Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach by Dan Ben Ami, Kobi Cohen, Qing Zhao

“…In this paper, we present a novel multi-armed bandit (MAB)-based approach for client selection to minimize the training latency without harming the ability of the model to generalize, that is, to provide reliable predictions for new observations. We develop a novel algorithm to achieve this goal, dubbed Bandit Scheduling for FL (BSFL). …”
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Deep Learning-Based Secrecy Performance of UAV-IRS NOMA Systems With Friendly Jamming by Kajal Yadav, Prabhat K. Upadhyay, Jules M. Moualeu, Amani A. F. Osman, Pedro H. J. Nardelli

“…Finally, a fully optimized deep neural network model is developed to predict the SOP under dynamic conditions. Numerical results demonstrate the efficacy of the proposed jamming-enabled system over its non-jamming counterpart. …”
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Research on power system transformation based on edge node technology under the background of carbon neutrality by LI Jin, GAO Hongliang, LIU Kemeng, XIE Hu

“…A stable time series is established according to the historical data of the power system, and then, the medium and long-term power demand is predicted through the exponential smoothing method as the basis of system transformation design. …”
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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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Data-driven machine learning with lattice distortion and thermodynamic parameters guided strength optimization of refractory high-entropy alloys by Shujian Ding, Yifan Zhang, Siyang Lei, Xiang Weng, Wenhui Li, Wei Ren, Jian Chen, Weili Wang

“…To address this difficulty, a data-driven machine learning (ML) model was established to predict the compressive yield strength (σ0.2) of RHEAs, which provides a design strategy with two pivotal descriptors concerning lattice distortion and thermodynamic parameters. …”
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Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…The proposed framework was validated by comparing the GA-RF predictions with simulation results under different reservoir conditions, which yielded a minimum relative error of 0.34% and an average relative error of 5.3%. …”
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Use of stepwise m5 model tree to forecast the P24max based on teleconnection indices by Golnar Ghanbarzadeh, Khalil Ghorbani, Meysam Salarijazi, Chooghi Bairam Komaki, Laleh Rezaei Ghaleh

“…The stepwise execution of the M5 model tree showed that the algorithm follows a greedy approach, and it is not necessary to use all variables to predict P24max. …”
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Method of Construction of pareto set At a dynamic initial data reception by S. V. Chebakov, L. V. Serebryanaya

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Improved Ant Colony Optimization for the Operational Aircraft Maintenance Routing Problem with Cruise Speed Control by Qing Zhang, Felix T. S. Chan, Xiaowen Fu

“…The operational aircraft maintenance routing problem (OAMRP) plays a critical part in producing considerable cost reductions for airlines, since its solution directly influences the number of operating leased aircraft. …”
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Deep Circuit Compression for Quantum Dynamics via Tensor Networks by Joe Gibbs, Lukasz Cincio

“…By the efficient use of environment tensors, the algorithm is scalable in depth far beyond prior work, and we present circuit compilations of up to 64 layers of $SU(4)$ gates. …”
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Amygdala activity for the modulation of goal-directed behavior in emotional contexts. by Kazutaka Maeda, Jun Kunimatsu, Okihide Hikosaka

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Energy management system for PV-based distributed generators in AC microgrids using an adapted JAYA optimizer to minimize operational costs, energy losses, and CO2 emissions by Nicolás Ignacio Labra-Cáceres, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya

“…To solve the model, an adapted version of the JAYA optimization algorithm was implemented, and its performance was compared against four established methodologies: the Chu & Beasley Genetic Algorithm (CBGA), Particle Swarm Optimization (PSO), the Vortex Search Algorithm (VSA), and Ant Lion Optimization (ALO). …”
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A qualitative process evaluation within a clinical trial that used healthcare technologies for children with asthma-insights and implications. by Louisa Lawrie, Stephen Turner, Seonaidh C Cotton, Jessica Wood, Heather M Morgan

“…<h4>Conclusion</h4>The use of technology and individual data within appointments was considered useful to both staff and families: closer monitoring and the educational impacts were especially highlighted. Utilising an algorithm was broadly acceptable, with caveats around clinicians using the recommendations as a guide only and wariness around extreme step-ups/downs considering contextual factors not taken into account.…”
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The Integration Of Artificial Intelligence In English Language Teaching And Machine Translation: A Bridge Between Theory And Practice In Language Teaching For Specific Purposes. by Hafida Slimani, Rachid Saim

“…However, it also raises challenges, such as the reliability of machine translations, algorithmic biases, and excessive dependence on technology. …”
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Optimizing stand-alone microgrids with lagrange multiplier technique: A cost-effective and sustainable solution for rural electrification by Rasha Elazab, Ahmed Mamdouh Ewais, Maged Ahmed Abu-Adma

“…It achieves up to 22 % lower net present costs (NPC) and up to 13 % lower cost of electricity (COE) compared to HOMER. Additionally, the algorithm demonstrates significant environmental benefits, with emissions reductions of up to 25 % for carbon dioxide and substantial decreases in carbon monoxide and nitrogen oxides. …”
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Peptide inhibitors of the anaphase promoting-complex that cause sensitivity to microtubule poison. by Scott C Schuyler, Yueh-Fu Olivia Wu, Hsin-Yu Chen, Yi-Shan Ding, Chia-Jung Lin, Yu-Ting Chu, Ting-Chun Chen, Louis Liao, Wei-Wei Tsai, Anna Huang, Lin-Ing Wang, Ting-Wei Liao, Jia-Hua Jhuo, Vivien Cheng

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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

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DECISION OF THE OPEN ASSIGNMENT PROBLEM BY STANDARD SIMPLEX METHOD by V. S. Mukha

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Analysis of effectiveness of the program of joined air traffic controlles and pilotes training by A. I. Stepnova, S. M. Stepanov, V. V. Borsoeva, V. A. Borsoev

“…Optimization of the educational process is currently an urgent task. The program of joint training can act as an optimization tool. …”
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Identification of copper metabolism-related subtypes, the development of a prognosis model, and characterization of the immune landscape in colorectal cancer by Geng Peng, Lin Zhong, Nan Lai, Lina Luo, Fu Cheng, Manzhao Ouyang

“…CMGs are effective biomarkers for predicting the prognosis of CRC patient and guiding immunotherapy.…”
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