River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…An adaptive threshold Sobel operator in the edge channel improves the model’s ability to extract edge features in STI. …”
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The Potential of Unsupervised Induction of Harmonic Syntax for Jazz by Ruben Cartuyvels, John Koslovsky, Marie-Francine Moens

“…Hierarchical structures describing a syntax of harmony have long been studied and proposed by music theorists, but algorithms that model these structures either require costly expert annotations for training or are based on music theorists' predispositions about harmonic syntax. …”
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Real-Time Multi-Vehicle Scheduling in Tasks With Dependency Relationships Using Multi-Agent Reinforcement Learning by Shupei Zhang, Huapeng Shi, Wei Zhang, Ying Pang, Pengju Sun

“…Firstly, this study introduces a classification model of task relationships through the binary assumption model of geographical areas and vehicles. …”
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Landslide Identification from Post-Earthquake High-Resolution Remote Sensing Images Based on ResUNet–BFA by Zhenyu Zhao, Shucheng Tan, Yiquan Yang, Qinghua Zhang

“…The experimental results indicate that the ResUNet–BFA model outperforms widely used algorithms in extracting landslide boundaries and details, resulting in fewer misclassifications and omissions. …”
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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…Many studies only focus on improving the machine learning classification algorithms to achieve higher performance. …”
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An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
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Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis by Maurilio Gustavo Nespeca, Rafael Rodrigues Hatanaka, Danilo Luiz Flumignan, José Eduardo de Oliveira

“…The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). …”
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Detection of left atrial enlargement in dogs using deep learning in thoracic radiographs by Lucas Auto Lopes, Anaemilia das Neves Diniz, Helio Silva Neto

“…The decision tree accuracy was 69.6%, sensitivity 68.0%, specificity 71.0%, and AUC 69.6%. The classifier model with different algorithms can help radiologists improve the analysis of medical images by reducing errors, starting a selective double reading. …”
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Detection of left atrial enlargement in dogs using deep learning in thoracic radiographs by Lucas Auto Lopes, Anaemilia das Neves Diniz, Helio Silva Neto

“…The decision tree accuracy was 69.6%, sensitivity 68.0%, specificity 71.0%, and AUC 69.6%. The classifier model with different algorithms can help radiologists improve the analysis of medical images by reducing errors, starting a selective double reading. …”
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AI-Powered Innovations in Food Safety from Farm to Fork by Binfeng Yin, Gang Tan, Rashid Muhammad, Jun Liu, Junjie Bi

“…Secondly, during food processing, sensors combined with machine learning algorithms are utilized to ensure regulatory compliance and monitor production parameters. …”
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AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

“…This study introduces a novel DE-FinFET featuring a stepped field plate to improve overall performance of device. Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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Risk prediction method for power Internet of Things operation based on ensemble learning by Chao Hong, Xiaoyun Kuang, Yiwei Yang, Yixin Jiang, Yunan Zhang

“…Compared with traditional models, the accuracy was 98.61%, and the overall accuracy was improved by 0.60%. …”
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Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
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Smart Farming: AI and IoT-Based Solutions for Real-Time Agriculture Monitoring by Kadao Anjali Krushna, Shivaji Ghorpade Bipin

“…The machine learning models are used to predict possible points of problems like disease outbreaks or nutrient deficiencies so that appropriate steps can be taken preemptively. …”
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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care by Diala Haykal

“…Perspectives: Looking forward, the development of diverse, inclusive datasets and transparent, patient-centered AI models will be essential to ensure that AI’s benefits reach all patients equitably and safely. …”
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Beyond purchase patterns: harnessing predictive analytics to anticipate unarticulated consumer needs by Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Mansour

“…The results underscore the importance of integrating human-centered design with algorithmic precision to translate predictive insights into actionable business value.…”
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Water Quality Monitoring: A Water Quality Dataset from an On-Site Study in Macao by Jiawei Gao, Bochao Chen, Su-Kit Tang

“…Among these models, Random Forest exhibited the best overall performance, achieving an accuracy of 98.10% and an F1 score of 98.99%. …”
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Collaborative filtering-based Madura Island tourism recommendation system using RecommenderNet by Permana Kurniawan Eka, Rahmat Abdullah Basuki, Wicaksana Dyo Adya, Ardianto Dicky

“…The collected data were processed, formatted, and modeled using the RecommenderNet architecture, with training and validation to optimize system performance. …”
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Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability by Krisztián Horváth, Ambrus Zelei

“…This is particularly important in the context of electric vehicles, where high-frequency tone noise should be reduced, benefiting both passengers and their environment. Improving these factors is in line with the goals of the United Nations and improves the quality of urban life. …”
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Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based... by Yasin P, Ding L, Mamat M, Guo W, Song X

“…The model demonstrated robust predictive performance and was effectively integrated into a user-friendly online application, offering a practical solution to enhance surgical decision-making and improve patient outcomes in real-time clinical settings.Keywords: tuberculosis spondylitis, osteoporosis, machine learning, threshold tuning, logistic regression…”
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