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CEEO: an innovative Coulomb-enhanced Equilibrium Optimizer for task scheduling of cloud services in IoT environments

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Computing 2025年第6期107卷 1-24页

作者： Ebrahimi Mood, Sepehr Souri, Alireza İnanç, Nihat Li, Kuan-Ching Department of Computer Science Yazd University Yazd Iran Department of Computer Engineering Faculty of Engineering Haliç University Istanbul34060 Turkey Department of Electrical and Electronics Engineering Faculty of Engineering Haliç University Istanbul34060 Turkey Department of computer science and information engineering Providence University Taichung43301 Taiwan

In this paper, we address the multi-objective task scheduling problem in cloud computing environments for IoT-generated tasks, focusing on minimizing makespan, load imbalance, energy consumption, and CO2 emissions. We propose a novel load imbalance metric tailored for this specific context and introduce an enhanced Equilibrium Optimizer (EO) algorithm, termed CEEO. The CEEO integrates a Coulomb operator inspired by Coulomb’s law to improve exploration and escape local optima in multimodal optimization problems. The algorithm’s performance is evaluated using standard benchmark functions from CEC2017, where it demonstrates significant improvements over existing optimization algorithms in terms of convergence speed and solution quality. In addition, the CEEO is applied to a simulated cloud computing task scheduling environment, considering varying numbers of tasks and virtual machines. The results reveal that CEEO consistently outperforms other scheduling algorithms, reducing makespan and improving load balancing, energy consumption, and CO2 emissions. Statistical analysis using the Friedman test confirms the statistical significance of these improvements. This research provides an efficient and robust solution for multi-objective task scheduling in cloud computing, offering substantial improvements in operational costs, execution time, and overall service quality. © The Author(s) 2025.

关键词： Scheduling algorithms

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Medicare fraud detection: a comparative study on the effectiveness of one-class and binary classification models

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International Journal of computers and Applications 2025年第3期47卷 323-328页

作者： Leevy, Joffrey L. Hancock, John Khoshgoftaar, Taghi M. Department of Electrical Engineering and Computer Science Florida Atlantic University Boca RatonFL United States

Research into Medicare fraud detection that utilizes machine learning methodologies is of great national interest due to the significant fiscal ramifications of this type of fraud. Our big data analysis pertains to three Medicare datasets: Part B, Part D, and DMEPOS. In this paper, One-Class Classification (OCC) and binary classification approaches are evaluated with six different classifiers. We note that when a practitioner is faced with a high cost or unreasonable wait associated with acquiring a second label for binary classification, OCC may intuitively seem like the better alternative. The evaluative metrics used in our study are Area Under the Receiver Operating Characteristic Curve (AUC) and Area Under the Precision-Recall Curve (AUPRC). As a result of our investigation, binary classification was found to be more effective than OCC in detecting Medicare fraud. Additionally, we determined that gradient-boosting algorithms, specifically CatBoost and XGBoost, yield the most robust performance. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Contrastive Learning

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Resolution-aware beam scanning for joint detection and communication in ISAC systems

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science China(Information sciences) 2025年第5期68卷 250-266页

作者： Yiming XU Dongfang XU Zhanyuan XIE Zheng JIANG Shenghui SONG Derrick Wing Kwan NG Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology China Telecom Research Institute School of Electrical Engineering and Telecommunications University of New South Wales

Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the design of sequential scanning beams for target detection with the required sensing resolution has not been tackled in the *** bridge this gap, this paper introduces a resolution-aware beam scanning design. In particular, the transmit information beamformer, the covariance matrix of the dedicated radar signal, and the receive beamformer are jointly optimized to maximize the average sum rate of the system while satisfying the sensing resolution and detection probability requirements.A block coordinate descent(BCD)-based optimization framework is developed to address the non-convex design problem. By exploiting successive convex approximation(SCA), S-procedure, and semidefinite relaxation(SDR), the proposed algorithm is guaranteed to converge to a stationary solution with polynomial time complexity. Simulation results show that the proposed design can efficiently handle the stringent detection requirement and outperform existing antenna-activation-based methods in the literature by exploiting the full degrees of freedom(DoFs) brought by all antennas.

关键词： integrated sensing and communication (ISAC) detection beam scanning resolution beamwidth

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Question Selection for Multi-Modal Code Search Synthesis using Probabilistic Version Spaces

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IEEE Transactions on Software engineering 2025年第6期51卷 1724-1744页

作者： Wu, Jiarong Jiang, Yanyan Wei, Lili Xu, Congying Cheung, Shing-Chi Xu, Chang The Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong McGill University Department of Electrical and Computer Engineering Montreal Canada Nanjing University State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing China

Searching the occurrences of specific code patterns (code search) is a common task in software engineering, and programming by example (PBE) techniques have been applied to ease customizing code patterns. However, previous PBE tools only synthesize programs meeting the input-output examples, which may not always align with the user intent. To bridge this gap, this paper proposes Excalibur, a multi-modal (example and natural language description) and interactive synthesizer for code search. Excalibur ensures that the generated programs are correct for the provided examples (soundness) and include the user-intended program (bounded completeness). Furthermore, Excalibur helps the user identify the user-intended program through question-answer interaction. To minimize the required interaction efforts, question selection is crucial. To improve question selection for code search, we propose probabilistic version spaces (ProbVS), in which the user-intended program’s probability is high and others are low. ProbVS combines traditional version spaces for compactly representing extensive programs and large language models (on the user-provided natural language description) for adjusting programs’ probabilities to align with users’ intents. Extensive experiments on a benchmark of 44 tasks demonstrated the effectiveness of Excalibur and ProbVS and demystified how ProbVS affects probability distributions and how the configurable parameters affect ProbVS. © 1976-2012 IEEE.

关键词： Normal distribution

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Provision of Ramp-rate Limitation as Ancillary Service from Distribution to Transmission System:Definitions and Methodologies for Control and Sizing of Central Battery Energy Storage System

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1507-1518页

作者： Spyros I.Gkavanoudis Kyriaki-Nefeli D.Malamaki Eleftherios O.Kontis Aditya Shekhar Umer Mushtaq Sagar Bandi Venu Charis S.Demoulias Department of Electrical&Computer Engineering Aristotle University of ThessalonikiThessalonikiGreece Electrical Engineering Mathematics&Computer Science DepartmentDelft University of TechnologyDelftNetherlands FENECON Gmbh DeggendorfGermany

The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid ***,grid operators have incorporated ramp-rate limitations(RRLs)for the injected DRES power in the grid *** the DRES penetration levels increase,the mitigation of high-power ramps is no longer considered as a system support function but rather an ancillary service(AS).Energy storage systems(ESSs)coordinated by RR control algorithms are often applied to mitigate these power ***,no unified definition of active power ramps,which is essential to treat the RRL as AS,currently *** paper assesses the various definitions for ramp-rate RR and proposes RRL method control for a central battery ESS(BESS)in distribution systems(DSs).The ultimate objective is to restrain high-power ramps at the distribution transformer level so that RRL can be traded as AS to the upstream transmission system(TS).The proposed control is based on the direct control of theΔP/Δt,which means that the control parameters are directly correlated with the RR requirements included in the grid *** addition,a novel method for restoring the state of charge(So C)within a specific range following a high ramp-up/down event is ***,a parametric method for estimating the sizing of central BESSs(BESS sizing for short)is *** BESS sizing is determined by considering the RR requirements,the DRES units,and the load mix of the examined *** BESS sizing is directly related to the constant RR achieved using the proposed ***,the proposed methodologies are validated through simulations in MATLAB/Simulink and laboratory tests in a commercially available BESS.

关键词： Battery energy storage system distributed renewable energy resource sizing distribution system transmission system ramp-rate limitation state of charge

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An electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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computer Modeling in engineering & sciences 2024年第8期140卷 1689-1710页

作者： Md.Abdur Rahim Fahmid Al Farid Abu Saleh Musa Miah Arpa Kar Puza Md.Nur Alam Md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim Department of Computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Department of Computer Science and Engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh Department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh Department of Electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh Department of Electrical and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM

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A feature selection-aided deep learning based deepfake video detection method

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Multimedia Tools and Applications 2025年 1-24页

作者： Mohiuddin, Sk Roy, Ayush Pani, Saptarshi Malakar, Samir Sarkar, Ram Department of Computer Science Asutosh College Kolkata700026 India Department of Electrical Engineering Jadavpur University Kolkata700032 India Department of Computer Science UiT The Arctic University of Norway Tromsø9019 Norway Department of Computer Science and Engineering Jadavpur University Kolkata700032 India

The rapid advancements in deepfake technology are imposing significant challenges in detecting manipulated media contents. In this work, we have introduced a deepfake detection method that utilizes three pre-trained convolutional neural network models, namely DenseNet-121, EfficientNet-B0, and Xception to extract deep learning features from preprocessed extracted video frames. Next, these features are stacked to generate diverse feature representations, and thus end up with high-dimensional features. After that, a feature selection strategy is employed on the combined features to eliminate redundant and less effective features. The selected features are then fed into the K-nearest neighbors classifier to decide whether a questioned video is a fake video or not. Two widely used deepfake video datasets, namely FaceForensics++ and Celeb-DF (V2) are used to evaluate the performance of the proposed technique following two experimental setups: intra- and inter-datasets. The results show that the model achieves area under curve scores of 98.50% (85.70%) and 97.70% (79.00%) in the intra-dataset (inter-dataset) setups while trained on the FaceForensics++ and Celeb-DF (V2) datasets, respectively. The performance of the proposed model is comparable to that of state-of-the-art methods. Source code of the proposed method can be found at: here. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Bidirectional Photoelectric Response of Perovskite Oxide-Based Synaptic ReRAM Device

IEEE Electron Device Letters

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IEEE Electron Device Letters 2024年第3期45卷 384-387页

作者： Shrivastava, Saransh Limantoro, Stephen Ekaputra Juliano, Hans Tseng, Tseung-Yuen Hsinchu30010 Taiwan Department of Electrical Engineering and Computer Science Hsinchu30010 Taiwan

Photo sensing capability of an artificial synaptic device make it more valuable for brain-inspired computing systems, which can conquer the von Neumann bottleneck. In this letter, Ba0.7 Sr0.3 TiO3 (BST) based single layered resistive random access memory (ReRAM) device is proposed with its four different photoelectric applications. First, bidirectional photoelectric response (BPR) is achieved via 405 and 633 nm wavelengths stimulation. Second, this novel BPR contributes to the emulation of light potentiation, and light depression behaviors. Third, an important neurological behavior 'experience dependent plasticity (EDP)' is mimicked by frequency modulation of 405 nm light pulse. Fourth, ultra-high (>200%) indices of post-tetanic potentiation and depression (PTP/PTD) are achieved by amplifying the device conductance as a result of two different pulse train stimulations. A convolutional neural network is designed to classify Zalando's article images with a test accuracy of 87.7%. These results provide an opportunity for the development of multi-wavelength dependent multifunctional artificial brain-inspired systems. © 1980-2012 IEEE.

关键词： Neural networks

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Deep reinforcement learning for online scheduling of photovoltaic systems with battery energy storage systems

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Intelligent and Converged Networks 2024年第1期5卷 28-41页

作者： Yaze Li Jingxian Wu Yanjun Pan the Department of Electrical Engineering University of ArkansasFayettevilleAR 72701USA the Department of Computer Science and Computer Engineering University of ArkansasFayettevilleAR 72701USA

A new online scheduling algorithm is proposed for photovoltaic(PV)systems with battery-assisted energy storage systems(BESS).The stochastic nature of renewable energy sources necessitates the employment of BESS to balance energy supplies and demands under uncertain weather *** proposed online scheduling algorithm aims at minimizing the overall energy cost by performing actions such as load shifting and peak shaving through carefully scheduled BESS charging/discharging *** scheduling algorithm is developed by using deep deterministic policy gradient(DDPG),a deep reinforcement learning(DRL)algorithm that can deal with continuous state and action *** of the main contributions of this work is a new DDPG reward function,which is designed based on the unique behaviors of energy *** new reward function can guide the scheduler to learn the appropriate behaviors of load shifting and peak shaving through a balanced process of exploration and *** new scheduling algorithm is tested through case studies using real world data,and the results indicate that it outperforms existing algorithms such as Deep *** online algorithm can efficiently learn the behaviors of optimum non-casual off-line algorithms.

关键词： photovoltaic(PV) battery energy storage system(BESS) Markov decision process(MDP) deep deterministic policy gradient(DDPG)

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