Presenting the model of factors affecting the resilience of entrepreneurial behavior in Technical and Vocational University of Alborz province by Ali Abdi Jamayran, Manouchehr Niknam, Hasan Rangriz

“…The purpose of this research is to provide a model of factors affecting the resilience of entrepreneurial behavior in Alborz Technical and Vocational University. …”
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Contrast-enhanced mammography-based interpretable machine learning model for the prediction of the molecular subtype breast cancers by Mengwei Ma, Weimin Xu, Jun Yang, Bowen Zheng, Chanjuan Wen, Sina Wang, Zeyuan Xu, Genggeng Qin, Weiguo Chen

“…Abstract Objective This study aims to establish a machine learning prediction model to explore the correlation between contrast-enhanced mammography (CEM) imaging features and molecular subtypes of mass-type breast cancer. …”
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A Hybrid VGG16‐ViT Approach With Image Processing Techniques for Improved White Blood Cell Classification and Disease Diagnosis: A Retrospective Study by Md Shahin Ali, Md. Maruf Hossain, Md. Mahfuz Ahmed, Kazi Rubaya Nowrin, S. M. Mahim, Shakib Al Hasan, Moutushi Akter Kona, Md Shafiqul Islam, Kazi Mowdud Ahmed, Md Mahbubur Rahman, Md Khairul Islam

“…The VGG16‐ViT model was trained and evaluated on two datasets to measure its performance. …”
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Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Then fifteen algorithms were used to establish models, and an ensemble model was established through soft voting based on the top five performance algorithms. …”
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Accuracy–Efficiency Trade-Off: Optimizing YOLOv8 for Structural Crack Detection by Jiahui Zhang, Zoia Vladimirovna Beliaeva, Yue Huang

“…To address the accuracy–efficiency trade-off faced by deep learning models in structural crack detection, this paper proposes an optimized version of the YOLOv8 model. …”
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Progressive multi-scale attention neural network for pneumonia classification in chest X-rays by Mohammad Reza Mahdiani

“…Unlike previous methods that overlook fine-grained edge information or fail to integrate multi-scale contextual features, our approach synergistically combines convolutional multi-scale feature extraction using depthwise separable convolutions with cross-layer feature fusion, Transformer blocks, advanced attention mechanisms, and a custom loss function that emphasizes diagnostically relevant edge details using Canny edge detection. …”
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Data Acquisition and Chatter Recognition Based on Multi-Sensor Signals for Blade Whirling Milling by Xinyu Li, Riliang Liu, Zhiying Zhu

“…The features are then input into an MLGRU-based chatter recognition model, incorporating a self-attention mechanism (SAM) for enhanced performance. …”
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Integrating particle swarm optimization with backtracking search optimization feature extraction with two-dimensional convolutional neural network and attention-based stacked bidir... by Jyotirmayee Rautaray, Sangram Panigrahi, Ajit Kumar Nayak

“…The model’s performance is assessed using datasets from DUC 2002, 2003, and 2005 for single-document summarization, and from DUC 2002, 2003, and 2005, Multi-News, and CNN/Daily Mail for multi-document summarization. …”
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Advanced Dense Text Detection in Graded Examinations Leveraging Chinese Character Components by Renyuan Liu, Yunyu Shi, Xian Tang, Xiang Liu

“…The above improvements comprehensively improve the performance of the network in detecting and segmenting the mini-components and subtle strokes of handwritten Chinese characters; The CEE model was tested on the self-constructed dataset with an accuracy of 84.6% and a mini-component mAP of 77.6%, which is an improvement of 7.4% and 8.4%, respectively, compared to the original model; The constructed dataset and improved model are well suited for applications such as writing grade examinations, and represent an important exploration of the development of educational intelligence.…”
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Probabilistic Forecasting of Offshore Wind Power Based on Dual-stage Attentional LSTM and Joint Quantile Loss Function by Xiangjing SU, Haibo YU, Yang FU, Shuxin TIAN, Haiyu LI, Fuhai GENG

“…To improve the probabilistic prediction accuracy, a multi-task joint quantile loss-based dual-attention probabilistic prediction model (MT-DALSTM) is proposed. Firstly, a feature and temporal dual attention mechanism is introduced to mine the correlation and temporal dependence among features, and attention weights are given to key features and time point information to improve the accuracy of power prediction. …”
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An IMU-Based Machine Learning System for Container Collision Position Identification by Xin Zhang, Zihan Song, Do-Myung Park, Byung-Kwon Park

“…Statistical analysis with the Friedman test confirmed significant differences in model and feature selection performance. The combination of k-nearest neighbors and extra trees achieved the highest accuracy of 97.1%, demonstrating that inexpensive IMU acceleration data can provide a cost-effective, efficient, and reliable solution for collision detection. …”
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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

“…After the course training, data indicators such as students’ homework, projects and exams are comprehensively extracted, and the correlation analysis between students’ performance and characteristics, time series analysis, feature fusion and weight analysis, model performance evaluation and prediction analysis are carried out. …”
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Res-RBG Facial Expression Recognition in Image Sequences Based on Dual Neural Networks by Xiangwei Mou, Yongfu Song, Xiuping Xie, Mingxuan You, Rijun Wang

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MM-iTransformer: A Multimodal Approach to Economic Time Series Forecasting with Textual Data by Shangyang Mou, Qiang Xue, Jinhui Chen, Tetsuya Takiguchi, Yasuo Ariki

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Machine learning-based radiomics prognostic model for patients with proximal esophageal cancer after definitive chemoradiotherapy by Linrui Li, Zhihui Qin, Juan Bo, Jiaru Hu, Yu Zhang, Liting Qian, Jiangning Dong

“…Dual-region radiomics features showed significantly better predictive performance. …”
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Improved bio-inspired with machine learning computing approach for thyroid prediction by Divya Kesavulu, Kannadasan R

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Rolling Bearing Reliability Assessment via Kernel Principal Component Analysis and Weibull Proportional Hazard Model by Fengtao Wang, Xutao Chen, Bosen Dun, Bei Wang, Dawen Yan, Hong Zhu

“…Successful reliability assessment, which is dependent on selecting features that accurately reflect performance degradation as the inputs of the assessment model, allows for the proactive maintenance of equipment. …”
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An Enhanced Measurement of Epicardial Fat Segmentation and Severity Classification using Modified U-Net and FOA-guided XGBoost by Rajalakshmi K, Palanivel Rajan S

“…They also demonstrate the suitability of the model to improve cardiovascular risk assessment and management.…”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Firstly, based on the diffusion model, a mask-embedding data augmentation method, MEDiffusion, is proposed. …”
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Integrated intraoperative predictive model for malignancy risk assessment of thyroid nodules with atypia of undetermined significance cytology by Cheng Li, Yong Luo, Yan Jiang, Qi Li

“…Clinical, ultrasound, and pathological features were extracted for analysis. Three models were developed: an IOFS model with IOFS results as sole predictor, a clinical model integrating clinical and ultrasound features, and an integrated model combining all features. …”
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