A Novel Local Binary Patterns-Based Approach and Proposed CNN Model to Diagnose Breast Cancer by Analyzing Histopathology Images by Mehmet Gul

“…The histopathology images improved with the QS-LBP method were then analyzed with the most commonly used Random Forest and Optimized Forest algorithms among machine learning algorithms. …”
Get full text

Development of a Weighted Average Ensemble Model for Predicting Officially Assessed Land Prices Using Grid Map Data and SHAP by Surin Im, Kangmin Kim, Geunhee Lee, Hoi-Jeong Lim

“…The model analyzes the impact of key variables through SHAP for improved interpretability. …”
Get full text

Multi-Skilled Project Scheduling for High-End Equipment Development Considering Newcomer Cultivation and Duration Uncertainty by Yaohui Liu, Ronggui Ding, Shanshan Liu, Lei Wang

“…Therefore, we put forward an adaptive simulation–optimization approach featuring two-fold: a simulation module capable of dynamically adjusting sample sizes based on convergence feedback and evaluating solutions with improved efficiency and stable accuracy; a tailored non-dominated sorting genetic algorithm II (NSGA-II) with adaptive evolutionary operators that enhance search effectiveness and ensure the identification of a well-distributed Pareto front. …”
Get full text

Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…The results indicated that among the four machine learning algorithms (XGBoost, LR, SVM, and Naive Bayes), the LR model demonstrated the best and most stable predictive performance. …”
Get full text

Three-Dimensional Shape Reconstruction from Digital Freehand Design Sketching Based on Deep Learning Techniques by Ding Zhou, Guohua Wei, Xiaojun Yuan

Get full text

Research on Dynamic Performance of Autonomous-rail Rapid Tram by ZHONG Hanwen, LI Xiaoguang, XIAO Lei, YANG Yong, ZHANG Chenlin, HUANG Ruipeng, YUAN Xiwen

“…Through detailed Simpack dynamic model, the simulation research was carried out to provide guidance for optimization and improvement of vehicle dynamic performance. …”
Get full text

Enhancing Aerosol Vertical Distribution Retrieval With Combined LSTM and Transformer Model From OCO-2 O2 A-Band Observations by YuXuan Wang, RuFang Ti, ZhenHai Liu, Xiao Liu, HaiXiao Yu, YiChen Wei, YiZhe Fan, YuYao Wang, HongLian Huang, XiaoBing Sun

“…Furthermore, a physics-based, information-driven band selection method was developed to simplify input data and reduce complexity. To enhance the algorithm's applicability, the model was applied across the entire African continent and adjacent water bodies. …”
Get full text

Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems by Marouane Ahmed Ghodbane, Toufik Mohamed Benchouia, Mohamed Chebaani, Mohamed Becherif, Yassine Himeur, Amar Golea, Abdelmoumen Ghilani, Zakaria Alili, Shadi Atalla, Wathiq Mansoor

“…This approach does not require an anemometer, mechanical parameters, or rotor position sensors, making the system simpler, more reliable, and cost-effective. The 3V FS-PTC algorithm enhances control performance by selecting the three most optimal voltage vectors, two active voltage vectors and one zero voltage vector. …”
Get full text

PolSAR Forest Height Estimation Enhancement With Polarimetric Rotation Domain Features and Multivariate Sensitivity Analysis by Fu-Gen Jiang, Ming-Dian Li, Si-Wei Chen

“…Then, we propose a Bayesian-optimized ensemble learning algorithm to improve the accuracy of forest height estimation. …”
Get full text

Advanced clustering and transfer learning based approach for rice leaf disease segmentation and classification by Samia Nawaz Yousafzai, Fahd N. Al-Wesabi, Hadeel Alsolai, Shouki A. Ebad, Inzamam Mashood Nasir, Emad Fadhal, Adel Thaljaoui

“…Also, the tent chaotic particle snow ablation optimizer is added into the learning process in order to improve the learning process and shorten the time of convergence. …”
Get full text

Research on Fault Diagnosis of Traction Power Supply System Based on PSO-LSSVM by Lei ZHANG

“…According to the working principle and characteristics of the train power supply system, the relationship between the fault phenomenon and the origin was analyzed, and the characteristic signals used for fault diagnosis were extracted. A fault diagnosis model based on PSO optimized least squares support vector machine was established, and PCA algorithm was used to extract data characteristics as input of fault diagnosis model, and reduce input dimension. …”
Get full text

Adaptive Quantum-Inspired Evolution for Denoising PCG Signals in Unseen Noise Conditions by Lubna Siddiqui, Ashish Mani, Jaspal Singh

“…The filter coefficients were optimised using the proposed QiEA with Adaptive Rotation Gate Operator (ARGO). The proposed algorithm accelerates convergence towards optimal solutions based on fitness feedback, improving filter optimisation while clamping rotation angles to maintain algorithm stability. …”
Get full text

Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…When domain judgments were derived from LLM-generated signaling questions using the RoB2 algorithm rather than direct LLM domain judgments, accuracy improved substantially for Domain 2 (adhering; 55-95) and overall (adhering; 70-90). …”
Get full text

Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Twenty-two clinical features available within the first 24 h of admission were selected to develop the prediction models. Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. …”
Get full text

Research on Key Technologies of Virtual Coupling Control System for Autonomous-rail Rapid Tram by HUANG Qiang, YUAN Xiwen, HU Yunqing, LI Cheng, HUANG Ruipeng, TANG Xiang

“…A safe braking model of autonomous-rail rapid tram is initiatively used to derive the minimum space headway for operation safety between coupled formations, and the collaborative planning and MPC-based collaborative control algorithms utilizing an optimal control approach are applied to guarantee the safe, punctual, comfortable, and efficient operation of coupled formations. …”
Get full text

Detecting Anomalies in Hydraulically Adjusted Servomotors Based on a Multi-Scale One-Dimensional Residual Neural Network and GA-SVDD by Xukang Yang, Anqi Jiang, Wanlu Jiang, Yonghui Zhao, Enyu Tang, Zhiqian Qi

“…This model uses a multi-scale one-dimensional residual neural network (M1D_ResNet) for feature extraction and a genetic algorithm (GA)-optimized support vector data description (SVDD). …”
Get full text

Machine Learning in the National Economy by Azamjon A. Usmonov

“…Methods of cleaning, normalization, and data transformation were used for data processing to improve model accuracy. The practical part of the study included the development of machine learning algorithms for predicting economic indexes. …”
Get full text

Deep learning models for detection of explosive ordnance using autonomous robotic systems: trade-off between accuracy and real-time processing speed by Vadym Mishchuk, Herman Fesenko, Vyacheslav Kharchenko

“…The main contribution of this study is the results of a detailed evaluation of the YOLOv8 and RT-DETR models for real-time EO detection, helping to find trade-offs between the speed and accuracy of each model and emphasizing the need for special datasets and algorithm optimization to improve the reliability of EO detection in autonomous systems.…”
Get full text

Model‐Free Deep Reinforcement Learning with Multiple Line‐of‐Sight Guidance Laws for Autonomous Underwater Vehicles Full‐Attitude and Velocity Control by Chengren Yuan, Changgeng Shuai, Zhanshuo Zhang, Jianguo Ma, Yuan Fang, YuChen Sun

Get full text

Dealing with the Outlier Problem in Multivariate Linear Regression Analysis Using the Hampel Filter by Amira Wali Omer, Taha Hussein Ali

“…These outliers may occur in the dependent variable or both independent and dependent variables, resulting in large residual values that compromise model reliability. Addressing outliers is essential for improving the accuracy and robustness of regression models.  …”
Get full text