Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…This study design may result in an increasing number of false positives and a significant decrease in the prediction rates and classification performance. Moreover, recent studies have focused on improving prediction performance using complex feature extraction and machine learning algorithms while ignoring comprehensive EEG channels and feature investigation in the prediction of finger movements from EEGs. …”
Get full text

Development of Explainable Machine Learning Models to Identify Patients at Risk for 1-Year Mortality and New Distant Metastases Postendoprosthetic Reconstruction for Lower Extremit... by Jiawen Deng, BHSc, Myron Moskalyk, BHSc, MSc, Madhur Nayan, MD, PhD, Ahmed Aoude, MEng, MD, FRCSC, Michelle Ghert, MD, FRCSC, Sahir Bhatnagar, PhD, Anthony Bozzo, MSc, MD, FRCSC

“…LightGBM was identified as the best-performing algorithm for both outcomes. For 1-year mortality prediction without percent necrosis, LightGBM achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% confidence interval [CI] 0.70-0.86) during cross-validation and 0.72 on internal validation. …”
Get full text

Exposing Face Manipulation Based on Generative Adversarial Network–Transformer and Fake Frequency Noise Traces by Qiaoyue Man, Young-Im Cho

“…In recent years, with the application of GANs and diffusion generative network algorithms, many highly realistic synthetic images are emerging, greatly increasing the potential for misuse, and deepfakes have become a serious social concern. …”
Get full text

Parameter estimation for networked SIR models with stochastic perturbations using JEKF: a study using COVID-19 daily data from Indian states by Prince Achankunju, Saroj Kumar Dash

“…This sophisticated estimation algorithm iteratively predicts and refines the state based on current estimates, combining model predictions with observed data to enhance accuracy, making it effective for estimating critical parameters in dynamic systems. …”
Get full text

Sparse long short-term memory for information fusion in wireless sensor networks by Yangfan Zhou, Mingchuan Zhang, Ping Xie, Junlong Zhu, Ruijuan Zheng, Qingtao Wu

“…Furthermore, the prediction accuracy of the sparse long short-term memory algorithm is almost the same as the other comparison algorithms.…”
Get full text

Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…A soft sensor model is studied to predict the BOD5 in a wastewater treatment plant to evaluate the proposed approach. …”
Get full text

How Re-Infections and Newborns Can Impact Visible and Hidden Epidemic Dynamics? by Igor Nesteruk

“…With the use of effective algorithms for parameter identification, the proposed approach can ensure effective predictions of visible and hidden numbers of cases and infectious and removed patients.…”
Get full text

Exploring the Role of Artificial Intelligence in Dental Implantology: A Scholarly Review by Abdulrahman Ahmed Aseri

“…AI-based technologies, such as machine learning algorithms, neural networks, and computer vision, are being increasingly utilized to interpret diagnostic imaging, predict implant outcomes, and customize treatment protocols tailored to individual patient needs. …”
Get full text

Employee loyalty evaluation using machine learning in technology-based small and medium-sized enterprises by Yong Shi, Yuan Wang, Hongkun zuo

“…Through several machine learning models and algorithms to predict employee loyalty, the feasibility of machine learning to predict employee loyalty is proved, and the evaluation of talent in TSMEs is supported by decision analysis. …”
Get full text

Potential geographical distribution of Carob tree (Ceratonia siliqua L., Leguminosae) in Morocco under climate change by Jalal Kassout, Soufian Chakkour, Abdeltif El Ouahrani, Younes Hmimsa, Salama El Fatehi, Yanzheng Yan, Rachid Hadria, Mohammed Ater

“…Our hypothesis suggests a reduction in suitable habitats for the carob tree under climate change scenarios. …”
Get full text

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. …”
Get full text

An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting by Haipeng Zhang, Hua Luo

“…Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. …”
Get full text

Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…After data augmentation, the prediction model exhibits significant reductions in RMSE and MAE along with an increase in the R² value. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Privacy-Preserving Machine Learning (PPML) Inference for Clinically Actionable Models by Baris Balaban, Seyma Selcan Magara, Caglar Yilgor, Altug Yucekul, Ibrahim Obeid, Javier Pizones, Frank Kleinstueck, Francisco Javier Sanchez Perez-Grueso, Ferran Pellise, Ahmet Alanay, Erkay Savas, Cetin Bagci, Osman Ugur Sezerman

“…Machine learning (ML) refers to algorithms (often models) that are learned directly from data, germane to past experience. …”
Get full text

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam. by Raja Das, Pham Van Tien, Karl W Wegmann, Madhumita Chakraborty

“…The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. …”
Get full text

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. …”
Get full text