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Performance Analysis and Nash Equilibria in a Taxi-Passenger System with Two Types of Passenger

SN Computer science 2023年第1期4卷 1-13页

作者： Nguyen, Hung Q. Phung-Duc, Tuan Graduate School of Science and Technology University of Tsukuba Tennodai 1-1-1 Ibaraki Tsukuba 305-8573 Japan Institute of Systems and Information Engineering University of Tsukuba Tennodai 1-1-1 Ibaraki Tsukuba 305-8573 Japan

This paper analyzes a taxi-passenger queueing system where there are two types of passengers differentiated by their mean matching times with taxis. System states can be observable or unobservable to agents. Performance measures of the system are derived using a Markov chain with three-dimensional states. Furthermore, we consider the case where multiple types of agents are strategic and use a multi-population game theoretical framework to analyze the system in equilibrium. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Game theory Queueing theory Strategic queueing Taxi-passenger system

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Differential amplifiers

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Self-Learning Based Dependable Offloading Optimization in Semi-Trusted Vehicular Edge Computing and Networks

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8141-8157页

作者： Li, Xuehan Jing, Tao Li, Ruinian Wang, Xiaoxuan Yan, Yu Fan, Xin Huo, Yan Yu, Fei Richard Beijing Jiaotong University School of Electronic and Information Engineering National Engineering Research Center of Advanced Network Technologies Beijing100044 China Bowling Green State University Department of CS Bowling GreenOH43403 United States Beijing Forestry University School of Information Science and Technology Beijing100083 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

As vehicular edge computing and networks (VECONs) emerge, Internet of vehicles (IoVs) is gaining significant advantages. To provide users with dependable services, VECONs need to offer efficient and secure task offloading services. Unfortunately, little effort has been put into addressing security issues such as the risk of privacy exposure when offloading data. Modeling and optimizing offloading dependability are affected by these issues. To address these concerns, a dependable three-layer offloading framework involving blockchain technology is presented in this paper, with fully homomorphic encryption (FHE) algorithm incorporated in order to mitigate privacy exposure risks. The framework divides tasks reasonably and introduces a novel measure of offloading dependability called cost from energy consumption, delay, and privacy exposure risk (cEDP) for constructing dependable offloading optimization. Additionally, a self-learning based dependable privacy preservation offloading (SDPPO) algorithm is presented that is capable of solving the optimal offloading problem in a decentralized manner. Simulation results show that the SDPPO algorithm outperforms its counterparts in terms of faster convergence speed, better cEDP convergence results, and improved scalability and tunability characteristics. © 1967-2012 IEEE.

关键词： Differential privacy

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Study on High-Level Structure of cognition control construction in Exploration and Exploitation within Multi-Armed Bandit Model of Reinforcement Learning

Study on High-Level Structure of cognition control construct...

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2023 International Symposium on Micro-NanoMechatronics and Human science, MHS 2023

作者： Tian, Jiaxing Jun, Izawa Graduate School of Science and Technology University of Tsukuba Empowerment Informatics Japan Institute of Systems and Information Engineering University of Tsukuba Tennodai 1-1-1 Tsukuba Ibaraki305-8573 Japan

ISBN: (纸本)9798350315073

Reinforcement learning models have been instrumental in simulating the behaviors of animals and humans, whose actions and choices are largely influenced by rewards. This study proposes a high-level environmental monitoring structure into cognitive models, optimizing the balance between exploration and exploitation in reinforcement learning theory. This approach allows for more flexible adaptation to complex environmental changes. We focus on a multi-armed bandit task, incorporating a hierarchical model that adds a high-level cognition control structure based on the cognitive system. This structure adjusts the balance between exploration and exploitation according to the perceived uncertainty of the environment. In a stable environment, the model minimizes exploration to maximize rewards. In contrast, in an unstable environment, the model promotes rapid exploration to identify the best strategy after environmental changes. This cognition-based hierarchical structure offers valuable insights for future studies about analyzing human responses to environmental uncertainty and exploration behavior. © 2023 IEEE.

关键词： Cognitive systems

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Development of Efficient and Robust Linkage Pattern Mining for Multiple Sequential Data

IAENG International Journal of Computer Science

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IAENG International Journal of Computer science 2025年第1期52卷 223-232页

作者： Maeda, Kyosuke Yokota, Issei Okada, Yoshifurni Lee, Saerom Division of Science for Creative Emergence Kagawa University Graduate School 2-1 Saiwai-cho Kagawa Takamatsu760-8523 Japan Division of Science for Creative Emergence Kagawa University Graduate School 2-1 Saiwai-cho Kagawa Takamatsu760-8523 Japan College of Information and Systems Muroran Institute of Technology 27-1 Mizumoto-cho Hokkaido Muroran050-8585 Japan Faculty of Engineering and Design Kagawa University 1-1 Saiwai-cho Kagawa Takamatsu760-8523 Japan

Linkage pattern mining is a method used to extract frequently occurring patterns from multiple sequential data without considering the similarity or correlation between frequent patterns. Therefore, it is expected to be a promising approach for disease prediction and voice data analysis. In the previous method, closed itemset mining was introduced in the linkage pattern-mining algorithm to ensure robustness against noise. Although this method can extract linkage patterns from noisy artificial dataseis, a reduction in computation time and stringent parameter settings are essential for its practical application to real data. In this study, we employed Episode Mining using Memory Anchor algorithm for frequent pattern mining to overcome the limitations of the previous method. The objective of this study is to develop a new robust linkage pattern-mining method that is more applicable to real data, A performance comparison between the previous and proposed methods using artificial datasets showed that the proposed method achieved a reduction in computation time while maintaining an extraction accuracy that is comparable to that of the previous method, particularly on noisy artificial datasets. © (2025), (International Association of Engineers). All rights reserved.

关键词： closed itemset EMMA interval graph linkage pattern sequential pattern mining

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A tree detection method based on trunk point cloud section in dense plantation forest using drone Li DAR data

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Forest Ecosystems 2023年第1期10卷 37-45页

作者： Yupan Zhang Yiliu Tan Yuichi Onda Asahi Hashimoto Takashi Gomi Chenwei Chiu Shodai Inokoshi Center for Research in Isotopes and Environmental Dynamics University of Tsukuba1-1-1TennodaiTsukubaIbaraki305-8572Japan Graduate School of Systems and Information Engineering University of Tsukuba1-1-1TennodaiTsukubaIbaraki305-8572Japan Department of International Environmental and Agricultural Science Tokyo University of Agriculture and Technology3-5-8SaiwaieFuchuTokyo183-8509Japan

Single-tree detection is one of the main research topics in quantifying the structural properties of forests. Drone Li DAR systems and terrestrial laser scanning systems produce high-density point clouds that offer great promise for forest inventories in limited areas. However, most studies have focused on the upper canopy layer and neglected the lower forest structure. This paper describes an innovative tree detection method using drone Li DAR data from a new perspective of the under-canopy structure. This method relies on trunk point clouds, with undercanopy sections split into heights ranging from 1 to 7 m, which were processed and compared, to determine a suitable height threshold to detect trees. The method was tested in a dense cedar plantation forest in the Aichi Prefecture, Japan, which has a stem density of 1140 stems·ha^(-1) and an average tree age of 42 years. Dense point cloud data were generated from the drone Li DAR system and terrestrial laser scanning with an average point density of 5000 and 6500 points·m^(-2), respectively. Tree detection was achieved by drawing point-cloud section projections of tree trunks at different heights and calculating the center coordinates. The results show that this trunk-section-based method significantly reduces the difficulty of tree detection in dense plantation forests with high accuracy(F1-Score=0.9395). This method can be extended to different forest scenarios or conditions by changing section parameters.

关键词： Tree detection Trunk sections Forest Drone LiDAR

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Experimental and Theoretical Analyses on Power Generation Characteristics of Co-axial MHD Energy Conversion Device

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IEEJ Transactions on Power and Energy 2023年第7期143卷 454-460页

作者： Hasebe, Takahiro Sasaki, Ryo Fujino, Takayasu Takana, Hidemasa Kobayashi, Hiromichi Graduate School of Science and Technology University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Department of Physics Keio University Hiyoshi Campus 4-1-1 Hiyoshi Kohoku-ku Yokohama223-8521 Japan

Experiments on power generation were conducted under the open-circuit condition to validate theoretical analyses on the power generation characteristics of a co-axial MHD energy conversion device. Considering distribution of externally applied magnetic field and the electromotive force induced by the rotation of the conductive inner cylinder, the results show that the experimental open-circuit voltage was lower than the theoretical one for the wide channel width, whereas the experimental open-circuit voltage was higher than the theoretical one for the narrow channel width. The inclination of the inner cylinder might cause the decrease in effective radial ratio. © 2023 The Institute of Electrical Engineers of Japan.

关键词： Magnetohydrodynamics

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Pilot Studies on Avrora Unior Car-Like Robot Control Using Gestures 16th

Pilot Studies on Avrora Unior Car-Like Robot Control Using G...

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16th International Conference on Electromechanics and Robotics "Zavalishin’s Readings", ERZR 2021

作者： Nikiforov, Nikita Tsoy, Tatyana Safin, Ramil Bai, Yang Svinin, Mikhail Magid, Evgeni Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Information Science and Engineering Department College of Information Science and Engineering Ritsumeikan University 1 -1 -1 Noji -higashi Kusatsu Shiga525-8577 Japan

ISBN: (纸本)9789811628139

Gesture recognition is not only an important communication channel in human-human interaction but it also allows a human to communicate with other intelligent devices. This paper presents a concept for controlling the car-like robot Avrora Unior locomotion using gestures. We created a list of 18 control commands that contains basic and compound commands. A group of 17 volunteers used this list to create individual control gestures independently. A small part of the obtained dataset of gestures was used with the Teachable machine service in order to preliminary evaluate a possibility of constructing a full-scale model and to train it appropriately. The obtained model demonstrated acceptable recognition rate. We also attempted to apply SURF and FLANN techniques for matching with the direct matching approach and the skeleton-based approach, but the matching results were not satisfactory. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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Holding Strategy Using Torso to Enable Humanoid Robots to Carry Heavier Objects

Holding Strategy Using Torso to Enable Humanoid Robots to Ca...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Tsuichihara, Satoki Yamada, Masayuki Hara, Kaito Garcia Ricardez, Gustavo A. Yuguchi, Akishige Takamatsu, Jun Wada, Takahiro Takahashi, Yasutake Ogasawara, Tsukasa University of Fukui Faculty of Engineering Department of Human and Artificial Intelligent Systems 3-9-1 Bunkyo Fukui Fukui910-8507 Japan Nara Institute of Science and Technology Division of Information Science 8916-5 Takayama Nara Ikoma630-0192 Japan College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi Shiga Kusatsu525-8577 Japan Tokyo University of Science Faculty of Advanced Engineering Department of Medical and Robotic Engineering Design 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan

ISBN: (纸本)9798350312072

To alleviate the lack of workforce endemic in contemporary societies, inventory management can be delegated to robots. However, current robotic solutions cannot operate effectively in narrow spaces that have limited unoccupied pathways, such as storage rooms. Humanoid robots can work in facilities designed for humans, including narrow spaces with partially obstructed pathways, as they can overcome small obstacles on the floor by stepping over them. However, their limited torque makes it difficult for the robots to carry many of the objects typically found in storage rooms such as boxes. On the other hand, when holding an object, using multiple body parts can help to distribute the object's load. In this research, we propose a holding strategy for humanoid robots using both arms in conjunction with the torso to prevent exceeding the joint torque limit. We formulate the hands' force and the coordinates of the robot's center of gravity when holding an object with and without using the torso. Using the humanoid robot HRP-4, we compare the torque on the robot's joints when holding an object with two and three contact points. The results show that the three-point holding reduces the torque load on the shoulder and the chest joints. Moreover, we measure the torque of all joints in various torso-bending/leaning and arm-up/down postures while holding a 2-kg object using both arms and the torso. The results show that the leaning torso posture using the chest joint reduces the torque load on the shoulder and chest joints. © 2024 IEEE.

关键词： Anthropomorphic robots

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Empirical Research on 3D Analysis and Flow Prediction of Upstream Rivers Using Drones 13

Empirical Research on 3D Analysis and Flow Prediction of Ups...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Hoshino, Yukinobu Rathnayake, Namal Dang, Tuan Linh Rathnayake, Upaka School of Systems Engineering Kochi University of Technology Kochi Kami City Japan University of Tokyo River and Environmental Engineering Laboratory 7-3-1 Hongo Bunkyoku Tokyo Japan School of Information and Communications Technology Hanoi University of Science and Technology Hanoi Viet Nam Atlantic University of Technology Faculty of Engineering and Design Sligo Ireland

ISBN: (纸本)9798350373332

This study aims to develop an AI prediction system for watersheds, utilizing data from Sri Lanka and Vietnam in collaboration with overseas researchers. Initially, a foundational AI prediction system will be constructed, and basic data will be gathered based on river data from Japan. Subsequently, topographic data of the watershed area, managed by the joint research partner institution, will be incorporated into the AI prediction system through drone-based aerial measurement and analysis. Moreover, visits to the joint research institution will be conducted to gather information on water damage and electricity supply. This information will then be integrated into the AI prediction system. Utilizing the collected data and additional observation data, efforts will be made to enhance the accuracy of the AI prediction algorithm, identify potential issues, and overcome them. The ultimate goal is to establish new AI pre-diction technology by comparing the results of this study with both domestic and international research outcomes. This paper will present data from a drone scan of the upstream watershed and discuss the future use of AI based on the results of three-dimensional analysis and image processing. © 2024 IEEE.

关键词： Flood damage

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