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Pulsed Power Conference, International Conference on High-Power Particle Beams and International Symposium on Electromagnetic Launch Technology (EAPPC/BEAMS/EML), Euro-Asian

作者： Takuto Doi Shota Oishi Takashi Sakugawa Kaisei Nishimura Shinichiro Shobako Shinichi Shimasaki Tomohiko Yamashita Department of Computer Science & Electrical Engineering Graduate School of Science & Technology Kumamoto University Kumamoto Japan Department of Electro-Mechanical Systems Engineering National Institute of Technology Kagawa College Takamatsu Japan

ISBN: (数字)9789038661353

ISBN: (纸本)9798350352733

The authors investigate the potential of pulsed power technology in recycling of E-waste. Applying the pulsed discharge can separate composite materials into plastic and metal. In this study, pulsed discharge was applied to indium tin oxide (ITO) coated plastic films. We used two electrode types: rod-to-rod electrode and a pair of flat plate electrodes to investigate the effect of electrode structure on the metal removal area in detail. A series of single pulse discharges were applied at various electrode distances. As a result, it was revealed that metal can be removed over a wide range by the pulsed discharge using a pair of flat plate electrodes. When the gap between the electrodes was 30 mm, the removal area by the flat plate electrodes was approximately 3.4 times that by the rod electrodes. Analysis of the current density also revealed that the metal removal area was greatly affected by the current density.

关键词： Electrodes Particle beams Composite materials Shape Indium tin oxide Metals Plastic films Discharges (electric) Recycling Current density

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An Improved Multi -Offspring Genetic Algorithm with Elite Teacher Strategy for Traveling Salesman Problem

An Improved Multi -Offspring Genetic Algorithm with Elite Te...

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International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Hongyi Du Jiacheng Li Masato Noto Lei Li Graduate School of Science and Engineering Hosei University Tokyo Japan Department of Applied Systems and Mathematics Kanagawa University Yokohama Japan Faculty of Science and Engineering Hosei University Tokyo Japan

ISBN: (数字)9798350385106

ISBN: (纸本)9798350385113

In the field of genetic algorithms, despite significant advancements made by researchers, traditional genetic algorithms still face certain challenges. To enhance the performance of genetic algorithms in applications, the concept of multiple offspring generation has been proposed based on the principles of mathematical ecology theory and biological evolution. However, it should be noted that generating multiple offspring is primarily aimed at expanding the search space and does not guarantee that the offspring produced will be superior to the parents. Given the critical role of the crossover operation in the algorithm, our focus is on exploring improved methods for generating multiple offspring. We have introduced a novel approach to enhance the diversity among multi-offspring algorithms. Specifically, we have improved the Order Crossover(OX) and introduced a QuickSort mechanism to ensure diversity among the offspring. Furthermore, to validate the robustness of this idea, we apply it to other crossover techniques as well. Additionally, we have proposed the Elite Teacher strategy to address the inherent limitations of genetic algorithms. Our multi-offspring approach has been compared with other multi-offspring algorithms proposed in recent years in solving the Traveling Salesman Problem (TSP), along with a detailed investigation of algorithm performance. The research results demonstrate that our method has achieved significant advancements in terms of solving speed and overall efficiency.

关键词： Evolution (biology) Traveling salesman problems Robustness Iterative algorithms Ecology Computational efficiency Optimization

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Study on a Novel Voxel-Based 3D Printing Method on Magnetic-controlled Memory Fluid 19

Study on a Novel Voxel-Based 3D Printing Method on Magnetic-...

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19th IEEE International Conference on Automation science and engineering, CASE 2023

作者： Zhang, Shengjie Sun, Xudong Song, Zhongru Guo, Yifei Qu, Juntian Li, Zhenkun School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China North China University of Science and Technology Department of Mechanical Engineering Tangshan063210 China Hebei Industrial Robot Industry Technology Research Institute Tangshan063000 China Shenzhen International Graduate School Tsinghua University Shenzhen518055 China

ISBN: (纸本)9798350320695

Combining the 'programmable' characteristics of smart materials with 3D printing technology can realize the integration of structural design and manufacturing. Magnetic controlled smart fluid owns the characteristics of flexible solid-liquid transformation, high driving efficiency and high safety. Soft robot driven by magnetic controlled intelligent fluid can realize a bionic movement similar to that of single-celled organisms. In this paper, we propose a reversible 3D printing method of magnetic phase transformation using a similar mechanism of sol-gel transformation in protoplasm. A magnetically controlled Pickering emulsion system with strong thixotropic properties was constructed and its microscopically self-assembled structure was characterized. The yielding and memory recovery characteristics of the magnetic-controlled memory fluid (MMF) were studied by means of steady-state and dynamic shear measurement, and the optimal rheological parameters suitable for printing were determined. A 3D printing platform and a memory elimination platform for coordinated control of magnetic field and motion system were built to further study and optimize the printing process. Finally, the composite structure is controlled by an array magnetic field to realize an amoeba-like motion. Novel voxel-based 3D printing and its application in soft robots can provide new ideas for space exploration, biomedicine, military reconnaissance and many other fields. © 2023 IEEE.

关键词： Emulsification

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Fast Steady-State Analysis Method for Cage Induction Motors Based on Polyphase TP-EEC Method in a Rotational Reference Frame

Fast Steady-State Analysis Method for Cage Induction Motors ...

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International Conference on Electrical Machines and systems (ICEMS)

作者： Hiroyuki Kaimori Yasuhito Takahashi Shinji Wakao Science Solutions International Laboratory Inc. Tokyo Japan Department of Electrical Engineering Doshisha University Kyoto Japan Graduate School of Advanced Science and Engineering Waseda University Tokyo Japan

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

This paper proposes a fast steady-state analysis method for cage induction motors (IMs) based on the time- periodic explicit-error-correction (TP-EEC) method. To address the high computational costs associated with time- stepping steady-state analysis of cage IMs, we expand the application scope of the dq-TP-EEC method, which was originally developed for three-phase electric machines in a rotational reference frame, to polyphase machines by taking account of slip frequency in the rotor. The effectiveness of the proposed method is demonstrated through the steady-state analysis of two types of cage IMs with closed and semi-closed rotor slots. Numerical results confirm the validity of the method and show that smaller time intervals significantly improve convergence in transient analysis when the slip is not very small. In addition, the limitations of the proposed method due to the large time constant with low slip frequency are investigated.

关键词： Couplings Magnetic flux Time-frequency analysis Induction motors Rotors Steady-state Error correction Transient analysis Bars Convergence

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Unpacking consumer motivations for upcycled food purchases in Japan

Food and Humanity

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Food and Humanity 2025年 4卷

作者： Mori, Ryota Seo, Yuna Department of Industrial and Systems Engineering Graduate School of Science and Technology Tokyo University of Science 2641 Yamasaki Chiba Noda Japan

This study examines the factors influencing consumer purchase intentions for upcycled food products, distinguishing between non-purchasers and purchasers. A comprehensive methodology was employed, beginning with questionnaire development and data collection, followed by factor analysis for each consumer group to identify key factors and reduce dimensionality. Multiple regression analysis was then conducted with purchase intention as the dependent variable and other factors as independent variables. Cluster analysis, based on factor scores representing purchase intention, was performed to categorize consumers into high, medium, and low purchase intention groups. ANOVA was used to explore socio-demographic differences within these groups. The findings reveal distinct motivations between non-purchasers and purchasers of upcycled foods. For non-purchasers with higher purchase intentions, factors such as sustainable consumption practices, curiosity, food waste awareness, and environmental responsibility were prominent. This group, which resembles early adopters, is motivated by ethical consumption and personal growth, suggesting that targeted marketing emphasizing innovation and sustainability could encourage their transition into purchasers. In contrast, purchasers prioritized sensory factors such as taste and price over product safety and quality. While they value sustainability, their purchase decisions are influenced more by practical concerns such as affordability and sensory enjoyment. Consequently, marketing strategies targeting purchasers should focus on taste, affordability, and the broader impact of reducing food waste. This study contributes to the understanding of consumer behavior toward upcycled foods by emphasizing the importance of segmenting the market based on purchase behavior. Non-purchasers are more likely to respond to messages highlighting innovation and ethical values, while purchasers are more responsive to messages focusing on sensory attributes

关键词： Marketing strategy Purchase intention Sustainable consumption Upcycled foods

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Optimized Pseudo–Linearization–Based Model Predictive controller Design: Direct Data–Driven Approach

arXiv

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arXiv 2023年

作者： Sekine, Mikiya Tsuruhara, Satoshi Ito, Kazuhisa The Graduate School of Engineering and Science Mechanical Engineering Shibaura Institute of Technology 307 Fukasaku Saitama Minuma 3378570 Japan The Graduate School of Engineering and Science Functional Control Systems Shibaura Institute of Technology 307 Fukasaku Saitama Minuma 3378570 Japan The Department of Machinery and Control Systems Shibaura Institute of Technology 307 Fukasaku Saitama Minuma 3378570 Japan

To reduce the typical time–consuming routines of plant modeling for model–based controller designs in SISO systems, the fictitious reference iterative tuning (FRIT) method has been proposed and proven to be effective in many applications. However, it is generally difficult to properly select a reference model without a prior information on the plant. This significantly affects the control performance and might considerably degrade the system performance. To address this problem, we propose a pseudo–linearization (PL) method using FRIT, and design a new controller for SISO nonlinear systems by combining data–driven and model–based control methods. The proposed design considers input constraints using model predictive control. The effectiveness of the proposed method was evaluated based on several practical references using numerical simulations for hysteresis and dead zone classes and experiments involving artificial muscles with hysteresis characteristics. © 2023, CC BY-NC-ND.

关键词： Model predictive control

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A New Combined PV Output Power Forecasting Model Based on Optimized LSTM Network

A New Combined PV Output Power Forecasting Model Based on Op...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Heydari, Azim Keynia, Farshid Fekih, Afef Tjernberg, Lina Bertling Barchi, Grazia Moser, David Eurac Research Institute for Renewable Energy Bolzano Italy Graduate University of Advanced Technology Institute of Science and High Technology and Environmental Sciences Department of Energy Management and Optimization Kerman Iran University of Louisiana at Lafayette Department of Electrical and Computer Engineering LafayetteLA United States KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350331790

One of the most challenging problems in designing and implementing effective management strategies and demand responses in renewable-rich grids is the uncertainty associated with the power output (PO) of solar photovoltaic (PV) systems. The exact and trustworthy prediction of PV power can provide substantial decision support for planning and operating power systems. This paper develops an intelligent PV output power (PV-OP) forecasting model. The proposed PV-OP forecasting model consists of an Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) signal decomposition model to decompose the original PV output power signal to different frequencies, LSTM neural network as a main forecaster engine, and multi-objective NSGA-II optimization algorithm as a hyperparameters optimizer. The developed PV power forecasting model was validated using the PV power datasets of an off-grid village located in Chalokwa, Zambia. The obtained results confirmed the performance and accuracy of the proposed PV output power forecasting model. © 2023 IEEE.

关键词： Multiobjective optimization

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Data Completeness-aware Transmission control for Large Spatio-Temporal Data Retention

Data Completeness-aware Transmission Control for Large Spati...

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Kaneyasu, Hotaka Nobayashi, Daiki Tsukamoto, Kazuya Ikenaga, Takeshi Lee, Myung Graduate School of Engineering Kyushu Institute of Technology Fukuoka Japan Kyushu Institute of Technology Faculty of Engineering Department of Electrical and Electronics Engineering Fukuoka Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering Department of Computer Science and Networks Fukuoka Japan City College of New York Department of Electrical and Computer Engineering New York United States

ISBN: (纸本)9781665441544

With the development of IoT technology, various kinds of data are generated by IoT devices. Some of this data contains information on geographical location and time. We refer to such data as spatio-temporal data (STD). Since the 'local production and consumption' of STD is effective for location-dependent applications, we have proposed an STD retention system that utilizes vehicles as data sources. STD sources ranges from simple sensory data to large video data. However, since previous methods assumed to retain an STD consisting of only one packet, retention of large STD sources may suffer from frequent packet collisions due to the increase in the number of packet transmissions. In this paper, we propose a data completeness-aware transmission control mechanism for large STD retention. Our simulation results showed that the proposed scheme reduces channel collision by suppressing the forwarding of incomplete data, and achieved a nearly 100% coverage rate. © 2022 IEEE.

关键词： Internet of things

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Simulating the Gravitational Displacement of a Gigantic Manipulator Posture Using Lumped Stiffness-Matrix Modeling on a Physics Engine

Simulating the Gravitational Displacement of a Gigantic Mani...

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

作者： Maruyama, T. Ogawa, S. Jaklin, N. Tolsma, S. Tsubouchi, T. Graduate School of Systems and Information Engineering University of Tsukuba Ibaraki Tsukuba-shi305-8573 Japan National Institutes for Quantum Science and Technology Department of Iter Project Ibaraki-ken Naka-shi311-0193 Japan Da Vincilaan 31 6716 WC Netherlands

ISBN: (纸本)9798350312072

The ITER project seeks to construct the world's largest fusion device to validate fusion as a viable energy source. The blanket remote handling system (BRHS) manages blanket modules weighing up to four tons, which shield the vessel from fusion plasma. A virtual reality (VR) environment is indispensable for effective motion planning and monitoring during BRHS operations. However, gravitational displacements over 100 mm at the end -effector pose a challenge to achieving the required ±50 mm error range of the VR relative to the actual manipulator. To address this issue, we propose a method utilizing the lumped model, in which virtual joints simulating the stiffness of the manipulator links are implemented. The physics engine of the VR software calculates the deformation of the virtual joints. Since stiffness parameters are obtained through structural analysis, this approach eliminates the need for actual equipment measurements. The virtual joints feature a six-degree-of-freedom (6-DoF) spring, commonly used in the lumped model, and a full stiffness matrix for better simulation. Through evaluation, we reduced the maximum VR error from 97.8 mm (rigid model) to 64.6 mm (6-DoF spring model). Although the maximum error still exceeded the ±50 mm requirement, the proposed method significantly improved the VR accuracy. © 2024 IEEE.

关键词： Manipulators

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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