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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Kodai Kitagawa Mitsumasa Hida Chikamune Wada Hiroaki Yamamoto Department of Industrial Systems Engineering National Institute of Technology Hachinohe College Hachinohe Japan Department of Rehabilitation Osaka Kawasaki Rehabilitation University Kaizuka Japan Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Physical Therapy Fukuoka Tenjin Medical Rehabilitation Academy Fukuoka Japan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

Vertebral force during manual lifting causes lower back pain (LBP) among workers in various occupational fields. Continuous monitoring of vertebral force is required for preventing LBP. Vertebral force can be measured directly by implant devices; however, these implant devices are difficult to install on general workers. Non-invasive technologies such as an optical motion capture system could estimate vertebral force, however, special measurement devices are necessary. The objective of this study is to propose non-invasive measurement method for vertebral force using ordinary digital camera. The proposed method predicts vertebral forces by machine learning and sagittal plane posture during manual lifting. The proposed method predicted vertebral forces for 48 trials manual lifting via leave-one-out-cross-validation. Training and testing of the proposed method used OrthoLoad database that included sagittal 2D images and vertebral force obtained from implant device. The results showed that the proposed method using model tree algorithm could predict vertebral force by greater than 0.7 correlation with actual values. These results indicate possibility that the proposed method can be used for vertebral force assessments using ordinary devices.

关键词： Training Force measurement Force Manuals Machine learning Implants Optical variables measurement Predictive models Monitoring Testing

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Optical coherent dot-product chip for sophisticated deep learning regression

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Light(science & Applications) 2021年第12期10卷 2330-2341页

作者： Shaofu Xu Jing Wang Haowen Shu Zhike Zhang Sicheng Yi Bowen Bai Xingjun Wang Jianguo Liu Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong University800 Dongchuan RoadShanghai 200240China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Institution of Semiconductors Chinese Academy of SciencesBeijing 100083China

Optical implementations of neural networks(ONNs)herald the next-generation high-speed and energy-efficient deep learning computing by harnessing the technical advantages of large bandwidth and high parallelism of ***,due to the problems of the incomplete numerical domain,limited hardware scale,or inadequate numerical accuracy,the majority of existing ONNs were studied for basic classification *** that regression is a fundamental form of deep learning and accounts for a large part of current artificial intelligence applications,it is necessary to master deep learning regression for further development and deployment of ***,we demonstrate a silicon-based optical coherent dot-product chip(OCDC)capable of completing deep learning regression *** OCDC adopts optical fields to carry out operations in the complete real-value domain instead of in only the positive *** reusing,a single chip conducts matrix multiplications and convolutions in neural networks of any ***,hardware deviations are compensated via in-situ backpropagation control provided the simplicity of chip ***,the OCDC meets the requirements for sophisticated regression tasks and we successfully demonstrate a representative neural network,the AUTOMAP(a cutting-edge neural network model for image reconstruction).The quality of reconstructed images by the OCDC and a 32-bit digital computer is *** the best of our knowledge,there is no precedent of performing such state-of-the-art regression tasks on ONN *** is anticipated that the OCDC can promote the novel accomplishment of ONNs in modern AI applications including autonomous driving,natural language processing,and scientific study.

关键词： neural hardware coherent

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Detectability of Resistive Open Defects with Analog Relaxation Oscillators Under Unit-to-Unit Variations of Dies

Detectability of Resistive Open Defects with Analog Relaxati...

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IEEE International Conference on 3D System Integration, 3DIC

作者： Yuya Yamahashi Yuto Ohtera Hiroyuki Yotsuyanagi Shyue-Kung Lu Masaki Hashizume Graduate School of Sciences and Technology for Innovation Tokushima University Tokushima Japan Graduate School of Advanced Technology and Science Tokushima University Tokushima Japan Graduate School of Technology Industrial and Sciences Tokushima University Tokushima Japan Department of Electrical Engineering National Taiwan University to Science and Technology Taipei Taiwan Tokushima Study Center Open University of Japan Tokushima Japan

ISBN: (数字)9798331516505

ISBN: (纸本)9798331516512

We designed a built-in test circuit to detect resistive open defects at interconnects between dies in 3D stacked ICs using relaxation oscillators made of only analog circuit elements. We also designed a test circuit by which process variations of the oscillators could be eliminated in tests. We examined the detectability of such resistive open defects by the test method based on the test circuit in a 3D stacked IC made of dies whose process variations were not identical by circuit simulations. The results show that resistive open defects of 7.0 and above can be detected by the test circuit.

关键词： Resistance Three-dimensional displays Circuit simulation Integrated circuit interconnections System integration Analog circuits Product design Quality assessment Oscillators Testing

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An Effective Strategy for Improving the Performance of Electrodeposited Fe-W Alloy Plating: Tailoring Microstructure by Graphene Incorporation

SSRN

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SSRN 2023年

作者： Shinohara, Yu Park, Jae-Hyeok Hagio, Takeshi Kim, Jae-Il Lee, Woo-Young Umehara, Noritsugu Ichino, Ryoichi Department of Chemical Systems Engineering Graduate School of Engineering Nagoya University Nagoya464-8603 Japan Institute of Materials Innovation Institutes of Innovation for Future Society Nagoya University Nagoya464-8601 Japan Department of Micro-Nano Mechanical Science and Engineering Graduate School of Engineering Nagoya University Nagoya464-8603 Japan Gwangju61007 Korea Republic of

Despite the excellent performance of hard Cr plating using hexavalent chromium (Cr6+), its use is being restricted owing to recent environmental regulations. Electrodeposited Fe-W alloy is considered a possible alternative, but its high coefficient of friction (COF), high wear rate owing to tribo-oxidation, and high corrosion rate hinder its practical application. In this study, we attempted to solve these problems by modifying the microstructure of Fe-W alloy by incorporating 2D-structured graphene. The effect of graphene incorporation on the structure of the Fe-W alloy and its properties, especially microhardness, wear, and corrosion resistance, were investigated. The results showed the graphene effectively modified the columnar structure of the Fe-W alloy by inhibiting the vertical growth of clusters during electrodeposition, leading to fragmentation of the vertical cluster boundaries. This improved the hardness by as much as 17% up to 9.1 GPa, and the corrosion resistance by changing the corrosion mechanism from localized corrosion to uniform corrosion. In addition, the graphene reduced the COF and wear rate by reducing the Fe2O3 formed by tribo-oxidation to a lower oxidation state. The structural modification of the plating by graphene incorporation thus provides an effective solution to improving the performance of Fe-W alloys. © 2023, The Authors. All rights reserved.

关键词： Corrosion resistance

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Molecular insight of dissolved organic matter and chlorinated disinfection by-products in reclaimed water during chlorination with permanganate preoxidation

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Chemosphere 2024年 349卷 140807页

作者： Hu, Wei Niu, Xi-Zhi Chen, Huan Ye, Bei Liang, Jun-Kun Guan, Yun-Tao Wu, Qian-Yuan Environmental Protection Key Laboratory of Microorganism Application and Risk Control Guangdong Provincial Engineering Research Center for Urban Water Recycling and Environmental Safety Institute of Environment and Ecology Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Environmental Engineering and Science Program Department of Chemical and Environmental Engineering University of Cincinnati CincinnatiOH45221 United States Department of Environmental Engineering and Earth Science Clemson University SC29634 United States

Permanganate is a common preoxidant applied in water treatment to remove organic pollutants and to reduce the formation of disinfection by-products. However, the effect of permanganate preoxidation on the transformation of dissolved effluent organic matter (dEfOM) and on the formation of unknown chlorinated disinfection by-products (Cl-DBPs) during chlorination remains unknown at molecular level. In this work, the molecular changes of dEfOM during permanganate preoxidation and subsequent chlorination were characterized using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Permanganate preoxidation was found to decrease the DBE (double bond equivalent) and AImod (modified aromaticity index) of the dEfOM. The identity and fate of over 400 unknown Cl-DBPs during KMnO4-chlorine treatment were investigated. Most Cl-DBPs and the precursors were found to be highly unsaturated aliphatic and phenolic compounds. The Cl-DBPs precursors with lower H/C and lower O/C were preferentially removed by permanganate preoxidation. Additionally, permanganate preoxidation decreased the number of unknown Cl-DBPs by 30% and intensity of unknown Cl-DBPs by 25%. One-chlorine-containing DBPs were the major Cl-DBPs and had more CH2 groups and higher DBEw than Cl-DBPs containing two and three chlorine atoms. 60% of the Cl-DBPs formation was attributed to substitution reactions (i.e., +Cl–H, +2Cl–2H, +3Cl–3H, +ClO–H, +Cl2O3–2H). This work provides detailed molecular level information on the efficacy of permanganate preoxidation on the control of overall Cl-DBPs formation during chlorination. © 2023 Elsevier Ltd

关键词： Chlorination

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Effective Two-Stage Double Auction for Dynamic Resource Trading in Edge Networks via Overbooking

arXiv

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arXiv 2025年

作者： Wu, Sicheng Liwang, Minghui Wang, Deqing Wang, Xianbin Wu, Chao Tang, Junyi Li, Li Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China The Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China The Department of Electrical and Computer Engineering Western University ON Canada The School of Public Affairs Zhejiang University Hangzhou310027 China School of Information Science and Engineering Lanzhou University Lanzhou China The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

To facilitate responsive and cost-effective computing resource scheduling and service delivery over edge-assisted mobile networks, this paper investigates a novel two-stage double auction methodology via utilizing an interesting idea of resource overbooking to overcome dynamic and uncertain nature from edge servers (sellers) and demand from mobile devices (as buyers). The proposed auction integrates multiple essential factors such as social welfare maximization and decision-making latency (e.g., the time for determining winning seller-buyer pairs) reduction, by introducing a stagewise strategy: an overbooking-driven pre-double auction (OPDAuction) for determining long-term cooperations between sellers and buyers before practical resource transactions as Stage I, and a real-time backup double auction (RBDAuction) for handling residual resource demands during actual transactions. In particular, by applying a proper overbooking rate, OPDAuction helps with facilitating trading contracts between appropriate sellers and buyers as guidance for future transactions, by allowing the booked resources to exceed supply. Then, since pre-auctions may cause risks, our RBDAuction adjusts to real-time market changes, further enhancing the overall social welfare. More importantly, we offer an interesting view to show that our proposed two-stage auction can support significant design properties such as truthfulness, individual rationality, and budget balance. Through extensive experiments, we demonstrate good performance in social welfare, time efficiency, and computational scalability, outstripping conventional methods in dynamic edge computing settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Budget control

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Effects of atmospheric transparency on Telescope Array air shower analysis 38

Effects of atmospheric transparency on Telescope Array air s...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Mizuno, K. Tomida, T. Yamazaki, K. 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. Academic Assembly School of Science and Technology Institute of Engineering Shinshu University Nagano Nagano Japan Mathematical and Physical Sciences Science and Engineering Chubu University Aichi Kasugai Japan 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 Chiba Kashiwa277-8582 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 Kanagawa Yokohama221-8686 Japan Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Kofu Yamanashi400-8511 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 Brussels Belgium Department of Physics

The Telescope Array (TA) experiment continues to observe Ultra High Energy Cosmic Rays (UHECRs) both with its original TA detectors as well as with the new TAx4 expansion detectors. These observations employ Fluorescence Detectors (FDs) to capture the air shower induced by the primary UHECRs. The FD observes fluorescence light emitted from atmospheric nitrogen molecules excited by air shower particles. Observation of the FD extends over tens of kilometers, and the fluorescence light is attenuated by scattering from atmospheric molecules and aerosols during the propagation process. Seasonal dependence was found when evaluating the attenuation of fluorescence by aerosols. We will report on the effects of this seasonal dependence on TA air shower analysis. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Fluorescence

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Preference Aligned Diffusion Planner for Quadrupedal Locomotion control

arXiv

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arXiv 2024年

作者： Yuan, Xinyi Shang, Zhiwei Wang, Zifan Wang, Chenkai Shan, Zhao Zhu, Meixin Bai, Chenjia Li, Xuelong Wan, Weiwei Harada, Kensuke Graduate School of Engineering Science Osaka University Japan Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology Guangzhou China China Telecom China Department of Statistics and Data Science Southern University of Science and Technology China School of Transportation Southeast University China

Diffusion models demonstrate superior performance in capturing complex distributions from large-scale datasets, providing a promising solution for quadrupedal locomotion control. However, the robustness of the diffusion planner is inherently dependent on the diversity of the pre-collected datasets. To mitigate this issue, we propose a two-stage learning framework to enhance the capability of the diffusion planner under limited dataset (reward-agnostic). Through the offline stage, the diffusion planner learns the joint distribution of state-action sequences from expert datasets without using reward labels. Subsequently, we perform the online interaction in the simulation environment based on the trained offline planner, which significantly diversified the original behavior and thus improves the robustness. Specifically, we propose a novel weak preference labeling method without the ground-truth reward or human preferences. The proposed method exhibits superior stability and velocity tracking accuracy in pacing, trotting, and bounding gait under different speeds and can perform a zero-shot transfer to the real Unitree Go1 robots. The project website for this paper is at https://***. io/preference-aligned-diffusion-legged/. Copyright © 2024, The Authors. All rights reserved.

关键词： Robustness (control systems)

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Distributed online generalized Nash Equilibrium learning in multi-cluster games: A delay-tolerant algorithm

arXiv

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arXiv 2024年

作者： Liu, Bingqian Wen, Guanghui Fang, Xiao Huang, Tingwen Chen, Guanrong Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China Science Program Texas A&M University at Qatar Doha Qatar Department of Electrical Engineering City University of Hong Kong Hong Kong

This paper addresses the problem of distributed online generalized Nash equilibrium (GNE) learning for multicluster games with delayed feedback information. Specifically, each agent in the game is assumed to be informed a sequence of local cost functions and constraint functions, which are known to the agent with time-varying delays subsequent to decision-making at each round. The objective of each agent within a cluster is to collaboratively optimize the cluster's cost function, subject to time-varying coupled inequality constraints and local feasible set constraints over time. Additionally, it is assumed that each agent is required to estimate the decisions of all other agents through interactions with its neighbors, rather than directly accessing the decisions of all agents, i.e., each agent needs to make decision under partial-decision information. To solve such a challenging problem, a novel distributed online delay-tolerant GNE learning algorithm is developed based upon the primaldual algorithm with an aggregation gradient mechanism. The system-wise regret and the constraint violation are formulated to measure the performance of the algorithm, demonstrating sublinear growth with respect to time under certain conditions. Finally, numerical results are presented to verify the effectiveness of the proposed algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Learning algorithms

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PupilRec: Leveraging Pupil Morphology for Recommending on Smartphones

PupilRec: Leveraging Pupil Morphology for Recommending on Sm...

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作者： Shen, Xiangyu Jiang, Hongbo Liu, Daibo Yang, Kehua Deng, Feiyang Lui, John C. S. Liu, Jiangchuan Dustdar, Schahram Luo, Jun Hunan University College of Computer Science and Electronic Engineering Hunan Changsha410082 China The City University of Hong Kong School of Graduate Studies Hong Kong The Chinese University of Hong Kong Computer Science and Engineering Department Hong Kong Simon Fraser University School of Computing Science BurnabyBCV5A 1S6 Canada Vienna University of Technology Distributed Systems Group Vienna1040 Austria Nanyang Technological University School of Computer Engineering 639798 Singapore

As mobile shopping has gradually become the mainstream shopping mode, recommendation systems are gaining an increasingly wide adoption. Existing recommendation systems are mainly based on explicit and implicit user behaviors. However, these user behaviors may not directly indicate users' inner feelings, causing erroneous user preference estimation and thus leading to inaccurate recommendations. Inspired by our key observation on the correlation between pupil size and users' inner feelings, we consider using the change of pupil size when browsing to model users' preferences, so as to achieve targeted recommendations. To this end, we propose PupilRec as a computer-vision-based recommendation framework involving a mobile terminal and a server side. On the mobile terminal, PupilRec collects users' pupil size change information through the front camera of smartphones;it then preprocesses the raw pupil size data before transmitting them to the server. On the server side, PupilRec utilizes the Tsfresh package and Random Forest algorithm to figure out the key time-series features directly implying user preferences. PupilRec then trains a neural network to fit a user preference model. Using this model, PupilRec predicts user preference to obtain a user-product matrix and further simplifies it by singular value decomposition. Finally, the real-time recommendation is achieved by a collaborative filtering module that retrieves recommended contents to users smartphones. We prototype PupilRec and conduct both experiments and field studies to comprehensively evaluate the effectiveness of PupilRec by recruiting 67 volunteers. The overall results show that PupilRec can accurately estimate users' preference and can recommend products users interested in. © 2014 IEEE.

关键词： Smartphones

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