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A sEMG-based Muscle-Compensation-Error Elimination Module for the Home-Based Bilateral Rehabilitation system

IEEE Robotics and Automation Letters 2025年第7期10卷 6696-6703页

作者： Wang, Hanze Guo, Shuxiang Li, He Ding, Mingchao Southern University of Science and Technology Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China Beijing Institute of Technology Aerospace Center Hospital School of Life Science The Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology Beijing100081 China Beijing Institute of Technology Department of Peripheral Vascular Intervention Aerospace Center Hospital School of Life Science Beijing100081 China

Home-based bilateral training using exoskeletons is considered an effective rehabilitation method to restore the normal motion function of stroke patients' limbs. However, due to the imbalance of limb muscle strength, muscle compensation of the functional upper limb will cause surface electromyography (sEMG) signal fluctuations. The signal fluctuations will lead to prediction errors, thereby affecting the effect of bilateral rehabilitation. To eliminate the prediction error caused by muscle compensation, a novel rehabilitation module for a home-based bilateral rehabilitation robotic system is proposed in this letter. This sEMG-driven rehabilitation module, which incorporates the channel splitting and transferable frequency domain, first identifies the type of muscle compensation mixed in continuous movement and then eliminates the error caused by muscle compensation. Online experiments were conducted to evaluate the system in tracking accuracy and muscle-compensation-error elimination, which showed the proposed rehabilitation system with rehabilitation module achieved fast adaption to the patient's compensatory movement as well as improving the effect of robot-assisted bilateral training. © 2025 IEEE.

关键词： Human rehabilitation equipment

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Dynamic Modeling of Key Operating Parameters for Supercritical Circulating Fluidized Bed Units based on Data-Knowledge-Driven Method

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Journal of Thermal Science 2024年第3期33卷 1216-1230页

作者： YU Haoyang GAO Mingming ZHANG Hongfu CHEN Jiyu LIU Jizhen YUE Guangxi The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing102206China CHN Energy New Energy Technology Research Institute Co. Ltd.Beijing102209China Department of Energy and Power Engineering Tsinghua UniversityBeijing100084China

To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)***,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been ***,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB *** model parameters are determined based on the operating data of the unit and continuously optimized in real ***,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam ***,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB *** model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.

关键词： circulating fluidized bed dynamic model data-knowledge-driven method deep learning power plant

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Multi‐granularity re‐ranking for visible‐infrared person re‐identification

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CAAI Transactions on Intelligence technology 2023年第3期8卷 770-779页

作者： Yadi Wang Hongyun Zhang Duoqian Miao Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghaiChina Department of Electrical and Computer Engineering University of AlbertaEdmontonAlbertaCanada System Research Institute Polish Academy of SciencesWarsawPoland

Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.

关键词： computer vision recognition

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A recurrent neural network architecture for android mobile data analysis for detecting malware infected data

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Soft Computing 2024年第21期28卷 12917-12928页

作者： Murugan, Prabhu Manimaran, A. Sundar, Ramesh Dakshinamoorthy, Prabakar Rajaram, Gnanajeyaraman Garg, Shruti Department of ECE Saveetha School of Engineering Simats Chennai602105 India Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Simats Chennai602105 India Department of Netwoking and Communication School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur India Department of Data Science and Business System School of Computing SRM Institute of Science and Technology SRM Nagar Kattankulathur India Department of Applied Machine Learning Saveetha School of Engineering Saveetha Institute of Medical and Technological Sciences Tamilnadu Chennai India Birla Institute of Technology Mesra Ranchi India

One of the latest modern communication devices is a mobile device seriously affected by multiple malware. Malware is a virus software installed automatically by hackers on various computing devices. Malware corrupts the system software, kills *.exe files, and tries to access user-sensitive data from the device. Around the world, 80% of people use smartphones, and 70% use Android phones. All Android phones are installed with anti-virus software but not used properly. Thus, it creates a pathway for malware to enter Android mobile devices and deploy vulnerabilities. Several earlier methods have focused on using the malware detection method by analyzing static data, which cannot identify the dynamic behavior of the malware. Thus, this paper implemented one of the deep learning algorithms, RNN, for identifying and detecting malware activities in Android mobile devices statically and dynamically. An IoT network architecture is proposed for experimenting with the RNN algorithms verifying the performance. The results of the RNN method show that it is better than other models in malware detection in mobile devices. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Android malware

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Flash‑Induced High‑Throughput Porous Graphene via Synergistic Photo‑Effects for Electromagnetic Interference Shielding

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Nano-Micro Letters 2023年第11期15卷 1-18页

作者： Jin Soo Lee Jeong‑Wook Kim Jae Hee Lee Yong Koo Son Young Bin Kim Kyoohee Woo Chanhee Lee Il‑Doo Kim Jae Young Seok Jong Won Yu Jung Hwan Park Keon Jae Lee Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak‑roYuseong‑guDaejeon 34141Republic of Korea School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak‑roYuseong‑guDaejeon 34141Republic of Korea Department of Printed Electronics Nano‑Convergence Manufacturing Systems Research DivisionKorea Institute of Machinery and Materials(KIMM)156 Gajeongbuk‑RoYuseong‑GuDaejeon 34103Republic of Korea Department of Mechanical System Design Engineering Seoul National University of Science and Technology232 Gongneung‑roNowon‑guSeoul 01811Republic of Korea Department of Mechanical Engineering(Department of Aeronautics Mechanical and Electronic Convergence Engineering)Kumoh National Institute of Technology61 Daehak‑roGumiGyeongbuk 39177Republic of Korea

Porous 2D materials with high conductivity and large surface area have been proposed for potential electromagnetic interference(EMI)shielding materials in future mobility and wearable applications to prevent signal noise,transmission inaccuracy,system malfunction,and health ***,we report on the synthesis of lightweight and flexible flash-induced porous graphene(FPG)with excellent EMI shielding *** broad spectrum of pulsed flashlight induces photo-chemical and photo-thermal reactions in polyimide films,forming 5×10 cm^(2)-size porous graphene with a hollow pillar structure in a few *** resulting material demonstrated low density(0.0354 g cm^(−3))and outstanding absolute EMI shielding effectiveness of 1.12×10^(5) dB cm^(2) g^(−1).The FPG was characterized via thorough material analyses,and its mechanical durability and flexibility were confirmed by a bending cycle ***,the FPG was utilized in drone and wearable applications,showing effective EMI shielding performance for internal/external EMI in a drone radar system and reducing the specific absorption rate in the human body.

关键词： Porous graphene Flash lamp Photo-pyrolysis High-throughput Electromagnetic interference shielding

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Towards explainable traffic flow prediction with large language models

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Communications in Transportation Research 2024年第1期4卷 474-490页

作者： Xusen Guo Qiming Zhang Junyue Jiang Mingxing Peng Meixin Zhu Hao Frank Yang Intelligent Transportation Thrust System HubThe Hong Kong University of Science and Technology(Guangzhou)Guangzhou511400China Department of Civil and System Engineering Johns Hopkins UniversityBaltimore21218USA Guangdong Provincial Key Lab of Integrated Communication Sensing and Computation for Ubiquitous Internet of ThingsGuangzhou511400China

Traffic forecasting is crucial for intelligent transportation *** has experienced significant advancements thanks to the power of deep learning in capturing latent patterns of traffic ***,recent deep-learning architectures require intricate model designs and lack an intuitive understanding of the mapping from input data to predicted *** both accuracy and explainability in traffic prediction models remains a challenge due to the complexity of traffic data and the inherent opacity of deep learning *** tackle these challenges,we propose a traffic flow prediction model based on large language models(LLMs)to generate explainable traffic predictions,named *** transferring multi-modal traffic data into natural language descriptions,xTP-LLM captures complex time-series patterns and external factors from comprehensive traffic *** LLM framework is fine-tuned using language-based instructions to align with spatial-temporal traffic flow ***,xTP-LLM shows competitive accuracy compared with deep learning baselines,while providing an intuitive and reliable explanation for *** study contributes to advancing explainable traffic prediction models and lays a foundation for future exploration of LLM applications in transportation.

关键词： Traffic flow predictionLarge language models Spatial-temporal prediction Explainability

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Automated Detection of Harmful Insects in Agriculture: A Smart Framework Leveraging IoT, Machine Learning, and Blockchain

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4787-4798页

作者： Rahman, Wahidur Hossain, Muhammad Minoar Hasan, Md. Mahedi Iqbal, Md. Sadiq Rahman, Mohammad Motiur Fida Hasan, Khondokar Moni, Mohammad Ali Mawlana Bhashani Science and Technology University Department of Computer Science and Engineering Tangail1902 Bangladesh Uttara University Department of Computer Science and Engineering Dhaka1230 Bangladesh Prime University Department of Management and Information System Mirpur Dhaka1216 Bangladesh Bangladesh University Department of Computer Science and Engineering Dhaka1207 Bangladesh School of Professional Studies CanberraNSW2052 Australia Artificial Intelligence and Cyber FuturesInstitute Charles Sturt University AI & Digital Health Technology BathurstNSW2795 Australia

Paddy cultivation is a significant global economic sector, with rice production playing a crucial role in influencing worldwide economies. However, insects in paddy farms predominantly impact the growth rate and ecological equilibrium of the agricultural field. Hence, the precise and timely identification of insects in agricultural settings presents a potential strategy for addressing this issue. This study aims to implement an automated system for paddy farming by employing a real-time framework that incorporates the Internet of Things (IoT), blockchain technology, and Deep Learning (DL) algorithms. The primary emphasis of the DL-based system is on the timely identification of pests. In contrast, integrating the IoT and blockchain technologies facilitates stablishing a fully automated system with security within the agricultural domain. The DL-based system includes a secondary dataset of paddy insects, and then preprocessing, feature extraction, and identification have been performed. Besides, an IoT-based system is embodied with a camera module and microprocessor, accompanied by some apparatus required to automate the whole system. In addition, the research also includes the blockchain to secure each individual data transmission among the several IoT components and the cloud server. While examining the proposed solution, various experimental data have been systematically documented and analyzed. The proposed framework attained a peak accuracy of 98.91% using the VGG19 model and ensemble classifiers to detect the pest with a specificity of 99.14% and a precision of 98.21%. The study additionally quantifies the mean duration of the cloud response when integrated with IoT, yielding an average time of 1.71 s after pest identification. Nevertheless, the system has exhibited a high level of efficacy in the context of real-time monitoring and automation of paddy farms. © 2020 IEEE.

关键词： Blockchain

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Development and application of quantitative methods for mixed uncertainty

Development and application of quantitative methods for mixe...

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2024 Annual Conference on Transactions of the American Nuclear Society, ANS 2024

作者： Peng, Cuiting Hu, Mengyan Xiong, Qingwen Yang, Jun Department of Nuclear Engineering and Technology School of Energy and Power Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Sichuan Chengdu610213 China

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Bacterial and cancerous cell membrane fused liposome coordinates with PD-L1 inhibitor for cancer immunotherapy

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Nano Research 2024年第9期17卷 8389-8401页

作者： Xianjin Luo Chenglong Li Zhaofei Guo Hairui Wang Penghui He Yuanhao Zhao Yi Lin Chunting He Yingying Hou Yongshun Zhang Guangsheng Du Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial TechnologyWest China School of PharmacySichuan UniversityChengdu 610064China Pharmaceutical Biotechnology Department of PharmacyLMU MunichButenandt Strasse 5-13Munich 81377Germany Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijing 100871China

Although tumor cell membranes with broad-spectrum antigens have been explored for cancer vaccines for decades,their relatively poor capacity to stimulate immune responses,especially cellular immune responses,has limited their ***,we presented a novel bacterial and cancerous cell membrane fusogenic liposome for co-delivering cell membrane-derived antigens and ***,a programmed death-ligand 1(PD-L1)inhibitor,JQ-1,was incorporated into the formulation to tackle the up-regulated PD-L1 expression of antigen-presenting cells(APCs)upon vaccination,thereby augmenting its anti-tumor *** fusogenic liposomes demonstrated significantly improved cellular uptake by APCs and effectively suppressed PD-L1 expression in bone marrow-derived dendritic cells(BMDCs)in *** subcutaneous vaccination,the nano-vaccines efficiently drained to the tumor-draining lymph nodes(TDLNs),and significantly inhibited PD-L1 expression of both dendritic cells(DCs)and macrophages within the TDLNs and *** a result,the liposomal vaccine induced robust innate and cellular immune responses and inhibited tumor growth in a colorectal carcinoma-burden mouse *** summary,the fabricated cell membrane-based fusogenic liposomes offer a safe,effective,and easily applicable strategy for tumor immunotherapy and hold potential for personalized cancer immunotherapy.

关键词： fusogenic liposome tumor cell membrane adjuvant programmed death-ligand 1(PD-L1)inhibitor tumor draining lymph nodes

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A Simple Method to Measure the Contact Angle of Metal Droplets on Graphite

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Nanomanufacturing and Metrology 2023年第4期6卷 35-45页

作者： Bozhao Wu Yongping Kang Cai Lu Langquan Shui Wengen Ouyang Qi Peng Qiankun He Ze Liu Department of Engineering Mechanics School of Civil EngineeringWuhan UniversityWuhan 430072HubeiChina School of Civil Engineering Architecture and Environment Hubei University of TechnologyWuhan 430068HubeiChina System Design Institute of Hubei Areospace Technology Academy Wuhan 430040China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China

The determination of solid–liquid interfacial tension plays an important role in science and ***,we propose a simple method to directly measure the contact angle between metal droplets and a graphite substrate for the determination of metal–graphite interfacial *** proposed method involves the synthesis of micro-and nanosized metal droplets on graphite by arc *** to its small volume,the rapid cooling of the prepared metal droplets on the graphite substrate leads to the freezing of equilibrium contact confguration after *** observe that the measured contact angle between micro-and nanosized Au(or Ag)particles and the graphite substrate is almost size independent,even though the size of the particles synthesized herein is 1–3 orders of magnitude smaller than that studied in previous *** addition,the interfacial tensions of Au and Ag on the step edges(edge plane)of graphite are found to be larger than that on the(0001)plane(basal plane).The proposed method provides a simple approach to determine the solid–liquid interfacial tension and may be efective in the study of interface related science and technology.

关键词： Metal droplets Graphite/graphenes Contact angle Interfacial tension

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