What If VEC Is Moving: Probabilistic Model of Task Execution Through Offloading in Vehicular Computing Environments by Asmaa Ibrahim, Bassem Mokhtar

“…The features of vehicular networks, including the rapid movement of vehicles and the fluctuating distribution of vehicle densities, present challenges to task offloading with in the VEC. Numerous algorithms have been suggested to address these challenges and provide an effective task-offloading framework. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Efficient base metal exploration in northern New Brunswick, Canada through a hybrid ANN integrated with ABC and PSO methods by Claire Dusabemariya, Wei Qian, Romuald Bagaragaza, Ajibola Richard Faruwa, Ali Mossad

“…By integrating Artificial Neural Networks (ANN) with metaheuristic algorithms, specifically Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO), the research optimizes resistivity inversion techniques to enhance geophysical exploration. …”
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The negative linear relationship between oxidative balance scores and constipation: a cross-sectional study from NHANES 2005–2010 by Liqian Xuan, Yang Chen, Chang Liu, Yahui Dai

“…The three machine learning algorithms including Xgboost, Randomforest, and AdaBoost was used to analyze the important component of OBS in constipation.ResultsA total of 8,074 participants were involved. …”
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Predicting plant uptake of potential contaminants of emerging concerns using machine learning models (2018–2025): A global review by Alexis Munyengabe, Maria Fezile Banda, Wilma Augustyn

“…It identifies dominant predictors and modelling approaches while highlighting significant research gaps: limited data, inconsistent feature reporting, and underexplored uncertainty-sensitivity coupling. …”
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Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Energy Peer-to-Peer (P2P) systems have thus been shown to be beneficial for prosumers and consumers through reductions in energy cost while also being attractive to grid or service providers. …”
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Enhancing dosimetric precision in the treatment of cancerous tumors: Gamma Index validation and Monte Carlo simulations of 6 and 12 megavoltage photon beams from Varian Medical lin... by Ali H. D. Alshehri

“…IntroductionThe accuracy of dose delivery in radiotherapy is paramount to maximize tumor control while minimizing damage to surrounding healthy tissues. …”
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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Recent research has explored machine learning-based approaches using smartphone accelerometers to classify intoxicated gait patterns. While neural network approaches have emerged, due to the significant challenges with collecting intoxicated gait data, gait datasets are often too small to utilize such approaches. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington’s Disease, ataxia, or Tourette Syndrome. …”
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Ensemble stacked model for enhanced identification of sentiments from IMDB reviews by Komal Azim, Alishba Tahir, Mobeen Shahroz, Hanen Karamti, Annia Almeyda Vazquez, Angel Rojas Vistorte, Imran Ashraf

“…The suggested ensemble RRLS model performs better than other learning algorithms and achieves a 90% accuracy rate, outperforming current methods. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…This success has led to the development of several advanced sharpness-based algorithms aimed at addressing the limitations of SAM, such as Adaptive SAM, Surrogate-Gap SAM, Weighted SAM, and Curvature Regularized SAM. …”
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A Novel Hybrid Analysis Method of LLC Resonant Converter for High Accuracy and Low Computational Burden by Su-Seong Park, Rae-Young Kim

“…This paper proposes an analysis model that can estimate the efficiency of the converter and the temperature of component parts with high accuracy while requiring a relatively low computational burden when analyzing LLC resonant converters. …”
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Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation by K. Radha, Yepuganti Karuna

“…Our goal is to generate multiple realistic retinal fundus images based on tubular structured annotations while simultaneously creating binary masks from the retinal fundus images. …”
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An analytic research and review of the literature on practice of artificial intelligence in healthcare by Salma Mizna, Suraj Arora, Priyanka Saluja, Gotam Das, Waled Abdulmalek Alanesi

“…Addressing ethical and security considerations is crucial for the successful integration of AI in healthcare while upholding patient safety and legal standards. …”
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Factors influencing the spatial distribution of police stops and their efficacy in crime prevention and control by Zhuoying Fan, Xuewei Zhang, Guangwen Song, Chunxia Zhang

“…The space is partitioned using hierarchical clustering after applying the XGBoost and SHAP algorithms to determine the factors related to police stops. …”
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AI Act as EU Legislator’s Response to Challenges of Artificial Intelligence Development by Monika Wyszomirska

“…In this article, the author analyses the main challenges of AI regulation, highlighting the difficulties of defining AI, protecting human rights, ensuring algorithmic transparency, and balancing the innovation of this technology with human and environmental safety. …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

“…We compare three disaggregation algorithms with a benchmark model by efficiently selecting a subset of training data through three query strategies that identify the data requiring labeling. …”
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Enhanced gap-filling for satellite-derived crop monitoring using temperature-driven reconstruction techniques by Flavian Tschurr, Lukas Valentin Graf, Achim Walter, Helge Aasen

“…Our approach requires fewer satellite observations compared to traditional remote sensing time series algorithms, making it suitable for agricultural areas with high cloud cover. …”
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High-Level Implicit Enumerations for Quadratic Periodic Train Timetabling with Prioritized Cross-Line Operations by Congcong Zou, Hongxia Lv, Miaomiao Lv, Shaoquan Ni, Qinglun Zhong

“…The results demonstrate that our proposed method can efficiently achieve flexible while recoverable operational times for the cross-line services and the proposed implicit enumeration algorithms significantly outperform the direct linearization, which increases the search space significantly due to the considerable dimensionality of the periodic decision variables involved. …”
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