A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) is proposed to optimize the Backpropagation Neural Network (BP) model (PSO-GWO-BP) and a pressure drop prediction model for the joint station export system is established using PSO-GWO-BP. …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The algorithm effectively handled the CT images at the preprocessing stage, and the deep learning model performed well in detecting and classifying nodules. …”
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Comparative Assessment of Several Effective Machine Learning Classification Methods for Maternal Health Risk by Md Nurul Raihen, Sultana Akter

“…Maternal risk analysis can improve prenatal care, improve mother and baby health, and optimize healthcare resources by identifying misclassified observations using machine learning algorithms such as LDA, QDA, KNN, Decision Tree, Random Forest, Bagging, and Support Vector Machine, all of which have a significant impact on maternity health risk assessment. …”
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Day-Ahead Scheduling of IES Containing Solar Thermal Power Generation Based on CNN-MI-BILSTM Considering Source-Load Uncertainty by Kun Ding, Yalu Sun, Boyang Chen, Jing Chen, Lixia Sun, Yingjun Wu, Yusheng Xia

“…The validity of the proposed model is verified by algorithm prediction simulation and day-ahead scheduling experiments under different configurations.…”
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Convergence of evolving artificial intelligence and machine learning techniques in precision oncology by Elena Fountzilas, Tillman Pearce, Mehmet A. Baysal, Abhijit Chakraborty, Apostolia M. Tsimberidou

“…Currently, many operational and technical challenges exist related to data technology, engineering, and storage; algorithm development and structures; quality and quantity of the data and the analytical pipeline; data sharing and generalizability; and the incorporation of these technologies into the current clinical workflow and reimbursement models.…”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…This AI-driven helmet detection model demonstrates significant potential in improving occupational safety by assisting safety officers, especially in confined environments, reducing human error, and enhancing efficiency.…”
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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…As Machine Learning algorithms become increasingly embedded in decision-making processes, particularly for traffic management and other high-level commitment applications, concerns regarding the transparency and trustworthiness of complex ‘black-box’ models have grown. …”
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Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

“…One way to improve IDS performance is by using machine learning. …”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

“…This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. …”
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Multi-label classification for image tamper detection based on Swin-T segmentation network in the spatial domain by Li Li, Kejia Zhang, Jianfeng Lu, Shanqing Zhang

“…Our method introduces three key innovations: (1) A spatial perception module that combines the spatial rich model (SRM) with constrained convolution, enabling focused detection of tampering traces while suppressing interference from image content; (2) A hierarchical feature learning architecture that integrates Swin Transformer with UperNet for effective multi-scale tampering pattern recognition; and (3) A comprehensive optimization strategy including auxiliary supervision, self-supervised learning, and hard example mining, which significantly improves model convergence and detection accuracy. …”
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Fast Multimodal Trajectory Prediction for Vehicles Based on Multimodal Information Fusion by Likun Ge, Shuting Wang, Guangqi Wang

“…Finally, we propose a multi-stage decoder that generates more accurate and reasonable predicted trajectories by predicting trajectory reference points and performing spatial and posture optimization on the predicted trajectories. Comparative experiments with existing advanced algorithms demonstrate that our method improves the minimum Average Displacement Error (minADE), minimum Final Displacement Error (minFDE), and Miss Rate (MR) by 10.3%, 10.3%, and 14.5%, respectively, compared to the average performance. …”
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MUFFNet: lightweight dynamic underwater image enhancement network based on multi-scale frequency by Dechuan Kong, Dechuan Kong, Yandi Zhang, Xiaohu Zhao, Yanqiang Wang, Lei Cai

“…A Multi-Scale Joint Loss framework facilitates dynamic network optimization.ResultsExperimental results demonstrate that MUFFNet outperforms existing state-of-the-art models while consuming fewer computational resources and aligning enhanced images more closely with human visual perception.DiscussionThe enhanced images generated by MUFFNet exhibit better alignment with human visual perception, making it a promising solution for improving underwater robotic vision systems.…”
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Flexible interconnected support for decarbonizing local energy systems with high penetration distributed energy resources and electric vehicles by Xuefei Zhang, Niancheng Zhou, Jianquan Liao, Qianggang Wang, Yiyao Zhou, Xiaolong Xu, Edris Pouresmaeil

“…Furthermore, the total line losses of the LESs can be reduced by optimizing the transmitted power of the device by utilizing a genetic algorithm. …”
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Designing and implementing a Web-based real time routing service for crisis management (a case study for district 11 of Tehran) by javad sadidi, seyed hassan hosseini sajedi

“…In this service ANP model was used to evaluate increasing interaction between the factors, and since the purpose of this study was to find the best possible routs between two nodes by non-negative weight according to the main distance factor, Dijkstra's algorithm has been chosen as a proper routing algorithm. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…We propose CWA-YOLO, a detection framework integrating multi-scale feature fusion and an enhanced small-object detection head into YOLOv8 to improve accuracy across variable conditions. Additionally, a federated learning (FL) system tailored for substations enables collaborative model training without centralized data sharing, addressing privacy concerns and data heterogeneity. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Experimental findings indicate that the CSGEH-YOLO algorithm surpasses the baseline YOLOv8s, achieving a 3.1% improvement in mAP. …”
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Numerical Methodology for Enhancing Heat Transfer in a Channel with Arc-Vane Baffles by Piphatpong Thapmanee, Arnut Phila, Khwanchit Wongcharee, Naoki Maruyama, Masafumi Hirota, Varesa Chuwattanakul, Smith Eiamsa-ard

“…The calculations utilize the finite volume method, and the SIMPLE algorithm is executed with the QUICK scheme. For the analysis of turbulent flow, the finite volume method with the Renormalization Group (RNG) <i>k-ε</i> turbulence model was used. …”
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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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A Registration Method for Historical Maps Based on Self-Supervised Feature Matching by Zikang Qin, Yumin Feng, Gang Wu, Qing Dong, Tianxin Han

“…Experimental results indicate that our solution achieves superior performance compared to existing models, with RMSE reduced by up to 20%, ROCC improved by up to 10%, and processing time shortened by at least 15%.…”
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Blind super-resolution network based on local fuzzy discriminative loss for fabric data augmentation by Ning Dai, Xiaohan Hu, Kaixin Xu, Xudong Hu, Yanhong Yuan, Bo Cao, Luhong Shi

“…To address these challenges, this paper proposes a blind super-resolution algorithm for fabric defect data augmentation. The model is based on Real-ESRGAN and has been optimized specifically for the resolution degradation module to better adapt to the resolution degradation process in fabric images. …”
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