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10th International Conference on Leading Edge Manufacturing Technologies in 21st Century, LEM 2021

作者： Bakier, Mohammed A.Y.A. Matsumoto, Ryuunosuke Fuchiwaki, Masaki Khajornrungruang, Panart Suzuki, Keisuke Department of Mechanical Information Science and Technology Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 820-8502 Japan Department of Mathematics Faculty of Science Assiut University Egypt

Pattern effect as dishing and erosion on Cu-CMP process become a serious problem to fabricate multilevel interconnect in advanced ULSI devices. In the current study, planarization models using patterned wafer and ANSYS software are suggested to make precise predictions of the post-CMP surface height to support optimize the layout design. The slurry flow effect on the copper body has been investigated and the removed mass character is monitored through the stress distribution at the solid domain. By determination of the removal regions by the calculation, we can avoid the dishing and erosion areas in the patterned area from the post-CMP process. © 2021 The Japan Society of Mechanical Engineers.

关键词： Silicon wafers

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Adopt digital micromirror devise (DMD) for wavefront correction and wavefront sensing in adaptive optical system

Adopt digital micromirror devise (DMD) for wavefront correct...

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Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace systems 2024

作者： Liu, Hong-Je Lee, Shu-Sheng Lee, Hsiang-Chieh Huang, Jiun-Woei Lee, Chih-Kung Institute of Applied Mechanics National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei106 Taiwan Department of Systems Engineering & Naval Architecture National Taiwan Ocean University No.2 Bei-ning Rd. Keelung City202 Taiwan Institute of Photonics & Optoelectronics National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei106 Taiwan Depart. of Electrical Engineering National Taiwan University Taiwan Department of Engineering Science & Ocean Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei106 Taiwan Graduate School of Advanced Technology National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei106 Taiwan

ISBN: (数字)9781510672055

ISBN: (纸本)9781510672048

This study introduces an advanced Adaptive Optics (AO) technique employing a Digital Micromirror Device (DMD) for effective wavefront correction. The innovation lies in utilizing the DMD as a Spatial Light Modulator (SLM), marking a departure from traditional methods that mainly used Liquid Crystal on Silicon (LCoS) for this purpose. With its high resolution (912×1440 pixels) and ultra-fast response, the DMD enhances the system's efficiency in correcting optical aberrations. By applying the Lee Hologram Method within off-axis binary holography, our approach generates inverse wavefronts to counteract environmental distortions, thereby improving image clarity. The integration of a DMD-assisted Lateral Shearing Interferometer, which adjusts the incident light angle through wavefront modulation, accelerates optical path difference (OPD) measurement. Implementing a Five-Step Phase Shifted Method for both X and Y directional fringe patterns facilitates rapid phase retrieval. This process, crucial for reconstructing and correcting wavefront aberrations, leverages the differential phase information from the Lateral Shearing Interferometer. Our experimental results affirm the system's effectiveness in not only rectifying wavefront distortions but also in showcasing the enhanced performance capabilities brought forth by the DMD-assisted Lateral Shearing Interferometer. © 2024 SPIE.

关键词： Adaptive optics

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Ion irradiation induced crystalline disorder accelerates interfacial phonon conversion and reduces thermal boundary resistance

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Physical Review B 2024年第16期109卷 165421-165421页

作者： Thomas W. Pfeifer Henry Aller Eric R. Hoglund Ethan A. Scott John A. Tomko Habib Ahmad Alan Doolittle Ashutosh Giri Khalid Hattar Alan J. H. McGaughey Patrick E. Hopkins Department of Mechanical and Aerospace Engineering University of Virginia Charlottesville Virginia 22904 USA Department of Mechanical Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Department of Materials Science and Engineering University of Virginia Charlottesville Virginia 22904 USA Sandia National Laboratories Albuquerque New Mexico 87185 USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia 30332 USA Center for Advanced Electronics & Photovoltaic Engineering IIUI Islamabad Department of Mechanical Industrial and Systems Engineering University of Rhode Island Kingston Rhode Island 02881 USA Department of Nuclear Engineering University of Tennessee Knoxville Tennessee 37996 USA Department of Physics University of Virginia Charlottesville Virginia 22904 USA

Traditional understanding of the thermal boundary resistance (TBR) across solid-solid interfaces posits that the vibrational densities of states overlap between materials dictates interfacial energy transport, with phonon scattering occurring at the interface. Using atomistic simulations, we show a mechanism for control of TBR; point defects near an interface can lead to both short- and midrange disorder, accelerating the conversion of vibrational energy between bulk and interfacial modes, ultimately reducing the TBR. We experimentally demonstrate this reduction through ion irradiation of gallium nitride and subsequently measuring the TBR across Al/GaN interfaces.

关键词： Crystal defects Defects Irradiation effects Lattice dynamics Phonons Thermal boundary conductance Vibrational states Interfaces Semiconductor compounds Transducers Ion implantation Molecular dynamics Thermoreflectance

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Changes of composition and antibiotic resistance of fecal coliform bacteria in municipal wastewater treatment plant

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Journal of Environmental sciences 2024年第12期146卷 241-250页

作者： Luoyao Wen Yunwei Cui Luodong Huang Chunzhong Wei Gangan Wang Junya Zhang Yanbo Jiang Yuansong Wei Peihong Shen State Key Joint Laboratory of Environmental Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Life Science and Technology Guangxi UniversityNanning 530005China Nanning Engineering&Technology Research Center for Water Safety Guangxi Beitou Environmental Protection&Water Group Co.LTD.Nanning 530025China Department of Isotope Biogeochemistry Helmholtz Centre for Environmental Research–UFZLeipzig 04318Germany University of Chinese Academy of Sciences Beijing 100049China International Graduate School at Shenzhen Tsinghua UniversityShenzhen 518055China

The dynamics of the composition and antibiotic resistance of the fecal coliform bacteria(FCB)in a typical wastewater treatment plant(WWTP)were investigated concerning the seasonal *** showed that WWTP could remove the FCB concentration by 3∼5 logs within the effluent of 10^(4)∼10^(5)CFU/L,but the antibiotic resistant rate of FCB species increased significantly after *** dominant FCB changed from Escherichia coli in the influent(∼73.0%)to Klebsiella pneumoniae in the effluent(∼53.3%)after WWTP,where the Escherichia coli was removed the most,while Klebsiella pneumoniae was the most *** secondary tank removed the most of FCB(by 3∼4 logs)compared to other processes,but increased all the concerned antibiotic resistant *** potential super bugs of FCB community showing resistance to all the target antibiotics were selected in the biological treatment unit of *** FCB showed the highest multiple antibiotic resistance(92.9%)in total which even increased to 100%in the *** has the highest antibiotic resistant rate in FCB,with a multiple antibiotic resistance rate of 98.4%.These indicated that the Klebsiella pneumoniae not just Escherichia coli should be specially emphasized after WWTP concerning the health risk associated with FCB community.

关键词： Fecal coliform bacteria Antibiotic resistance Wastewater treatment plant Antibiotic resistant bacteria Multiple antibiotic resistance

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Effects of cutting conditions on materials properties of austenitic stainless steels

Journal of Engineering Research

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Journal of engineering Research 2025年第2期13卷 1117-1126页

作者： Ryutaro Kondo Mitsuhiro Okayasu Hao Wen Jin Kawasaki Graduate School of Natural Science and Technology Okayama University 3-1-1 Tsushimanaka Kita-ku Okayama 700-8530 Japan Department of Mechanical and Systems Engineering Okayama University 3-1-1 Tsushimanaka Kita-ku Okayama 700-8530 Japan

Austenitic stainless steel SUS304 is widely used in various engineering applications, including semiconductor manufacturing equipment and food processing machinery, owing to its exceptional material characteristics such as non-magnetic properties, high corrosion resistance, strength, and ductility. However, concerns have arisen in recent years regarding potential alterations in the material properties of austenitic stainless steel after machining processes. As the cutting process was conducted widely to make various engineering applications with different machining conditions, an examination of the effect of machining conditions on the material properties is important. In the present study, the influence of cutting conditions on the microstructure and mechanical of SUS304 was experimentally and numerically investigated, where three types of ball-end mills with rake angles (- 20°, − 3°, and 5°) and different cutting speeds (50 m･min −1 and 100 m･min −1 ) were conducted with plane and side machining to investigate the cutting properties. Material properties of SUS304 can be changed by the cutting resistance of the above cutting process, in particular the low rake angles under plane machining, where the high cutting resistance makes high dislocation density and strain-induced martensite formation. This occurrence made the low corrosion resistance as well as low ductility. On the contrary, no significant effect of the cutting speeds on the cutting resistance was detected compared to the condition of the rake angle on the plane machining. The reasons behind this will be discussed in detail systematically in this paper. From this approach, it could be clarified to maintain the high material properties of SUS304 even after the cutting process, which could be useful to make design of the engineering applications.

关键词： Austenitic stainless steel Cutting Rake angle Strain-induced martensite Mechanical property

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Robustness of Hand Motor Function Evaluation System on Home Rehabilitation Device 4

Robustness of Hand Motor Function Evaluation System on Home ...

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

作者： Furudate, Yuta Arai, Takehiro Chiba, Kaori Ishida, Yuji Mikami, Sadayoshi Hma Nursing and Rehabilitation Academy Biomedical Science and Engineering Research Center Hokkaido Hakodate Japan Future University Hakodate Graduate School of Systems Information Science Hokkaido Hakodate Japan Hma Nursing and Rehabilitation Academy Department of Occupational Therapy Hokkaido Hakodate Japan

ISBN: (纸本)9781665419048

Continuous hand rehabilitation at home is important for hemiplegic patient because the hand is difficult to recover. Nevertheless, a patient cannot sufficiently receive rehabilitation compared with in clinic and it may lead to worsening condition. In this study, we try to solve problems by developing hand rehabilitation device which enables patient to do self-rehabilitation. To realize the device, evaluation system for feedback is important. We have also proposed the evaluation system by calculating dissimilarity with healthy subject's finger movement which is measured by pressure sensors. Although our system shows good relationship with patients who has various condition, it is unclear whether the system has same tendency even hardware is modified. Therefore, we experiment the robustness of evaluation system by using 2 devices. As a result, evaluation system does not depend on hardware modification. © 2022 IEEE.

关键词： Patient rehabilitation

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Significant chlorine emissions from biomass burning affect the long-term atmospheric chemistry in Asia

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National science Review 2024年第9期11卷 213-222页

作者： Di Chang Qinyi Li Zhe Wang Jianing Dai Xiao Fu Jia Guo Lei Zhu Dongchuan Pu Carlos A.Cuevas Rafael P.Fernandez Weigang Wang Maofa Ge Jimmy C.H.Fung Alexis K.H.Lau Claire Granier Guy Brasseur Andrea Pozzer Alfonso Saiz-Lopez Yu Song Tao Wang Atmospheric Chemistry Department Max Planck Institute for Chemistry Department of Atmospheric Chemistry and Climate Institute of Physical Chemistry Blas CabreraCSIC Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Environment Research Institute Shandong University Division of Environment and Sustainability The Hong Kong University of Science and Technology Environmental Modeling Group Max Planck Institute for Meteorology Institute of Environment and Ecology Tsinghua Shenzhen International Graduate SchoolTsinghua University Environmental Central Facility Institute for the Environment The Hong Kong University of Science and Technology Atmospheric Chemistry Modeling& Remote Sensing Research Group Southern University of Science and Technology Institute for Interdisciplinary Science (ICB) National Research Council (CONICET)FCEN-UNCuyo Institute of Chemistry Chinese Academy of Sciences NOAA Chemical Sciences Laboratory/CIRES University of Colorado Laboratoire d’Aerologie CNRSUniversity of Toulouse UPS Atmospheric Chemistry Observation & Modeling Laboratory National Center for Atmospheric Research State Key Joint Laboratory of Environmental Simulation and Pollution Control Department of Environmental Science Peking University

Biomass burning（BB） is a major source of trace gases and particles in the atmosphere,influencing air quality,radiative balance,and *** studies have mainly focused on the BB emissions of carbon and nitrogen species with less attention on *** chlorine chemistry has significant effects on atmospheric chemistry and air ***,quantitative information on chlorine emissions from BB,particularly the long-term trend and associated atmospheric impacts,is limited both on regional and global ***,we report a long-term（20 01-2018） high-resolution BB emission inventory for the major chlorine-containing compounds（HCl,chloride,and CH3Cl） in Asia based on satellite *** estimate an average of 730 Gg yr-1chlorine emitted from BB activity in Asia,with China contributing the largest share at 24.2%(177 Gg yr-1),followed by Myanmar at 18.7% and India at 18.3%.Distinct seasonal patterns and significant spatial and interannual variability are observe d,mainly driven by human-mediated changes in agricultural *** incorporating the newly developed chlorine emission inventory into a global chemistry-climate model（CAM-Chem）,we find that the BB-chlorine emissions lead to elevated levels of HCl and CH3Cl(monthly average up to 2062 and 1421 parts per trillion by volume（pptv）,respectively),subsequently resulting in noticeable changes in oxidants（up to 3.1% in O3and 17% in OH radicals）.The results demonstrate that BB is not only a significant source of air pollutants but also of oxidants,suggesting a larger role of BB emissions in the atmospheric chemistry and oxidation process than previously *** light of the projected increase in BB activity toward the end of the century and the extensive control of anthropogenic emissions worldwide,the contribution of BB emissions may become fundamental to air quality composition in the future.

关键词： biomass burning emission chlorine emission inventory tropospheric halogen chemistry atmospheric oxidants CAM-Chem model

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HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning

arXiv

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arXiv 2025年

作者： Yang, Xiaohong Liwang, Minghui Wang, Xianbin Cheng, Zhipeng Hosseinalipour, Seyyedali Dai, Huaiyu Jiao, Zhenzhen School of Informatics Xiamen University Fujian China Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Japan Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering Western University ON Canada School of Future Science and Engineering Soochow University Suzhou China Department of Electrical Engineering University at Buffalo-SUNY BuffaloNY United States Department of Electrical and Computer Engineering NC State University RaleighNC United States iF-Labs Beijing Teleinfo Technology Company Ltd. CAICT Beijing China

The rapid growth of AI-enabled Internet of Vehicles (IoV) calls for efficient machine learning (ML) solutions that can handle high vehicular mobility and decentralized data. This has motivated the emergence of Hierarchical Federated Learning over vehicle-edge-cloud architectures (VEC-HFL). Nevertheless, one aspect which is underexplored in the literature on VEC-HFL is that vehicles often need to execute multiple ML tasks simultaneously, where this multi-model training environment introduces crucial challenges. First, improper aggregation rules can lead to model obsolescence and prolonged training times. Second, vehicular mobility may result in inefficient data utilization by preventing the vehicles from returning their models to the network edge. Third, achieving a balanced resource allocation across diverse tasks becomes of paramount importance as it majorly affects the effectiveness of collaborative training. We take one of the first steps towards addressing these challenges via proposing a framework for multi-model training in dynamic VEC-HFL with the goal of minimizing global training latency while ensuring balanced training across various tasks—a problem that turns out to be NP-hard. To facilitate timely model training, we introduce a hybrid synchronous-asynchronous aggregation rule. Building on this, we present a novel method called Hybrid Evolutionary And gReedy allocaTion (HEART). The framework operates in two stages: first, it achieves balanced task scheduling through a hybrid heuristic approach that combines improved Particle Swarm Optimization (PSO) and Genetic Algorithms (GA);second, it employs a low-complexity greedy algorithm to determine the training priority of assigned tasks on vehicles. Experiments on real-world datasets demonstrate the superiority of HEART over existing methods. © 2025, CC BY-NC-ND.

关键词： Federated learning

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Vertebral Force Prediction during Manual Lifting using Sagittal Plane Posture and Machine Learning

Vertebral Force Prediction during Manual Lifting using Sagit...

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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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