A machine learning-based depression risk prediction model for healthy middle-aged and older adult people based on data from the China health and aging tracking study by Fang Xia, Jie Ren, Linlin Liu, Yanyin Cui, Yufang He

“…BackgroundPredicting depression risk in adults is critical for timely interventions to improve quality of life. To develop a scientific basis for depression prevention, machine learning models based on longitudinal data that can assess depression risk are necessary.MethodsData from 2,331 healthy older adults who participated in the China Health and Retirement Longitudinal Study (CHARLS) from 2018 to 2020 were used to develop and validate the predictive model. …”
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Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning by Shuai Zhou, Shuai Zhou, Shuai Zhou, Shuai Zhou, Zexiang Liu, Zexiang Liu, Zexiang Liu, Haoge Huang, Haoge Huang, Haoge Huang, Hanxu Xi, Xiao Fan, Xiao Fan, Xiao Fan, Yanbin Zhao, Yanbin Zhao, Yanbin Zhao, Xin Chen, Xin Chen, Xin Chen, Yinze Diao, Yinze Diao, Yinze Diao, Yu Sun, Yu Sun, Yu Sun, Hong Ji, Feifei Zhou, Feifei Zhou, Feifei Zhou

“…After training and optimizing multiple ML algorithms, we generated a model with the highest area under the receiver operating characteristic curve (AUROC) to predict short-term outcomes following DCM surgery. …”
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Dynamic Reporting Nodes Selection Method for Network Awareness Based on Active–Passive Integrated Network Telemetry in LEO Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

“…Specifically, an APINT model is built which can dynamically select the optimal reporting node and reduce awareness time through the bidirectional aggregation of telemetry packets along the service path. …”
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Performance Testing and Analysis of a New GNSS Spoofing Detection Method in Different Spoofing Scenarios by Li Junzhi, Wu Haitao, Gao Jinfeng, Liu Fang, Zhang Yu, Li Gangqiang, He Yu

“…To overcome these shortcomings, this study extracts multi-dimensional parameters from observational data. By improving the RF algorithm and introducing a weighted voting mechanism to optimize the classification decision process, a high-precision classification model is constructed. …”
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Investigations into Picture Defogging Techniques Based on Dark Channel Prior and Retinex Theory by Lihong Yang, Zhi Zeng, Hang Ge, Yao Li, Shurui Ge, Kai Hu

“…The method involves building a two-stage optimization framework: in the first stage, global contrast enhancement is achieved by Retinex preprocessing, which effectively improves the detail information regarding the dark area and the accuracy of the transmittance map and atmospheric light intensity estimation; in the second stage, an a priori compensation model for the dark channel is constructed, and a depth-map-guided transmittance correction mechanism is introduced to obtain a refined transmittance map. …”
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Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly by Claudio Urrea

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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…The main purpose of this study is to address these challenges and improve vehicle detection in ITS environments. We propose a novel detection framework, YDFNet, that integrates the YOLOv10 algorithm for fast feature extraction, the BiFPN (Bidirectional Feature Pyramid Network) for multi-scale feature fusion, and the DETR (Detection Transformer) architecture for global feature modeling. …”
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Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…In particular, under high-density and mixed traffic conditions, the trajectory optimization model significantly improves traffic flow, reduces congestion, decreases energy consumption, and lowers the incidence of traffic accidents, thereby offering a theoretical foundation for the implementation of intelligent transportation systems.…”
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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Subsequently, an automatic optimization algorithm for the reference point of the agricultural vehicle is designed to prevent excessive steering during path tracking. …”
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Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance by HUANG Zhenzhen, SUN Jinlin, DING Shihong

“…Subsequently, an automatic optimization algorithm for the reference point of the agricultural vehicle is designed to prevent excessive steering during path tracking. …”
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Short-Term Load Forecasting for Electrical Power Distribution Systems Using Enhanced Deep Neural Networks by Shewit Tsegaye, Sanjeevikumar Padmanaban, Lina Bertling Tjernberg, Kinde Anlay Fante

“…This represents a 7.486% improvement over the prediction obtained using only LSTM model. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Key predictors included spatially lagged spectral bands (e.g., Green_lag, NIR_lag, RedEdge_lag) and VIs (e.g., CREI, GCI, NCPI, ARI, CCCI), highlighting the value of integrating neighborhood data for improved corn yield prediction. This study underscores the importance of spatial context in corn yield prediction and lays the foundation for future research across diverse agricultural settings, focusing on optimizing neighborhood size, integrating spatial and spectral data, and refining spatial dependencies through localized search algorithms.…”
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Enabling High-Level Worker-Centric Semantic Understanding of Onsite Images Using Visual Language Models with Attention Mechanism and Beam Search Strategy by Hui Deng, Kejie Fu, Binglin Yu, Huimin Li, Rui Duan, Yichuan Deng, Jia-rui Lin

“…The addition of the attention mechanism and beam search strategy improves the model, making it more accurate and generalizable. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Key AI techniques, including support vector machines (SVMs) (7.90% of studies), decision trees, and gradient-boosting models, offer substantial improvements in cost prediction and resource optimization. …”
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A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…In experimental evaluations, the system demonstrated a detection rate improvement of up to 1.9 times faster compared to traditional models in identifying and isolating malicious nodes, while maintaining consistent trust evaluations for legitimate nodes. …”
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Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature by Muhammad Ishtiaq, Saurabh Tiwari, Molakatala Nagamani, Sung-Gyu Kang, Nagireddy Gari Subba Reddy

“…The ANN model’s findings offer valuable insights for researchers and designers, aiding in developing steel components with optimized properties. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. …”
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Satellite-Derived Bathymetry Combined With Sentinel-2 and ICESat-2 Datasets Using Deep Learning by Weidong Zhu, Yanying Huang, Tiantian Cao, Xiaoshan Zhang, Qidi Xie, Kuifeng Luan, Wei Shen, Ziya Zou

“…The model employs BOA to optimize the key hyperparameters of the CNN-BILSTM architecture, thereby improving inversion performance. …”
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An Efficient Anomalous Sound Detection System for Microcontrollers by Yi-Cheng Lo, Tsung-Lin Tsai, Chieh-Wen Yang, An-Yeu Wu

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