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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Toshiki Goto Yu Shibuya Master’s Program of Information Science Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9781728198026

ISBN: (纸本)9781728198033

Playing competitive online games is usually fun but sometimes player feels unpleasant and is stressed regardless of games content. When a player is stressed, her/his motivation for games decrease. The purpose of this study is to make competitive online games more enjoyable by reducing player's stress. We propose a system that detects player's stress in a competitive online game by her/his RRI and automatically presents calm scent of lavender oil with an aroma diffuser and a fan when she/he is stressed. In the proposed system, each player wears an armband-type pulse sensor and plays a game with a controller while looking at the display. The system get the player's heart rate from armband-type pulse sensor in real time. Next, the system calculates the RRI from heart rate and determines that the player is stressed when her/his RRI is greater than the threshold. To evaluate the proposed system, we are going to experiment to check the functionality of the proposed system, investigate how long to play the game and under what conditions to detect participants' stress in the game and evaluate whether the proposed system can reduce participants stress in a real environment.

关键词： Heart rate Fans Rail to rail inputs Oils Games Real-time systems Stress

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Maternal Progesterone and Adipose mPRΕ in Pregnancy Regulate the Embryonic Nutritional State

SSRN

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SSRN 2024年

作者： Watanabe, Keita Yamano, Mayu Miyamoto, Junki Ohue-Kitano, Ryuji Masujima, Yuki Sasahara, Daiki Mouri, Yuki Kono, Nozomu Inuki, Shunsuke Osakada, Fumitaka Nagaoka, Kentaro Aoki, Junken Sugiura, Yuki Ohno, Hiroaki Kondoh, Eiji Kimura, Ikuo Laboratory of Molecular Neurobiology Graduate School of Biostudies Kyoto University Sakyo-ku Kyoto606-8501 Japan Department of Molecular Endocrinology Graduate School of Pharmaceutical Sciences Kyoto University Sakyo-ku Kyoto606-8501 Japan Department of Applied Biological Science Graduate School of Agriculture Tokyo University of Agriculture and Technology Fuchu Tokyo183-8509 Japan Department of Biological & Environmental Chemistry Kindai University 11-6 Kayanomori Iizuka Fukuoka820-8555 Japan Noster Inc. Kamiueno Muko-shi Kyoto617-0006 Japan Graduate School of Pharmaceutical Sciences The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Department of Bioorganic Medicinal Chemistry Graduate School of Pharmaceutical Sciences Kyoto University Sakyo-ku Kyoto606-8501 Japan Laboratory of Cellular Pharmacology Graduate School of Pharmaceutical Sciences Nagoya University Japan Laboratory of Neural Information Processing Institute for Advanced Research Nagoya University Japan AMED-CREST Japan Agency for Medical Research and Development Chiyoda-ku Tokyo100-0004 Japan Laboratory of Veterinary Physiology Graduate School of Agriculture Tokyo University of Agriculture and Technology Fuchu Tokyo183-8509 Japan Department of Moonshot Research and Development Program Japan Science and Technology Agency Chiyoda-ku Tokyo102-0076 Japan Center for Cancer Immunotherapy and Immunobiology Kyoto University Graduate School of Medicine Kyoto Japan Department of Obstetrics and Gynecology Faculty of Life Sciences Kumamoto University 1-1-1 Honjo Chuo-Ku Kumamoto Kumamoto860-8556 Japan

Sex steroid hormones such as progesterone play a pivotal role in reproductive functions and maintaining pregnancy;however, the impact of progesterone on the interaction between mother and embryo is unclear. Here, we demonstrate that the relationship between maternal progesterone and membrane progesterone receptor epsilon (mPRΕ) in adipose tissue regulates embryonic nutritional environment and growth after birth in mice. The activation of adipose mPRΕ by increased progesterone during pregnancy enhanced maternal insulin resistance through the production of prostaglandins, thereby efficiently providing glucose to embryos. The offspring of mPRΕ-deficient mothers exhibited metabolic dysfunction, whereas mPRΕ-deficient mothers with high-fat-diet-induced obesity exhibited improved insulin sensitivity. These findings establish the importance of progesterone as a nutritional regulator between mother and embryo, and suggest that mPRΕ modulators could be developed to treat pregnant glycemic control disorders such as gestational diabetes mellitus, as well as metabolic syndrome in offspring. © 2024, The Authors. All rights reserved.

关键词： Obstetrics

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Reduce Fingerprint Construction for Positioning IoT Devices Based on Generative Adversarial Nets 1

Reduce Fingerprint Construction for Positioning IoT Devices ...

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1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020

作者： Tarekegn, Getaneh Berie Juang, Rong-Terng Lin, Hsin-Piao Munaye, Yirga Yayeh Belay Adege, Abebe National Taipei University of Technology Department of International Graduate Program in Electrical Engineering and Computer Science Taipei Taiwan Feng Chia University Department of Electronic Engineering Taichung Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei Taiwan Debre Markos University Department of Information Technology Debre Markos Ethiopia

ISBN: (纸本)9781665404839

Fingerprint-based positioning is popular and applicable for Internet of Things (IoT) applications to offer seamless, intelligent and adaptive location-aware services for IoT devices. However, it takes time and cost to build the radio-map. This paper proposed deep convolutional Generative adversarial nets (DCGANs) to minimize the site survey time and cost, and to mitigate signal fluctuations. The radio-map was designed for receiving radio signals from detectable wireless local area network (WLAN) and cellular networks in scalable environments. The proposed fingerprinting-based positioning is a sequential combination of the hybrid support vector machine and long short-term memory algorithms. The experimental results indicate that the proposed method achieves a promising and reasonable positioning performance for IoT devices in scalable wireless environments. © 2020 IEEE.

关键词： Support vector machines

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Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport

Deep reinforcement learning of event-triggered communication...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Kazuki Shibata Tomohiko Jimbo Takamitsu Matsubara Autonomous Distributed Cooperative Control Program Data Analytics Research-Domain Toyota Central R&D Labs. Inc. Japan Graduate School of Science and Technology Division of Information Science Nara Institute of Science and Technology Nara Japan

In this paper, we explore a multi-agent reinforcement learning approach to address the design problem of communication and control strategies for multi-agent cooperative transport. Typical end-to-end deep neural network policies may be insufficient for covering communication and control; these methods cannot decide the timing of communication and can only work with fixed-rate communications. Therefore, our framework exploits event-triggered architecture, namely, a feedback controller that computes the communication input and a triggering mechanism that determines when the input has to be updated again. Such event-triggered control policies are efficiently optimized using a multi-agent deep deterministic policy gradient. We confirmed that our approach could balance the transport performance and communication savings through numerical simulations.

关键词： Deep learning Automation Conferences Reinforcement learning Computer architecture Numerical simulation Timing

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Photonic Terahertz Phased Array

arXiv

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arXiv 2024年

作者： Niu, Li Feng, Xi Zhang, Xueqian Lu, Yongchang Wang, Qingwei Xu, Quan Chen, Xieyu Ma, Jiajun Qiu, Haidi Sha, Wei E.I. Zhang, Shuang Alù, Andrea Zhang, Weili Han, Jiaguang Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering The Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin300072 China Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science & Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical & Electronic Engineering University of Hong Kong 999077 Hong Kong Photonics Initiative Advanced Science Research Center City University of New York New York10031 United States Physics Program Graduate Center City University of New York New York10016 United States School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74078 United States Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China

Phased arrays are crucial in various technologies, such as radar and wireless communications, due to their ability to precisely control and steer electromagnetic waves. This precise control improves signal processing and enhances imaging performance. However, extending phased arrays to the terahertz (THz) frequency range has proven challenging, especially for high-frequency operation, broadband performance, two-dimensional (2D) phase control with large antenna arrays, and strong phase modulation. Here, we introduce a photonic platform to realize a THz phased array that bypasses the above challenges. Our method employs 2D phase coding with 2-bit across a broad THz frequency range from 0.8 to 1.4 THz. The core of our design is a pixelated nonlinear Pancharatnam-Berry metasurface driven by a spatially modulated femtosecond laser, allowing precise phase control of THz signals. We showcase the effectiveness of our method through four proof-of-concept applications: single beamforming, dual beamforming, imaging and vortex beam generation. The realized photonic platform provides a promising pathway for developing broadband phased arrays in the THz regime. Copyright © 2024, The Authors. All rights reserved.

关键词： Terahertz waves

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Mechanically reprogrammable Pancharatnam-Berry metasurface for microwaves

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Advanced Photonics 2022年第1期4卷 69-79页

作者： Quan Xu Xiaoqiang Su Xueqian Zhang Lijuan Dong Lifeng Liu Yunlong Shi Qiu Wang Ming Kang Andrea Alù Shuang Zhang Jiaguang Han Weili Zhang Tianjin University Center for Terahertz Waves and College of Precision Instrument and Optoelectronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education of China)TianjinChina Shanxi Datong University Institute of Solid State Physics and College of Physics and Electronic ScienceShanxi Province Key Laboratory of Microstructure Electromagnetic Functional MaterialsDatongChina Wuhan University of Technology School of Information EngineeringWuhanChina Tianjin Normal University College of Physics and Materials ScienceTianjinChina City University of New York Advanced Science Research CenterPhotonics InitiativeNew YorkUnited States City University of New York Graduate CenterPhysics ProgramNew YorkUnited States University of Hong Kong Faculty of ScienceDepartment of PhysicsHong KongChina University of Hong Kong Department of Electrical and Electronic EngineeringHong KongChina Guilin University of Electronic Technology Guangxi Key Laboratory of Optoelectronic Information ProcessingSchool of Optoelectronic EngineeringGuilinChina Oklahoma State University School of Electrical and Computer EngineeringStillwaterOklahomaUnited States

Metasurfaces have enabled the realization of several optical functionalities over an ultrathin platform,fostering the exciting field of flat *** metasurfaces are achieved by arranging a layout of static meta-atoms to imprint a desired operation on the impinging wavefront,but their functionality cannot be *** and programmability of metasurfaces are the next important step to broaden their impact,adding customized on-demand functionality in which each meta-atom can be individually *** demonstrate a mechanical metasurface platform with controllable rotation at the meta-atom level,which can implement continuous Pancharatnam–Berry phase control of circularly polarized *** the proof-of-concept experiments,we demonstrate metalensing,focused vortex beam generation,and holographic imaging in the same metasurface template,exhibiting versatility and superior *** dynamic control of electromagnetic waves using a single,low-cost metasurface paves an avenue towards practical applications,driving the field of reprogrammable intelligent metasurfaces for a variety of applications.

关键词： reprogrammable metasurfaces Pancharatnam-Berry phase mechanical metasurfaces microwaves

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Entropic Herding

arXiv

引用

arXiv 2021年

作者： Yamashita, Hiroshi Suzuki, Hideyuki Aihara, Kazuyuki Intelligent Mobility Society Design Social Cooperation Program Graduate School of Information Science and Technology the University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Suita-shi Osaka Japan International Research Center for Neurointelligence the University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan

Herding is a deterministic algorithm used to generate data points that can be regarded as random samples satisfying input moment conditions. The algorithm is based on the complex behavior of a high-dimensional dynamical system and is inspired by the maximum entropy principle of statistical inference. In this paper, we propose an extension of the herding algorithm, called entropic herding, which generates a sequence of distributions instead of points. Entropic herding is derived as the optimization of the target function obtained from the maximum entropy principle. Using the proposed entropic herding algorithm as a framework, we discuss a closer connection between herding and the maximum entropy principle. Specifically, we interpret the original herding algorithm as a tractable version of entropic herding, the ideal output distribution of which is mathematically represented. We further discuss how the complex behavior of the herding algorithm contributes to optimization. We argue that the proposed entropic herding algorithm extends the application of herding to probabilistic modeling. In contrast to original herding, entropic herding can generate a smooth distribution such that both efficient probability density calculation and sample generation become possible. To demonstrate the viability of these arguments in this study, numerical experiments were conducted, including a comparison with other conventional methods, on both synthetic and real data. © 2021, CC BY.

关键词： Dynamical systems

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Improving quantitation accuracy in isobaric-labeling mass spectrometry experiments with spectral library searching and feature-based peptide-spectrum match filter

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Scientific Reports 2023年第1期13卷 1-10页

作者： Kuo, Tzu-Yun Wang, Jen-Hung Huang, Yung-Wen Sung, Ting-Yi Chen, Ching-Tai Department of Biochemical Science and Technology National Taiwan University Taipei 10617 Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Statistical Science Academia Sinica Taipei 11529 Taiwan Institute of Information Science Academia Sinica Taipei 11529 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei 11221 Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan Department of Bioinformatics and Biomedical Engineering Asia University Taichung 41354 Taiwan Center for Precision Health Research Asia University Taichung 41354 Taiwan

Isobaric labeling relative quantitation is one of the dominating proteomic quantitation technologies. Traditional quantitation pipelines for isobaric-labeled mass spectrometry data are based on sequence database searching. In this study, we present a novel quantitation pipeline that integrates sequence database searching, spectral library searching, and a feature-based peptide-spectrum-match (PSM) filter using various spectral features for filtering. The combined database and spectral library searching results in larger quantitation coverage, and the filter removes PSMs with larger quantitation errors, retaining those with higher quantitation accuracy. Quantitation results show that the proposed pipeline can improve the overall quantitation accuracy at the PSM and protein levels. To our knowledge, this is the first study that utilizes spectral library searching to improve isobaric labeling-based quantitation. For users to conveniently perform the proposed pipeline, we have implemented the feature-based filter being executable on both Windows and Linux platforms;its executable files, user manual, and sample data sets are freely available at https://***/comics/Software_*** . Furthermore, with the developed filter, the proposed pipeline is fully compatible with the Trans-Proteomic Pipeline. © 2023, Springer Nature Limited.

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Developing the “Healthcare CEO App” for patients with type 1 diabetes transitioning from adolescence to young adulthood: A mixed-methods study

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Nursing Open 2023年第3期10卷 1755-1766页

作者： Chiang, Yueh-Tao Chang, Chi-Wen Yu, Hsing-Yi Tsay, Pei-Kwei Lo, Fu-Sung Chen, Chi-Wen Lin, Wen-Yen Hsu, Chien-Lung An, Chi Moons, Philip School of Nursing College of Medicine Chang-Gung University Taoyuan Taiwan Division of Pediatric Endocrinology & Genetics Department of Pediatrics Chang-Gung Memorial Hospital Taoyuan Taiwan Department of Nursing Chang-Gung Memorial Hospital Taoyuan Taiwan Department of Public Health and Center of Biostatistics College of Medicine Chang-Gung University Taoyuan Taiwan College of Medicine Chung-Gung University Taoyuan Taiwan College of Nursing National Yang Ming Chiao Tung University Taipei Taiwan Department of Information Management National Taichung University of Science and Technology Taichung Taiwan Department of Information Management Chang-Gung University Taoyuan Taiwan Graduate Institute of Management Chang Gung University Tao-Yuan Taiwan Master of Science Degree Program in Innovation for Smart Medicine Tao-Yuan Taiwan Department of Psychiatry Chang Gung Memorial Hospital at Linkou Tao-Yuan Taiwan Department of Public Health and Primary Care KU Leuven-University of Leuven Leuven Belgium Institute of Health and Care Sciences University of Gothenburg Gothenburg Sweden Department of Paediatrics and Child Health University of Cape Town Cape Town South Africa

Aim: To develop and test a mobile application that supports the disease self-management of adolescents with type 1 diabetes during their transition to early adulthood. Design: A sequential mixed-methods design was employed. Methods: The application content was designed according to previously identified care needs and expectations, followed by application development on the Android operating system. From the outpatient clinic of the Department of Paediatric Endocrinology and Metabolism at a medical centre in northern Taiwan, 35 individuals aged between 16–25 years participated in application testing. Results: The overall median score of the QUIS was 4–5, most of the 25% quartile was 4–5, and all of the 75% quartile was 5, indicating adequate user interaction satisfaction. © 2022 The Authors. Nursing Open published by John Wiley & Sons Ltd.

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Multimodal deep learning framework for image popularity prediction on social media

arXiv

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arXiv 2021年

作者： Abousaleh, Fatma S. Cheng, Wen-Huang Yu, Neng-Hao Tsao, Yu Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Electronics Department of Electronics Engineering National Chiao Tung University Hsinchu30010 Taiwan The College of Design Department of Design National Taiwan University of Science and Technology Taipei10607 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan

Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting image popularity on social media. The popularity of an image can be affected by several factors, such as visual content, aesthetic quality, user, post metadata, and time. Thus, considering all these factors is essential for accurately predicting image popularity. In addition, the efficiency of the predictive model also plays a crucial role. In this study, motivated by multimodal learning, which uses information from various modalities, and the current success of convolutional neural networks (CNNs) in various fields, we propose a deep learning model, called visual-social convolutional neural network (VSCNN), which predicts the popularity of a posted image by incorporating various types of visual and social features into a unified network model. VSCNN first learns to extract high-level representations from the input visual and social features by utilizing two individual CNNs. The outputs of these two networks are then fused into a joint network to estimate the popularity score in the output layer. We assess the performance of the proposed method by conducting extensive experiments on a dataset of approximately 432K images posted on Flickr. The simulation results demonstrate that the proposed VSCNN model significantly outperforms state-of-the-art models, with a relative improvement of greater than 2.33%, 7.59%, and 14.16% in terms of Spearman’s Rho, mean absolute error, and mean squared error, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

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