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Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

CAAI Transactions on Intelligence Technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad Nasir Saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

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ALF - Ambient Assisted Living for Healthcare Framework Based on IoMT and Big Data 7th

ALF - Ambient Assisted Living for Healthcare Framework Based...

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7th International Conference on Smart City Applications, SCA 2022

作者： Zahoor, Kanwal Bawany, Narmeen Zakaria Center for Computing Research Department of Computer Science and Software Engineering Jinnah University for Women Karachi74600 Pakistan

ISBN: (纸本)9783031268519

A rapid technology change has significant opportunities for almost every industry, especially for healthcare. By using advanced network technologies and Internet of Medical Things (IoMT) devices, health professionals can monitor remotely and respond to emergency cases efficiently. Ambient Assistive living (AAL) aims to improve living conditions for the elderly and disabled people. Data from heterogeneous sensors allow AAL systems to continuously monitor the health status of the elderly. The main contribution of this paper is to propose an Ambient Assisted Living Framework (ALF) for health care. The framework - ALF for health care comprises four layers namely, data sources, data integration, data analytics and ambient assisted living applications for healthcare. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Multi-Scale Fusion and Decomposition Network for Single Image Deraining

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IEEE Transactions on Image Processing 2024年 33卷 191-204页

作者： Wang, Qiong Jiang, Kui Wang, Zheng Ren, Wenqi Zhang, Jianhui Lin, Chia-Wen Wuhan University National Engineering Research Center for Multimedia Software School of Computer Science Wuhan430072 China Sun Yat-sen University School of Cyber Science and Technology Guangzhou510275 China Hangzhou Dianzi University College of Computer Science and Technology Hangzhou310018 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan

Convolutional neural networks (CNNs) and self-attention (SA) have demonstrated remarkable success in low-level vision tasks, such as image super-resolution, deraining, and dehazing. The former excels in acquiring local connections with translation equivariance, while the latter is better at capturing long-range dependencies. However, both CNNs and Transformers suffer from individual limitations, such as limited receptive field and weak diversity representation of CNNs during low efficiency and weak local relation learning of SA. To this end, we propose a multi-scale fusion and decomposition network (MFDNet) for rain perturbation removal, which unifies the merits of these two architectures while maintaining both effectiveness and efficiency. To achieve the decomposition and association of rain and rain-free features, we introduce an asymmetrical scheme designed as a dual-path mutual representation network that enables iterative refinement. Additionally, we incorporate high-efficiency convolutions throughout the network and use resolution rescaling to balance computational complexity with performance. Comprehensive evaluations show that the proposed approach outperforms most of the latest SOTA deraining methods and is versatile and robust in various image restoration tasks, including underwater image enhancement, image dehazing, and low-light image enhancement. The source codes and pretrained models are available at https://***/qwangg/MFDNet. © 1992-2012 IEEE.

关键词： Image reconstruction

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Integrating Chatbot Functionality in a Patient Summary Based Healthcare System

Integrating Chatbot Functionality in a Patient Summary Based...

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34th Medical Informatics Europe Conference, MIE 2024

作者： Vasili, Aliki Schiza, Eirini Schizas, Christos N. Pattichis, Constantinos S. Department of Computer Science and Biomedical Engineering Research Center University of Cyprus Cyprus CYENS Centre of Excellence Cyprus National eHealth Authority Cyprus

ISBN: (纸本)9781643685335

The integration of chatbots in healthcare has gained attention due to their potential to enhance patient engagement and satisfaction. This paper presents a healthcare chatbot providing comprehensive access to patient summaries, aligned with the European Patient Summary. Leveraging Natural Language Processing (NLP) capabilities, our chatbot employs intent classification using the fine-tuned bioBERT model to categorize user queries effectively and extract relevant information from the patient summary stored in a database. We detail our methodology, which involves dataset creation, hyperparameter tuning, and model evaluation. Results demonstrate the effectiveness of our approach, with the trained model achieving high precision, recall, and F1 score across intent classes. Our study underscores the potential of emerging NLP techniques in patient interaction and healthcare delivery, covering the way for smarter, user-friendly companions. © 2024 The Authors.

关键词： Electronic health record

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A Hybrid Approach for Enhancing Line Parameter Estimation in Power Systems

A Hybrid Approach for Enhancing Line Parameter Estimation in...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Asprou, Markos Panayiotou, Christos G. Stavrou, Andreas University of Cyprus Kios Research and Innovation Center of Excellence Department of Electrical and Computer Engineering Nicosia Cyprus Electricity Authority of Cyprus Nicosia Cyprus

ISBN: (纸本)9789531842976

Accurate modeling of power systems is crucial for various control center applications. One of the key components in a power system model is the transmission lines. The line model includes parameters such as series impedance and shunt admittance, which are typically assumed to be time-invariant. However, these parameters vary based on the ambient and operating conditions of the system. Therefore, it is essential for the different monitoring and protection applications of the power system to have an accurate visualization of the line parameter variance throughout the day. In this context, this paper develops a hybrid line parameter estimation scheme that makes use of the available Phasor Measurement Unit (PMUs) measurements and Neural Network (NN) estimations to calculate the series line parameters of the transmission lines. The developed scheme was tested in the IEEE 14-bus system under realistic ambient and operating conditions, showcasing its practical applicability and enhanced accuracy. © 2024 IEEE.

关键词： Phasor measurement units

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment 31

A Modified Dempster Shafer Approach to Classification in Sur...

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31st International Conference on Electrical engineering, ICEE 2023

作者： Iranfar, Arash Soleymannejad, Mohammad Moshiri, Behzad Taghirad, Hamid D. School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada Industrial Control Center of Excellence Faculty of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350312560

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is. © 2023 IEEE.

关键词： Classification (of information)

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Electromyography (EMG) Signal Acquisition for Exoskeleton Control: Enhancing Precision in Human-Machine Interaction

Electromyography (EMG) Signal Acquisition for Exoskeleton Co...

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2024 International Conference on Smart Electronics and Communication Systems, ISENSE 2024

作者： Rajendra Thilahar, C. Manoharan, Madhanagopal Sudalai, Perumal Kumaravelu, R. Sadayan, Rajendra Boopathy Kaliaraj, Gobi Saravanan Saveetha Engineering college Department of Computer Science and Engineering Chennai India Makerspace Center of Excellence for Additive Manufacturing Sathyabama Institute of Science and Technology Chennai India Karpaga Vinayaga College of Engineering and Technology Department of Mechanical Engineering Chennai India Saveetha Engineering College Department of Artificial Intelligence and Data Science Tamilnadu Chennai India College of Engineering Guindy Anna University Department of Mechanical Engineering Chennai India Center of Excellence for Additive Manufacturing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798331528126

Electromyography (EMG) signals, which measure the electrical activity of muscles during contraction, deal with the hope of controlling the actions of the exoskeleton. This paper exposes the acquisition and application of EMG signals for precise and responsive control of exoskeletons. Moreover, the natural neuromuscular signals generated by the user aim to create a seamless interface between the human body and the assistive device, enhancing functionality and user experience. The EMG signals are obtained by placing the electrodes in the respective area of our body, filtering the data, signal amplification, and using noise reduction techniques. Furthermore, EMG data is processed for noise removal, where artefacts ensure the clarity and reliability of the acquired signals. Those signals were used to develop a control algorithm to translate muscle activity into corresponding exoskeleton movements. The challenges and limitations associated with EMG-based controls are signal variability, cross-talk, and calibration. Finally, this paper presents results, which demonstrate that EMG-based control offers a high degree of accuracy and responsiveness, especially requiring to control the fine motor rotation and varying force levels. This approach not only improves the usability of exoskeletons for individuals with mobility impairments but also has certain potential applications like EMG-controlled exoskeletons in various domains, including rehabilitation, assistive technology, various military settings and human-machine interfaces. EMG-driven systems to revolutionize the field of wearable robotics, paving the way for more intuitive and effective human-machine interfaces. © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi Gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

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Global video object segmentation with spatial constraint module

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Computational Visual Media 2023年第2期9卷 385-400页

作者： Yadang Chen Duolin Wang Zhiguo Chen Zhi-Xin Yang Enhua Wu Engineering Research Center of Digital Forensics Ministry of EducationSchool of Computer and SoftwareNanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Internet of Things for Smart City Department of Electromechanical EngineeringUniversity of MacaoMacao 999078China State Key Laboratory of Computer Science Institute of SoftwareUniversity of Chinese Academy of SciencesBeijing 100190China Faculty of Science and Technology University of MacaoMacao 999078China

We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory *** some extent,our method solves the two difficulties encountered in traditional video object segmentation:one is that the single frame calculation time is too long,and the other is that the current frame’s segmentation should use more information from past *** algorithm uses a global context(GC)module to achieve highperformance,real-time *** GC module can effectively integrate multi-frame image information without increased memory and can process each frame in real ***,the prediction mask of the previous frame is helpful for the segmentation of the current frame,so we input it into a spatial constraint module(SCM),which constrains the areas of segments in the current *** SCM effectively alleviates mismatching of similar targets yet consumes few additional *** added a refinement module to the decoder to improve boundary *** model achieves state-of-the-art results on various datasets,scoring 80.1%on YouTube-VOS 2018 and a J&F score of 78.0%on DAVIS 2017,while taking 0.05 s per frame on the DAVIS 2016 validation dataset.

关键词： video object segmentation semantic segmentation global context(GC)module spatial constraint

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Interaction of the spatial configurations and active mobility in megacity, Thailand

Interaction of the spatial configurations and active mobilit...

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2023 International Conference on Industry Sciences and computer Science Innovation, iSCSi 2023

作者： Iamtrakul, Pawinee Chayphong, Sararad Kantavat, Pittipol Center of Excellence in Urban Mobility Research and Innovation Faculty of Architecture and Planning Thammasat University Pathumthani12120 Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand

Healthy living and well-being at all ages are one of the UN Sustainable Development Goals. Active mobility is a must as a basic choice for healthy individuals and communities in sustainable cities. However, commuting by walking presents a critical challenge in the city with rapid urbanization, leading to auto dependency rather than a non-motorized mode of residents' daily mobility. By employing spatial configurations of urban physical elements, the interaction between its association and active mobility can be unfolded. Bangkok, a megacity in Thailand, is used as a case study for the objective assessments by generating data from on-street images and incorporating it into the analysis through geographic information systems (GIS). The finding based on the results of spatial configurations related to the pedestrian volume can then be quantified. The linkage between the physical environment-both sidewalks and their surrounding context-can demonstrate its significance in term of relationship. This information is useful for promoting compact urban development with consideration of the availability of transportation systems, especially public transport, which can lead to the promotion of healthy cities and environmental protection while solving traffic problems. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Sustainable development

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