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Survey of Resources Allocation Techniques with a Quality of Service (QoS) Aware in a Fog Computing Environment

computers, Materials & Continua 2023年第7期76卷 1291-1308页

作者： Wan Norsyafizan WMuhamad Kaharudin Dimyati Muhammad Awais Javed Suzi Seroja Sarnin Divine Senanu Ametefe School of Electrical Engineering College of EngineeringUniversity Teknologi Mara40450Shah AlamSelangorMalaysia Department of Electrical Engineering Faculty of EngineeringUniversity Malaya50603KualaLumpurMalaysia Department of Electrical and Computer Engineering COMSATS University Islamabad45550Pakistan

The tremendous advancement in distributed computing and Internet of Things(IoT)applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud ***,suitable and effective applications could be performed to satisfy the applications’latency *** allocation techniques are essential aspects of fog networks which prevent unbalanced load *** resource management techniques can improve the quality of service *** to the limited and heterogeneous resources available within the fog infrastructure,the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT *** has been limited research on resource management strategies in fog networks in recent years,and a limited systematic review has been done to compile these *** article focuses on current developments in resource allocation strategies for fog-IoT networks.A systematic review of resource allocation techniques with the key objective of enhancing QoS is *** involved in conducting this systematic literature review include developing research goals,accessing studies,categorizing and critically analysing the *** resource management approaches engaged in this article are load balancing and task offloading *** the load balancing approach,a brief survey of recent work done according to their sub-categories,including stochastic,probabilistic/statistic,graph theory and hybrid techniques is provided whereas for task offloading,the survey is performed according to the destination of task *** load balancing and task-offloading approaches contribute significantly to resource management,and tremendous effort has been put into this critical ***,this survey presents an overview of these extents and a comparative ***,the study discusses ongoing research issues and potential future directio

关键词： Resource management task offloading load balancing QoS latency energy consumption

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Stochastic Computing Convolutional Neural Network Architecture Reinvented for Highly Efficient Artificial Intelligence Workload on Field-Programmable Gate Array

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Research 2024年第2期2024卷 55-79页

作者： Yang Yang Lee Zaini Abdul Halim Mohd Nadhir Ab Wahab Tarik Adnan Almohamad School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal 14300 Penang Malaysia School of Computer Sciences Universiti Sains MalaysiaGelugor11800 PenangMalaysia Electrical-Electronics Engineering Department Faculty of EngineeringKarabuk University78050 KarabukTurkiye

Stochastic computing(SC)has a substantial amount of study on application-specific integrated circuit(ASIC)design for artificial intelligence(AI)edge computing,especially the convolutional neural network(CNN)***,SC has little to no optimization on field-programmable gate array(FPGA).Scaling up the ASIC logic without FPGA-oriented designs is inefficient,while aggregating thousands of bitstreams is still challenging in the conventional *** research has reinvented several FPGA-efficient 8-bit SC CNN computing architectures,i.e.,SC multiplexer multiply-accumulate,multiply-accumulate function generator,and binary rectified linear unit,and successfully scaled and implemented a fully parallel CNN model on Kintex7 *** proposed SC hardware only compromises 0.14%accuracy compared to binary computing on the handwriting Modified National Institute of Standards and Technology classification task and achieved at least 99.72%energy saving per image feedforward and 31?more data throughput than modern *** to SC,early decision termination pushed the performance baseline exponentially with minimum accuracy loss,making SC CNN extremely lucrative for AI edge computing but limited to classification *** SC's inherent noise heavily penalizes CNN regression performance,rendering SC unsuitable for regression tasks.

关键词： hardware Highly rendering

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Brain tumors segmentation using a hybrid filtering with U-Net architecture in multimodal MRI volumes

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International Journal of Information Technology (Singapore) 2024年第2期16卷 1033-1042页

作者： Esmaeilzadeh Asl, Sima Chehel Amirani, Mehdi Seyedarabi, Hadi Department of Electrical Engineering Urmia University Urmia Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

Brain MRI makes it possible to evaluate brain tumor diagnosis and treatment. There are, however, many challenges for automated brain tumor segmentation, and these challenges have become tougher as deep learning has progressed. Gliomas tumors, which can be proliferated quickly, can develop anywhere and in any shape in the brain. This article presents a new method for automated brain tumor segmentation using hybrid filters and employing 3D medical images. The U-Net model is employed for semantic segmentation. 2D MRIs are taken from 3D MRI, which allows us to view the tumor in two dimensions in three levels (axial, sagittal, and coronal). This ensures that there are not any tumor points that have been overlooked for detection, and the tumor volume images are available in two dimensions. In addition, three types of MRI are used to segment this tumor from each patient. In these three types of MRI, the Glioma tumor is more visible than the fourth type (T2). To improve the tumor segmentation, a hybrid filter, including the bilateral filter and blacktop hat, is used for pre-processing. The intersection of these images is used to evaluate the model. Experimental results showed that the proposed approach demonstrates better tumor segmentation compared to similar studies. In addition, the computational and memory used is lower than what has been done in recent research. The Dice coefficient and Hausdorff distance are estimated at 91.34% and 3.74 for the whole tumor image in the present work, respectively. Experiments show that our method is an optimal method for the segmentation of brain images. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2023.

关键词： Brain tumor Deep learning Medical image segmentation U-Net

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Quad-Mode H-Beam Metasurface-Embedded Dual-Band Circularly-Polarized Multi-Tiered Antenna Scheme With 5G (n79) and Wi-Fi 6E Capabilities

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IEEE Access 2025年 13卷 89844-89857页

作者： Supreeyatitikul, N. Chomtong, P. Konpang, J. Thitimahatthanakusol, P. Akkaraekthalin, P. Rajamangala University of Technology Krungthep Faculty of Engineering Department of Electrical and Telecommunication Engineering Bangkok10120 Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok10800 Thailand Rajamangala University of Technology Isan Faculty of Engineering and Technology Department of Telecommunications Engineering and Digital Innovation Nakhon Ratchasima30000 Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok10800 Thailand

This research proposes a quad-mode H-beam metasurface (MTS)-embedded dual-band circularly-polarized (CP) multi-tiered antenna scheme with 5G (n79) and Wi-Fi 6E capabilities. The proposed antenna scheme consists of three layers of corner-truncated FR-4 substrates without an air gap. The upper substrate contains an array of 3× 4 H-beam MTS elemental units tilted at 49°. The middle substrate is a copper plate with a horizontal Z-shaped slot at its center functioning as the ground plane, and the lower substrate contains a microstrip feed line. Characteristic mode analysis (CMA) is employed to optimize the circular polarization of the MTS structure. Results show that Modes 1 & 2 at 4.81 GHz and Modes 4 & 9 at 6.2 GHz contribute to CP radiation. The measured return loss bandwidths of the antenna are 19.37% (4.63 - 5.56 GHz) and 9.51% (5.97 - 6.56 GHz) for the 5G (n79) and Wi-Fi 6E bands. The measured axial ratio bandwidths are 13.33% (4.6 - 5.24 GHz) and 1.77% (6.15 - 6.26 GHz), with maximum gains of 5.2 and 3.9 dBic at 5.5 and 6.2 GHz, respectively. Unlike conventional MTS-based CP antennas which employ rectangular- or square-shaped MTS elements for single-band operation, this work utilizes H-beam-shaped MTS elemental units to achieve dual-band CP capability. Additionally, rather than traditional full-wave methods, CMA is used to optimize circular polarization. Essentially, the proposed antenna scheme is suitable for 5G (n79) and Wi-Fi 6E communications. © 2013 IEEE.

关键词： Circular polarization

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User Input Search - Custom Motion Estimation Algorithm Optimized for UAVs 46

User Input Search - Custom Motion Estimation Algorithm Optim...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331042

Unmanned aerial vehicle technology is growing rapidly as it finds its application in the various industries, including military & defense, agriculture, logistics, transportation, healthcare, entertainment and many others. One of the fastest growing industries including drones is the entertainment industry. More specifically, First Person View (FPV) piloting has become a popular sport which attracts huge masses. In FPV systems, the pilot wears FPV goggles and controls the drone using a controller, and the drone transmits video data to the goggles in real time. Since drones usually fly very quickly, the video quality in terms of resolution, compression artefacts and end-to-end delay must be maintained. This paper explores the idea of optimizing the Motion Estimation (ME) algorithm of existing High Efficiency Video Coding (HEVC) algorithms by utilizing user input from the controller. For example, if the drone is directed to hover to the left, then it would make sense to search for the most similar blocks in the previous video frame only on the left side of the referent block. For the purpose of this research, a HEVC video coder was customized to receive additional input besides the video data - the user input from the controller, or in other words, drone movement directions. We call this ME algorithm User Input Search (UIS). Our UIS algorithm is compared with the standard ME algorithms and its efficiency is tested. © 2023 MIPRO Croatian Society.

关键词： Real time systems

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Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

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Intelligent Automation & Soft Computing 2023年第2期35卷 2117-2134页

作者： Anas Quteishat M.A.A.Younis Electrical Engineering Department Faculty of Engineering TechnologyAl-Balqa Applied UniversityAl-SaltJordan Department of Electrical and Computer Engineering Sohar UniversitySultanate of Oman

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and *** resources are vital for all countries in terms of their economies and *** a result,selecting the optimal option for any country is critical in terms of energy *** country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global *** the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous *** study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp *** hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective *** best-suited renewable energy alternative is discovered using the approach presented.

关键词： Multi characteristic decision making framework fuzzy sets fuzzy theory renewable energy energy resource selection

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Comparing Centralized and Decentralized Storage in Microgrids: Implications for Consumer Behavior 28

Comparing Centralized and Decentralized Storage in Microgrid...

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28th International electrical Power Distribution Conference, EPDC 2024

作者： Dousti, Hazhir Hagh, Mehrdad Tarafdar Jirdehi, Mehdi Ahmadi Kermanshah University of Technology Faculty of Electrical Engineering Department of Electrical Engineering Kermanshah Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9798350385502

Due to the increase in demand for electricity, the lack of fossil fuels, and the use of renewable energy sources, the use of energy storage systems becomes necessary. The use of storage systems in different parts of microgrids has countless advantages. These benefits include improving the overall efficiency of the system, increasing the stability of the network, the possibility of optimal control strategies at both the national and regional levels and the effective identification of vulnerabilities in the system. This paper focuses on the issue of coordinated and optimal energy management in a microgrid, especially when dealing with centralized and decentralized storage. This study simultaneously examines the impact of the presence of storage systems in both centralized and decentralized modes, as well as the creation of incentive policies to reduce demand. It examines the interaction between these two factors and their effects on cost reduction and overall network voltage deviation. The work has been done on a standard IEEE network with 69 buses using MATLAB software. It has been shown that in the presence of decentralized energy storage, network performance and consumer consumption are better, and network losses and voltage deviations are also reduced. © 2024 IEEE.

关键词： Renewable energy

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Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing

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Annals of Data Science 2025年第1期12卷 223-252页

作者： Shamsinejad, Elham Banirostam, Touraj Pedram, Mir Mohsen Rahmani, Amir Masoud Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams, leveraging in-memory processing within the Spark framework. The approach is founded on the principle of K-anonymity and propels the field forward by critically evaluating various anonymization methods and algorithms, benchmarking their performance with respect to time and space complexities. A distinctive formula for optimized cluster determination in the K-means algorithm is presented, along with a novel tuple expiration time strategy for the efficient purging of clusters. The integration of these components into Spark’s RDD and MLlib modules results in a significant decrease in execution time and data loss rates, even with increasing data volumes. The paper’s notable contributions are its methodological advancements that offer a robust, scalable solution for data anonymization, safeguarding user privacy without sacrificing data utility or processing efficiency. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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A Review of Anonymization Algorithms and Methods in Big Data

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Annals of Data Science 2025年第1期12卷 253-279页

In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of users. This study was conducted with the aim of finding a solution to this challenge. In this study, we examined various data anonymization methods, including differential privacy, advanced encryption, and strong access controls. In addition, the operation, advantages, disadvantages, and use of these methods, the challenges of adapting these methods to big data, and possible solutions for them were also examined. Our results show that traditional data anonymization methods lack scalability, leading to privacy breaches and data loss. When faced with large volumes of data, these methods may not be able to fully process the data. Also, these methods may be ineffective against re-identification attacks, linkage attacks, and inference attacks. We introduced emerging methods that are capable of providing improved privacy with minimal data loss. These methods have scalability for big data. Finally, we examined future research works and raised important questions that can help improve existing algorithms or develop new methods, better manage the complexity and scale of unstructured data. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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Close Quarters Permittivity Detection Based on Tagging Antenna Sensor for Solid Material Characterization

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Progress in Electromagnetics Research C 2025年 154卷 21-29页

作者： Alam, Syah Surjati, Indra Mardian, Raden D. Sari, Lydia Daffin, Ghatfan Iznih Zakaria, Zahriladha Asrar, Leni D. Firmansyah, Teguh Department of Electrical Engineering Universitas Trisakti West Jakarta11440 Indonesia Faculty of Electronic and Computer Engineering and Technology Universiti Teknikal Malaysia Melaka 76100 Malaysia Department of Electrical Engineering Universitas Sultan Ageng Tirtayasa Banten 42117 Indonesia

This research proposes a tagging antenna sensor for permittivity detection of solid materials based on a close quarter approach. The sensor is proposed to operate at a frequency of 2.53 GHz using a single port resonator with a reflection coefficient (S11) ≤ −10 dB. The sample is placed directly in the sensing area of the antenna sensor based on the concentration of the electric field. Permittivity detection is proposed based on the resonant frequency shift of the transmission coefficient (S21) using interrogator antennas separated by a distance of (d) = 100 mm determined using the Fresnel region. Based on the measurement results, the antenna sensor has a high accuracy of 96% while the sensitivity and ∆F are 0.39% and 0.012 GHz, respectively. Moreover, the sensitivity ofthe proposed sensor is still low due the low concentration of the electric field. Therefore, increasing the sensitivity of the antenna sensor can be recommended as further work such as combining the structure of single port resonator with another structure such as interdigital capacitor and artificial magnetic conductor (AMC). Finally, this research makes a significant contribution to the permittivity detection of solid materials with a close quarter approach to support real time and flexible measurements and can be recommended for several applications for the biomedical, pharmaceutical, and material quality control industries. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Permittivity measurement

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