Image Classification to Identify Style Composition Ratios in Crossover Cars by Hung-Hsiang Wang, Hung-Jui Su

“…As the global demand for multifunctional and high-performance vehicles increases, automotive manufacturers face significant challenges in designing new crossover models. …”
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Development of a machine learning-based prediction model for serious bacterial infections in febrile young infants by Jina Lee, Jong Seung Lee, Seak Hee Oh, Jun Sung Park, Reenar Yoo, Soo-young Lim, Dahyun Kim, Min Kyo Chun, Jeeho Han, Jeong-Yong Lee, Seung Jun Choi

“…Urinalysis, C-reactive protein and procalcitonin were identified as top-tier features in the XGB model.Conclusions The ML-based prediction model demonstrated robust performance, with superior specificity and perfect sensitivity, which may enhance the accuracy of SBI detection and reduce the costs associated with false positives.…”
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Health assessment and health trend prediction of wind turbine bearing based on BO-BiLSTM model by Zhenen Li, Yujie Xue

“…The network integrates the selected degradation features and constructs a health index curve; (4) Based on the constructed health index curve, optimize the BiLSTM network hyperparameters through Bayesian and establish a BO-BiLSTM network model to achieve a more accurate and scientific prediction of the health index trend.…”
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Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients by Wenwei Zuo, Xuelian Yang

“…In addition, the SHAP (Shapley Additive Explanations) method was used to rank the importance of features and to interpret the final model. Results We screened seven features to construct a predictive model. …”
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Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

“…Specifically, in terms of the root mean square error (RMSE), the Spearman-GCN-GRU model exhibits a respective decrease of 13.90%, 11.66%, and 8.36% compared to the GRU, GCN and deep neural network (DNN) models, demonstrating its superior predictive performance.…”
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CloudSense: A model for cloud type identification using machine learning from radar data by Mehzooz Nizar, Jha K. Ambuj, Manmeet Singh, S.B. Vaisakh, G. Pandithurai

“…Among various ML models evaluated Light Gradient Boosting Machine (LightGBM) demonstrate superior performance in classifying cloud types with a BAC (Balanced Accuracy) of 0.79 and F1-Score of 0.8. …”
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Research on Indoor Object Detection and Scene Recognition Algorithm Based on Apriori Algorithm and Mobile-EFSSD Model by Wenda Zheng, Yibo Ai, Weidong Zhang

“…Object detection results are converted into text features, and the Apriori algorithm extracts object associations. …”
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A review on amino acid based protein classification using supervised artificial intelligence (AI) models by Rida Zulfiqar, Talha Ahmed Khan, Abdullah Ayub Khan, Rubaika Akhtar, Sajid Ullah

“…Consequently, the study's findings demonstrated significant performance disparities between deep learning models like 1D Dilated CNN and machine learning models like SVM, Random Forest, and Naive Bayes. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…The proposed model combined with transformer-based long-term dependency modeling and convolution-based visual feature extraction to improve object detection performance. …”
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AI-powered prediction model for neoadjuvant chemotherapy efficacy: comprehensive analysis of breast cancer histological images by Fengling Li, Yani Wei, Wenchuan Zhang, Yuanyuan Zhao, Jing Fu, Xiuli Xiao, Yan Qiu, Yuhao Yi, Yongquan Yang, Hong Bu

“…We developed an artificial intelligence (AI)-driven integrated predictive model (IPM) combining histopathological, clinical, and immune features to address this challenge. …”
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Mapping Global Solar Radiation from Long-Term Satellite Data in the Tropics Using an Improved Model by S. Janjai, I. Masiri, S. Pattarapanitchai, J. Laksanaboonsong

“…In order to test its performance, the model is employed to calculate monthly average daily global solar radiation at 36 solar monitoring stations across the country. …”
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Identification of Depression Patients Using LIF Spiking Neural Network Model From the Pattern of EEG Signals by Rekha Sahu, Prasant Kumar Pattnaik, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah

“…A Spiking Neural Network is a machine learning approach that emphasizes the data value and manipulates the value to find the particular signal feature. Finding the specific abnormal features of electroencephalography signals can help to detect depression patients. …”
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Sentimental analysis based federated learning privacy detection in fake web recommendations using blockchain model by Jitendra Kumar Samriya, Amit Kumar, Ashok Bhansali, Meena Malik, Varsha Arya, Wadee Alhalabi, Bassma Saleh Alsulami, Brij B. Gupta

“…A comprehensive evaluation of effectiveness is performed for each classifier. Results from the classification process indicated that a predictive model could be developed, leveraging tweet data, to distinguish between spam and non-spam content and to determine associated sentiment. …”
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A Remote Sensing Semantic Self-Supervised Segmentation Model Integrating Local Sensitivity and Global Invariance by Buxun Zhang, Xiaoyan Guo, Sen Yang

“…This framework combines the strengths of contrastive learning and masked image modeling, focusing on both global feature information invariant to augmentations and the rich internal detail of the images. …”
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Predicting Social Media Popularity With Large Language Models: Transforming Metadata Into Semantic-Enriched and Contextualized Text by Tianjian Chen, Jiang Huang, Xuetong Wu, Changcheng Shao

“…Disregarding this relationship leads to issues such as loss of context, incomplete feature representation, difficulty in feature engineering, and lack of domain knowledge integration. …”
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CNN-Transformer-BiGRU: A Pump Fault Detection Model for Industrialized Recirculating Aquaculture Systems by Wei Shao, Chengquan Zhou, Dawei Sun, Chen Li, Hongbao Ye

“…Using it improved the accuracy, precision, and recall by 1.86%, 1.97%, and 1.86%, respectively, relative to the convolutional neural network and long short-term memory (CNN-LSTM) model. Conclusions: Hence, the proposed model has superior performance indicators. …”
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Real-time monitoring and optimization of machine learning intelligent control system in power data modeling technology by Qiong Wang, Zuohu Chen, Yongbo Zhou, Zhiyuan Liu, Zhenguo Peng

“…Recursive feature elimination method can be used for feature selection in the model, and multi-model integration method can be used for feature fusion. …”
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VDMS: An Improved Vision Transformer-Based Model for PM_2.5 Concentration Prediction by Tong Zhao, Meixia Qu

“…These enhancements contribute to greater stability and robustness in feature representation, ultimately improving prediction performance. …”
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Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model. by Kaustubh Supekar, Vinod Menon

“…Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. …”
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Modeling agro-hydrological surface-subsurface processes in a semi-arid, intensively irrigated river basin by Salam A. Abbas, Ryan T. Bailey, Jeffrey G. Arnold, Michael J. White, Ali Mirchi

“…The model is tested against streamflow and groundwater head, showing good performance along the Arkansas River and the alluvial corridor. …”
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