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TCOA: Triple-Check Offloading Algorithm for Roadside Units and Vehicular Microclouds in 5G Networks and Beyond

IEEE Access 2023年 11卷 84985-85001页

作者： Qiu, Bo-Jun Hsieh, Cheng-Ying Chen, Jyh-Cheng Dressler, Falko National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan Tu Berlin School of Electrical Engineering and Computer Science Berlin10623 Germany

Next-generation intelligent transportation systems aim to achieve many cooperative perception and cooperative driving functions that require considerable computational resources. Offloading such tasks via mobile edge computing is considered part of the solution;this approach is currently being studied within the scope of 5G networks and beyond. In the automotive context, such edge systems could be roadside units (RSUs), which can easily be overloaded at peak times. Vehicular microcloud approaches have been proposed to overcome such problems by sharing the computational resources of nearby cars. In this study, we propose an offloading system architecture to enable such offloading in a vehicular microcloud interconnected by a 5G core network. We model the system as a queueing model to derive closed-form solutions for selected performance metrics. Based on our insights, we propose the triple-check offloading algorithm (TCOA) to obtain both the best offloading ratio of the vehicular microcloud to the entire offloading system and the optimal maximum number of the remaining vehicle instances in the vehicular microcloud. Our simulation results show that the proposed TCOA achieves better system performance than four other offloading schemes in terms of cost, response time, service rate, and cost response-time production service rate division (CRPSD). © 2013 IEEE.

关键词： 5G mobile communication systems

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Implications of EU Battery Regulation on Circular Economy: Barriers and Opportunities for Repurposing Electric Vehicle Batteries

Implications of EU Battery Regulation on Circular Economy: B...

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

作者： Lin, Yi-Chun Beyene, Yared Bekele Tjernberg, Lina Bertling Kth Royal Institute of Technology School of Electrical and Computer Science Stockholm Sweden Addis Ababa University School of Electrical and Computer Engineering Addis Ababa Ethiopia

ISBN: (纸本)9789531842976

This paper presents a study of the impact of EU battery regulations, specifically Regulation (EU) 2023/1542, on end-of-life batteries, primarily focusing on repurposing within the supply chain. Qualitative data was gathered from stakeholders in the battery supply chain using a combination of surveys and interviews. interviews provide deeper insights into aspects beyond the survey's scope, enhancing our understanding of how EU regulations influence the supply chain. The findings reveal a nuanced landscape where EU regulations bring advantages through defined producer responsibilities, improved safety standards, and facilitated data sharing. The study explores various circular business models within this context, emphasizing the need for a functional value network and effective stakeholder coordination. This research contributes valuable insights as the EU pursues circularity in the battery supply chain. By addressing barriers, capitalizing on opportunities, and promoting collaboration, it supports a sustainable and circular future in the EV battery supply chain, optimizing initial investments and aligning with the energy transition goals. © 2024 IEEE.

关键词： Battery Pack

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Slow Convergence of interacting Kalman Filters in Word-of-Mouth Social Learning 60

Slow Convergence of Interacting Kalman Filters in Word-of-Mo...

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60th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2024

作者： Krishnamurthy, Vikram Rojas, Cristian R. School of Electrical and Computer Engineering Cornell University United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798331541033

We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measurement of the conditional mean of the previous Kalman filter. The prior is updated by the m-th Kalman filter. When m=2, and the observations are noisy measurements of a Gaussian random variable, the covariance goes to zero as k-1/3 for 7kappa;observations, instead of O(k-1) in the standard Kalman filter. In this paper we prove that for m agents, the covariance decreases to zero as k-(2m-1), i.e, the learning slows down exponentially with the number of agents. We also show that by artificially weighing the prior at each time, the learning rate can be made optimal as k-1. The implication is that in word-of-mouth social learning, artificially re-weighing the prior can yield the optimal learning rate. © 2024 IEEE.

关键词： Kalman filters

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MIMO IMPEDANCE MODELLING OF GRID FOLLOWING INVERTER WITH LOCAL VOLTAGE CONTROL 14

MIMO IMPEDANCE MODELLING OF GRID FOLLOWING INVERTER WITH LOC...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Saridaki, Georgia Kotsampopoulos, Panos Hatziargyriou, Nikos Luo, Xi Batzelis, Efstratios Singh, Abhinav School of Electrical and Computer Engineering National Technical University of Athens Greece School of Electronics and Computer Science University of Southampton Southampton United Kingdom

ISBN: (纸本)9781837242689

In recent years, in response to the global climate crisis, inverter-based energy resources (IBRs) have been massively integrated into power systems. Their effective operation and control lie on a wide variety of inner, outer, and synchronization control loops which have been reported to interact and compromise power system's stability. In this study, a Multi-Input-Multi-Output (MIMO) impedance model for a three-phase grid following inverter with local voltage control has been proposed. This linear time invariant model takes into consideration the delay and the coupling between the control blocks and serves as a simpler and more computationally efficient method to capture oscillations and interactions in time and frequency domain. It can predict instabilities caused by the different control layers along with the frequencies of the oscillations. The effect of the delay, the current control tuning parameters and the interactions between the current controller and the local voltage controller have been highlighted. The results have been validated in time and frequency domain simulations in SIMULINK environment. © The Institution of engineering & Technology 2024.

关键词： Frequency domain analysis

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Review of AI & XAI-based breast cancer diagnosis methods using various imaging modalities

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Multimedia Tools and Applications 2025年第5期84卷 2209-2260页

作者： Karthiga, R. Narasimhan, K. Thanikaiselvan, V. Hemalatha, M. Amirtharajan, Rengarajan Department of ECE SRM Institute of Science and Technology Ramapuram Chennai600089 India School of Electrical & Electronics Engineering SASTRA Deemed University Thanjavur613 401 India School of Electronics Engineering Vellore Institute of Technology Vellore India Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia

Breast cancer is a significant health concern;early detection and treatment are critical to improving patient outcomes. Artificial Intelligence has the potential to assist healthcare professionals in the diagnosis and treatment of breast cancer, and clinical decision support systems using AI algorithms can help to improve the accuracy and speed of breast cancer detection and diagnosis. By analysing large amounts of data from various imaging modalities, AI algorithms can help identify breast cancer early, increasing the chances of successful treatment. This survey aims to briefly overview the most prevalent breast cancer types, their staging, and the methods and modalities for their diagnosis to address these problems. Our investigation showed that, when compared to ML, DL techniques achieved the highest accuracy, with an approximate 2% improvement in accuracy. This review article mainly focuses on four commonly used imaging modalities: Mammogram, Thermogram, Ultrasound imaging and histopathology images. This survey critically analyzes breast cancer detection approaches and modalities, as well as a cost-to-accuracy comparison. Explainable AI (XAI) techniques and their application for breast cancer diagnosis are critically examined, as well as their advantages and limitations. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Lung cancer

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Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

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Australian Journal of electrical and Electronics engineering 2024年第3期21卷 213-227页

作者： Shirley, C.P. Pattar, Jagannath Kavitha Rani, P. Saini, Sumit Ranga, Jarabala Elangovan, D. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Madanapalle Institute of Technology & Science Madanapalle India Department of M.Tech Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electrical Engineering School of Engineering & Technology Central University of Haryana Mahendergarh India Detartment of Electrical and Electronics Engineering Ramachandra College of Engineering Eluru India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Electrical and Electronics Engineering Chaitanya Bharathi institute of technology Hyderabad India

By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO). ©, Engineers Australia.

关键词： Energy utilization

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The Past, Present, and Future of Storage Technologies (Part 1 of 2)

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ACM TRANSACTIONS ON STORAGE 2025年第1期21卷 1-3页

作者： Kuenning, Geoff Won, Youjip Zhao, Ming Computer Science Harvey Mudd College Claremont United States Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea (the Republic of) School of Computing and Information Sciences Arizona State University Tempe United States Computer Science Stony Brook University Stony Brook United States

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A Speech Enhancement Algorithm Combining Wavelet Transform and Adaptive Filters 6

A Speech Enhancement Algorithm Combining Wavelet Transform a...

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6th IEEE international Conference on Image Processing, Applications and Systems, IPAS 2025

作者： Shrestha, Aayam Ghorshi, Seyed Joorabchi, Marjan Panahi, Issa Firouzeh, Fereshteh Fakhar The University of Texas at Tyler Department of Electrical and Computer Engineering TX United States Sharif University of Technology School of Science and Engineering Iran The University of Texas at Dallas Department of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798331506520

Noise as an unwanted interference can significantly degrade speech signals, especially those recorded by many microphones. This interference is modeled as additive noise that originates from a range of sources including White Gaussian Noise (WGN), babble, crowd, large city, and traffic noises. These disturbances can alter the characteristics of speech signals reducing both their quality and intelligibility. This paper introduces a novel approach designed to reduce noise and enhance the quality and intelligibility of speech signals. The proposed method combines Wavelet Transform with Adaptive Filters, specifically the Wiener filter and RLS filter. The evaluation process involves testing noisy speech signals under realistic conditions with different signal-to-noise ratios (SNRs) and different types of additive noise. The objective measure is used for evaluation, including the perceptual evaluation of speech quality (PESQ). Results show that combining Wiener or RLS filtering with Wavelet Transform significantly improves noise reduction, outperforming the use of Wavelet Transform alone. © 2025 IEEE.

关键词： Adaptive filtering

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Autonomous Valet Parking Using Camera Switching and Car Headings

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Journal of Institute of Control, Robotics and Systems 2022年第3期28卷 273-279页

作者： Kim, Woo Bin Kim, Ye Bin Hong, Yu Min Hwang, Sung Soo School of Computer Science and Electrical Engineering Handong Global University Korea Republic of

Autonomous valet parking(AVP) is a system that allows a vehicle to detect a parking space and park without any human intervention. This paper explores the efficient use of monocular visual simultaneous localization and mapping(visual-SLAM) in AVP scenarios, while also highlighting several problems arising from current AVP methods. These problems include the difficulties of performing a loop closure in narrow places and the unreliability of the estimated scale between the real-world and SLAM maps. This paper explores two methods for resolving these problems. The first solution is to perform AVP without loop closure. This can be done through a camera switching method that uses the front camera while parking, and the rear camera in return driving scenarios. The second solution involves making use of an alternative automatic parking algorithm that utilizes a car’s heading. Most automatic parking algorithms utilize monocular visual-SLAM, but it is difficult to calculate an accurate scale using this method. The alternative automatic parking algorithm using a car's heading could eliminate these issues with scaling. Each method was tested in three different locations, returning average success rates of 80% in return driving and 93.3% in automatic parking. The methods highlighted in this paper only utilize cameras, which are inexpensive compared to other sensors and are expected to contribute to commercializing the AVP system. © ICROS 2022.

关键词： Cameras

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Towards an Improved Understanding of Features for More interpretable Landscape Analysis

Towards an Improved Understanding of Features for More Inter...

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2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Gallagher, Marcus Munoz, Mario University of Queensland School of Electrical Engineering and Computer Science Brisbane Australia The University of Melbourne School of Computer and Information Systems ParkvilleVIC Australia

ISBN: (纸本)9798400704956

Landscape analysis has received increasing attention in the literature, with a major focus on producing feature data to be used in a machine learning pipeline for automatic algorithm selection and configuration. In contrast, the original purpose of landscape analysis (i.e. to develop theory and techniques to understand the structure of fitness landscapes) has been somewhat overshadowed. This paper aims to clarify the purpose of landscape features, emphasizing the need for clear definitions of distance or similarity between optimization problem instances. It argues that current methodologies' shortcomings can be better understood from this perspective and advocates for more interpretable features and distances to gain explainable insights into problem instances, algorithm-problem mappings, and improved benchmarking of black-box algorithms. © 2024 Copyright held by the owner/author(s).

关键词： Optimization algorithms

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