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2023 International Conference on Advanced Mechatronic Systems, ICAMechS 2023

作者： Ge, Zhikang Wang, Zhuo Bai, Xiaoping Wang, Xiaoxiong Man, Zhihong Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Swinburne University of Technology Faculty of Science Engineering and Technology Melbourne Australia

ISBN: (纸本)9798350307474

In this paper, a novel adaptive terminal sliding-mode control (ATSMC) method is developed for road vehicles with uncertain dynamics. It is shown that the designed adaptive laws can recursively update the controller parameters based on the estimation values of the unknown parameter bound in the Lyapunov sense, and then the lateral position error can be driven to zero in a finite time. In comparison to the conventional sliding-mode-based vehicle lateral control method, the proposed ATSMC not only ensures fast error convergence, but also eliminates the requirement for known bounded information in controller design. Simulation results are presented to demonstrate the good performance of the proposed ATSMC scheme. © 2023 IEEE.

关键词： Sliding mode control

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Exploring different Actor Roles in Orchestrations of System of Systems

Exploring different Actor Roles in Orchestrations of System ...

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IEEE International Conference on System of Systems engineering (SoSE)

作者： Tomas Nordstrom Leon Rene Sutfeld Terese Besker RISE Research Institutes of Sweden AB and Department of Applied Physics and Electronics Umeå University Sweden Computer Science RISE Research Institutes of Sweden AB Gothenburg Sweden Systems Engineering RISE Research Institutes of Sweden AB Gothenburg Sweden

ISBN: (数字)9798350365917

ISBN: (纸本)9798350365924

The rising complexity and interconnectedness of contemporary systems engineering solutions have spurred the development of Systems-of-Systems (SoS). Within a SoS, we find interconnected constituent systems (CSs), each possessing individual capabilities and managerial autonomy. For effective management of a SoS, a dedicated orchestration mechanism is crucial. However, currently, there is a lack of a well-defined internal structure or an understanding of roles and interactions between sub-parts of the Orchestrator. This paper proposes a framework for SoS orchestration, identifying distinct actors and their functional roles for an effective SoS operation. Our framework consists of two main groups: SoS Governors (handling legal and financial aspects) and the Orchestrator (responsible for the overall SoS operation). Key actors within the Orchestrator are identified and described, including the Goal Transformer, Registrar, Composer, Executor, Cartographer, Data Curator, and Translator. The paper concludes by discussing the dynamic collaboration between orchestration actors and the significance of clearly defining these roles for complex SoS management. This study offers a foundation for future research and practice in SoS orchestration, potentially enhancing these complex systems’ resilience, effectiveness, and overall management.

关键词： Law Collaboration Transformers Complexity theory System of systems Resilience

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Receiver-Based Data Communication for Wireless Sensor Networks 2

Receiver-Based Data Communication for Wireless Sensor Networ...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Chitra Kiran, N. Parkash, Jai Cheerla, Sreevardhan Shanmugaraja, P. Manohara, M. Madan, Parul Alliance University Department of Electronics and Communication Engineering Karnataka Bangalore560068 India Gulzar Group of Institutes Department of Computer Science and Engineering Punjab Khanna141401 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communications Engineering Andhra Pradesh Vaddeswaram522302 India Sona College of Technology Department of Information Technology Tamil Nadu Salem636005 India Mohan Babu University School of Engineering Andhra Pradesh Tirupati517102 India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350315905

As the Web of Things (IoT) has created throughout recent years, unlicensed radio range has become more clogged with brilliant wireless gadgets that are utilized in an assortment of use spaces, prominently the 2.4 GHz ISM band. One of the easiest and most productive answers for energy-compelled networks is the wake-up receiver (WuRx). Rather than utilizing a conventional radio, this innovation empowers energy-independent on-request communication for persistent observing. One of the WSN methods that utilizes the most investment is directing. Consequently, planning an energy-effective steering procedure is fundamental. This exploration proposes Grouped WuRx based on Multicast wake-up (CWM), a progressive Wake-up Receiver-based directing convention that all the while streamlines energy use and time productivity for indoor conditions. In our proposed technique, bunches are made inside the organization. Estimation discoveries show that, in contrast with past directing conventions, our proposed arrangement has much better execution as far as conveyance delay and further developed energy effectiveness. © 2023 IEEE.

关键词： Wireless sensor networks

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Analyzing Customer Psychological and Behavioral Attributes in Corporate Social Responsibility in Supply Chain Management Using a Multilayer Perceptron Approach 2

Analyzing Customer Psychological and Behavioral Attributes i...

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2nd IEEE International Conference on Emerging Research in Computational science, ICERCS 2024

作者： Agnihotri, Kuldeep Kamidi, Deepthi Ranjan, Radha Vasudevan Unni, Manu Babu K, Ramesh Vijaya Jayanthi, N. ISBA Group of Institutes Department of Commerce & Management Madhya Pradesh Indore India Vignan Institute of Technology and Science Department of Computer Science and Engineering Telangana Hyderabad India Amity University Law Amity Law School Bihar Patna India Department of Management Karnataka Bangalore India SRKR Engineering College Department of English and Foreign Languages Andhra Pradesh Bhimavaram India Periyar Maniammai Institute of Science and Technology Deemed to be University Department of Commerce Tamilnadu Thanjavur India

ISBN: (纸本)9798331534950

Despite the fact that CSR is currently important in the retail industry, academic research on its influence is sparse. Retailers have a great interest in understanding the influence of customer opinion on CSR initiatives because the system serves as a conduit between producers and consumers. Understanding the impact of CSR projects on store bottom lines is critical for contextualising the system's results. The suggested technique includes preprocessing, feature selection, and model training. This step involved cleaning the dataset with a text-processing method that assigned each document three numerical values: document length, token number, and token length. The best approach is to model feature selection using Latent Dirichlet Allocation (LDA). The MLP was used to train the model in the specified approach. The suggested model has an average accuracy rate of 94.35%, which is greater than cutting-edge alternatives like as SVM and CNN. © 2024 IEEE.

关键词： Sales

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Video-Based Respiratory Monitoring System for Inactive Non-Human Primates 5

Video-Based Respiratory Monitoring System for Inactive Non-H...

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Jiang, Hongru Bu, XiangDong Xu, Zhen Shi, Qianqian Tang, Huajin Chen, Yao School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Bio-X Institutes Shanghai Jiao Tong University Shanghai200240 China Tsinghua University Department of Precision Instrument Beijing100084 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798331529192

Non-human primates (NHPs) are critical in neuroscience research, where researchers implant electrodes into their brains to observe neuronal activity. However, the high post-operative mortality rate of NHPs remains a significant concern, primarily due to inadequate post-surgical monitoring. Thus, it is essential to develop a monitoring system for assessing their physiological status. Conventional wearable monitoring devices are often removed by NHPs, making it challenging to monitor their well-being. To address this issue, we propose a video-based monitoring system that utilizes Eulerian video magnification techniques and principal component analysis to detect and estimate the respiratory rate remotely. The results show that our method has a difference of less than 1 breathing rate per minute compared to a commercial monitor and works well in experiments involving different species, demonstrating the accuracy and effectiveness of our method. We found that Gaussian pyramid representation has lower requirements for the ROI selection, making it more robust for practical applications. The proposed system has the potential to improve animal welfare and facilitate new experiments in neuroscience research. © 2024 IEEE.

关键词： Mammals

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Enhanced Electrocardiogram Data Compression and Classification Using 2D Convolutional Neural Networks

Enhanced Electrocardiogram Data Compression and Classificati...

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Emerging Systems and Intelligent Computing (ESIC), International Conference on

作者： Amrendra Singh Yadav Preeti Mehta Deepti Mishra Rabindra Kumar Barik Department of Computer Science and Engineering AVM-Indian Institute of Information Technology and Management Gwalior India Department of Computer Science and Engineering National Institutes of Technology Delhi Delhi India School of Economics and Commerce KIIT Deemed to be University Bhubaneshwar India School of Computer Application KIIT Deemed to be University Bhubaneshwar India

ISBN: (数字)9798331522100

ISBN: (纸本)9798331522117

The task of electrocardiogram (ECG) classification is a combination of data compression and classification of signals based on the patient’s health. This paper introduces a novel technique for compressing electrocardiogram (ECG) images and utilizing these compressed images for accurate classification. We transform ECG signals into images and compress them to reduce their size while preserving classification accuracy significantly. Our approach employs a 2-dimensional Convolutional Neural Network (2-D CNN) model and achieves an impressive accuracy of 97% even after compressing the images by up to 76%. The proposed technique was tested on the widely-used MIT-BIH Arrhythmia Dataset, demonstrating its robustness and efficacy. Maintaining high classification accuracy despite significant image compression is crucial for efficient storage and transmission in resource-constrained environments. This method holds substantial potential for real-time monitoring and diagnosis in telemedicine applications, emphasizing the importance of our contribution to the field.

关键词： Accuracy Image coding Biological system modeling Data compression Transforms Electrocardiography Robustness Convolutional neural networks Optimization Batch normalization

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Enhanced Electrocardiogram Data Compression and Classification Using 2D Convolutional Neural Networks 5

Enhanced Electrocardiogram Data Compression and Classificati...

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5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Yadav, Amrendra Singh Mehta, Preeti Mishra, Deepti Barik, Rabindra Kumar AVM-Indian Institute of Information Technology and Management Department of Computer Science and Engineering Gwalior India National Institutes of Technology Delhi Department of Computer Science and Engineering Delhi India Kiit Deemed to be University School of Economics and Commerce Bhubaneshwar India Kiit Deemed to be University School of Computer Application Bhubaneshwar India

ISBN: (纸本)9798331522100

The task of electrocardiogram (ECG) classification is a combination of data compression and classification of signals based on the patient's health. This paper introduces a novel technique for compressing electrocardiogram (ECG) images and utilizing these compressed images for accurate classification. We transform ECG signals into images and compress them to reduce their size while preserving classification accuracy significantly. Our approach employs a 2-dimensional Convolutional Neural Network (2-D CNN) model and achieves an impressive accuracy of 97% even after compressing the images by up to 76%. The proposed technique was tested on the widely-used MIT-BIH Arrhythmia Dataset, demonstrating its robustness and efficacy. Maintaining high classification accuracy despite significant image compression is crucial for efficient storage and transmission in resource-constrained environments. This method holds substantial potential for real-time monitoring and diagnosis in telemedicine applications, emphasizing the importance of our contribution to the field. © 2025 IEEE.

关键词： Electrocardiography

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Flow-aware synthesis: A generic motion model for video frame interpolation

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Computational Visual Media 2021年第3期7卷 393-405页

作者： Jinbo Xing Wenbo Hu Yuechen Zhang Tien-Tsin Wong Department of Computer Science and Engineering the Chinese University of Hong KongHong Kong SARChina Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesChina

A popular and challenging task in video research,frame interpolation aims to increase the frame rate of *** existing methods employ a fixed motion model,e.g.,linear,quadratic,or cubic,to estimate the intermediate warping ***,such fixed motion models cannot well represent the complicated non-linear motions in the real world or rendered ***,we present an adaptive flow prediction module to better approximate the complex motions in ***,interpolating just one intermediate frame between consecutive input frames may be insufficient for complicated non-linear *** enable multi-frame interpolation,we introduce the time as a control variable when interpolating frames between original ones in our generic adaptive flow prediction *** and quantitative experimental results show that our method can produce high-quality results and outperforms the existing stateof-the-art methods on popular public datasets.

关键词： flow-aware generic motion model video frame interpolation

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Automatic recognition of tweek atmospherics and plasma diagnostics in the lower ionosphere with the machine learning method

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Earth and Planetary Physics 2023年第3期7卷 407-413页

作者： Mao Zhang GaoPeng Lu HaiLiang Huang ZhengWei Cheng YaZhou Chen Steven A.Cummer JiaYi Zheng JiuHou Lei School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China Key Laboratory of Atmospheric Optics Anhui Institute of Optics and Fine MechanicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China National Key Laboratory on Electromagnetic Environment Effects Army Engineering UniversityShijiazhuang CampusShijiazhuang 050003China Electrical and Computer Engineering Department Duke UniversityDurhamNC 27708USA

Tweek atmospherics are extremely low frequency and very low frequency pulse signals with frequency dispersion characteristics that originate from lightning discharges and that propagate in the Earth–ionosphere waveguide over long *** this study,we developed an automatic method to recognize tweek atmospherics and diagnose the lower ionosphere based on the machine learning *** differences(automatic−manual)in each ionosphere parameter between the automatic method and the manual method were−0.07±2.73 km,0.03±0.92 cm^(−3),and 91±1,068 km for the ionospheric reflection height(h),equivalent electron densities at reflection heights(Ne),and propagation distance(d),***,the automatic method is capable of recognizing higher harmonic tweek *** evaluation results of the model suggest that the automatic method is a powerful tool for investigating the long-term variations in the lower ionosphere.

关键词： machine learning method tweek atmospherics reflection height D-region ionosphere

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Non-invasive estimation of the powder size distribution from a single speckle image

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Light(science & Applications) 2024年第10期13卷 2221-2230页

作者： Qihang Zhang Ajinkya Pandit Zhiguang Liu Zhen Guo Shashank Muddu Yi Wei Deborah Pereg Neda Nazemifard Charles Papageorgiou Yihui Yang Wenlong Tang Richard D.Braatz Allan S.Myerson George Barbastathis Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 117543Singapore Department of Chemical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Process Chemistry Development Takeda Pharmaceuticals International Co40 Landsdowne StCambridgeMA 02139USA ShinrAI Center for AI/ML Data Sciences InstitutesTakeda Pharmaceuticals International Co650 E Kendall StCambridgeMA 02142USA Present address:Department of Precision Instruments Tsinghua UniversityBeijing 100084China

Non-invasive characterization of powders may take one of two approaches:imaging and counting individual particles;or relying on scattered light to estimate the particle size distribution(PSD)of the *** former approach runs into practical difficulties,as the system must conform to the working distance and other restrictions of the imaging *** latter approach requires an inverse map from the speckle autocorrelation to the particle *** principle relies on the pupil function determining the basic sidelobe shape,whereas the particle size spread modulates the sidelobe *** recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network,trained efficiently through a physics-informed semi-generative *** this work,we eliminate one of the most time-consuming steps of our previous method by engineering the pupil *** judiciously blocking portions of the pupil,we sacrifice some photons but in return we achieve much enhanced sidelobes and,hence,higher sensitivity to the change of the size *** result is a 60×reduction in total acquisition and processing time,or 0.25 seconds per frame in our *** real-time operation in our system is not only more appealing toward rapid industrial adoption,it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying,blending,and other chemical and pharmaceutical manufacturing processes.

关键词： speckle size distribution

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