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Cloud–Edge Collaboration for Industrial Internet of Things: Scalable Neurocomputing and Rolling-Horizon Optimization

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IEEE Internet of Things Journal 2025年第12期12卷 19929-19943页

作者： Li, Qiyue Li, Lijuan Liu, Zhi Sun, Wei Li, Weitao Li, Jie Zhao, Wei Hefei University of Technology Engineering Technology Research Center of Industrial Automation Anhui Province School of Electrical Engineering and Automation Anhui Hefei230009 China University of Electro-Communications Department of Computer and Network Engineering Chofu182-8585 Japan Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Anhui University of Technology School of Computer Science and Technology Maanshan243099 China

Cloud–edge collaboration and edge intelligence have greatly driven the growth of the Industrial Internet of Things (IIoT). However, the jittery network delay and limited computational resources of edge servers make it difficult to meet the stringent latency requirements in IIoT, and so far there is no good solution to solve this problem. To this end, we introduce scalable neurocomputing, which provides neural networks with different utilities and computation resource requirements, to be deployed on edge servers of cloud–edge IIoT systems. We then optimize such systems by formulating data scheduling and system computational resource allocation as an infinite horizon optimization problem, considering that the data collection from end devices is an infinite long-term process. To solve this hard problem, we design a rolling prediction-optimization framework that transforms the infinite horizon problem into a truncated finite horizon optimization that maximizes the average system utility while satisfying the stringent delay constraints. We have conducted extensive simulations and built a prototype system, which verify the feasibility and performance of our proposed scheme. © 2014 IEEE.

关键词： Cloud platforms

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Grasshopper KUWAHARA and Gradient Boosting Tree for Optimal Features Classifications

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computers, Materials & Continua 2022年第8期72卷 3985-3997页

作者： Rabab Hamed M.Aly Aziza I.Hussein Kamel H.Rahouma The Higher Institute for Management and Information Technology Minya61768Egypt Department of Electrical and Computer Engineering Effat UniversityJeddahKSA Electrical Engineering Department Faculty of EngineeringMinia UniversityMinia6111Egypt

This paper aims to design an optimizer followed by a Kawahara filter for optimal classification and prediction of employees’*** algorithm starts by processing data by a modified K-means technique as a hierarchical clustering method to quickly obtain the best features of employees to reach their best *** work of this paper consists of two *** first part is based on collecting data of employees to calculate and illustrate the performance of each *** second part is based on the classification and prediction techniques of the employee *** model is designed to help companies in their decisions about the employees’*** classification and prediction algorithms use the Gradient Boosting Tree classifier to classify and predict the *** of the paper give the percentage of employees which are expected to leave the company after predicting their performance for the coming *** also show that the Grasshopper Optimization,followed by“KF”with the Gradient Boosting Tree as classifier and predictor,is characterized by a high *** proposed algorithm is compared with other known techniques where our results are fund to be superior.

关键词： Metaheuristic algorithm KUWAHARA filter Grasshopper optimization algorithm and Gradient boosting tree

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Grid-Forming Inverters for Enhancing Stability and Resilience in Distribution Networks under Transients and Restoration

Grid-Forming Inverters for Enhancing Stability and Resilienc...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Selim, Alaa Zhao, Junbo Seo, Gab-Su Ding, Fei Cui, Bai University of Connecticut Department of Electrical and Computer Engineering United States National Renewable Energy Laboratory Power Systems Engineering Center GoldenCO80401 United States Iowa State University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350313604

The increasing integration of distributed energy resources in distribution networks has significantly reduced system inertia, posing challenges to grid stability during transient events, such as Cold Load Pickup (CLPU). This paper proposes the implementation of grid-forming inverters (GFMs) to enhance the stability of low-inertia distribution systems. The paper also investigates the performance of the GFM-based approach in maintaining voltage profiles along the distribution feeder, especially during CLPU scenarios without synchronous machines. A comparison is made between the GFM-based system and the conventional synchronous machine setup. The synchronous machine is chosen as a reference point for evaluating the effectiveness of the GFM-based approach. The GFM-based system's performance is assessed under various challenging scenarios, including short-circuit faults, islanding, and a combination of these through extensive simulations. The results demonstrate the potential of GFMs to stabilize a distribution system and outperform the traditional rigid synchronous machine during transient events. © 2024 IEEE.

关键词： Electric power distribution

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Joint Activity Detection and Channel Estimation in MIMO Grant-Free Random Access Networks

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IEEE Transactions on Wireless Communications 2025年第6期24卷 4793-4808页

作者： Yang, Boran Zhang, Xiaoxu Hao, Li Karagiannidis, George K. Southwest Jiaotong University Provincial Key Laboratory of Information Coding and Transmission Chengdu611756 China Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki541-24 Greece

Massive machine communication is predicted to provide widespread and unparalleled connectivity for cellular Internet of Things (IoT) applications via multiple-input multiple-output (MIMO) and grant-free random access (GF-RA) techniques. Compressed sensing (CS) has been widely advocated to support massive connectivity due to the bursty nature of traffic transmission. In this paper, the joint activity detection and channel estimation in MIMO-enabled GF-RA system is formulated as a block single measurement vector (SMV) problem and efficiently addressed by using Bayesian-based CS algorithms. First, the pattern coupled sparse Bayesian learning (PCSBL) and block sparse Bayesian learning (BSBL) algorithms are introduced to solve this problem, where the potential block sparsity properties induced by multi-antenna reception are exploited by assigning the structured hyperpriors. Then, by embedding the Generalized Approximate Message Passing (GAMP) technique into the PCSBL and BSBL frameworks to enable effective approximation of posterior distributions, we propose two computationally efficient Bayesian learning algorithms, i.e., GAMP-PCSBL and GAMP-BSBL. Fortunately, the proposed Bayesian algorithms allow automatic learning of block sparse solutions without requiring noise level and user sparsity ratio as explicit conditions. Simulation results show that the proposed algorithms provide improved performance gains over the standard CS-based methods. © 2002-2012 IEEE.

关键词： Channel estimation

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Wideband Signal Generation Using Egyptian Fractions and Application to Instantaneous Impedance Measurements

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IEEE Sensors Journal 2025年第11期25卷 19555-19562页

作者： Majzoub, Sohaib Allagui, Anis Elwakil, Ahmed S. Zhang, Di University of Sharjah Departments of Electrical Engineering and Computer Engineering Sharjah United Arab Emirates University of Sharjah Department of Sustainable and Renewable Energy Engineering Sharjah United Arab Emirates Florida International University Department of Mechanical and Materials Engineering MiamiFL33174 United States Nile University Nanoelectronics Integrated Systems Center Cairo3242020 Egypt University of Calgary Department of Electrical and Software Engineering CalgaryT2N 1N4 Canada

In this work, we investigate the use of Egyptian fractions to construct wideband signals with a near-flat power spectrum. In particular, it is well-known that wideband signals can be obtained using composite multisine signals. However, the choice of the frequencies and/or phase shifts in these sinusoids is critical to approach a flat power spectrum with a low crest factor. A number of known methods, such as using Rudin-Shapiro polynomials or random phases, have been used in this problem. However, the use of Egyptian fractions has not been explored yet, despite being easier to generate and implement. Here, we construct multisine signals (in the form of a voltage) based on different Egyptian fraction sequences (EFSs) and use them to measure the linear time-invariant impedance of an RC circuit and then the instantaneous impedance of nonlinear time-varying solar cell. Two methods are used to generate these signals: 1) the EFSs are assigned to the phase angles or 2) they are used to set the values of the angular frequencies. The accuracy of measurements is assessed via comparison to the standard sine-sweep method using a research-grade Biologic VSP-300 electrochemical station showing acceptable results. © 2001-2012 IEEE.

关键词： Sheet resistance

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Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video

Disentangling Spatio-Temporal Knowledge for Weakly Supervise...

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2025 IEEE/CVF Winter Conference on Applications of computer Vision, WACV 2025

作者： Liao, Guiqiu Jogan, Matjaz Koushik, Sai Eaton, Eric Hashimoto, Daniel A. University of Pennsylvania Pcaso Laboratory Department of Surgery United States University of Pennsylvania Department of Electrical and Systems Engineering United States University of Pennsylvania Department of Computer and Information Science United States

ISBN: (纸本)9798331510831

Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring extensive annotations of object masks, relying instead on coarse video labels indicating object presence. WSVOS in surgical videos is, however, more challenging due to the complex interaction of multiple transient objects, such as surgical tools moving in and out of the surgical field. In this scenario, state-of-the-art WSVOS methods struggle to learn accurate segmentation maps. We address this problem by introducing ViDeo Spatio-Temporal disentanglement Networks (VDST-Net), a framework to disentangle complex spatio-temporal object interactions using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). A teacher network is designed to help a temporal-reasoning student network resolve activation conflicts, as the student leverages temporal dependencies when specifics about object location and timing in the video are not provided. We demonstrate the efficacy of our framework on a challenging surgical video dataset where objects are, on average, present in less than 60% of annotated frames, and compare our method to state-of-the-art methods on surgical data and on a public dataset commonly used to benchmark WSVOS. Our method outperforms state-of-the-art techniques and generates accurate segmentation masks under video-level weak supervision. Our code is available at: https://***/PCASOlab/VDST-net. © 2025 IEEE.

关键词： Image segmentation

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Electric Bike Security and Protection System 2

Electric Bike Security and Protection System

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Maniraj, P. Murugan, A. Durai Gokul, R. Shalini, A.S. Kesavan, K. Kavin, P. M. Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Karur India M. Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Computer Science and Business Systems Karur India M. Kumarasamy College of Engineering Electrical and Electronics Engineering Karur India

ISBN: (纸本)9798350349221

With the developing prevalence of electric bicycles (e-bicycles) as a feasible and proficient method of transportation, guaranteeing their security has turned into a foremost concern. Electric bicycles are important resources helpless against robbery and harm, to conquer this issue the venture proposes the improvement of an Electric Vehicle Burglary Location and Warning Framework utilizing IOT innovation. The framework integrates sensors to screen electric vehicles for unapproved access and utilizes Radio Recurrence ID innovation to improve security. After recognizing an unfair RFID section or any dubious movement, the framework sets off a caution to tell the proprietor and naturally locks the back tire, forestalling robbery. This framework could be an instrument for deflecting the robbery of electric vehicles and keeping proprietors from monetary misfortunes. In a period of developing IOT-based security arrangements, this framework offers an important expansion to safeguard electric vehicle and their venture. © 2024 IEEE.

关键词： Electric vehicles

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Wrist measurement for millimeter-wave non-invasive glucose monitoring: Numerical analysis of an anatomically realistic tissue model 46

Wrist measurement for millimeter-wave non-invasive glucose m...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Azuma, Lena Natsuaki, Ryo Hirose, Akira The University of Tokyo Department of Bioengineering Tokyo Japan The University of Tokyo Department of Electrical Engineering and Information Systems Tokyo Japan

ISBN: (纸本)9798350371499

This paper shows the advantages of wrist measurement for millimeter-wave (MMW) non-invasive glucose monitoring based on an anatomically realistic tissue model. The wrist possesses not only its good accessibility but also its thin epidermis and the existence of a radial artery, which enable MMW to acquire blood signals with a high sensitivity. We analyze their scattering characteristics according to blood glucose change in a frequency range of 60-90 GHz. Analysis results indicate that MMW senses skin microvasculature and radial artery, leading to high sensitivity to blood glucose levels. This work contributes to achieving reliable non-invasive blood glucose monitoring. © 2024 IEEE.

关键词： Glucose sensors

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A Review of Genome to Chaos: Exploring DNA Dynamics in Security

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Multimedia Tools and Applications 2024年 1-28页

作者： Aashiq Banu, S. Rao, L. Koteswara Priya, P. Shanmuga Thanikaiselvan Hemalatha, M. Dhivya, R. Rengarajan, Amirtharajan Department of Systems Engineering Military Technological College Muscat Oman Department of ECE Koneru Lakshmaiah Education Foundation Telangana Hyderabad500043 India Department of Electronics and Communication Engineering Rajalakshmi Engineering College ThandalamChennai602105 India Vellore632 014 India Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia Department of Electronics and Communication Engineering Mepco Schlenk Engineering College Tamilnadu Sivakasi626005 India School of Electrical & amp Electronics Engineering SASTRA Deemed University Thanjavur613401 India

One of the largest and fastest-growing industries globally is e-healthcare. Digital medical imaging constantly evolves, advancing from standard computed tomography to powerful multi-dimensional imaging. This medical imaging forms patients’ real-time electronic health records (EHR), making it a prime target for hackers. To counter cipher-attacks, it is necessary to secure medical imaging. This research thoroughly analyses the properties of DNA chaos-based digital medical image encryption and reviews various algorithms. Researchers have performed several statistical and differential metrics, conducting simulation experiments to determine which methodology provides the best security outcome. The paper concludes by analysing significant advances in medical image encryption and emphasising future challenges. This paper discusses the importance of securing medical images, the potential breaches, and the security needs, providing a comprehensive review of DNA-based chaos cryptography techniques. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Electronic health record

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Proposed Privacy Preservation Technique for Color Medical Images

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Intelligent Automation & Soft Computing 2023年第4期36卷 719-732页

作者： Walid El-Shafai Hayam A.Abd El-Hameed Noha A.El-Hag Ashraf A.M.Khalaf Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd El-Samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Nowadays,the security of images or information is very *** paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image ***,the secret medical image is encrypted using Advanced Encryption Standard(AES)***,the secret report of the patient is embedded into the encrypted secret medical image with the Least Signiﬁcant Bit(LSB)watermarking *** that,the encrypted secret medical image with the secret report is concealed in a cover medical image,using Kekre’s Median Codebook Generation(KMCG)***,the stego-image obtained is split into 16 ***,it is sent to the *** adopt this strategy to send the secret medical image and report over a network *** proposed technique is assessed with different encryption quality metrics including Peak Signal-to-Noise Ratio(PSNR),Correlation Coefﬁcient(Cr),Fea-ture Similarity Index Metric(FSIM),and Structural Similarity Index Metric(SSIM).Histogram estimation is used to conﬁrm the matching between the secret medical image before and after *** results demonstrate that the proposed technique achieves good performance with high quality of the received medical image and clear image details in a very short processing time.

关键词： LSB steganography AES algorithm KMCG algorithm

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