Optimizing Energy Efficiency in Vehicular Edge-Cloud Networks Through Deep Reinforcement Learning-Based Computation Offloading by Ibrahim A. Elgendy, Ammar Muthanna, Abdullah Alshahrani, Dina S. M. Hassan, Reem Alkanhel, Mohamed Elkawkagy

“…A novel load-balancing algorithm is proposed to effectively redistribute vehicles among RSUs, considering factors such as RSUs load, computational capacity, and data rate. …”
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HECM-Plus: Hyper-Entropy Enhanced Cloud Models for Uncertainty-Aware Design Evaluation in Multi-Expert Decision Systems by Jiaozi Pu, Zongxin Liu

“…To address this gap, we propose HECM-Plus, an algorithm integrating Expectation (<i>Ex</i>), <i>En</i>, and <i>He</i> to holistically model geometric and probabilistic uncertainties in cloud models. …”
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Dynamic Bayesian network modeling for longitudinal data on child undernutrition in Ethiopia (2002–2016) by Getnet Bogale Begashaw, Getnet Bogale Begashaw, Temesgen Zewotir, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Haile Mekonnen Fenta

“…We used a built-in Bayes server tool to identify potential features, followed by building the structure of the directed acyclic graph using a structural learning algorithm. The maximum posterior is determined using the relevance tree algorithm. …”
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Application of Multi-Inflammatory Index to Predict Atrial Fibrillation Risk in Patients with Coronary Heart Disease: A Retrospective Machine Learning Study by Hou L, Su K, Zhao J, He T, Li Y

“…In the training set, LightGBM achieved an AUC of 0.958, accuracy of 0.851, and sensitivity of 0.943, while in the testing set, it achieved an AUC of 0.757 and accuracy of 0.821. …”
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Optimization and Estimation of the State of Charge of Lithium-Ion Batteries for Electric Vehicles by Luc Vivien Assiene Mouodo, Petros J. Axaopoulos

“…Because of the work’s novelty, the methodological approach combines the extended Kalman filter algorithm (EKF) with the noise matrix, which is updated in this case through an iterative process. …”
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VIS/NIR Spectroscopy as a Non-Destructive Method for Evaluation of Quality Parameters of Three Bell Pepper Varieties Based on Soft Computing Methods by Meysam Latifi Amoghin, Yousef Abbaspour-Gilandeh, Mohammad Tahmasebi, Mohammad Kaveh, Hany S. El-Mesery, Mariusz Szymanek, Maciej Sprawka

“…To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). …”
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An Optimized Cascaded CNN Approach for Feature Extraction From Brain MRIs for Tumor Classification by Santosh Kumar Chhotray, Debahuti Mishra, Sarada Prasanna Pati, Sashikala Mishra

“…The bald eagle optimization (BEO) algorithm is used to optimize the hyperparameters while balancing exploration and exploitation. …”
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Learning Rate Tuner with Relative Adaptation (LRT-RA): Road to Sustainable Computing by Saptarshi Biswas, Sumagna Dey, Subhrapratim Nath

“…The proposed method achieves 84.96% accuracy on the CIFAR-10 dataset while reducing the power usage to 0.07 kWh, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> emissions to 0.05, and both <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><msub><mi>O</mi><mi>x</mi></msub></mrow></semantics></math></inline-formula> emissions to 0.00003 pounds, during the whole training and testing process.…”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…It enhances the features extracted from MobileNet-V2, ResNet50, and EfficientNet-B0 networks using metaheuristic algorithms and bidirectional long-short-term memory (Bi-LSTM) from the CT image. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To complement the random field modeling, an enhanced PSO algorithm is proposed for 3D slope stability analysis. …”
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Watershed Health Prediction based on Surface Water Quality Variables (Case Study: Taleghan Watershed) by Payam Ebrahimi, Ali Salajegheh, Mohsen Mohseni Saravi, Arash Malekian, Amir Sadoddin

“…In this study, the gene expression algorithm for modeling water quality data and its changes has been investigated. …”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…Additionally, the study assessed the impact of various spectral indices on enhancing the results from the classification of Landsat 8 imagery, while also evaluating the efficacy of support vector machine (SVM) and maximum likelihood algorithms in producing maps with satisfactory accuracy and precision.   …”
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Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

“…ESS complements energy storage and keeps it functional and reliable while EMS makes it completely functional by devising ways to reduce costs and enhance efficiency. …”
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Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy by Siyu He, Chunyu Li, Mingxin Lu, Fang Lin, Sangyu Hu, Junfang Zhang, Luying Peng, Li Li

“…Methods We constructed a single-cell transcriptional atlas of DCM and normal patients. Then, the xCell algorithm, EPIC algorithm, MCP counter algorithm, and CIBERSORT method were applied to identify DCM-related cell types with a high degree of precision and specificity using RNA-seq datasets. …”
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Development and pilot-testing of the Alopecia Areata Assessment Tool (ALTO). by David G Li, Kathie P Huang, Fan Di Xia, Cara Joyce, Deborah A Scott, Abrar A Qureshi, Arash Mostaghimi

“…<h4>Results</h4>239 patients (59 AA cases and 180 non-AA cases) completed the ALTO and were included for analysis. Algorithm 5 demonstrated the highest sensitivity (89.8%) while algorithm 3 demonstrated the highest specificity (97.8%). …”
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Deep encoder-decoder networks for belt longitudinal tear detection by Lei You, Minghua Luo, Xinglin Zhu, Bin Zhou

“…The input images are downscaled using a sorting algorithm to extract the information of pixels with high grayscale values as the input feature map for the neural network. …”
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Thoracoabdominal stab wounds: modern surgical tactics by B. N. Kotiv, I. M. Samokhvalov, V. Ju. Markevich, I. I. Dzidzava, O. V. Barinov, V. V. Suvorov, A. V. Goncharov, K. V. Petukhov

“…The objective was to determine the optimal therapeutic and diagnostic algorithm for thoracoabdominal injury.Material and methods. …”
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Hybrid multi-objective optimization of µ-synthesis robust controller for frequency regulation in isolated microgrids by Abdallah Mohammed, Ahmed Kadry, Maged Abo-Adma, Adel El Samahy, Rasha Elazab

“…The controller is optimized using multi-objective particle swarm optimization (MOPSO) and multi-objective genetic algorithm (MOGA) under inequality constraints, employing a Pareto front to identify optimal solutions. …”
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Stackelberg Game Based on Trajectory Prediction for Lane Change in Mixed Traffic by Baichuan Shi, Li Zhai, Chang Liu

“…An improved Stackelberg game model integrates trajectory prediction of human-driven vehicles, while a bi-level optimization algorithm combining model predictive control and genetic algorithms jointly optimizes acceleration sequences and lane-change timing. …”
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Zero-Sum-Game-Based Fixed-Time Event-Triggered Optimal Consensus Control of Multi-Agent Systems Under FDI Attacks by Jing Yang, Ruihong Li, Qintao Gan, Xinxin Huang

“…Moreover, a critic-only online reinforcement learning (RL) algorithm is proposed to approximate the optimal policy, in which the critic neural networks are constructed by the experience replay-based approach. …”
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