class="btn"><a href="https://us02web.zoom.us/webinar/register/WN_AUZKUzCmRGanCaKhPHwOaw">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Morioka.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span> <span class="time">YouTube</span></div> <h4>Introduction to Electromagnetic Metrology: Precision Electromagnetic measurements</h4> <p class="name">Takehiro Morioka (National Institute of Advanced Industrial Science and Technology)</p> <p class="contents">A fundamental quantity in free space electromagnetic measurements is the electric (or magnetic) field strength, and many standard documents of electromagnetic compatibility (EMC) regulate the field level radiated from a device. An antenna is employed for the field strength measurement, and its sensitivity against the impinging field is ordinarily calibrated by a certificated laboratory. Even though a variety of antennas has been developed and are integrated into many systems, for the precision measurements a fundamental antenna, such as a dipole still has many advantages due to its simple structure. Antenna factor (AF) is a well-known parameter to show the antenna sensitivity. Similar to many other measurement quantities the AF cannot be measured directly and should be related to the measurable quantities. Calibration of the instrument links your measured values to the higher measurement standards with uncertainty. To confirm measured AF the measurement site ideality should also be investigated since antennas couple with the surrounding objects.In this talk, you will learn about metrological approach in carrying out the precision E-field measurement including the uncertainty analysis. Since an open-area test site (OATS) and a semi-anechoic chamber simulating a half-free space are used for EMC measurements below 1 GHz, the dipole AF calibration at the OATS by the three-antenna method is explained. However, since it is a time-consuming method and almost impossible to obtain AF at every height above the ground plane, a practical approach to obtain the height dependence of AF above a ground plane is performed considering the effects of the environment. In addition, the strong requirement showing the measurement reliability draws more attention to uncertainty analysis, and the concept of uncertainty analysis is explained first followed by some concrete estimation examples for the better understanding of the process. </p> <p class="btn"><a href="https://youtu.be/9OQuL0pxxIc">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Wadayama.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span> <span class="time">YouTube</span></div> <h4>Deep Unfolding — A Data Driven Approach for Signal Processing —</h4> <p class="name">Tadashi Wadayama (Nagoya Institute of Technology)</p> <p class="contents">Deep learning is not only useful for training deep neural networks, but it can also be applied to optimize the internal parameters of "differentiable iterative algorithms" involving input and output. Based on well-known iterative algorithms, it is possible to construct flexible algorithms with data-based learnability by embedding learnable parameters within them. This approach is known as deep unfolding. This talk provides an introduction to and an overview of deep unfolding, focusing on sparse signal recovery algorithms, which represent one of the linear inverse problems. In the first half of the talk, we will present the basics of deep unfolding by showing several examples, including gradient descent, projected gradient descent, and the proximal gradient method. In the second half, we will discuss a sparse signal recovery problem and present a sparse signal recovery algorithm derived through deep unfolding, explaining the observed convergence acceleration in algorithms constructed based on deep unfolding.</p> <p class="btn"><a href="https://youtu.be/HSxthK6F1eA">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Jinno.JPG" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span> <span class="keyword">Livestream: Monday, March 18, 15:00 PM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Swarm Intelligence Optimization and Machine Learning</h4> <p class="name">Kenya JIN’NO (Department of Intelligence Systems, Tokyo City University)</p> <p class="contents">In recent years, deep learning has exhibited remarkable performance, leading to the proposal of numerous applications characterized by high accuracy and efficiency. Deep learning systems learn their parameters through gradient descent methods, which rely on gradient information of the loss function to minimize the output loss. Given the vast number of parameters within deep learning systems, the associated loss functions are anticipated to possess numerous local minima. Consequently, the learning process can become ensnared in these local solutions, potentially halting progress and preventing the achievement of desired performance levels. To circumvent these issues, the adoption of swarm intelligence optimization methods, which do not depend on gradient information for optimization, has been proposed. These methods offer an alternative means of training deep learning models by leveraging the collective behavior and intelligence of groups. This presentation will explore the outcomes and challenges associated with employing swarm intelligence optimization for deep learning. By examining these aspects, we aim to shed light on the potential of these optimization techniques to enhance the learning process and overcome the limitations posed by conventional gradient-based methods.</p> <p class="btn"><a href="https://youtu.be/u-HMgFo9eaY">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Kise.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Elementary</span><span class="level">Intermediate</span> <span class="keyword">Livestream: Wednesday, February 28, 10:30 AM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Reading of "Reading" for "Actuating": Augmenting Human Reading and Learning by Sensing and Actuating Technologies</h4> <p class="name">Koichi Kise (Osaka Metropolitan University)</p> <p class="contents"> Reading constitutes a pivotal element in the architecture of our knowledge acquisition processes. Analogous to the adage, "You are what you eat," it is equally pertinent to assert that our intellectual fabric is woven from the threads of our reading material; a substantial portion of our knowledge is derived from this fundamental activity. This presentation delves into the concept of "meta-reading" — the analysis of reading behavior — as a window into the reader's interests, cognitive level, and psychological state. This talk will unveil the findings of our recent research, which navigates through the intricate landscape of reading and learning behaviors. Specifically, it focuses on the deployment of various feedback mechanisms, or 'actuators', tailored to enhance the reader's engagement and comprehension. The efficacy of these actuators is contingent on their alignment with the individual characteristics of the reader. In addition to presenting these insights, the talk will showcase practical applications, demonstrating how the nuanced understanding of reading behavior can be leveraged to optimize learning processes. Case studies and examples of effective actuation strategies, grounded in our behavioral analysis, will be highlighted. Furthermore, the talk will commence with an introductory overview of the German Research Center for Artificial Intelligence (DFKI) and its Japan Laboratory. This is to provide context, as much of the research discussed is affiliated with the pioneering efforts undertaken at DFKI. </p> <p class="btn"><a href=https://youtu.be/xUGCzAi-SIs">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Yamazaki.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span><span class="keyword">Livestream: Wednesday, December 27, 10:00 AM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>From QoS to QoE: Review of Changes in Service Quality Research</h4> <p class="name">Tatsuya Yamazaki (Niigata University)</p> <p class="contents"> The recent focus in networking has shifted from Quality of Service (QoS) to Quality of Experience (QoE). QoS traditionally dealt with mechanisms and technologies for controlling network traffic and managing network resources, often through differentiated handling and resource allocation for high-priority traffic. Although QoS evaluation involves parameters like bandwidth, throughput, latency, delay jitter, and packet loss for network systems, human intervention is rarely considered in this context. In contrast, QoE has become a key metric for assessing user satisfaction with service quality. QoE is subjective and linked to user perceptions and expectations, leading to ongoing research challenges. These challenges include how to measure subjective QoE, how to connect QoE with QoS parameters related to system performance, and how to integrate QoE into multimedia and communication services. Researchers have made significant contributions in addressing these issues. QoE's definition by ITU-T as "the overall acceptability of an application or service" is somewhat ambiguous, so it is more practical to focus on specific applications to discuss QoE. Currently, video streaming and Web applications are prominent areas of QoE research due to their high user demand. In this lecture, the historical evolution of QoS and QoE is discussed, with a particular emphasis on current QoE research topics, especially in the context of video streaming. Researchers are making strides in understanding and improving the user experience in these application domains. </p> <p class="btn"><a href="https://youtu.be/nSs2V47tOc0">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Nakagawa.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Elementary</span><span class="keyword">Livestream: Tuesday, November 14, 3:00 PM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>AI and ethics</h4> <p class="name">Prof. Hiroshi Nakagawa (RIKEN Center for Advanced Intelligence Project)</p> <p class="contents"> The following three themes of AI ethics will be presented. 1. Problems of generative AI: Text-generating AI such as ChatGPT and image-generating AI such as Midjouorney have started to be widely used, and their limitations and abuses have been discussed. This paper presents an analysis of these issues from ethical and other perspectives. 2. Avatars are being used more and more recently. when they become autonomous, a generative AI is expected to be utilized for the conversational ability of these avatars. In such a situation, issues such as trust of autonomous avatars will be discussed. 3. AI ethics has been discussed in the EU for recent years, and has been proceeding toward legislation in the form of the Trustworthy AI Guidelines, the AI White Paper, and the AI act. We briefly explain this process of the current status of AI ethics in the EU, including technical aspects. </p> <p class="btn"><a href="https://youtu.be/AHcqY5Uewz4">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Fujita.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span><span class="keyword">Livestream: Tuesday, October 26, 3:00 PM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Explore the Latest Fundamentals of AI-based Computer-Aided Diagnosis (AI-CAD) for Medical Imaging</h4> <p class="name">Prof. Hiroshi FUJITA (Gifu University)</p> <p class="contents">With AI "deep learning" technology, which is a type of "machine learning" (learning functions and rules) in which computers learn by themselves, the accuracy of image recognition has reached a level that exceeds that of humans. Computer-aided diagnosis of medical images, so-called CAD, has rapidly entering the mainstream of practical medicine. Especially in the detection of breast cancer by mammography (breast imaging), it is a part of daily clinical work. In this case, the computer output is used as a "second opinion" to help the doctor interpret the image. However, recent powerful AI technologies, including deep learning, have taken CAD development and performance to the next level, traditional CAD has diversified, and even autonomous diagnostic AI is emerging. This is sometimes called AI-CAD and is gradually shifting from a mere R & D level to a commercialization level, verification at the actual clinical stage, and insurance reimbursement stage. In this talk, we would like to examine and discuss the current state of AI-CAD, and the problems that need to be solved in order to make AI-CAD more practical in clinical practice. Through this presentation, we hope that many audiences will become more interested in AI-CAD for medical imaging and will engage in research and development in this field. References: 1) H.Fujita, “AI-based computer-aided diagnosis (AI-CAD): The latest review to read first,” Radiological Physics and Technology (RPT), vol.13, no.1, pp.6-19, 2020, received Most Citation Award (2023.4) from RPT journal. 2) G.Lee and H.Fujita (Eds.), “Deep Learning in Medical Image Analysis: Challenges and Applications,” Springer, 2020.</p> <p class="btn"><a href="https://youtu.be/bAT5f_NTdkk">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Takahashi.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">65mins</span><span class="level">Elementary</span><span class="keyword">YouTube Premiere Session: Saturday, September 30, 6:30 PM JST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Introduction to optical circuit</h4> <p class="name">Prof. Hiroshi Takahashi (Sophia University)</p> <p class="contents">In this introductory talk, I will review the fundamentals of optical circuit devices, which are essential components in optical communication systems. An optical circuit consists of optical waveguides with a width of several microns formed on a substrate. It is highly compact and can be mass-produced at a low cost. First, I will derive the wave equation and represent the electric field for optical waveguides as mathematical notation to describe light within optical circuits. Then, I introduce the definition and usage of the transfer function to explain the operating principles of the following optical circuit devices. The optical switch is based on the Mach-Zehnder interferometer (MZI) optical circuit with an integrated electric micro heater. It is employed for altering the light path within optical fiber communication networks. The transmission characteristics of asymmetric MZI circuits exhibit periodic frequency dependence and can be utilized as a frequency filter and frequency discriminator. The arrayed-waveguide grating (AWG) consists of hundreds of waveguides and functions similarly to a diffraction grating. It is used as a wavelength demultiplexer in wavelength division multiplexing optical communication systems. The optical circuit for a coherent receiver is constructed using two 90-degree hybrid circuits and a polarization splitter circuit. It is used in conjunction with photodiodes and various electronic components to extract the phase of the modulated optical signal. Phase modulation is an essential technique for achieving ultra-high-speed communication exceeding 100 Gbit/s, making this device of utmost importance.</p> <p class="btn"><a href="https://youtu.be/XokO9rF-W3k">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Hirokawa.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Intermediate</span><span class="level">Advanced</span><span class="keyword">Livestream: Tuesday, August 29, 16:00 PM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Two-dimensional rectangular-coordinate orthogonal multiplexing antenna system for non-far field region communication</h4> <p class="name">Prof. Jiro Hirokawa (Tokyo Institute of Technology)</p> <p class="contents">This talk presents an orthogonal multiplexing antenna system for non-far field region communication, which is based on two-dimensional polarity in the rectangular coordinate system. In other words, it is based on two-fold symmetry and anti-symmetry between the transmission modes. The two-dimensional polarity comes from the structural symmetry of magic-T components used in the corporate-feed circuit in the antenna in the millimeter-wave band. The structural symmetry gives wideband operation. The feasibility is shown by a system where a corporate-feed waveguide slot array antenna and a monopulse circuit are combined. We experimentally confirm 4-multiplex 40cm CW transmission using an 80GHz-band 16x16-slot waveguide array, 8-multiplex 20cm CW transmission using a 60GHz-band 16x16-slot dual-polarization waveguide slot array, and 2-multiplex 40cm QPSK transmission using a 60GHz- band 16x16-slot waveguide array. </p> <p class="btn"><a href="https://youtu.be/DHg7mEIxz3Y">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar_Ikeguchi.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Elementary</span><span class="level">Intermediate</span><span class="keyword">Livestream: Tuesday, July 25, 4:00 PM JST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Analysis of Complex Dynamical Behavior as a Temporal Network</h4> <p class="name">Prof. Tohru Ikeguchi (Tokyo University of Science)</p> <p class="contents">In this webinar, we will discuss the analysis of time-varying complex phenomena by considering measured contact data as a temporal network. Firstly, we will introduce some of the contact data currently recorded. Then, as an elemental technique for analyzing these contact data as temporal networks, we explain the analysis method for static networks. Secondly, we explain the importance of analyzing such contact data as temporal networks. We also explain how to transform contact data into temporal networks. Thirdly, we explain the distance measure between temporal networks in order to detect and quantify system dynamics from the transformed temporal networks. Furthermore, we explain how to analyze the dynamics of the changes in the contact data by converting the temporal changes in the distance into time series signals using the classical multidimensional scaling method. Finally, we conclude the methods for analyzing contact data as a temporal networks,and discuss a future direction of network analysis.</p> <p class="btn"><a href="https://youtu.be/OZ-scc1uTUQ">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Ushiku.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Intermediate</span><span class="keyword">YouTube Premiere Session: Friday, June 30, 6:30 PM JST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Invitation to Vision and Language</h4> <p class="name">Prof. Yoshitaka Ushiku (OMRON SINIC X Corp.)</p> <p class="contents">This talk aims to introduce the technical area called Vision and Language to those with experience in research and development applying deep learning to images and texts. Until the end of the 2000s, machine learning for images and text was independently studied in computer vision and natural language processing, creating distinct technical systems. As a result, the mutual barriers to entry for technologies that handle both images and text were a challenge. When deep learning enabled images and text to be analyzed with similar neural network architectures, this mutual barrier to entry was significantly mitigated. Thus, an integrated understanding of images and text, which had begun to be studied, blossomed all at once. In this presentation, I will introduce such research fields of Vision and Language, broadly classifying them according to the modality of input/output (i.e., image or text). Vision and Language can also be considered as the study of multimodal/cross-modal machine learning; there are some points to be aware of. I will discuss some of those points in the last part of this talk. Nowadays, generative models, which generate images from texts, have attracted a great deal of attention, and I expect that many people are interested in this field. Through this presentation, I hope that such people will become more interested in Vision and Language and will engage in research and development in this field.</p> <p class="btn"><a href="https://www.youtube.com/watch?v=rM3x4k1j6rQ">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar_kawanishi.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">110mins</span><span class="level">Elementary</span><span class="level">Intermediate</span><span class="keyword">YouTube Premiere Session: Wednesday, May 31, 6:30 PM JST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Basics and recent progress in lightwave modulators</h4> <p class="name">Prof. Tetsuya Kawanishi (Waseda University)</p> <p class="contents">The purpose of this webinar is to provide basics of electro-optical modulation which plays an important role in photonic networks such as fiber optic links, visible light communications, and fiber wireless, as well as in high-performance sensing systems. This webinar will offer as an overview of various types of optical modulation devices, focusing on modulators based on the electro-optic effect (Pockels effect), called electro-optic (EO) modulators, which induce optical phase retardation by an electric field applied thoroughly through an electrode. By using optical interferometers based on the EO effect, a variety of functions can be achieved, including phase modulation, intensity modulation, and vector modulation. Mach-Zehnder interferometer modulators (MZMs) are very useful for the most common modulation schemes, such as on-off keying (OOK) and binary phase shift keying (BPSK). In addition, MZMs would be elements for more complex modulators, high-speed optical switches, vector modulators, etc.</p> <p class="btn"><a href="https://player.vimeo.com/video/833151190?h=f99fb86f16">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar_hayashi.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">45mins</span><span class="level">Intermediate</span><span class="keyword">YouTube Premiere Session: Friday, April 28, 6:30 PM JST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Introduction of Electromagnetic Information Security</h4> <p class="name">Prof. Yuichi Hayashi (Nara Institute of Science and Technology)</p> <p class="contents">With the rising importance of information security, the necessity of implementing better security measures in the physical layer as well as the upper layers is becoming increasing apparent. Given the develop-ment of more accurate and less expensive measurement devices, high-performance computers, and larger storage devices, the threat of ad-vanced attacks at the physical level has expanded from the military and governmental spheres to commercial products. In this paper, we review the issue of information security degradation through electromagnetic (EM)-based compromising of security measures in the physical layer (i.e., EM information security). Owing to the invisibility of EM radia-tion, such attacks can be serious threats. We first introduce the mecha-nism of information leakage through EM radiation and interference and then present possible countermeasures. Finally, we explain the latest research and standardization trends related to EM information security.</p> <p class="btn"><a href="https://player.vimeo.com/video/819745458?h=a7e5a7feff">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> <!--</li><a href="https://player.vimeo.com/video/819745458?h=a7e5a7feff">Check<i class="fas fa-arrow-circle-right">--!> <!----!> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Ueta.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Elementary</span><span class="level">Intermediate</span><span class="keyword">Livestream: Wednesday, March 15, 10:30 AM JST/KST (GMT+9)</span><span class="time">YouTube</span></div> <h4>Locating and Controlling Chaotic Saddles</h4> <p class="name">Prof. Tetsushi Ueta (Tokushima University)</p> <p class="contents">Some planar discrete nonlinear systems may have a horseshoe structure with stable and unstable manifolds associated with a saddle fixed point. Under this situation, as is well known, there are infinitely many unstable periodic points around the saddle. By making correspondence of the cross sections of manifolds and symbolic dynamics, one can obtain a “candidate area” containing an unstable periodic point whose period is given by the gray code. These unstable periodic points can be stabilized by applying any chaos control technique into that candidate area, for which the external force control method exhibits a very robust control performance. In this talk, a horseshoe structure derived by the Poincaré mapping for a two-dimensional nonautonomous hybrid system is analyzed as an example. As an example, locating scheme for unstable periodic points is demonstrated, and their control results are presented.</p> <p class="btn"><a href="https://player.vimeo.com/video/813398768?h=8833103365">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Kai.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Beginner</span><span class="level">Intermediate</span><span class="time">YouTube</span></div> <h4>Augmenting Humans — From Physiology Signals towards Digitalized Emotion</h4> <p class="name">Prof. Kai Kunze (Keio University)</p> <p class="contents">In my research, I combine design and technology to augment human senses, looking for novel interaction paradigms. Engineering and computing have often been used to mimic or surpass some human abilities (for example autonomous driving, playing Go). Such efforts appear to put humans and computers in a competitive relationship, as emphasized in AI vs. Human game competitions. Once fantastic fear of AIs “replacing” human workers is now taken much more seriously and discussed in the public sphere. My research proposes a different approach to the human-computer relationship by applying a cooperative and empowering framework, using wearable computing to actively augment human capabilities. At the beginning of my talk, I will discuss our efforts to augment audiences with physiological sensors to understand more about audience/performer entrainment and create feedback spirals. I explore the concepts of entrainment and what it means to be live in person at a meeting/concert or other gathering. We discuss application scenarios of capturing inter-personal synchrony between audience and performers as well as potential body schema extension technologies. </p> <p class="btn"><a href="https://player.vimeo.com/video/799001897?h=32c6b95d37">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Hirata2.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Intermediate</span><!--<span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span>--!></div> <h4>Study of Propagation Characteristics of Terahertz Waves in Beyond 5G</h4> <p class="name">Prof.Akihiko Hirata (Chiba Institute of Technology)</p> <p class="contents">The use of 300 GHz band wireless links is currently being considered for various use cases such as backhaul/fronthaul lines, mobile access, wireless local area networks (LANs), and body area networks (BANs) as a way of achieving >100-Gbit/s data rate. In order to make these use cases practical, it is necessary to evaluate the radio propagation characteristics in the 300 GHz band and build a radio propagation model at this frequency. To build a radio propagation model for each of the above use cases, we conduct various radio propagation experiments and simulations. In this lecture, I will present the results of these experiments and simulations of radio propagation in the 300 GHz band.</p> <p class="btn"><a href="https://player.vimeo.com/video/794708134?h=1a0b3c0ecd">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Hasegawa.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><!--<span class="level">●Elementary/Intermediate/Advanced●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span><span class="keyword">●●</span>--!></div> <h4>Past, present, and future of Internet congestion control</h4> <p class="name">Prof.Go Hasegawa (Tohoku University)</p> <p class="contents">Internet Congestion control is essential not only from the performance perspective but also for its stability and robustness. Congestion control has been the subject of continuous research and development since the birth of the Internet. <br> In this lecture, we review the Internet congestion control mechanisms that have been proposed, studied, and implemented so far. First, we summarize the existing congestion control mechanisms from the viewpoint of metrics for the degree of network congestion, that is, loss-based, delay-based, bandwidth-based mechanisms, and their hybrid mechanisms.Next, we introduce the history of the congestion control deployed for specialized network environments such as wireless networks, high-speed and long-delay networks, and datacenter networks.<br> We further introduce the congestion control mechanisms which utilize some information obtained from the network, such as Explicit Congestion Notification (NCP) and eXplicit Control Protocol (XCP). Some existing mechanisms which introduce in-network control, such as Performance Enhancing Proxy (PEP), are also explained.<br> We then explain recent research trends in congestion control mechanisms, including the congestion control plane that implements congestion control mechanisms in user space, SDN-based congestion control, and machine learning-based congestion control.<br> Finally, the lecturer introduces his recent research on in-Network Congestion Control architecture (NCC), which breaks away from the end-to-end principle on which the existing Internet congestion control relies, and divides the network between the transmitting and receiving terminals into multiple sub-networks, and applies congestion control algorithms algorithm for each sub-network separately.</p> <p class="btn"><a href="https://player.vimeo.com/video/794705846?h=6061858afe">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Horio.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Elementary</span><span class="level">Intermediate</span></div> <h4>Brainmorphic Computing Paradigm and Hardware</h4> <p class="name">Prof.Yoshihiko Horio (Tohoku University)</p> <p class="contents">In order to realize brain-specific computational schemes such as consciousness/subconsciousness, prediction, inference, memory, attention, self, etc., novel computational principle, architecture, and devices are required, which would be very different from those in von Neumann-type digital computers. This talk introduces the brainmorphic computing paradigm and its hardware architecture. In the brainmorphic computing paradigm, information processing is performed through imitating the anatomical and physiological structure and dynamics of the brain, which have been evolutionally developed. The latest knowledge from brain science, especially, on high-order brain specific functions coemerged from high-dimensional complex structure and neuro-dynamics, should be reflected in the brainmorphic computing paradigm. In addition, the bodily and environmental constraints are considered and utilized as embodiment in this computational paradigm. In order to implement the brainmorphic computing paradigm as hardware, physical and dynamical characteristics of the novel brain-type constituent devices, especially nonlinear analog circuits, and nanometer-scale materials and devices, should be naturally utilized. Our efforts on physical implementation of the brainmorphic computing hardware are illustrated; for example, spin-orbit torque devices for naturally realize neuronal and synaptic dynamics directly, and a chaotic neural network reservoir for computation through high-dimensional complex dynamics.</p> <p class="btn"><a href="https://player.vimeo.com/video/776000700?h=137b7f644f">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Hirata.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">60mins</span><span class="level">Elementary</span><span class="level">Intermediate</span></div> <h4>Introduction to Bioelectromagnetics – Fundamentals and Applications</h4> <p class="name">Prof.Akimasa Hirata (Nagoya Institute of Technology)</p> <p class="contents">The human body whose electrical behavior depend on the frequency should be considered in the modern design of wireless devices which are used in proximity of the human body. However, the complexity of the modeling may depend not only on the frequency but also the individual variabilities, environmental factors, size of the devices and use scenarios. In this lecture, first, a discussion on modeling of the human in the electromagnetics for different cases is provided. Then, the effect of the human presence on the wireless devices including wireless communication terminals and wireless power transfer systems is explained considering typical exposures scenarios. The electromagnetic fields emitted from the electrostatic discharge is also discussed.</p> <p class="btn"><a href="https://player.vimeo.com/video/746720206?h=3271cfd595">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Taroumaru.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">40mins</span><span class="level">Intermediate</span><span class="keyword">Sampling theorem</span><span class="keyword">Antenna array</span><span class="keyword">Antenna diversity</span></div> <h4>MIMO and Smart Antenna with Single RF-Baseband Chain and Switching Antenna Array</h4> <p class="name">Prof.Makoto Taromaru (Fukuoka University)</p> <p class="contents">MIMO, diversity, or adaptive array antenna, so called “smart antenna,” is an effective technique by space-domain processing to enhance channel capacity or to mitigate multipath fading and interference. However, it is difficult to reduce its cost, circuit size, and power consumption because it needs one by one RF-to-baseband chain for each array element; large scale RF/baseband hardware is necessary especially for large number of antenna elements i.e., massive MIMO and so on. To solve this problem, fast periodical antenna switching or beam scanning techniques have been proposed, where we call them “switching antenna array”. Although these are very attractive since MIMO or digital beamforming can be done with a single analog RF/baseband chain, they cannot perfectly have the same properties as the conventional multi receiver/transmitter architecture due to antenna switching or sampling. In this talk, spurious response/emission, and SNR (signal-to-noise ratio) property of the switching antenna array, are theoretically analyzed, and BER: bit error rate performance is quantitatively evaluated.</p> <p class="btn"><a href="https://player.vimeo.com/video/751975910?h=b10abc83a4">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/poster02.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Intermediate</span></div> <h4>Technologies and Commercial Applications of Far Field Wireless Power Transfer</h4> <p class="name">Naoki Shinohara (Kyoto University)</p> <p class="contents">A far field Wireless Power Transfer (WPT) is one of innovative radio wave applications and is recently considered as one of game changing technologies based on radio wave. It had been studied historically with microwaves and its application has been narrow beam WPT in which the wireless power is transmitted from one transmitter to one receiver with high beam efficiency. Recently, the WPT is applied as wide beam WPT in which the wireless power is transmitted from one/multi transmitter(s) to one/multi receiver(s) with various radio waves like a wireless communication system. In this talk, I introduce basic theory and technology, recent innovative technologies, and commercial applications of the far field WPT in the world. It involves an antenna / beam forming technology and a circuit technology in a receiver. Additionally, I also introduce discussion status of new radio regulation for the far field WPT in Japan and in the world. </p> <p class="btn"><a href="https://player.vimeo.com/video/705269423?h=0d07218c78">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Hirose.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">90mins</span><span class="level">Intermediate</span><span class="keyword">Artificial intelligence (AI)</span><span class="keyword">Neural network hardware</span><span class="keyword">Edge computing</span><span class="keyword">Photonics</span><span class="keyword">Spin</span><span class="keyword">Pattern information representation and processing</span></div> <h4>Physical Reservoir Computing: Its Advantages and Significance</h4> <p class="name">Prof.Akira Hirose (The University of Tokyo)</p> <p class="contents">This talk focuses on reservoir computing and its physical realization in the AI & sensor-network era. First, we have a glance of the hardware history in artificial intelligence (AI) including logic architecture and neural networks. The key point in modern AI is emphasized, namely, pattern information representation and pattern information processing. We also present the basic idea and dynamics of reservoir computing by referring to deep learning and time-serial information processing. Then we look through various physical reservoir-computing ideas briefly to catch the variety of physics used in this area and also the key properties. In particular, we go into the details of reservoirs based on photonics and spin waves. The former has been studied for long, resulting in an accumulation of experiences. The latter is new and rich in nonlinearity, hysteresis, anisotropy and dispersion, which enhance the processing ability. Lastly, we discuss the prospects of reservoir computing in the near future society in the context of edge-computing as well as server use in the sensor-network society.</p> <p class="btn"><a href="https://player.vimeo.com/video/703567383?h=e61f2d7d05">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> <li class="clearfix"> <figure><img src="../../assets/img/activities/webinar/English-webinar-Fujishima.jpg" alt=""/></figure> <div class="txt"> <div class="tag"><span class="time">40mins</span><span class="level">Advanced</span><span class="keyword">wireless communication</span><span class="keyword">terahertz</span><span class="keyword">CMOS</span><span class="keyword">6G</span><span class="keyword">beyond 5G</span><span class="keyword">transceiver</span><span class="keyword">300 GHz</span></div> <h4>Sub-Terahertz Transceivers in Silicon</h4> <p class="name">Prof.Minoru Fujishima (Hiroshima University)</p> <p class="contents">The 300GHz band is a frequency band recently identified for wireless communication and is attracting attention towards 6G.However, it is generally believed that as the frequency increases, the communication distance becomes shorter and the applications are limited. In this talk, the relationship between frequency and communication distance will be explained, and the possibility of a 299GHz transceiver using CMOS integrated circuits will be discussed.</p> <p class="btn"><a href="https://player.vimeo.com/video/682632771?h=99ba12594c">Check<i class="fas fa-arrow-circle-right"></i></a></p> </div> </li> </ul> </section> </div> <!-- /.inner --> </section> </section> <!-- /#main --> <footer> <div class="inner"> <nav class="nav01 clearfix"> <ul> <li> <p class="toggle">President's room<i class="fas fa-plus"></i></p> <ul> <li><a href="/eng_r/president/index.html">President's room</a></li> <li><a href="/eng_r/about/president_list.html">President List</a></li> </ul> </li> <li> <p class="toggle">Archive<i class="fas fa-plus"></i></p> <ul> <li><a href="https://www.ieice.org/publications/search/index.php?lang=en" target="_blank">Search for paper</a></li> <li><a href="https://www.journal.ieice.org/index.php?lang=E" target="_blank">The Journal of IEICE 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