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38th IEEE Region 10 Conference, TENCON 2023

作者： Krutphong, Kodchakorn Leelawat, Natt Tang, Jing Ota, Eri Suzuki, Rie Murakami Taoka, Yuki Punyabukkana, Proadpran Environmental Engineering and Disaster Management Program Mahidol University Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Thailand Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Thailand International School of Engineering Chulalongkorn University Thailand Center for International Education Tokyo Institute of Technology Japan School of Environmet and Society Tokyo Institute of Technology Japan Department of Computer Engineering Faculty of Engineering Chulalongkorn University Thailand The Learning Innovation Center Chulalongkorn University Thailand

ISBN: (纸本)9798350302196

A collaborative course called Global Awareness for Technology Implementation was conducted by the Faculty of engineering, Chulalongkorn University, Thailand, and the Tokyo Institute of Technology, Japan. The objective of this course was to facilitate the exchange of knowledge, perspectives, and experiences between Thai and Japanese students through project work, using an engineering design approach and the design thinking process to create innovation relevant to the Sustainable Development Goals (SDGs). During the class, experts shared their knowledge and experiences with the students. The students then worked on their respective projects to develop solution concepts using the design thinking process. The proposed ideas include the application for English class, smart water quality checker, hydrogen-based energy system for rural area, reduced wasted fashion solution, and auto waste sorting machine. Finally, this study concluded with a summary of the results and findings on the empathy process in the chosen SDGs, and of the commonalities and differences between Thailand and Japan in terms of ideation. © 2023 IEEE.

关键词： Students

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A High-Resolution Approach for Dynamic Traffic Police Gestures Recognition Based on Spatial Context and Temporal Features Fusion 8

A High-Resolution Approach for Dynamic Traffic Police Gestur...

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8th International Conference on Image, Vision and Computing, ICIVC 2023

作者： He, Jian Jiang, Shengsheng Wei, Xin Zhang, Cheng Dong, Ruihai Beijing Engineering Research Center for IOT Software and Systems Beijing University of Technology Beijing China Beijing University of Technology Faculty of Information Technology Beijing China School of Computer Science University College Dublin Dublin Ireland

ISBN: (纸本)9798350335231

According to the requirement of recognizing traffic police gestures for driver assistance systems and intelligent vehicles, a universal model for dynamic traffic police gesture recognition is firstly introduced, of which can accurately present the spatial context (such as the relative lengths of skeletons, the angles between each skeleton w. r. t. gravity, and part features) of the traffic police gestures. Secondly, an architecture which can respectively extract spatial context and temporal features of dynamic traffic police gesture is proposed. Meanwhile, deep neural network and LSTM are introduced to build a high-resolution traffic police gestures recognizer (namely HRTPGR). At last, the open Police Gesture Dataset is used to train and test TPGR, and the experimental results show that the TPGR achieves a state-of-the-art accuracy with 98.7% for dynamic traffic police gestures recognition, and has strong anti-interference ability to light, background and gesture shape changes. © 2023 IEEE.

关键词： Gesture recognition

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HTEC foot:A novel foot structure for humanoid robots combining static stability and dynamic adaptability

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Defence Technology(防务技术) 2025年第2期44卷 30-51页

作者： Jintao Zhang Xuechao Chen Zhangguo Yu Lianqiang Han Zhifa Gao Qingrui Zhao Gao Huang Ke Li Qiang Huang School of Mechatronical Engineering Beijing Institute of TechnologyNo.5South StreetZhongguancunHaidian DistrictBeijing100081China Key Laboratory of Biomimetic Robots and Systems Ministry of EducationNo.5South StreetZhongguancunHaidian DistrictBeijing100081China School of Information Science and Technology Beijing University of TechnologyNo.100PingleyuanChaoyang DistrictBeijing100124China Innovation Center for Control Actuators Beijing Institute of Precision Mechatronics and ControlsDonggaodiFengtai DistrictBeijing100076China

Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental *** this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics ***,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human ***,the kinematics and REH dynamics of the HTEC model were *** on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was ***,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid *** foot static stability is *** enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone *** proposed design method and structure,the mobility of the humanoid robot is improved.

关键词： Humanoid robot Bionic structure Passive foot structure Rigid-elastic hybrid dynamics model Optimal stiffness matching

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Robust Online Epistemic Replanning of Multi-Robot Missions

arXiv

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arXiv 2024年

作者： Bramblett, Lauren Miloradović, Branko Sherman, Patrick Papadopoulos, Alessandro V. Bezzo, Nicola Departments of Systems and Information Engineering and Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States Division of Intelligent Future Technologies Mälardalen University Sweden

As Multi-Robot systems (MRS) become more affordable and computing capabilities grow, they provide significant advantages for complex applications such as environmental monitoring, underwater inspections, or space exploration. However, accounting for potential communication loss or the unavailability of communication infrastructures in these application domains remains an open problem. Much of the applicable MRS research assumes that the system can sustain communication through proximity regulations and formation control or by devising a framework for separating and adhering to a predetermined plan for extended periods of disconnection. The latter technique enables an MRS to be more efficient, but breakdowns and environmental uncertainties can have a domino effect throughout the system, particularly when the mission goal is intricate or time-sensitive. To deal with this problem, our proposed framework has two main phases: i) a centralized planner to allocate mission tasks by rewarding intermittent rendezvous between robots to mitigate the effects of the unforeseen events during mission execution, and ii) a decentralized replanning scheme leveraging epistemic planning to formalize belief propagation and a Monte Carlo tree search for policy optimization given distributed rational belief updates. The proposed framework outperforms a baseline heuristic and is validated using simulations and experiments with aerial vehicles. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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Characterization of Systematic Bias in ALOS-2 Multilooked Interferograms

Characterization of Systematic Bias in ALOS-2 Multilooked In...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ryu Sugimoto Yu Morishita Masanobu Shimada Ryo Natsuaki Chiaki Tsutsumi Ryosuke Nakamura Toru Kouyama Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Japan Division of Architectural Civil and Environmental Engineering School of Science and Engineering Tokyo Denki University Japan Department of Electrical Engineering and Information Systems The University of Tokyo Japan

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Interferometric SAR time series analysis using multilooked interferograms has measured ground deformation with high accuracy over large areas, but is known to be contaminated by a systematic bias when using only short-term interferograms. This bias, also referred to as a "fading signal", has been investigated using the abundant time series data from Sentinel-1 C-band SAR, and soil moisture and biomass changes have been suggested as two possible causes for the observed bias. Several correction methods have been proposed to mitigate the phase bias, assuming a periodic observation strategy. The phase bias is supposed to increase with the wavelength, but the bias in ALOS-2 L-band SAR has not been investigated in detail because the data distribution policy restricts its users. In addition, these correction methods are not suitable for the infrequently observed data such as ALOS-2. In this paper, we investigated the systematic bias in ALOS-2 multilooked interferograms with respect to various interferometric pairs. We also corrected the phase bias using the noise-filtering technique. The bias in ALOS-2 multilooked interferograms showed >3 mm/year with an average temporal baseline of 144 days, which is equivalent to that of Sentinel-1 with the temporal baseline of 78 days. That is, the bias effect toward the temporal baseline was larger in ALOS-2 than in Sentinel-1. The noise-filtering technique could mitigate the bias with less pairs regardless of land-use.

关键词： Fading channels Systematics Soil measurements Time series analysis Soil moisture Sentinel-1 Geoscience and remote sensing

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ChatAN: Interval Adaptive Normalization based on ChatGPT Knowledge Augmentation 8

ChatAN: Interval Adaptive Normalization based on ChatGPT Kno...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Yang, Hanyu Zhao, Xiaoyong Wang, Lei Zhang, Jingle Li, Jianhua Beijing Information Science & Technology University School of Information & Management Beijing China Beijing Information Science & Technology University Information Systems Institute Beijing Advanced Innovation Center for Materials Genome Engineering Beijing China City Brain Zhongguancun Science City City Brain Co. Ltd. Beijing China

ISBN: (纸本)9798350302455

Big data streams have massive and complex characteristics. Due to the lack of global static information, the normalization of large data streams is susceptible to outliers and conceptual drift, which leads to incorrect modeling results. In addition, in online anomaly detection applications, it is significant to ensure real-time data processing to prevent severe consequences from missing critical points due to data flow backlogs. In this paper, we propose a method for interval adaptive normalization based on ChatGPT knowledge augmentation. The approach combines domain knowledge obtained by ChatGPT knowledge augmentation with interval adaptive sliding windows. Experimental results on three datasets in the cybersecurity domain show that the anomaly detection algorithm incorporating our proposed normalization algorithm achieves the maximum improvement of 32.46% and 32.68% in AUCROC and AUCPR compared to the traditional normalization method. © 2023 IEEE.

关键词： Anomaly detection

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Shaping free-electron radiation via van der Waals heterostructures

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Light(Science & Applications) 2023年第8期12卷 1457-1458页

作者： Xiao Lin Hongsheng Chen Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterCollege of Information Science&Electronic EngineeringZhejiang UniversityHangzhou 310027China international Joint Innovation Center the Electromagnetics Academy at Zhejiang UniversityZhejiang UniversityHaining 314400China Key Laboratory of Advanced Micro/Nano Electronic Devices&Smart Systems of Zhejiang Jinhua Institute of Zhejiang UniversityZhejiang UniversityJinhua 321099China Shaoxing Institute of Zhejiang University Zhejiang UniversityShaoxing 312000China

The van der Waals heterostructures with aperiodic stackings have been exploited to shape the spatiotemporal wavefront of free-electron X-ray radiation.

关键词： free stacking exploit

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Comparison of Functional State of Human Body before and after the Laboratory Practice Work 25

Comparison of Functional State of Human Body before and afte...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Rumyantseva, Anastasia A. Ordzhonikidze, Mikhail A. Kosorukov, Artem E. Smyshlyaeva, Anastasia V. Shchukin, Sergei I. Volkov, Alexander K. Department of Biomedical Engineering Systems BMSTU Moscow Russia Division of Reliability Safety and Durability of aviation Equipment and products FAU "GosNIIAS" Moscow Russia Department of Medical and technical technologies BMSTU Moscow Russia Scientific and Educational Medical and Technological Center BMSTU Moscow Russia

ISBN: (纸本)9798350389234

The functional state of the human body is an assessment that determines the level of vital activity of the body and its response to the load. Therefore, this estimate is very important of interest. Modern methods of such an assessment are based on the analysis of individual body systems. This may result in missing deviations from the normal state of the unanalyzed system. It has been established that the electrokinetic properties of buccal epithelial cells reflect the onset of any inflammatory process in the human body. This study compares the functional state of the human body before and after laboratory studies, which was assessed using the electrokinetic properties of cells. It was revealed that the zeta potential of students' cells taken before the start of practice was significantly lower than after classes, which indicates a connection between the work of sensory systems and the electrokinetic properties of buccal epithelium cells. © 2024 IEEE.

关键词： Electrotherapeutics

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Few-Shot Object Detection Based on Contrastive Learning 6

Few-Shot Object Detection Based on Contrastive Learning

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6th International Conference on Intelligent Robotics and Control engineering, IRCE 2023

作者： Wang, Hao Yu, Xiaoxi Chen, Dongyue Deng, Shizhuo College of Information Science and Engineering Northeastern University Shenyang China Foshan Graduate School of Innovation Northeastern University Foshan China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China

ISBN: (纸本)9798350326338

Few-shot object detection is a challenging research topic in the field of computer vision. In scenarios with a limited number of training samples, traditional object detection algorithms often suffer from overfitting, leading to subpar classification accuracy and imprecise localization. To address these challenges, we propose a few-shot object detection algorithm based on contrastive learning, encompassing the design of data strategies and model structures. To mitigate the issues arising from limited data and insufficient intra-class diversity, we introduce data augmentation strategies involving saliency-mixed image enhancement and data resampling. Additionally, to tackle problems such as misclassification of new instances and inaccurate object localization, we design a comprehensive model structure for few-shot object detection based on contrastive learning. Experimental evaluations are conducted on general datasets PASCAL VOC. The results demonstrate the high effectiveness and practicality of the proposed approach in few-shot object detection tasks, underscoring its significant research significance and practical application value. © 2023 IEEE.

关键词： Object detection

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Safety Benefits Evaluation of Mixed Traffic Flow with Connected and Automated Vehicles under Snowy Conditions 7

Safety Benefits Evaluation of Mixed Traffic Flow with Connec...

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7th IEEE International Conference on Transportation information and Safety, ICTIS 2023

作者： Lu, Zhaoyou Ding, Naikan Gao, Jin Fu, Chuanyun Zhang, Hui Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Transport Beijing China School of Transportation Science and Engineering Harbin Institute of Technology Beijing China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China Engineering Research Center of Transportation Information and Safety Ministry of Education Wuhan China

ISBN: (纸本)9798350308532

Connected and automated vehicles are widely agreed to bring tremendous benefits to the traffic system. But the understanding of them is still challenging due to the complexity of the mixed traffic flow of human-driven (HDVs), automated vehicles (AVs), and connected and automated vehicles (CAVs), and due to our limited knowledge of the impacts of adverse weather conditions. Given this, this study was driven to test the safety performance of the above mixed traffic flow both in sunny and snowy conditions under various market penetration rates (MPRs) using SUMO. Minimum gap, the acceleration/deceleration ability of vehicles, and the drivers' desired (minimum) time headway were specifically calibrated for car-following behaviors by a Kolmogorov-Smirnov test based on data collected at an intersection in China. Three surrogate safety measures, i.e., time to collision (TTC), Time-Exposed TTC (TET), and brake rate (BR), were utilized to evaluate the real-time crash risk variations. The results show that 1) the safety performance improved in sunny and snowy conditions when the traffic flow was mixed with AVs and CAVs;2) the improvement of AVs and CAVs in avoiding serious conflicts was more significant in the snowy condition, and 3) the performance of the braking rate was different when MPRs increased in the sunny and snowy conditions. In addition, the difference in safety benefits between AVs and CAVs in sunny and snowy conditions was analyzed. The findings of this study provide valuable insights for managing connected and automated traffic under the snowy condition on urban roads. © 2023 IEEE.

关键词： Risk assessment

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