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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Wang, Mengdi Wang, Shaohong Ma, Chao Key Laboratory of Modern Measurement and Control Technology Ministry of Edu. Beijing Information Science and Technology Beijing China Beijing Key Lab of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology Beijing China

ISBN: (纸本)9781837242672

The need for assistive devices such as lower limb exoskeletons is steadily growing, making quick and precise gait recognition essential for optimal operation of these apparatuses. The knowledge distillation method was applied to gait recognition in this work. First, we took participant lower limb gait data, which we then resampled with step frequency taken into account. Next, multi-layer perceptron (MLP) with distinct layers were modeled by educators and students. The process of knowledge distillation was used to improve the accuracy of participant activity recognition by transferring knowledge from the sophisticated teacher model to the lightweight student model. On the training set, the teacher model's accuracy average was 96.4%. Following the process of knowledge distillation, the accuracy of the student model was 95.48%, representing a 1.12% improvement compared to the non-distilled model, with only 0.53M parameters and shorter training duration. The results demonstrate that knowledge distillation can improve the recognition speed and stability of gait recognition models, enabling more accurate and reliable results within the same patient population, thus providing more effective support for medical diagnosis and rehabilitation treatment. © The Institution of engineering & technology 2024.

关键词： Exoskeleton (Robotics)

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Ozone-based advanced oxidation processes in water treatment: recent advances, challenges, and perspective

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Environmental science and Pollution Research 2025年第7期32卷 3531-3570页

作者： Mahmoodi, Mohammadreza Pishbin, Esmail Department of Civil Architectural and Environmental Engineering The University of Texas at Austin 2515 Speedway AustinTX78712 United States Bio-Microfluidics Lab Department of Electrical Engineering and Information Technology Iranian Research Organization for Science and Technology Tehran Iran

Water pollution, driven by a variety of enduring contaminants, poses considerable threats to ecosystems, human health, and biodiversity, highlighting the urgent need for innovative and sustainable treatment approaches. Ozone-based advanced oxidation processes (AOPs) have demonstrated significant efficacy in breaking down stubborn pollutants, such as organic micropollutants and pathogens, that are not easily addressed by traditional treatment techniques. This review offers an in-depth analysis of ozonation mechanisms, covering both the direct oxidation by ozone and the indirect reactions facilitated by hydroxyl radicals, emphasizing their effectiveness and adaptability across various wastewater matrices. Significant progress in the combination of ozonation with additional technologies, including UV irradiation, hydrogen peroxide (H₂O₂), catalytic systems, and biological treatments, is examined, highlighting their effectiveness in enhancing pollutant breakdown, increasing biodegradability, and reducing secondary pollution. Hybrid methods, including catalytic ozonation and ozone-biological treatment, show significant enhancements in process efficiency and cost-effectiveness, while effectively tackling challenges associated with energy use and byproduct generation. Despite the promising possibilities, obstacles remain, such as scalability issues, high operational costs, and the risk of generating potentially harmful transformation products. Cutting-edge approaches, including the creation of sophisticated catalysts, integration of processes, and refinement of reactor designs, are suggested to address these challenges and improve the real-world implementation of ozone-based advanced oxidation processes. This review highlights the significant potential of ozone-based advanced oxidation processes as sustainable approaches for wastewater treatment, providing an essential route to environmental conservation and safeguarding public health. © The Author(s), under exclusive lice

关键词： Ozonization

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Deep Learning to Classify Bacterial Species in the same Genus

Deep Learning to Classify Bacterial Species in the same Genu...

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2024 International Conference on Electronics, information, and Communication, ICEIC 2024

作者： Sheela, Sherin Piang, May Phu Sakorntanant, Sakda Poomrittigul, Suvit Treebupachatsakul, Treesukon School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Biomedical Engineering Thailand Pathumwan Institute of Technology Faculty of Science and Technology Department of Software Engineering and Information System Bangkok Thailand School of Information Technology King Mongkut's Institute of Technology Ladkrabang Thailand

ISBN: (纸本)9798350371888

Bacterial strains in the same genus share highly similar morphology, gram-staining characteristics, colony sizes, and spatial arrangements. Therefore, identifying them by deep learning can be quite challenging. This study aimed to assess the classification of 7 species of bacteria from 2 genera of Bacillus and Vibrio by using 8 Convolutional Neural Network (CNN) models. We implemented Python programming along with Keras API within the Jupyter Notebook. The models were constructed and evaluated under unbalanced and balanced datasets by augmentation (rotation, flip, etc.). Transfer learning with fine-tuning, and pre-processing of mixup and label smoothing were also applied to reduce overfitting and enhance generalization. Based on the experimental results on private dataset, the results of InceptionResNetV2 emerged as the top-performing model with a notable accuracy of 82.8%, 88.6% precision, 78.4% recall, and 78.0% F1-score when label smoothing was applied at 0.5 on balanced dataset. © 2024 IEEE.

关键词： Neural network models

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FedRKG: A Privacy-Preserving Federated Recommendation Framework via Knowledge Graph Enhancement 18th

FedRKG: A Privacy-Preserving Federated Recommendation Framew...

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18th International Conference on Green, Pervasive, and Cloud Computing, GPC 2023

作者： Yao, Dezhong Liu, Tongtong Cao, Qi Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computing Science University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9789819998951

Federated Learning (FL) has emerged as a promising approach for preserving data privacy in recommendation systems by training models locally. Recently, Graph Neural Networks (GNN) have gained popularity in recommendation tasks due to their ability to capture high-order interactions between users and items. However, privacy concerns prevent the global sharing of the entire user-item graph. To address this limitation, some methods create pseudo-interacted items or users in the graph to compensate for missing information for each client. Unfortunately, these methods introduce random noise and raise privacy concerns. In this paper, we propose FedRKG, a novel federated recommendation system, where a global knowledge graph (KG) is constructed and maintained on the server using publicly available item information, enabling higher-order user-item interactions. On the client side, a relation-aware GNN model leverages diverse KG relationships. To protect local interaction items and obscure gradients, we employ pseudo-labeling and Local Differential Privacy (LDP). Extensive experiments conducted on three real-world datasets demonstrate the competitive performance of our approach compared to centralized algorithms while ensuring privacy preservation. Moreover, FedRKG achieves an average accuracy improvement of 4% compared to existing federated learning baselines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Recommender systems

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Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models 41

Intersecting-Boundary-Sensitive Fingerprinting for Tampering...

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41st International Conference on Machine Learning, ICML 2024

作者： Bai, Xiaofan He, Chaoxiang Ma, Xiaojing Zhu, Bin Benjamin Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China Microsoft United States School of Computer Science and Technology Huazhong University of Science and Technology China Cluster and Grid Computing Lab China

Cloud-based AI services offer numerous benefits but also introduce vulnerabilities, allowing for tampering with deployed DNN models, ranging from injecting malicious behaviors to reducing computing resources. Fingerprint samples are generated to query models to detect such tampering. In this paper, we present Intersecting-Boundary-Sensitive Fingerprinting (IBSF), a novel method for black-box integrity verification of DNN models using only top-1 labels. Recognizing that tampering with a model alters its decision boundary, IBSF crafts fingerprint samples from normal samples by maximizing the partial Shannon entropy of a selected subset of categories to position the fingerprint samples near decision boundaries where the categories in the subset intersect. These fingerprint samples are almost indistinguishable from their source samples. We theoretically establish and confirm experimentally that these fingerprint samples' expected sensitivity to tampering increases with the cardinality of the subset. Extensive evaluation demonstrates that IBSF surpasses existing state-of-the-art fingerprinting methods, particularly with larger subset cardinality, establishing its state-of-the-art performance in black-box tampering detection using only top-1 labels. The IBSF code is available at: https://***/CGCL-codes/IBSF. Copyright 2024 by the author(s)

关键词： HTTP

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PERIODIC STATISTICAL ANALYSIS OF GAIT PHASE SEGMENTATION 10

PERIODIC STATISTICAL ANALYSIS OF GAIT PHASE SEGMENTATION

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Fu, Mingkai Wang, Shaohong Ma, Chao Key Laboratory of Modern Measurement and Control Technology Ministry of Edu. Beijing Information Science and Technology Beijing China Beijing Key Lab of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology Beijing China

ISBN: (纸本)9781837242672

In order to achieve accurate segmentation of gait phases for precise real-time control of lower limb exoskeleton robots, the periodic statistical analysis of human motion posture by using the inertial measurement unit is conducted. In current research, the data of forward and turning gait types were acquired and every gait type data were devised into eight for different gait phase segmentation. During the process, the phase division values for different types of subjects were calculated and the phase division of different subjects with the same gait type was calculated. The standard deviations for different gaits and phases for the same experimenter are all below 10, primarily oscillated around 4. For gait data from different subjects, the percentages at the same phase are all below 3. The results showed that the results from the feasible method could better accord with the characteristics of each stage of actual *** those results could provide reference for real-time judgment of gait phase and technical support for intelligent control of lower limb exoskeletons. © The Institution of engineering & technology 2024.

关键词： Exoskeleton (Robotics)

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R3 - Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic systems

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IEEE Access 2023年 11卷 119284-119312页

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Yee, Por Lip Ku, Chin Soon Alexan, Wassim Faculty of Media Engineering and Technology Computer Science Department Cairo11835 Egypt National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia Faculty of Information Engineering and Technology Communications Department Cairo11835 Egypt New Administrative Capital Mathematics Department Cairo13507 Egypt

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm's efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age. © 2013 IEEE.

关键词： Cryptography

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Brillouin Frequency Shift Extraction for BOTDA Based on Gramian Angular Fields 4

Brillouin Frequency Shift Extraction for BOTDA Based on Gram...

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4th International Computational Imaging Conference, CITA 2024

作者： Zhu, Borong Zhang, Zhihao Qian, Yuhao Ma, Xiaole Wang, Liang Yu, Kuanglu Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Laboratory for Next Generation Internet Access System School of Optics and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510688834

To accurately extract Brillouin frequency shift of BOTDA with large sweeping step sizes, a novel structure of GAFCNN is proposed, combining time series coding with convolutional neural networks. The experimental data validation results demonstrate that the GAFCNN is capable of obtaining more accurate results under large sweep steps and low signal-to-noise ratios (SNRs) than other current methods. © 2025 SPIE.

关键词： Convolutional neural networks

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Coexistence of Distributed Sensing and Ultra-simple Coherent RoF based Front-haul for Radio Access Network

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Journal of Lightwave technology 2025年第12期43卷 5669-5675页

作者： Liu, Maoqi Wang, Jingchuan Liu, Chen Yu, Changyuan Lu, Chao Huazhong University of Science and Technology National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Wuhan430074 China The Hong Kong Polytechnic University Photonics Research Institute Department of Electrical and Electronic Engineering Hong Kong

The radio access network requires high-speed transmission and multifunctionality to support the increasing demand for advanced communication services. Radio-over-fiber (RoF) technology fulfills these requirements by enabling the delivery of millimeter-wave (MMW) band wireless signals via optical fiber front-haul. This paper presents an ultra-simple RoF system that achieves the coexistence of distributed sensing and telecommunication. A commercially available coherent modulator achieves signal modulation and remote up-conversion by the beat between the residual carrier and the modulated radio signal. The linear-frequency modulated carrier enables distributed sensing while simultaneously serving as the beat tone of RoF communication, showcasing the potential for integrated sensing and communication (ISAC) applications in next-generation radio access networks. We demonstrate the sensing and transmission performance over a 10-km fiber link and a 1-m wireless MMW channel. The system achieves a distributed sensing detection sensitivity of 28 pΕ/√ Hz and supports 1.6 GBaud 16QAM radio transmission in the Ka-band of 28 GHz. © 1983-2012 IEEE.

关键词： Radio access networks

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