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A Silicon Monoxide Lithium-Ion Battery Anode with Ultrahigh Areal Capacity

Nano-Micro Letters 2022年第3期14卷 229-243页

作者： Jiang Zhong Tao Wang Lei Wang Lele Peng Shubin Fu Meng Zhang Jinhui Cao Xiang Xu Junfei Liang Huilong Fei Xidong Duan Bingan Lu Yiliu Wang Jian Zhu Xiangfeng Duan State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringSchool of Physics and ElectronicsHunan Key Laboratory of Two‑Dimensional MaterialsEngineering Research Center of Advanced Catalysis of the Ministry of EducationHunan UniversityChangsha 410082People’s Republic of China International Graduate School at Shenzhen Tsinghua UniversityShenzhen 518057People’s Republic of China Key Laboratory of Structures Dynamic Behavior and Control of the Ministry of Education Key Laboratory of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information TechnologyHarbin Institute of TechnologyHarbin 150090People’s Republic of China School of Energy and Power Engineering North University of ChinaTaiyuan 030051People’s Republic of China Department of Chemistry and Biochemistry University of CaliforniaLos AngelesCA 90095USA

Silicon monoxide(SiO)is an attractive anode material for next-generation lithium-ion batteries for its ultra-high theoretical capacity of 2680 mAh g−*** studies to date have been limited to electrodes with a rela-tively low mass loading(<3.5 mg cm^(−2)),which has seriously restricted the areal capacity and its potential in practical *** areal capacity with such high-capacity materials is critical for capitalizing their potential in practi-cal ***,we report a monolithic three-dimensional(3D)large-sheet holey gra-phene framework/SiO(LHGF/SiO)composite for high-mass-loading *** specifically using large-sheet holey graphene building blocks,we construct LHGF with super-elasticity and exceptional mechanical robustness,which is essential for accommodating the large volume change of SiO and ensuring the structure integrity even at ultrahigh mass ***,the 3D porous graphene network structure in LHGF ensures excellent electron and ion *** systematically tailoring microstructure design,we show the LHGF/SiO anode with a mass loading of 44 mg cm^(−2)delivers a high areal capacity of 35.4 mAh cm^(−2)at a current of 8.8 mA cm^(−2)and retains a capacity of 10.6 mAh cm^(−2)at 17.6 mA cm^(−2),greatly exceeding those of the state-of-the-art commercial or research ***,we show an LHGF/SiO anode with an ultra-high mass loading of 94 mg cm^(−2)delivers an unprecedented areal capacity up to 140.8 mAh cm^(−2).The achievement of such high areal capacities marks a critical step toward realizing the full potential of high-capacity alloy-type electrode materials in practical lithium-ion batteries.

关键词： Silicon monoxide Large-sheet holey graphene Lithium-ion batteries High mass loading Ultra-high areal capacity

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Experimental and Theoretical Analyses on Power Generation Characteristics of Co-axial MHD Energy Conversion Device

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IEEJ Transactions on Power and Energy 2023年第7期143卷 454-460页

作者： Hasebe, Takahiro Sasaki, Ryo Fujino, Takayasu Takana, Hidemasa Kobayashi, Hiromichi Graduate School of Science and Technology University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Department of Physics Keio University Hiyoshi Campus 4-1-1 Hiyoshi Kohoku-ku Yokohama223-8521 Japan

Experiments on power generation were conducted under the open-circuit condition to validate theoretical analyses on the power generation characteristics of a co-axial MHD energy conversion device. Considering distribution of externally applied magnetic field and the electromotive force induced by the rotation of the conductive inner cylinder, the results show that the experimental open-circuit voltage was lower than the theoretical one for the wide channel width, whereas the experimental open-circuit voltage was higher than the theoretical one for the narrow channel width. The inclination of the inner cylinder might cause the decrease in effective radial ratio. © 2023 The Institute of Electrical Engineers of Japan.

关键词： Magnetohydrodynamics

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Integrating Linguistic and Citation Information with Transformer for Predicting Top-Cited Papers 1

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18th International Conference on Web Information systems and Technologies, WEBIST 2022

作者： Ochi, Masanao Shiro, Masanori Mori, Jun’ichiro Sakata, Ichiro Department of Technology Management for Innovation Graduate School of Engineering The University of Tokyo Hongo 7-3-1 Tokyo Bunkyo Japan Human Informatics and Interaction Research Institute National Institute of Advanced Industrial Science and Technology Umezono 1-1-1 Central2 Ibaraki Tsukuba Japan

ISBN: (数字)9783031430886

ISBN: (纸本)9783031430879

Academic literature contains many different types of data, including language, citations, figures, tables, etc. Released in 2017 for natural language processing, the Transformer model is widely used in fields as diverse as image processing and network science. Transformer models trained on large datasets have been shown to perform well on different tasks when trained on additional small amounts of new data. Most studies of classification and regression in the academic literature have designed individually customized features for specific tasks without fully considering data interactions. Customizing features for each task is costly and complex. This paper addresses this issue by proposing a basic framework that can be consistently applied to various tasks from the diverse information in academic literature. Specifically, we propose an end-to-end fusion method that combines linguistic and citation information of academic literature data utilizing two Transformer models. The experiments were conducted using a dataset on 67 disciplines extracted from the Web of science, one of the largest databases about academic literature, and classified papers with the top 20% of citations five years after publication. The results show that the proposed method improves the F-measure by 0.028 compared to using only citation or linguistic information on average. Repeated experiments on 67 data sets also showed that the proposed model has the smallest standard deviation of F values. In other words, our proposed method shows the best average performance and is stable with a small variance of the F-value. We also conducted a comparative analysis between the dataset’s characteristics and the proposed method’s performance. The results show that our proposed method correlates poorly with the dataset’s characteristics. In other words, our proposed method is highly versatile. Based on the above, our proposed method is superior regarding F-value, learning stability, and generality. © 2023, The

关键词： Large dataset

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HelmetPoser: A Helmet-Mounted IMU Dataset for Data-Driven Estimation of Human Head Motion in Diverse Conditions

arXiv

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arXiv 2024年

作者： Li, Jianping Leng, Qiutong Liu, Jinxin Xu, Xinhang Jin, Tongxin Cao, Muqing Nguyen, Thien-Minh Yuan, Shenghai Cao, Kun Xie, Lihua School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

Helmet-mounted wearable positioning systems are crucial for enhancing safety and facilitating coordination in industrial, construction, and emergency rescue environments. These systems, including LiDAR-Inertial Odometry (LIO) and Visual-Inertial Odometry (VIO), often face challenges in localization due to adverse environmental conditions such as dust, smoke, and limited visual features. To address these limitations, we propose a novel head-mounted Inertial Measurement Unit (IMU) dataset with ground truth, aimed at advancing data-driven IMU pose estimation. Our dataset captures human head motion patterns using a helmet-mounted system, with data from ten participants performing various activities. We explore the application of neural networks, specifically Long Short-Term Memory (LSTM) and Transformer networks, to correct IMU biases and improve localization accuracy. Additionally, we evaluate the performance of these methods across different IMU data window dimensions, motion patterns, and sensor types. We release a publicly available dataset, demonstrate the feasibility of advanced neural network approaches for helmet-based localization, and provide evaluation metrics to establish a baseline for future studies in this field. Data and code can be found at https://***/HelmetPoser. ***/. © 2024, CC BY.

关键词： Helmet mounted displays

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Understanding the Resilience of Urban Rail Transit:Concepts,Reviews,and Trends

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engineering 2024年第10期41卷 7-18页

作者： Yun Wei Xin Yang Xiao Xiao Zhiao Ma Tianlei Zhu Fei Dou Jianjun Wu Anthony Chen Ziyou Gao Beijing Mass Transit Railway Operation Corporation Ltd. Beijing 100044China School of Systems Science Beijing Jiaotong UniversityBeijing 100044China Traffic Control Technology Corporation Ltd. Beijing 100160China Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

As the scale of urban rail transit(URT)networks expands,the study of URT resilience is essential for safe and efficient *** paper presents a comprehensive review of URT resilience and highlights potential trends and directions for future ***,URT resilience is defined by three primary abilities:absorption,resistance,and recovery,and four properties:robustness,vulnerability,rapidity,and ***,the metrics and assessment approaches for URT resilience were *** metrics are divided into three categories:topology-based,characteristic-based,and performance-based,and the assessment methods are divided into four categories:topological,simulation,optimization,and *** of various metrics and assessment approaches revealed that the current research trend in URT resilience is increasingly favoring the integration of traditional methods,such as conventional complex network analysis and operations optimization theory,with new techniques like big data and intelligent computing technology,to accurately assess URT ***,five potential trends and directions for future research were identified:analyzing resilience based on multisource data,optimizing train diagram in multiple scenarios,accurate response to passenger demand through new technologies,coupling and optimizing passenger and traffic flows,and optimal line design.

关键词： Urban rail transit Resilience assessment Resilience improvement Network disruption

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Uncertainty analysis of virtualized systems with live migration

Uncertainty analysis of virtualized systems with live migrat...

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering (QR2MSE 2022)

作者： J. Zhang J. Zheng H. Okamura T. Dohi Graduate School of Advanced Science and Engineering Hiroshima University Higashihiroshima Japan Department of Information Science and Engineering Ritsumeikan University Kusatsu Japan

Benefiting from the advantages of virtualization technology, virtualized systems have been widely studied and adopted in enterprise systems, aimed at reducing resource usage and enhancing system reliability. An important feature of virtualized systems is the virtual machine (VM) live migration, which brings convenience to transfer running VMs from one physical server to another without service interruption. To achieve a high available/reliable virtualized system, it is crucial to evaluate its system availability/reliability. The model-based approach is commonly used and proved effective. However, it is well-known that the model parameters typically involve estimation error due to the limitation of data samples or expert's knowledge, so-called uncertainty. In this paper, we analyze the uncertainty propagation in the availability model of a virtualized system with live migration through a momentbased approximation method. A numerical experiment is conducted to quantify the impact of the parameter uncertainty on the system availability.

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Estimating Person Location in Bathroom with Spatial Ultrasound and Variational autoencoder

Estimating Person Location in Bathroom with Spatial Ultrasou...

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IEEE Symposium (IUS) Ultrasonics

作者： Shun Sato Yuto Yasuda Ryotaro Ohara Riku Hamabe Takayuki Genda Shoya Imanaka Shintaro Izumi Hiroshi Kawaguchi Graduate School of System Informatics Kobe University Kobe Japan Department of Computer Science and Systems Engineering Kobe University Kobe Japan Graduate School of Science Technology and Innovation Kobe University Kobe Japan

In bathrooms, a fall can lead to severe injuries or even drowning. While taking preventive measures against such accidents is crucial, it's equally important to swiftly detect and request rescue when they occur. In such scenarios, knowing the exact location of the person in the bathroom becomes critical. However, concerns related to privacy and costs make the use of cameras and lidar impractical. To address these issues, we propose a method for estimating the 3D location of a person within the bathroom using ultrasound correlation values as input for a deep neural network. To validate our approach, we conduct experiments using two sensors in this study. The results are promising, as we achieved a mean square error of just 10.48 cm.

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Consensus control of Leader-Following Multi-Agent systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

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2023 China Automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

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Improved Method of Preparation for Shape-memory Polymer Sheet with Embedded Electrical Heating Wire for Use in Pneumatic Artificial Rubber Muscle

Improved Method of Preparation for Shape-memory Polymer Shee...

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SICE Annual Conference

作者： Yuta Okamura Kazuto Takashima Toshiro Noritsugu Toshiharu Mukai Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Mimasaka University Tsuyama Japan Department of Information Engineering Faculty of Information Engineering Meijo University Nagoya Japan

We improved the structure of a shape-memory polymer (SMP) sheet with an embedded electrical heating wire, thus enhancing the manufacturing reproducibility and durability of flexible and multi-degree-of-freedom pneumatic artificial rubber muscles. We prepared two types of SMP sheets using the previous and improved methods and compared the mechanical properties via bending and tensile tests. The SMP sheets were then attached to a pneumatic artificial rubber muscle, and subjected to a bending angle test and an isometric test to evaluate their bending properties.

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