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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Itai, Shiroh Nariai, Tomoko Kojima, Hiroaki Hiroshima Institute of Technology Department of Electrical Systems Engineering Hiroshima Japan Takachiho University Department of Business Administration Tokyo Japan Industrial Science and Technology Artificial Intelligence Research Center National Institute of Advanced Tsukuba Japan

ISBN: (纸本)9781665419048

As the percentage of the older adults population increases worldwide, both the risk of social isolation of the older adults and the shortage of nursing care personnel have become major issues. To address these issues, we have developed a recreational program, the scenario-type robot-assisted recreation, to promote communication among the older adults in aged care facilities. While the burden of the facility staff increases due to the COVID-19 pandemic, we improved the robot operation interface, developed a system to support the operation of this activity by the facility staff from a remote location, and developed a system to realize communication with remote family members, in order to smoothly operate this recreational activity by the facility staff by themselves. © 2022 IEEE.

关键词： Economic and social effects

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Method for creating privacy-preserving information using Probabilistic Latent Semantic Analysis

Method for creating privacy-preserving information using Pro...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Sugawara, Yuki Sakurai, Eiichi Motomura, Yoichi Okada, Yukihiko Tanabe, Kai Tsukao, Akiko Kuno, Shinya National Institute of Advanced Industrial Science and Technology Koto Japan University of Tsukuba Tsukuba Japan National Institute of Advanced Industrial Science and Technology Artificial Intelligence Research Center Koto Japan Institute of Systems and Information Engineering Center for Artificial Intelligence Research University of Tsukuba Tsukuba Japan University of Tsukuba Faculty of Health and Sport Sciences R&d Center for Smart Wellness City Policies Tsukuba Japan Tsukuba Wellness Research Co. Ltd Kashiwa Japan

ISBN: (纸本)9798350324457

In recent years, rapid digitization and technological advances have enabled governments and companies to utilize various types of personal information, including environment, medical, and lifestyle. Privacy protection is an important issue in the utilization of personal information, and anonymization methods such as k-anonymization and 1-diversity have been proposed in the past. However, to utilize data effectively, it is also important not to lose the usefulness of the information. Privacy protection and preserving the usefulness of information are in a trade-off relationship, and balancing these two aspects has been a difficult problem. Recently, microaggregation using clustering algorithms has been attracting attention as an anonymization method that ensures the usefulness of the data while protecting privacy. In this study, we proposed a new microaggregation method based on iterative processing using probabilistic latent semantic analysis and evaluated the proposed method based on the use case. The use case is a classification of social isolation and an analysis of the relationship with physical frailty risk using the classified groups. Compared to microaggregation using quasi-identifiers and microaggregation based on a conventional clustering algorithm, the proposed method was able to find social isolation characteristics obtained in the raw data with higher accuracy. In addition, in a more detailed analysis focusing on a population with certain characteristics, the proposed method was able to replicate the analysis results obtained using the raw data and to make appropriate assessments of the health risks. © 2023 IEEE.

关键词： microaggregation privacy-preserving Probabilistic Latent Semantic Analysis

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A Sequential Audio Spectrogram Transformer for Real-Time Sound Event Detection

A Sequential Audio Spectrogram Transformer for Real-Time Sou...

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European Signal Processing Conference (EUSIPCO)

作者： Takezo Ohta Yoshiaki Bando Keisuke Imoto Masaki Onishi Graduate School of Systems and Information Engineering University of Tsukuba Japan National Institute of Advanced Industrial Science and Technology Japan Department of Information Systems Design Doshisha University Japan

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

In this paper, we propose an audio spectrogram transformer (AST) for sequential inference and evaluate its real- time performance. ASTs are pre-trained in a self-supervised manner, such as masked autoencoding, and the pre-trained models are well-performing in sound event detection. However, the existing architectures are designed for offline inference, wherein the entire signal serves as the input, and are unsuitable for sequential inference as they require the input sequence to be split into short chunks. In this study, we design a sequential AST based on a memory token (MT-AST) and its training method and conduct comprehensive experiments regarding the chunk length configuration. Specifically, we extend the offline AST with special tokens that memorize past signal information so that the network avoids repetitive inference of the same signal. While our model has limited inference capability, we train it using knowledge distillation from BEATs, a large-scale pre-trained model. Compared to the offline architecture, our model achieved higher performance by pre-training with AudioSet and fine-tuning for the URBAN-SED and DESED datasets. In addition, we conducted experiments to investigate the input chunk length considering performance-latency trade-offs and revealed the optimal configurations. We revealed that our model requires at least one extra second of input to maintain the performance.

关键词： Training Performance evaluation Event detection Image edge detection Europe Computer architecture Transformers Real-time systems Computational complexity Spectrogram

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Research on Metamaterial technology for Microwave Wireless Power Transfer

Research on Metamaterial Technology for Microwave Wireless P...

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International Symposium on Antennas and Propagation (ISAP)

作者： Tsunayuki Yamamoto Takeo Kobashi Tamami Maruyama Department of Integrated Science and Technology National Institute of Technology Tsuyama College Tsuyama-shi Japan Advanced Electronics and Information System Engineering Course National Institute of Technology Tsuyama College Tsuyama-shi Japan Department of Production Systems Engineering Institute of Technology Hakodate College Hakodate-shi Japan

ISBN: (数字)9798350364774

ISBN: (纸本)9798350364781

In this paper, two technologies of metamaterial for microwave wireless power transfer are shown. One is a zeroth-order resonance for a microwave snow melting system, and another one is a focusing reflector for realizing of a highly efficient wireless power transfer space. A zeroth-order resonance leads a uniformed microwave heating and a flexibility of feeding in a snow melting system. Focusing reflector can make some electromagnetic hot and null points in a space. These are expected to be required technologies for highly efficient wireless power transfer.

关键词： Microwave antennas Microwave technology Electromagnetic heating Snow Focusing Wireless power transfer Resonance Metamaterials Electromagnetics Microwave propagation

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Scalable intensity-based photonic matrix-vector multiplication processor using single-wavelength time-division-multiplexed signals

arXiv

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arXiv 2025年

作者： Chai, Chengli Tang, Rui Okano, Makoto Toprasertpong, Kasidit Takagi, Shinichi Takenaka, Mitsuru Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo113-8656 Japan National Institute of Advanced Industrial Science and Technology Ibaraki305-8568 Japan

Photonic integrated circuits provide a compact platform for ultrafast and energy-efficient matrix-vector multiplications (MVMs) in the optical domain. Recently, schemes based on time-division multiplexing (TDM) have been proposed as scalable approaches for realizing large-scale photonic MVM processors. However, existing demonstrations rely on coherent detection or multiple wavelengths, both of which complicate their operations. In this work, we demonstrate a scalable TDM-based photonic MVM processor that uses only single-wavelength intensity-modulated optical signals, thereby avoiding coherent detection and enabling simplified operations. A 32-channel processor is fabricated on a Si-on-insulator (SOI) platform and used to experimentally perform convolution operations in a convolutional neural network (CNN) for handwritten digit recognition, achieving a classification accuracy of 93.47% for 1500 images. © 2025, CC BY.

关键词： Convolution

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Enabling technology and core theory of synthetic biology

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Science China(Life Sciences) 2023年第8期66卷 1742-1785页

作者： Xian-En Zhang Chenli Liu Junbiao Dai Yingjin Yuan Caixia Gao Yan Feng Bian Wu Ping Wei Chun You Xiaowo Wang Tong Si Faculty of Synthetic Biology Shenzhen Institute of Advanced TechnologyShenzhen 518055China Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China State Key Laboratory of Plant Cell and Chromosome Engineering Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Microbial Metabolism Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin 300308China Ministry of Education Key Laboratory of Bioinformatics Center for Synthetic and Systems BiologyBioinformatics DivisionBeijing National Research Center for Information Science and TechnologyDepartment of AutomationTsinghua UniversityBeijing 100084China

Synthetic biology provides a new paradigm for life science research(“build to learn”)and opens the future journey of biotechnology(“build to use”).Here,we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology,including synthesis and assembly of a genome,DNA storage,gene editing,molecular evolution and de novo design of function proteins,cell and gene circuit engineering,cell-free synthetic biology,artificial intelligence(AI)-aided synthetic biology,as well as *** also introduce the concept of quantitative synthetic biology,which is guiding synthetic biology towards increased accuracy and predictability or the real rational *** conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

关键词： synthetic biology quantitative synthetic biology genome synthesis and assembly DNA storage molecular evolution de novo design computer-aided design cell engineering gene circuit chassis cell artificial intelligent(AI) biofoundry

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One Solution to the Cost-Sharing Issue by the Sweden Game Experiment and Educational Effects

One Solution to the Cost-Sharing Issue by the Sweden Game Ex...

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advanced Applied Informatics Winter (IIAI-AAI-Winter), International Congress on

作者： Masashi Kawaguchi Takashi Kusaka Naohiro Ishii Masayoshi Umeno Department of Electrical & Electronic Engineering National Institute of Technology Suzuka College Suzuka Japan Department of General Education National Institute of Technology Suzuka College Suzuka Japan Information Systems Architecture Course Advanced Institute of Industrial Technology Tokyo Japan Department of Electronic Engineering Chubu University Kasugai Japan

The issue of cost-sharing has been familiar since ancient times. Even today, it is used in various situations, such as cost-sharing for infrastructure development and contributions to neighborhood associations. Many methods have been proposed for the cost-sharing problem. One typical solution is the Shapley value. However, there are cases where the best solution cannot be obtained. In addition, if the solution is disadvantageous to the parties, there is a risk of dissatisfaction and failure to reach an agreement. On the other hand, gaming solutions are attracting attention. A mutually satisfactory solution can be obtained by gaming by solving the cost-sharing problem between the parties. Furthermore, better solutions than other methods have been derived. In this paper, we report on the optimal solution derived from the gaming results, its educational effects, and the results of a webinar on gaming in Finland and Japan.

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End-to-End Visuomotor Learning from Virtual Environment to Real Robot

End-to-End Visuomotor Learning from Virtual Environment to R...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Kei Higuchi Constantin Uhde Gordon Cheng Ixchel G. Ramirez-Alpizar Gentiane Venture Natsuki Yamanobe Graduate School of Engineering Mechanical Systems Engineering Tokyo University of Agriculture and Technology Japan National Institute of Advanced Industrial Science and Technology (AIST) Japan Institute for Cognitive Systems Technical University of Munich Germany Department of Mechanical Engineering Faculty of Engineering The University of Tokyo Japan

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Robots can acquire skills to accomplish a target task by learning human manipulations. In this study, we build an end-to-end visuomotor learning system for a robot to learn multiple tasks in a virtual environment, and then perform the same tasks in a real environment without re-training. We use domain randomization to improve the generalization performance of the learning model. To effectively tackle this challenge, we build an integrated learning system that jointly learns robot motions and visual features of the task. The experimental results show that our system can perform multiple tasks with a high success rate and is able to successfully bridge the Sim2Real gap, compared to learning motion and visual features separately.

关键词： Learning systems Robot motion Bridges Visualization Image recognition Computer aided software engineering Virtual environments Motors Robots Image reconstruction

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Additive manufacturing of a Co-Cr-W alloy by selective laser melting:In-situ oxidation,precipitation and the corresponding strengthening effects

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Journal of Materials Science & technology 2022年第30期125卷 171-181页

作者： Kefeng Li Zhi Wang Kaikai Song Khashayar Khanlari Xu-Sheng Yang Qi Shi Xin Liu Xinhua Mao Institute of New Materials Guangdong Academy of SciencesGuangzhou 510650China National Engineering Research Center of Powder Metallurgy of Titanium and Rare Metals Guangzhou 510650China Guangdong Key Laboratory for Advanced Metallic Materials Processing South China University of TechnologyGuangzhou 510641China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China Advanced Manufacturing Technology Research Center Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518000China

Additive manufacturing exhibits great potentials for the fabrication of novel materials due to its unique non-equilibrium solidification and heating *** this work,a novel nano-oxides dispersion strengthened Co28 Cr9 W1.5 Si(wt.%)alloy,fabricated by laser powder bed fusion(LPBF),was comprehensively *** the layer-by-layer featured process,in-situ formation of Si rich,amorphous,nano-oxide inclusions was observed,whose formation is ascribed to the high affinity of Si to ***,distinctive body-centered cubic(BCC)Co5 Cr3 Si2 nano-precipitates with an 8-fold symmetry were also confirmed to *** precipitates,rarely reported in previous studied Co-Cr alloys,were found to tightly bond with the in-situ ***,the morphologies,the size distributions as well as the microstructure of the interface between the matrix and the inclusions were investigated in detail and their influence on the tensile deformation was also *** existence of transition boundaries between these inclusions and the matrix strongly blocked the movement of dislocations,thereby increasing the strength of the *** was understood that when the plastic deformation proceeds,the fracture occurs in the vicinity of the oxide inclusions where dislocations accumulate.A quantitative analysis of the strengthening mechanism was also established,in which an additional important contribution to strength(~169 MPa)caused by the effects of in-situ formed oxide inclusions was calculated.

关键词： Co-Cr-W-Si alloy Selective laser melting Oxide inclusion Precipitation Strengthening mechanisms

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Affinity-Weighted RandAugment for Problem-Oriented Augmentation

Affinity-Weighted RandAugment for Problem-Oriented Augmentat...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yuna Park Tomoumi Takase Keisuke Kameyama Masaki Onishi Degree Programs in Systems and Information Engineering and Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology (AIST) Japan Institute of Systems and Information Engineering University of Tsukuba

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Data augmentation is a technique with the potential to improve model generalization performance. Automatic Augmentation, which autonomously designs suitable data augmentation strategies, has significantly improved performance. One of the effective Automatic Augmentation is RandAugment (RA), which randomly selects methods to apply from the set of available augmentations. However, its selection with equal probabilities for all available augmentations is not ideal. In this study, we propose Affinity-Weighted RandAugment which assigns weights to the selection probabilities for the available augmentations in RA. The weights are calculated based on the value of Affinity, which represents the distributional similarity between original and augmented data. Affinity provides the prediction of the effect of each augmentation according to both the model and the dataset in advance. This enables the assignment of weights to the selection probabilities with low computational cost. As an additional effort, whether Affinity could be obtained at a much lower computational cost was considered. Based on these insights we implemented Single-Pass Affinity-Weighted RA, which can achieve effective weighting for RA without additional or separate learning. Experiments in image classification using CIFAR-10/100 and Describable Textures Dataset (DTD) demonstrated that Affinity-Weighted RandAugment achieves better test accuracy in comparison with the other known RA methods.

关键词： Accuracy Computational modeling Neural networks Probability Predictive models Data augmentation Data models

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