Numerical model of surface morphology and solid-liquid contact angle in wire electrical discharge machining by Zhi Chen, Yifei Zhou, Zefeng Yang, Zhizhong Zhang, Jian Li, Guojun Zhang, Fenglin Han

Get full text

A Hybrid Fault Diagnosis Model for Rolling Bearing With Optimized VMD and Fuzzy Dispersion Entropy by Xin Xia, Xiaolu Wang, Weilin Chen

“…To improve the efficiency of feature extraction and fault diagnosis, a hybrid model based on optimized variational mode decomposition (VMD), fuzzy dispersion entropy (FDE), and a support vector machine (SVM) is proposed. …”
Get full text

Advancing Underwater Vision: A Survey of Deep Learning Models for Underwater Object Recognition and Tracking by Mahmoud Elmezain, Lyes Saad Saoud, Atif Sultan, Mohamed Heshmat, Lakmal Seneviratne, Irfan Hussain

“…State-of-the-art (SOTA) models, including AGW-YOLOv8, Feature-Adaptive FPN, and Dual-SAM, have shown substantial improvements in addressing occlusions, camouflaging, and small underwater object detection. …”
Get full text

Automated severity level estimation of wheat rust using an EfficientNet-CBAM hybrid model by Sapna Nigam, Rajni Jain, Vaibhav Kumar Singh, Ashish Kumar Singh, Hari Krishna, Hari Krishna

“…Moreover, comparative analysis against state-of-the-art CNN models highlights the superior performance of our approach. …”
Get full text

Comparison of deep learning models for predictive maintenance in industrial manufacturing systems using sensor data by Wenjun Li, Ting Li

“…Through ablation studies and feature importance analysis, we identify critical components and parameters that influence model performance. …”
Get full text

A network intrusion detection method based on contrastive learning and Bayesian Gaussian Mixture Model by Liyou Liu, Ming Xu

“…However, existing machine learning-based NIDS often require complex feature engineering, which demands significant domain expertise and experimentation, leading to suboptimal model performance in complex network environments. …”
Get full text

A Machine-Learning Model for the Prediction of Triple-Negative Breast Cancer Based on Multiparameter MRI by Cai Y, Li Y, Wang W, Zhou Y, Wang J, Zhang L, Lu H

“…The machine learning classifier XGboost was developed based on the features to predict TNBC. The area under the receiver operating characteristic (ROC) curve (AUC) was applied to evaluate the model prediction ability. …”
Get full text

A target detection model HR-YOLO for advanced driver assistance systems in foggy conditions by Yao Zhang, Na Jia

“…Abstract To improve the accuracy and real-time performance of detection algorithms in Advanced Driver Assistance Systems (ADAS) under foggy conditions, this paper introduces HR-YOLO, an improved YOLO-based model specifically designed for vehicle and pedestrian detection. …”
Get full text

Development and Experimental Validation of Auxiliary Rolling Bearing Models for Active Magnetic Bearings (AMBs) Applications by Anna Tangredi, Enrico Meli, Andrea Rindi, Alessandro Ridolfi, Pierluca D’Adamio, Amedeo Frilli, Duccio Fioravanti, Benjamin Defoy

“…Some of the elements of the proposed model have been previously introduced in literature; however the present work proposes some new features of interest. …”
Get full text

A Deep Learning based Optimization Model for Based Computer Interface of Wheelchair Directional Control by Zaid Raad Saber Zubair

“… An efficient recognition model is highly recommended while trying to analyze brain signal pattern for Motor Imagery (MI) signal. …”
Get full text

CSCA-YOLOv8: A lightweight network model for evaluating drought resistance in mung bean. by Dongshan Jiang, Jinyang Liu, Haomiao Zhang, Wenxiang Liang, Ziqiu Luo, Wenlong An, Shicong Li, Xin Chen, Xingxing Yuan, Shangbing Gao

“…We also verified the excellent performance and generalization performance of the model using the collected MDD dataset. …”
Get full text

ML modeling of ultimate and relative bond strength for corroded rebars based on concrete and steel properties by Alireza Hosseinzadeh Kashani, Mansour Ghalehnovi, Hossein Etemadfard

Get full text

A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques by Cong Peng, Cheng Gong, Xiaoya Zhang, Duxian Liu

“…Additionally, Shapley Additive Explanations (SHAP) were applied to interpret feature importance within the model, revealing the clinical factors that influence survival predictions.ResultsAmong the nine models, the lightGBM model exhibited the best performance, with an AUC and F1 score of (0.8, 0.809) for 1-year survival prediction, (0.809, 0.751) for 3-year survival prediction, and (0.773, 0.611) for 5-year survival prediction. …”
Get full text

LLM-MalDetect: A Large Language Model-Based Method for Android Malware Detection by Ruirui Feng, Hui Chen, Shuo Wang, Md Monjurul Karim, Qingshan Jiang

Get full text

Optimized Prediction of Weapon Effectiveness in BVR Air Combat Scenarios Using Enhanced Regression Models by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…This study investigates high-performance models for predicting the Weapon Engagement Zone (WEZ) in beyond-visual-range (BVR) air combat scenarios. …”
Get full text

High-Precision Defect Detection in Solar Cells Using YOLOv10 Deep Learning Model by Lotfi Aktouf, Yathin Shivanna, Mahmoud Dhimish

“…This study presents an advanced defect detection approach for solar cells using the YOLOv10 deep learning model. Leveraging a comprehensive dataset of 10,500 solar cell images annotated with 12 distinct defect types, our model integrates Compact Inverted Blocks (CIBs) and Partial Self-Attention (PSA) modules to enhance feature extraction and classification accuracy. …”
Get full text

Prediction of failures in the project management knowledge areas using optimized ensemble models in software companies by Lamia Berriche, Abderrazak Loulizi

“…The best soft voting combination—DT, KNN, LR, and CatBoost—achieved an accuracy of 93.21%. The stacking model with DT, KNN, and LR as base-learners and SVM as the meta-learner performed best, reaching 93.73%. …”
Get full text

Vehicle Lane Change Multistep Trajectory Prediction Based on Data and CNN_BiLSTM Model by Shijie Gao, Zhimin Zhao, Xinjian Liu, Yanli Jiao, Chunyang Song, Jiandong Zhao

“…Thirdly, the trajectory data of the US-101 dataset in NGSIM is selected to verify the performance of the CNN-BiLSTM model, and at the same time, it is compared with models such as CNN-LSTM, long short-term memory (LSTM), BiLSTM, and CNN-GRU-Att. …”
Get full text

Automated quantification of SARS-CoV-2 pneumonia with large vision model knowledge adaptation by Zhaohui Liang, Zhiyun Xue, Sivaramakrishnan Rajaraman, Sameer Antani

“…A dataset with 2599 CXR images was used for model training and evaluation. Results: The model based on the pretrained vision transformer (ViT) and self-supervised learning achieved the best performance in cross validation, with mean squared error (MSE) of 23.83 (95 % CI 22.67–25.00) and mean absolute error (MAE) of 3.64 (95 % CI 3.54–3.73). …”
Get full text

Application of Artificial Neural Network Models in Segmentation and Classification of Nodules in Breast Ultrasound Digital Images by Karem D. Marcomini, Antonio A. O. Carneiro, Homero Schiabel

Get full text