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IEEE International Conference on Networking, Sensing and control

作者： Shaoteng Fang Yuehao Zhao Kefan Wang Chenyu Tian Qi Kang Department of Control Science and Engineering Tongji University Shanghai China The School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney Australia Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Software Technology Dalian University of Technology Dalian China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

This study successfully applies the spatiotemporal transformer-based model to sea surface height anomaly prediction task. An improved ResNet autoencoder, named SW-GD Autoencoder, is proposed based on Sliced-Wasserstein distance and Gradient Difference loss functions to extract spatial feature information. This autoencoder demonstrates a reduced complexity and training difficulty compared to GAN-based architectures while maintaining high data generation quality. Additionally, the VidHRFormer model is employed for inference, introducing a large receptive field spatial feed-forward network module that enhances information transmission between adjacent patches in the feature map, thereby improving the observability of prediction results. To simplify training, we used a two-stage approach: first training the autoencoder separately, then combining it with VidHRFormer for final training. Compared to state-of-the-art ConvLSTM models, our method yields superior results.

关键词： Training Adaptation models Accuracy Predictive models Transformers Feature extraction Spatiotemporal phenomena Sensors Sea surface temperature Sea level

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Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network

arXiv

引用

arXiv 2024年

作者： Liu, Houze Li, Iris Liang, Yaxin Sun, Dan Yang, Yining Yang, Haowei New York University Department Computer Science and Engineering New York United States New York University Graduate School of Art & Science New York United States University of Southern California Viterbi School of Engineering Los Angeles United States Washington University Department of Electrical and Systems Engineering St. Louis United States Carnegie Mellon University School of Computer Science Pittsburgh United States University of Houston Cullen College Of Engineering Houston United States

Neural networks with relatively shallow layers and simple structures may have limited ability in accurately identifying pneumonia. In addition, deep neural networks also have a large demand for computing resources, which may cause convolutional neural networks to be unable to be implemented on terminals. Therefore, this paper will carry out the optimal classification of convolutional neural networks. Firstly, according to the characteristics of pneumonia images, AlexNet and InceptionV3 were selected to obtain better image recognition results. Combining the features of medical images, the forward neural network with deeper and more complex structure is learned. Finally, knowledge extraction technology is used to extract the obtained data into the AlexNet model to achieve the purpose of improving computing efficiency and reducing computing costs. The results showed that the prediction accuracy, specificity, and sensitivity of the trained AlexNet model increased by 4.25 percentage points, 7.85 percentage points, and 2.32 percentage points respectively. The graphics processing usage has decreased by 51% compared to the InceptionV3 mode. Copyright © 2024, The Authors. All rights reserved.

关键词： Image classification

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Morphology Evolution of Β-Phase in Al-Mg-Si Alloys During Aging Treatment

SSRN

引用

SSRN 2023年

作者： Ahmed, Abrar Uttarasak, Kanokwan Tsuchiya, Taiki Lee, Shouwon Nishimura, Katsuhiko Nunomura, Norio Shimizu, Kazuyuki Hirayama, Kyosuke Toda, Hiroyuki Yamaguchi, Masatake Tsuru, Tomohito Watanabe, Shoma Matsuda, Kenji Ikeno, Susumu Graduate School of Science and Engineering for Education University of Toyama Toyama930-8555 Japan Graduate School of Science and Engineering for Research University of Toyama Toyama930-8555 Japan Faculty of Science and Engineering Department of Materials Science and Engineering Kyoto University Kyoto606-8501 Japan Department of Mechanical Engineering Kyushu University Fukuoka819-0395 Japan Center for Computational Science and e-Systems Japan Atomic Energy Agency Ibaraki Tokai319-1195 Japan Nuclear Science and Engineering Center Japan Atomic Energy Agency Ibaraki Tokai319-1195 Japan

This study aims to clarify the growth process of the β-phase in Al-Mg-Si alloys from the point of view of morphology evolution. For this research, the β-phase orientation relationship, shape, growth process, misfit value, and interfacial condition between the β-phase and Al matrix were investigated using high-resolution transmission electron microscopy (HR-TEM), focus ion beam (FIB), and optical microscope (OM). Results include the identification of {111}β facets at the edges of the β-phase, as well as the proposal of two new three-dimensional shapes for the β-phase. We purposed the morphology evolution during the growth process of Mg2Si crystal and calculated the misfit to understand the unstable (111)β facet has a higher misfit value as compared to the (001)β and (011)β facets. Our observations provide how they influence the behavior of Mg2Si crystals, which is crucial for predicting the microstructural evolution of the Al-Mg-Si alloys and for designing materials with desired properties. © 2023, The Authors. All rights reserved.

关键词： High resolution transmission electron microscopy

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Ferroelectric transistors based on shear-transformation-mediated rhombohedral-stacked molybdenum disulfide

引用

Nature Electronics 2024年第1期7卷 29-38页

作者： Yang, Tilo H. Liang, Bor-Wei Hu, Hsiang-Chi Chen, Fu-Xiang Ho, Sheng-Zhu Chang, Wen-Hao Yang, Liu Lo, Han-Chieh Kuo, Tzu-Hao Chen, Jyun-Hong Lin, Po-Yen Simbulan, Kristan Bryan Luo, Zhao-Feng Chang, Alice Chinghsuan Kuo, Yi-Hao Ku, Yu-Seng Chen, Yi-Cheng Huang, You-Jia Chang, Yu-Chen Chiang, Yu-Fan Lu, Ting-Hua Lee, Min-Hung Li, Kai-Shin Wu, Menghao Chen, Yi-Chun Lin, Chun-Liang Lan, Yann-Wen Department of Physics National Taiwan Normal University Taipei Taiwan Taiwan Semiconductor Research Institute National Applied Research Laboratories Hsinchu Taiwan Department of Electrophysics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physics National Cheng Kung University Tainan Taiwan School of Physics Huazhong University of Science and Technology Wuhan China Institute of Cellular and Organismic Biology Academia Sinica Taipei Taiwan Department of Mathematics and Physics University of Santo Tomas Manila Philippines Program for Semiconductor Devices Materials and Hetero-integration Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Hsinchu Taiwan Department of Physics National Taiwan University Taipei Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

To develop low-power, non-volatile computing-in-memory device using ferroelectric transistor technologies, ferroelectric channel materials with scaled thicknesses are required. Two-dimensional semiconductors, such as molybdenum disulfide (MoS2), equipped with sliding ferroelectricity could provide an answer. However, achieving switchable electric polarization in epitaxial MoS2 remains challenging due to the absence of mobile domain boundaries. Here we show that polarity-switchable epitaxial rhombohedral-stacked (3R) MoS2 can be used as a ferroelectric channel in ferroelectric memory transistors. We show that a shear transformation can spontaneously occur in 3R MoS2 epilayers, producing heterostructures with stable ferroelectric domains embedded in a highly dislocated and unstable non-ferroelectric matrix. This diffusionless phase transformation process produces mobile screw dislocations that enable collective polarity control of 3R MoS2 via an electric field. Polarization–electric-field measurements reveal a switching field of 0.036 V nm−1 for shear-transformed 3R MoS2. Our sliding ferroelectric transistors are non-volatile memory units with thicknesses of only two atomic layers and exhibit an average memory window of 7 V with an applied voltage of 10 V, retention times greater than 104 seconds and endurance greater than 104 cycles. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Molybdenum disulfide

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Multi-objective Optimization of A CCHP System Model Integrated with P2G for Decarbonization 6

Multi-objective Optimization of A CCHP System Model Integrat...

引用

6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Wei, Pengyu Bamisile, Olusola Cai, Dongsheng Li, Jian Adun, Humphrey Huang, Qi Chengdu University of Technology School of Nuclear Technology and Automation Engineering Chengdu China University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control Chengdu China Cyprus International University KKTC Energy Systems Engineering Department Mersin10 Turkey

ISBN: (纸本)9798350347159

To realize the dual carbon policy, the goal of energy saving, and emission reduction, it is important to develop ways to better promote the low carbon economic operation of energy systems. Therefore, this research proposes an optimal operation strategy considering the electric-gas-cooling-heat demand response. Considering the demand response of each participant, an integrated energy system model with photovoltaic, wind energy, and traditional grid as energy supply. Also, electric energy, natural gas, cooling, and heating subsystems with co-production are established. With minimizing the overall system operation cost and optimizing environmental protection, the improved particle swarm optimization algorithm is used to solve the multi-constrained objective optimization problem. Finally, the optimized model is tested. The results from this study show that the energy system under cogeneration can find a balance between economy and environmental friendliness, and provide a reference for the subsequent energy supply configuration. © 2022 IEEE.

关键词： Environmental protection

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Hand disinfection detection using 2D image footage

Hand disinfection detection using 2D image footage

引用

2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Figueroa, David Nishio, Shuichi Yamazaki, Ryuji Ohta, Etsuko Hamaguchi, Shigeto Utsumi, Momoe Osaka University Graduate School of Engineering Science Toyonaka Japan Osaka University Institute for Open and Transdisciplinary Research Initiatives Toyonaka Japan Osaka University Hospital Department of Infection Prevention and Control Suita Japan Osaka University School of MedicineDivision of Fostering Required Medical Human Resources Center for Infectious Disease Education and Research Suita Japan Osaka University Hospital Division of Infection Control and Prevention Suita Japan Osaka University Graduate School of Medicine Department of Health Science Suita Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Inside medical environments, hand hygiene is very important to avoid healthcare-associated infections. The traditional method to measure hand sanitization guidelines consists of having an external observer watching the medical personnel, which can introduce bias and can only make the observations for a fixed amount of time. Some alternatives have been proposed, using different sensors and machine learning to replace the role of the observer, placing many sensors, or assuming that hand hygiene occurs in a fixed place, like a gel dispenser. In this paper, we report on our approach to detection and tracking of medical staff, as well as measuring their hand disinfection compliance using minimal equipment, obtaining only 2D images from one camera to avoid cluttering hospital space or changing the personnel's regular behavior. The procedure is based on detecting a person in each frame, analyzing different zones with different sizes inside the same image to optimize the detection and extract as much data as possible;then tracking each recognized person and finally recognizing the hand sanitization by the motion pattern of the wrists, achieving promising results for this task in this setup. © 2022 IEEE.

关键词： Disinfection

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Updates of the surface detector array of the TAx4 experiment 38

Updates of the surface detector array of the TAx4 experiment

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Kido, Eiji Abbasi, R.U. Abe, Y. Abu-Zayyad, T. Allen, M. Arai, Y. Arimura, R. Barcikowski, E. Belz, J.W. Bergman, D.R. Blake, S.A. Buckland, I. Cheon, B.G. Chikawa, M. Fedynitch, A. Fujii, T. Fujisue, K. Fujita, K. Fujiwara, R. Fukushima, M. Furlich, G. Gerber, Z. Globus, N. Hanlon, W. Hayashida, N. He, H. Hibi, R. Hibino, K. Higuchi, R. Honda, K. Ikeda, D. Inoue, N. Ishii, T. Ito, H. Ivanov, D. Iwasaki, A. Jeong, H.M. Jeong, S. Jui, C.C.H. Kadota, K. Kakimoto, F. Kalashev, O. Kasahara, K. Kasami, S. Kawakami, S. Kawata, K. Kharuk, I. Kido, E. Kim, H.B. Kim, J.H. Kim, J.H. Kim, S.W. Kimura, Y. Komae, I. Komori, K. Kusumori, Y. Kuznetsov, M. Kwon, Y.J. Lee, K.H. Lee, M.J. Lubsandorzhiev, B. Lundquist, J.P. Matsuyama, T. Matthews, J.A. Matthews, J.N. Mayta, R. Miyashita, K. Mizuno, K. Mori, M. Murakami, M. Myers, I. Nagataki, S. Nakai, K. Nakamura, T. Nishio, E. Nonaka, T. Ogio, S. Ohoka, H. Okazaki, N. Oku, Y. Okuda, T. Omura, Y. Onishi, M. Ono, M. Oshima, A. Oshima, H. Ozawa, S. Park, I.H. Park, K.Y. Potts, M. Pshirkov, M.S. Remington, J. Rodriguez, D.C. Rott, C. Rubtsov, G.I. Ryu, D. Sagawa, H. Saito, R. Sakaki, N. Sako, T. Sakurai, N. Sato, D. Sato, K. Sato, S. Sekino, K. Shah, P.D. Shibata, N. Shibata, T. Shikita, J. Shimodaira, H. Shin, B.K. Shin, H.S. Shinto, D. Smith, J.D. Sokolsky, P. Stokes, B.T. Stroman, T.A. Takagi, Y. Takahashi, K. Takamura, M. Takeda, M. Takeishi, R. Taketa, A. Takita, M. Tameda, Y. Tanaka, K. Tanaka, M. Thomas, S.B. Thomson, G.B. Tinyakov, P. Tkachev, I. Tokuno, H. Tomida, T. Troitsky, S. Tsuda, R. Tsunesada, Y. Udo, S. Urban, F. Vaiman, I.A. Warren, D. Wong, T. Yamazaki, K. Yashiro, K. Yoshida, F. Zhezher, Y. Zundel, Z. Department of Physics Loyola University Chicago ChicagoIL60660 United States Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano380-8554 Japan High Energy Astrophysics Institute Department of Physics and Astronomy University of Utah Salt Lake CityUT84112-0830 United States Graduate School of Science Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Department of Physics The Research Institute of Natural Science Hanyang University Seongdong-gu Seoul426-791 Korea Republic of Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba277-8582 Japan Institute of Physics Academia Sinica Taipei City115201 Taiwan Nambu Yoichiro Institute of Theoretical and Experimental Physics Osaka Metropolitan University Sugimoto Sumiyoshi Osaka558-8585 Japan Astrophysical Big Bang Laboratory RIKEN Wako Saitama351-0198 Japan Faculty of Engineering Kanagawa University Yokohama Kanagawa221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Kofu400-8511 Japan The Graduate School of Science and Engineering Saitama University Saitama Saitama338-8570 Japan Department of Physics SungKyunKwan University Jang-an-gu Suwon16419 Korea Republic of Department of Physics Tokyo City University Setagaya-ku Tokyo158-8557 Japan Institute for Nuclear Research The Russian Academy of Sciences Moscow117312 Russia Faculty of Systems Engineering and Science Shibaura Institute of Technology Minato-ku Tokyo337-8570 Japan Graduate School of Engineering Osaka Electro-Communication University Neyagawa-shi Osaka572-8530 Japan Service de Physique Théorique Université Libre de Bruxelles Brussels1050 Belgium Department of Physics Yonsei University Seodaemun-gu Seoul120-749 Korea Republic of Center for Astrophysics and Cosmology University of Nova Gorica Nova Gorica5297 Slovenia Faculty of Science Kochi University Kochi Kochi7

The TAx4 experiment plans to realize an Ultra High Energy Cosmic Rays (UHECR) detection area four times larger than that of the TA experiment. TAx4 will include five hundreds new surface detectors (SD) spaced at 2.08 km and two new fluorescence detectors (FD), which provides hybrid observation of UHECRs. We deployed 257 SDs in 2019 and completed building 2 FD stations in 2020, all operating stably. The data acquisition of the SDs is made via six communication towers, and inter-tower triggers have been recently implemented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Computer-assisted proofs for finding the monodromy of Picard-Fuchs differential equations for a family of K3 toric hypersurfaces

arXiv

引用

arXiv 2025年

作者： Ishige, Toshimasa Takayasu, Akitoshi Department of Mathematics and Informatics Graduate School of Science Chiba University Chiba263-8522 Japan Institute of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan

In this paper, we present a numerical method for rigorously finding the monodromy of linear differential equations. Beginning at a base point where certain particular solutions are explicitly given by series expansions, we first compute the value of fundamental system of solutions using interval arithmetic to rigorously control truncation and rounding errors. The solutions are then analytically continued along a prescribed contour encircling the singular points of the differential equation via a rigorous integrator. From these computations, the monodromy matrices are derived, generating the monodromy group of the differential equation. This method establishes a mathematically rigorous framework for addressing the monodromy problem in differential equations. For a notable example, we apply our computer-assisted proof method to resolve the monodromy problem for a Picard–Fuchs differential equation associated with a family of K3 toric hypersurfaces. Copyright © 2025, The Authors. All rights reserved.

关键词： Numerical methods

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Consistent and Asymptotically Efficient Localization from Range-Difference Measurements

arXiv

引用

arXiv 2023年

作者： Zeng, Guangyang Mu, Biqiang Shi, Ling Chen, Jiming Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen China The Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee the asymptotic identifiability of the model and show the consistency and asymptotic normality of the maximum likelihood (ML) estimator. Then, we devise an estimator that owns the same asymptotic property as the ML one. Specifically, we prove that the negative log-likelihood function converges to a function, which has a unique minimum and positive definite Hessian at the true source's position. Hence, it is promising to execute local iterations, e.g., the Gauss-Newton (GN) algorithm, following a consistent estimate. The main issue involved is obtaining a preliminary consistent estimate. To this aim, we construct a linear least-squares problem via algebraic operation and constraint relaxation and obtain a closed-form solution. We then focus on deriving and eliminating the bias of the linear least-squares estimator, which yields an asymptotically unbiased (thus consistent) estimate. Noting that the bias is a function of the noise variance, we further devise a consistent noise variance estimator that involves 3-order polynomial rooting. Based on the preliminary consistent location estimate, a one-step GN iteration suffices to achieve the same asymptotic property as the ML estimator. Simulation results demonstrate the superiority of our proposed algorithm in the large sample case. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Mathematical Simulation of Linear Ubiquitination in T Cell Receptor-Mediated NF-κB Activation Pathway

Mathematical Simulation of Linear Ubiquitination in T Cell R...

引用

International Symposium on Fusion of Mathematics and Biology, 2020

作者： Oikawa, Daisuke Hatanaka, Naoya Suzuki, Takashi Tokunaga, Fuminori Department of Pathobiochemistry Graduate School of Medicine Osaka City University Osaka Japan Division of Mathematical Science Department of Systems Innovation Graduate School of Engineering Science Osaka University Toyonaka Japan Center for Mathematical Modeling and Data Science Osaka University Toyonaka Japan

ISBN: (纸本)9789811648656

The linear ubiquitin chain assembly complex (LUBAC), composed of the HOIP, HOIL-1L, and SHARPIN subunits, activates the canonical nuclear factor-κB (NF-κB) pathway through the Met1 (M1)-linked linear ubiquitination activity. On the course of the T cell receptor (TCR)-mediated NF-κB activation pathway, LUBAC transiently associates with and linearly ubiquitinates the CARMA1-BCL10-MALT1 (CBM) complex. In contrast, the linear ubiquitination of NEMO, a substrate of the TNF-α-induced NF-κB activation pathway, was limited in the TCR pathway. A linear ubiquitin-specific deubiquitinase (DUB), OTULIN, plays a major role in downregulating LUBAC-mediated TCR signaling. Mathematical modeling indicated that linear ubiquitination of the CBM complex accelerates the activation of IκB kinase (IKK), as compared with the activity induced by linear ubiquitination of NEMO alone. Moreover, simulations of the sequential linear ubiquitination of the CBM complex suggested that the allosteric regulation of linear (de)ubiquitination of CBM subunits is controlled by the ubiquitin-linkage lengths. Thus, unlike the TNF-α-induced NF-κB activation pathway, the TCR-mediated NF-κB activation in T cells has a characteristic mechanism to induce LUBAC-mediated NF-κB activation. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Chemical activation

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