Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis by Hang Chen, Biao Wu, Biao Wu, Kunyu Guan, Liang Chen, Kangjie Chai, Maoji Ying, Dazhi Li, Weicheng Zhao

“…This research provides a valuable approach for the predictive diagnosis and targeted therapy of atherosclerosis.…”
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Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study by Kirill Reshetnikov, Daria Bykova, Daria Bykova, Konstantin Kuleshov, Konstantin Kuleshov, Konstantin Chukreev, Egor Guguchkin, Alexey Neverov, Gennady Fedonin

“…However, ABESS yielded lower prediction accuracy compared to logistic regression methods with regularization.…”
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Assessment of a Hyperspectral Remote Sensing Model Performance for Particulate Phosphorus in Optically Shallow Lake Water by Banglong Pan, Wuyiming Liu, Zhuo Diao, Qianfeng Gao, Lanlan Huang, Shaoru Feng, Juan Du, Qi Wang, Jiayi Li, Jiamei Cheng

“…This study aims to propose an algorithm to accurately predict the PP concentration and to assess the performance of the model. …”
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Automatic speech signal segmentation with chosen parametrization method by Cz. BASZTURA, T. SAWCZYN

“…The usability of three different parametrization methods - based on the analysis of zero-crossings, spectral analysis and linear prediction coding - was analyzed. No significant differences were observed in the efficiency of investigated parameters.…”
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Dynamic Bayesian Network Model for Overhead Power Lines Affected by Hurricanes by Kehkashan Fatima, Hussain Shareef

“…To characterize the stochastic properties of HIF, Monte Carlo simulation (MCS) is employed in conjunction with fragility curves (FC) and the scenario reduction (SCENRED) algorithm. The proposed DBN model evaluates the probability of asset failure and compares the results using stochastic Monte Carlo simulation based on the fragility curve scenario reduction algorithm (FC-MCS-SCENRED) model. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…The proposed framework employs an adaptive optimization algorithm that iteratively generates and refines shading device configurations, effectively balancing glare reduction, external visibility, and visual complexity. …”
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Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method by Ying-Chun CHANG, Ho-Chih CHENG, Min-Chie CHIU, Yuan-Hung CHIEN

“…Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. …”
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Estudio comparativo de técnicas de reducción de ruido en señales industriales mediante Transformada Wavelet Discreta y selección adaptativa del umbral by Antonio Cedeño Pozo Ing., Rafael Trujillo Codorniú Dr.

“…However, we aimed at evaluating their performance for industrial signal noise reduction. In particular, we analyze the behaviour of the Bayes Shrink, Normal Shrink, Modified Shrink, and Neight Shrink methods for the reduction of the Gaussian noise in industrial signals. …”
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Fast and resource efficient method for indoor localization based on fingerprint with varied scales by Yanfen LE, Zhuo TANG, Cunbao SHENG, Weibin SHI

“…To improve the prediction speed in indoor localization,a novel algorithm based on fingerprint with varied scales was proposed.It divided the region of interest into distinct zones with distinctive coverage indicators,and reference positions with different distribution density were set in the region.According the time relevance and strength vary of the RSS from the anchors,the grids-matching process was greatly sped up for the usage of coverage indictors and the features of the location fingerprint extracted with the PCA,which made the proposed method fit the demand of application with limited power and memory.Experimental results indicate that accuracy of the positioning is ensured with the reduced energy-consuming,and more flexible about the number of anchors and the grid distribution.…”
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Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…The objective is to maximize the reduction in delays for both buses and private vehicles at intersections and optimize carbon emission reduction. …”
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Computer Vision-Based Robotic System Framework for the Real-Time Identification and Grasping of Oysters by Hao-Ran Qu, Jue Wang, Lang-Rui Lei, Wen-Hao Su

“…In order to capture oyster motion dynamically on a conveyor belt, a Kalman filter (KF) combined with a Low-Pass filter algorithm was employed to predict oyster trajectories, thereby improving noise reduction and motion stability. …”
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Near-field sound source localization using principal component analysis–multi-output support vector regression by Lanmei Wang, Yao Wang, Guibao Wang, Jianke Jia

“…In this article, principal component analysis method, which is applied to image compression and feature extraction, is introduced into the dimension reduction of input characteristic variable of support vector regression, and a method of joint estimation of near-field angle and range based on principal component analysis dimension reduction is proposed. …”
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Optimal Over-Frequency Droop Control for DFIG-Based Wind Farms Under Unreliable Communication by Yaxin Wang, Donglian Qi, Jianliang Zhang, Yulin Chen

“…Nowadays, high penetration of wind power is integrated into power grids, and WTs usually adopt the MPPT algorithm to maximize power output, which decouples the rotor speeds of wind turbines (WTs) and system frequency. …”
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Variational quantum Hamiltonian engineering by Benchi Zhao, Keisuke Fujii

“…Furthermore, we show that VQHE is compatible with grouping strategies, enabling further reductions in measurement complexity for expectation value estimation. …”
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Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa a... by Shaun Scholes, Jennifer S Mindell, Mari Toomse-Smith, Annibale Cois, Kafui Adjaye-Gbewonyo

“…Laboratory- and non–laboratory-based World Health Organization (WHO) and Globorisk algorithms were used to calculate the predicted 10-year total (fatal and nonfatal) CVD risk. …”
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Optimization of State Clustering and Safety Verification in Deep Reinforcement Learning Using KMeans++ and Probabilistic Model Checking by Ryeonggu Kwon, Gihwon Kwon

“…The continuous state space is clustered using the KMeans++ algorithm, enabling efficient state space reduction. …”
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Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning by Pol Suárez, Francisco Alcántara-Ávila, Jean Rabault, Arnau Miró, Bernat Font, Oriol Lehmkuhl, Ricardo Vinuesa

“…The setup involves multiple zero-net-mass-flux jets and couples a computational fluid dynamics solver with a numerical multi-agent reinforcement learning framework based on the proximal policy optimization algorithm. Our results demonstrate up to 16% drag reduction at R e D  = 400, outperforming classical periodic control strategies. …”
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Characterization of Moisture Diffusion in Cured Concrete Slabs at Early Ages by Xiao Zhang, Hongduo Zhao

“…Lower w/c ratio tends to result in larger RH reduction. RH reduction considering both effect of diffusion and self-desiccation in early-age concrete is not sensitive to w/c ratio, but to curing method. …”
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Deep learning can reduce acquisition time of T2-weighted image in brain imaging by Eman Hassan El-Saeed Abou-ELMagd, Sabry Alameldin Elmogy, Dina Gamal Abdelzaher

“…Abstract Background We used the deep learning-based reconstruction algorithm to reduce the scan time for brain T2-weighted images (T2WI) with reduction of image noise and preservation of image quality. …”
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