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arXiv 2024年

作者： Lin, Yuxuan Chang, Yang Tong, Xuan Yu, Jiawen Liotta, Antonio Huang, Guofan Song, Wei Zeng, Deyu Wu, Zongze Wang, Yan Zhang, Wenqiang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai200438 China Shanghai Engineering Research Center of AI & Robotics Academy for Engineering & Technology Fudan University Shanghai200438 China Faculty of Computer Science Free University of Bozen-Bolzano Bolzano39100 Italy College of Information Technology Shanghai Ocean University Shanghai201306 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China

In the advancement of industrial informatization, unsupervised anomaly detection technology effectively overcomes the scarcity of abnormal samples and significantly enhances the automation and reliability of smart manufacturing. As an important branch, industrial image anomaly detection focuses on automatically identifying visual anomalies in industrial scenarios (such as product surface defects, assembly errors, and equipment appearance anomalies) through computer vision techniques. With the rapid development of Unsupervised industrial Image Anomaly Detection (UIAD), excellent detection performance has been achieved not only in RGB setting but also in 3D and multimodal (RGB and 3D) settings. However, existing surveys primarily focus on UIAD tasks in RGB setting, with little discussion in 3D and multimodal settings. To address this gap, this artical provides a comprehensive review of UIAD tasks in the three modal settings. Specifically, we first introduce the task concept and process of UIAD. We then overview the research on UIAD in three modal settings (RGB, 3D, and multimodal), including datasets and methods, and review multimodal feature fusion strategies in multimodal setting. Finally, we summarize the main challenges faced by UIAD tasks in the three modal settings, and offer insights into future development directions, aiming to provide researchers with a comprehensive reference and offer new perspectives for the advancement of industrial informatization. Corresponding resources are available at https://***/Sunny5250/Awesome-Multi-Setting-UIAD. Copyright © 2024, The Authors. All rights reserved.

关键词： Smart manufacturing

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Enhancing Federated Learning by One-Shot Transferring of Intermediate Features from Clients

Enhancing Federated Learning by One-Shot Transferring of Int...

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International Conference on Data science and advanced Analytics (DSAA)

作者： Youxingzhu Deng Yipeng Zhou Gang Liu Jessie Hui Wang Yu Shui College of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Computing Faculty of Science and Engineering Macquarie University Sydney Australia Institute for Network Sciences and Cyberspace Tsinghua University Peking China School of Computer Science University of Technology Sydney Sydney Australia

Federated learning (FL) is an emerging paradigm using a parameter server (PS) to coordinate multiple decentralized clients for training a common model without exposing their raw data. Despite its amazing capability in preserving data privacy, FL confronts two significant challenges that have not been sufficiently addressed by existing works, which are: 1) heterogeneous data distributed on clients given that the PS cannot alter data locations. 2) limited computation resources of FL clients who may conduct model training with mobile devices. To tackle these challenges, we propose a novel federated one-shot transferring of intermediate features (FedOTF) algorithm. More specifically, FedOTF consists of two stages: feature extraction and model reconstruction. To overcome challenge 1, clients in stage 1 only collaboratively train a small model in a federated manner, with the objective to extract features. In stage 2, intermediate features (generated by the small model trained by stage 1) are transferred from clients to the PS so that a large model can be trained to overcome challenge 2. In addition, the design of FedOTF is robust, which can flexibly diminish the number of communication rounds of stage 1 when network capacity is limited, and reduce the amount of exposed features when privacy is concerned. To verify the superiority of FedOTF, we conduct comprehensive experiments with real datasets. The experiment results demonstrate that FedOTF can significantly improve the model utility of FL because a better model can be finally obtained by the PS without incurring heavy computational load on clients. Besides, we conduct robustness evaluation of FedOTF which can achieve stable performance when varying network capacity and privacy requirement.

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Towards Efficient MIT query in Trajectory Data

Towards Efficient MIT query in Trajectory Data

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International Conference on Data engineering

作者： Jian Chen Hong Gao Kaiqi Zhang Jiachi Wang Yubo Luo Zhenqing Wu Jianzhong Li Faculty of Computing Harbin Institute of Technology Harbin China College of Mathematics and Computer Science Zhejiang Normal University Jinhua China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Maximizing Influence (Max-Inf) query is a fundamental operation in spatial data management. Given a set of weighted objects, this query aims to find an optimal location from a candidate set to maximize its influence, which is the total weight of its reverse nearest neighbors. Existing work commonly assumes that every object is in a fixed location. In real life, however, there are a wide variety of drive-in services (e.g., food joints, fuel stations, ATMs, etc.) that are widely accessed by mobile users (i.e., trajectories) instead of the fixed ones. It is urgent and challenging to solve the Max-Inf query in trajectory data (MIT). In this paper, we first define the MIT query which aims to find the optimal location to maximize the total weight of influenced trajectories. We propose a novel index structure, QB-tree to hierarchically group trajectories with similar activity regions together for subsequent unified processing, and classify trajectories inside the same node into multiple buckets according to their motion patterns. For each bucket, we construct a rectilinear polygon using the trajectories in it to exclude some irrelevant areas in the minimum boundary rectangle. Moreover, we develop a branch-and-bound approach called BBM to efficiently solve the MIT query. The algorithm adaptively partitions the candidates into disjoint regions and prunes the regions without containing optimal results. Then, by exploiting the QB-tree, the upper and lower bounds are efficiently computed with three-level pruning technique. Finally, we conduct extensive experiments on real and synthetic datasets to evaluate our index and algorithms, and the experimental results demonstrate that our algorithm has high performance in terms of efficiency, scalability, and genericity.

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Analog, Programmable Switched Capacitor FIR Filter Based on Rotator Architecture Implemented in CMOS technology

Analog, Programmable Switched Capacitor FIR Filter Based on ...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Paweł Pawłowski Rafał Długosz Marek Radkowski Mateusz Wątły Adam Dąbrowski Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Signal Processing and Electronic Systems Poznań University of Technology Poznań Poland Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Bydgoszcz Poland

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip.

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Postural Synergy Analysis of Continuous Hand Movements for Application to Prosthetic Hands

Postural Synergy Analysis of Continuous Hand Movements for A...

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International Congress on Image and Signal Processing, BioMedical engineering and Informatics (CISP-BMEI)

作者： Hai Jiang Yusuke Yamanoi Peiji Chen Xu Yong Guanglin Li Hiroshi Yokoi Xiaobei Jing Shenzhen Institute of Advanced Technology (SIAT) Chinese Academy of Sciences (CAS) Shenzhen China Department of Mechanical Engineering and Intelligent Systems The Univiersity of Electro-Communications Tokyo Japan Department of Elecrical Engineering Faculty of Engineering Tokyo University of Science Tokyo Japan

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

This paper focuses on exploring the coordinated movements used to control dexterous myoelectric prosthetic hands by hand motion analysis inspired by the motor synergy theory of the human hand. Recently, prosthetic hands have become multi-degree-of-freedom, and simultaneous proportional control of each finger is the most required challenge. In response to this problem, motor synergy is expected to play a key role in constructing the control method because it reduces the amount of information on the control object. In the experiment, we used a Leap Motion controller to measure 60 continuous hand movement data from four healthy individuals, analyzed based on principal component analysis methods, and extracted several principal component data used by humans to control various grasping movements. We produced a hand model with 19 degrees of freedom for visualizing the principal component data. The results of the visualization showed similarities in postural synergies among the four healthy individuals used to control continuous hand movements. Based on the acquired synergies, the number of learning data for the control method of myoelectric prosthetic hands will be greatly reduced.

关键词： Hands Proportional control Data visualization Signal processing Motors Motion measurement Motion analysis Informatics Prosthetic hand Principal component analysis

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Analysis of Typical Features Using an Angle-to-sEMG Decoder Model

Analysis of Typical Features Using an Angle-to-sEMG Decoder ...

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International Congress on Image and Signal Processing, BioMedical engineering and Informatics (CISP-BMEI)

作者： Zehao Liu Hai Jiang Yusuke Yamanoi Peiji Chen Xiaobei Jing Guanglin Li Hiroshi Yokoi Xu Yong Department of Mechanical Engineering and Intelligent Systems Univiersity of Electro-Communications Tokyo Japan Chinese Academy of Sciences (CAS) Shenzhen Institute of Advanced Technology (SIAT) Shenzhen China Department of Elecrical Engineering Faculty of Engineering Tokyo University of Science Tokyo Japan

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Current prosthetic control methods mainly rely on extensive data collection and the training of classification models. Nevertheless, achieving a balance between learning efficiency and classification accuracy remains a persistent challenge. In this paper, we introduce a novel prosthetic control approach that divides the processing of surface electromyography (sEMG) signals into two stages to predict corresponding joint angles. Initially, a pretrained model is utilized to infer the associated joint angles based on typical features. This methodology necessitates the mapping of individual sEMG signals to these typical features through a compact mapping network during application. we think that it will enhance hand motion recognition accuracy while minimizing learning duration though a pre-training approach. This study represents the initial phase, which involves the acquisition and evaluation of the similarity among typical features linked to joint angles. To this end, we constructed angle-to-sEMG models (decoders) and input the same unprocessed continuous joint angle data into the decoders of five participants. Subsequently, we utilized the resultant typical features as inputs for the encoders of different individuals. The findings indicate that, notwithstanding interindividual variability, there exists a degree of resemblance in the typical features associated with joint angles, thus enabling the generation of angle data resembling the true angles even across diverse subjects.

关键词： Training Analytical models Accuracy Biological system modeling Signal processing Electromyography Data models Decoding Surface treatment Prosthetics

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A Study on Impact-Aware Aerial Robots Colliding with the Environment at Non-Vanishing Speed

A Study on Impact-Aware Aerial Robots Colliding with the Env...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Gayatri Indukumar Alessandro Saccon Antonio Franchi Chiara Gabellieri Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to recover from impacts. The method leverages a reactive strategy not requiring low-level changes to the motion controller commonly implemented onboard quadrotors, which might be not viable or not desirable for most users. Extensive simulation tests show that the proposed strategy considerably increases the tolerated velocity at impact in tasks in which the robot either picks an object up or collides against an object to clear its way. Preliminary experimental results using Crazyflie UAVs are also presented.

关键词： Trajectory tracking Dynamics Lead Autonomous aerial vehicles Stability analysis Robustness computer crashes Trajectory Robots Quadrotors

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A Survey on Web Application Testing: A Decade of Evolution

arXiv

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arXiv 2024年

作者： Li, Tao Huang, Rubing Cui, Chenhui Towey, Dave Ma, Lei Li, Yuan-Fang Xia, Wen School of Computer Science and Engineering Macau University of Science and Technology Macau Taipa999078 China Macau University of Science and Technology Zhuhai MUST Science and Technology Research Institute Guangdong Province Zhuhai519099 China School of Computer Science University of Nottingham Ningbo China Zhejiang Ningbo999078 China School of Science University of Tokyo Tokyo113-0033 Japan Faculty of Information Technology Monash University MelbourneVIC Australia School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen518055 China

As one of the most popular software applications, a web application is a program, accessible through the web, to dynamically generate content based on user interactions or contextual data, for example, online shopping platforms, social networking sites, and financial services. Web applications operate in diverse environments and leverage web technologies such as HTML, CSS, JavaScript, and Ajax, often incorporating features like asynchronous operations to enhance user experience. Due to the increasing user and popularity of web applications, approaches to their quality have become increasingly important. Web Application Testing (WAT) plays a vital role in ensuring web applications’ functionality, security, and reliability. Given the speed with which web technologies are evolving, WAT is especially important. Over the last decade, various WAT approaches have been developed. The diversity of approaches reflects the many aspects of web applications, such as dynamic content, asynchronous operations, and diverse user environments. This paper provides a comprehensive overview of the main achievements during the past decade: It examines the main steps involved in WAT, including test-case generation and execution, and evaluation and assessment. The currently available tools for WAT are also examined. The paper also discusses some open research challenges and potential future WAT work. © 2024, CC BY.

关键词： Software testing

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on advanced Communications technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research Institute - GIRI.

关键词： Malware

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Efficient Detection of Invasive Stink Bugs Using Convolutional Neural Networks

Efficient Detection of Invasive Stink Bugs Using Convolution...

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Telecommunications Forum (TELFOR)

作者： Alexandru Dinca Nicoleta Angelescu Loretta Ichim Trandafir-Liviu Serghei Dan Popescu Faculty of Automatic Control and Computer Science National University of Science and Technology Politehnica Bucharest Bucharest Romania Faculty of Electrical Engineering Electronics and Information Technology Valahia University of Targoviste Targoviste Romania

Timely pest detection and identification is critical as part of modern agriculture. Halyomorpha Halys is a prevalent pest with proven harmful impacts on numerous crops and agricultural regions. The paper proposes an efficient model to improve the detection of two invasive stink bugs: Halyomorpha halys and Nezara Viridula. Automatic detection of these two bugs is essential in various fields, such as precision agriculture and integrated pest management. The high performances obtained in the present study open new perspectives for the further development of insect pest detection systems and can serve as a basis for future modifications and improvements of these models.

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