An ensemble time-embedded transformer model for traffic conflict prediction at RRFB pedestrian crossings by Md Jamil Ahsan, Mohamed Abdel-Aty, B M Tazbiul Hassan Anik, Zubayer Islam

“…Insights from the study can optimize RRFB performance by identifying conflict times and locations, improving driver alerts during peak hours, and ensuring smoother traffic flow and reliability.…”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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Machine Learning-Based Prediction of Feed Conversion Ratio: A Feasibility Study of Using Short-Term FCR Data for Long-Term Feed Conversion Ratio (FCR) Prediction by Xidi Yang, Liangyu Zhu, Wenyu Jiang, Yiting Yang, Mailin Gan, Linyuan Shen, Li Zhu

“…Feed conversion ratio (FCR) is a critical indicator of production efficiency in livestock husbandry. Improving FCR is essential for optimizing resource utilization and enhancing productivity. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Medical images (9/26, 34.6%) and electronic medical records (7/26, 26.9%) were the most commonly used data types. Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. The YOLO (You Only Look Once) neural network has significantly improved fruit detection through image processing and has automated several related tasks. …”
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Characterization of Irrigated Rice Cultivation Cycles and Classification in Brazil Using Time Series Similarity and Machine Learning Models with Sentinel Imagery by Andre Dalla Bernardina Garcia, Ieda Del’Arco Sanches, Victor Hugo Rohden Prudente, Kleber Trabaquini

“…The processing of input data and exploratory analysis were performed using a clustering algorithm based on Dynamic Time Warping (DTW), with K-means applied to the time series. …”
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The evaluation model of engineering practice teaching with complex network analytic hierarchy process based on deep learning by Xianlong Han, Xiaohui Chen

“…Abstract This study aims to effectively improve the quality evaluation system of engineering practice teaching in colleges and universities and enhance the efficiency of teaching management. …”
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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…Linear discriminant analysis was the most accurate (74.6%) algorithm with the shortest training time (0.9 s). …”
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Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…Thus, the proposed Weighted Hybrid Random Forest algorithm (WHBM) utilized the 63 features that comprise the whole brain volume. …”
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Reliability and Validity of the Single-Camera Markerless Motion Capture System for Measuring Shoulder Range of Motion in Healthy Individuals and Patients with Adhesive Capsulitis:... by Suji Lee, Unhyung Lee, Yohwan Kim, Seungjin Noh, Hungu Lee, Seunghoon Lee

“…Future enhancements to the algorithm and the incorporation of advanced metrics could improve its performance, facilitating broader clinical applications for diagnosing complex shoulder conditions.…”
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BedEye: A Bed Exit and Bedside Fall Warning System Based on Skeleton Recognition Technology for Elderly Patients by Liang-Bi Chen, Wan-Jung Chang, Tzu-Chin Yang

“…Falls are an important medical safety issue, and patients older than 65 years are the most prone to falling in hospitals. According to a previous study, approximately 80% of falls occur near hospital beds. …”
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Histopathological Image Analysis Using Machine Learning to Evaluate Cisplatin and Exosome Effects on Ovarian Tissue in Cancer Patients by Tuğba Şentürk, Fatma Latifoğlu, Çiğdem Gülüzar Altıntop, Arzu Yay, Zeynep Burçin Gönen, Gözde Özge Önder, Özge Cengiz Mat, Yusuf Özkul

“…Exosome treatments, particularly when administered post-cisplatin, significantly improve ovarian tissue recovery. …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…Abstract Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major cause of death. …”
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Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

“…In addition, regularization techniques were applied, including cross-validation, feature selection, boost methods, L1 (Lasso) and L2 (Ridge) regularization, as well as hyperparameter optimization. These strategies generated more robust and accurate models, with the multilayer perceptron regressor (MLP regressor) and extreme gradient boosting (XGBoost) algorithms standing out. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Enhancing stone matrix asphalt performance with sugarcane bagasse ash: Mechanical properties and machine learning-based predictions using XGBoost and random forest by Hamed Khani Sanij, Rezvan Babagoli, Reza Mohammadi Elyasi

“…The results revealed that the inclusion of 6 % SCBA yielded the most favorable outcomes. Marshall Stability increased significantly (up to 9.4 kN), ITS improved to 943 kPa, and moisture susceptibility was enhanced, demonstrating a higher tensile strength ratio compared to the control mixture. …”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…The increasing adoption of wind turbines as a key component of renewable energy generation necessitates the development of efficient and reliable maintenance strategies to ensure their optimal performance and safety. Among the most critical aspects of turbine maintenance is detecting and classifying defects in wind turbine blades, which are constantly exposed to extreme environmental conditions. …”
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Semantic Segmentation with Multispectral Satellite Images of Waterfowl Habitat by Mateo Gannod, Nicholas Masto, Collins Owusu, Cory Highway, Katherine Brown, Abigail Blake-Bradshaw, Jamie Feddersen, Heath Hagy, Douglas Talbert, Bradley Cohen

“…We found the use of multispectral bands was necessary and although the CIR composite and OSAVI index improved precision, the 12-band composite increased recall, the metric we were most interested in. …”
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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…Coal gangue sorting is the most basic, effective, and important technical measure to improve coal quality. …”
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Measurement Techniques for Highly Dynamic and Weak Space Targets Using Event Cameras by Haonan Liu, Ting Sun, Ye Tian, Siyao Wu, Fei Xing, Haijun Wang, Xi Wang, Zongyu Zhang, Kang Yang, Guoteng Ren

“…In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. …”
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