Friday, May 29, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Takeshi Ohkawa
Tokai University, Department of Embedded Technology, Associate Professor
FPGA Design Technology in intelligent robot systems
An intelligent robot system is a collection of so-called mechanical, electronic, and software technology, and the problem is how to integrate the respective elemental technologies. FPGA is already integrating electric and software design technology, but it is still difficult to design to realize high-performance processing, and the barriers are high for using it to construct robot systems. On the other hand, ROS (Robot Operating System) is currently accepted by robot system engineers as a development platform for robot software. This talk introduces the challenges and possibilities of FPGA design technology for intelligent robot systems, based on the challenge story of integrating FPGA and ROS.
Friday, June 12th, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Akihito Taya
Assistant Professor,
College of Science and Engineering,
Department of Integrated Information Technology,
Aoyama Gakuin University
Wireless Communications for Enhancing Vehicular Cooperation
The development of diverse sensors and machine learnings have made vehicles highly automated to realize efficient transportation and enable other diverse services, e.g., car sharings, by collecting information of traffic and road conditions. Vehicular communication technologies play an important role in such services because it is essential for vehicles to share information and cooperate with each other. This talk overviews vehicular cooperation realized by wireless communications, and introduces recent studies of vehicular communications, especially mmWave communications.
Friday, June 19, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Dr. Naoto Nishizuka
National Institute of Information and Communications Technology (NICT)
Tenure-track researcher
Deep Neural Networks Applied to Solar Flare Prediction
Solar flares sometimes affect our social infrastructures, and solar flare prediction is one of our important tasks for space weather forecast. People have tried to reveal fundamental mechanisms of a flare and to develop prediction methods. Now it is a hot topic to apply ML techniques to flare predictions, and some models have succeeded in improving skill scores. The deep neural network (DNN) is a newly developed algorithm which shows the highest accuracy of prediction in general. In DNN models, Convolutional Neural Network (CNN) can automatically extract features from images and accelerated DNN applications, but it has a disadvantage of unexplainability. Here, I introduce our solar flare prediction model using a DNN named Deep Flare Net (DeFN). This model can forecast the flare occurrence probability in the following 24 h and has been operated since April 2019. From 3×10^5 observation images taken by SDO during 2010?2015, we detected active regions and calculated 79 features for each region, to which we annotated labels of X-, M-, and C-class flares. The DeFN model consists of multilayer perceptrons with skip connections and batch normalizations. To statistically predict flares, the DeFN model was trained to optimize the true skill statistic (TSS). As a result, we succeeded in predicting flares with TSS=0.80 for >=M-class flares and TSS=0.63 for >=C-class flares. Note that in usual DNN models, the prediction process is a black box. However, in the DeFN model, the features are manually selected, and it is possible to analyze which features are effective for prediction after evaluation. In this talk, we would like to introduce the DeFN model and discuss future applications of DNN to space weather forecasting.
Friday, July 10, 2020 at 16:30-18:00
The URL of Teams will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Dr. Toshihiro Hattori
Vice President, Head of HW Unit
Digital Products Business
Automotive Solution Business Unit
Renesas Electronics Corporation
LSI design and current topics for automotive
Automotive is one of the major applications for the semiconductor devices, although getting worst impact by COVID-19. And the semiconductor devices are the key factors to support the current innovation of MOBILTY (automotive) systems. Firstly, I will explain the different needs, feature, and technology for automotive oriented LSI’s. As you know, Automotive technology is performing a drastic innovation leaded the key words “CASE (Connected, Autonomous, Shared & Services, Electric” and “MaaS (Mobility as a Service)”. I will overview the trends and needs for automotive LSI’s. Functional Safety and Security is the key technology required current automotive LSI’s. I will explain the trends and background of autonomous driving and show the example of the latest implementation for autonomous driving support LSI’s.
Friday, Oct 9th, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Mr. Eiji Takeuchi
General Manager
Project Promotion Division
EKO Instruments Co., Ltd.
Approach to global environmental issues through environment measurement
Global environmental issues are important threats to the survival of humankind and must be solved urgently. Various approaches are being made to solve the different issues such as global warming, climate change, natural disasters, carbon dioxide emission problems and energy problems. The development of environmental measurement technology is one of them. In order to know the current conditions of the global environment more precisely or accelerate the installation of renewable energy, measurement technologies are becoming diversified and sophisticated. This talk introduces some examples: remote sensing technologies such as water vapor LIDAR and wind LIDAR, a high-precision measurement technology for solar irradiance and radiation and monitoring technologies for photovoltaic power generation.
Friday, November 13th, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Masaki Waga
Assistant Professor, Graduate School of Informatics, Kyoto University
Monitoring of cyber-physical systems with timed pattern matching
Nowadays, many physical systems, including automotive systems, robots, and healthcare systems, are controlled or monitored by computers. These systems are called cyber-physical systems (CPSs). Since many CPSs are safety-critical, safety assurance of CPSs is an important task. This talk introduces monitoring (or runtime verification) of CPSs as an example of the safety assurance of CPSs. Among various mathematical formulation of the monitoring problem, this talk summarizes the timed pattern matching problem and its generalization, which locates where a safety violation occurs in a monitored execution.
Friday, December 18th, 2020 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Yuncan Zhang
Ph.D. Student
Department of Communications and Computer Engineering,
Graduate School of Informatics, Kyoto University
Network Service Scheduling in Network Virtualization
Network virtualization plays a key role in the next-generation networking paradigm with enabling multiple tenants to share the same physical infrastructure. By leveraging the technologies of network function virtualization, a platform with network virtualization provides virtualized resources of networking, computing, and functionality to users in a cost-effective and dynamic manner. While network virtualization brings a more flexible and efficient network, it makes network service provisioning more challenging. This talk addresses challenges of network service mapping and scheduling in network virtualization, including basics and ongoing research topics.
Friday, January 15th, 2021 at 16:30-18:00
The URL of Zoom will be announced via faculty’s mailing list 3 days before the colloquium.
The lecture material will be available in PandA at 16:00 on the day of the colloquium.
The lecture will be recorded, and video and audio will be available on PandA.
Prof. Akira Suzuki
Associate Professor
Graduate School of Information Sciences, Tohoku University
Combinatorial Reconfiguration Applied to the Distribution Network Configuration
In the field of combinatorial optimization, search problems (optimization problems) to find the optimal one among a huge number of combinations have been treated for many years. There are a wide variety of optimization problems that can occur in the real world, and optimization problems have been solved in many fields to maximize profits or minimize losses. On the other hand, even if an optimal solution is found, whether the solution can be used in practice is another matter. For example, even if a configuration with lower distribution loss is found in the distribution network, it is another matter whether it is possible to change to the better configuration by repeatedly switching switches without causing power failure or short circuit. Based on this situation, research on “reconfiguration problems” has been promoted in the field of “combinatorial reconfiguration” in recent years. A reconfiguration problem is a problem to find a way to make a step-by-step transformation from a solution to the other solution to a problem. In this talk, we would like to introduce one of the applications of combinatorial reconfigurations to the minimization of distribution loss in distribution networks as an example.