Dynamic load balancing in cloud computing using predictive graph networks and adaptive neural scheduling by K. Rajammal, M. Chinnadurai

“…Experimental evaluations of the proposed model with diverse workload scenarios demonstrate significant improvements in terms of throughput, energy efficiency, make span and response time. Additionally, comparative analyses with existing optimization algorithms exhibit the proposed model ability in managing the loads in cloud computing. …”
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Analysis on Acoustic Disturbance Signals Expected During Partial Discharge Measurements in Power Transformers by Michał KUNICKI

“…This paper presents comparative analysis of various acoustic signals expected during partial discharge (PD) measurements in operating power transformer. …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…First, both GARCH model and SVM are developed to forecast short-term electricity price of New South Wales in Australia. Then, ACO algorithm is applied to determine the weight coefficients. …”
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Crop-Free-Ridge Navigation Line Recognition Based on the Lightweight Structure Improvement of YOLOv8 by Runyi Lv, Jianping Hu, Tengfei Zhang, Xinxin Chen, Wei Liu

“…The research results indicate that this method significantly reduces the size of the model parameters and improves the recognition speed, providing a more efficient solution for the autonomous navigation of intelligent carrier aircraft.…”
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Cluster-based Sleep Scheduling Protocol for Mobile Wireless Sensors Network by Omnia Mezghani, Mahmoud Mezghani

“…Experimental results demonstrate that the proposed cluster-based scheduling algorithm, based on the perimeter coverage of sensors, provides higher energy efficiency and longer lifetime coverage for MWSNs as compared to other protocols.…”
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Combining non-Monotone trust rregion method with a new adaptive radius for unconstrained optimization problems by Seyed Hamzeh Mirzaei, Ali Ashrafi

“…In addition, it significantly reduces computational costs compared to traditional algorithms. On the other hand, the new adaptive radius avoids the ineffectiveness of the trust region close to the solution.…”
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On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. …”
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

“…Results This study conducted an experiment with six comparative sampling methods, six datasets, and three machine learning algorithms. …”
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Dunes Identification Based on Attention Mechanism With Dual-Branch Codec by Zhaobin Wang, Yan Li, Yue Shi, Yaonan Zhang, Xuejun Guo

“…A series of ablation experiments, effectiveness analyses, and comparative studies across different algorithms on two datasets were conducted to evaluate the generalization ability of dual-branch codec network based on attention mechanism across diverse datasets. …”
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Optimizing flood resilience in China’s mountainous areas: Design flood estimation using advanced machine learning techniques by Xuemei Wang, Ronghua Liu, Chaoxing Sun, Xiaoyan Zhai, Liuqian Ding, Xiao Liu, Xiaolei Zhang

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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…What this means Medications to control heart disease risk factors, intensive lifestyle programmes and strong government policies are all important in reducing the global burden of heart disease. More research directly comparing different strategies and looking at long-term, real-world effects is needed.…”
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Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review by Mostafa Ogab, Sofiane Zaidi, Abdelhabib Bourouis, Carlos T. Calafate

“…From an initial pool of 1,909 records, 62 relevant reports are selected to address the identified research questions. The selected studies are categorized according to publication year, venue, journal, drone domain, IDS type, utilized algorithms, datasets, attack classifications, and software environments. …”
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A Review of Common Techniques for Visual Simultaneous Localization and Mapping by Yong Dai, Jiaxin Wu, Duo Wang

“…Among all sorts of SLAM, visual SLAM (V-SLAM) has become the key academic research due to its advantages of low price, easy installation, and simple algorithm model. …”
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Graph-Based User-Centric Recommender System Using Neo4j, Cypher, and Jaccard Similarity in the Field of e-Commerce by Simona-Vasilica Oprea, Adela Bara

“…We further propose an algorithm for building a graph-based recommendation system for e-commerce to offer personalized suggestions. …”
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Bridge facility health detection method based on DATA random subspace by Xiaoyan Shen

“…The method combines the singular value jump recognition and projection reconstruction techniques to determine the effective modal order of the structural vibration signals, and uses projection reconstruction techniques to improve the accuracy of the modal parameters. Compared with other algorithms, the research algorithm has higher bridge data detection accuracy, with an average data detection accuracy of 95.84 % and an accuracy growth rate of 26.9 %. …”
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Fully convolutional neural networks for processing observational data from small remote solar telescopes by Piotr Jóźwik-Wabik, Adam Popowicz

“…For this purpose, we use chromosphere data from the 50 mm small H $$\alpha$$ Telescope of the Silesian University of Technology acquired over many months under various atmospheric conditions. We compare the obtained results with the results of raw data processing by a state-of-the-art deterministic algorithm, multi-frame blind deconvolution (MFBD). …”
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Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

“…Most of the recent research has focused on the Internet of Things (IoT) and its applications. …”
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Simultaneous Optimal Allocation of EVCSs and RESs Using an Improved Genetic Method by Majid Farjamipur, Hossein Lotfi, Mohammad Hassan Nikkhah

“…In order to manage the demand on the side of consumers and even out the load curve, the time of use mechanism as one of the demand response programs has been considered in this study. In this research, the improved nondominant sorting genetic algorithm is proposed to solve the problem, and the results of the proposed method are also compared with the conventional genetic and particle swarm optimization algorithms. …”
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Swarm learning network for privacy-preserving and collaborative deep learning assisted diagnosis of fracture: a multi-center diagnostic study by Yi Xie, Yi Xie, Xinmeng Wang, Huiwen Yang, Huiwen Yang, Jiayao Zhang, Honglin Wang, Zineng Yan, Jiaming Yang, Zhiyuan Yan, Zhiwei Hao, Pengran Liu, Yijie Kuang, Zhewei Ye, Zhewei Ye

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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

“…Future research will explore the application of the vein imaging system in robotic venous blood collection to facilitate real-time puncture guidance.…”
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