Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling by Mrudul Jambulkar, Shivam Ojha, Amit Shelke, Anowarul Habib

“…To overcome these challenges, this study proposes an unsupervised learning framework that combines k-means clustering with a multi-phase gamma process to detect and model damage in aluminum plates. …”
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Identification of Abnormal Electricity Consumption Behavior of Low-Voltage Users in New Power Systems Based on a Combined Method by Jiaolong Gou, Xudong Niu, Xi Chen, Shuxin Dong, Jing Xin

“…In the second stage, based on the coarse classification results from GBDT, the data are partitioned into multiple subsets, and the KNN algorithm is applied to fine classification within each subset. …”
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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

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Advancements and trends in mangrove species mapping based on remote sensing: A comprehensive review and knowledge visualization by Yuqi Wu, Chunyan Lu, Kexin Wu, Wenna Gao, Nuocheng Yang, Jingwen Lin

“…Existing studies have utilized various remote sensing image for mangrove species classification, including airborne hyperspectral, spaceborne visible, infrared, multispectral, hyperspectral, synthetic aperture radar (SAR), and drone-borne visible, infrared, multispectral, hyperspectral, light detection and ranging (LiDAR) data. Classification algorithm development has evolved four stages, from pixel-based methods to object-oriented approaches, progressing to approaches incorporating machine learning algorithms, and currently advancing towards ensemble learning and deep learning. …”
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Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…The proposed TL-SAM framework effectively extracts spatial and spectral features from patient health data, optimizing classification accuracy. Furthermore, the model employs an Improved Wild Horse Optimization with Levy Flight Algorithm (IWHOLFA) for hyperparameter tuning, enhancing its predictive performance. …”
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Non-Iterative Reconstruction and Selection Network-Assisted Channel Estimation for mmWave MIMO Communications by Jing Yang, Yabo Guo, Xinying Guo, Pengpeng Wang

“…Millimeter-wave (mmWave) MIMO systems have emerged as a key enabling technology for next-generation wireless networks, addressing the growing demand for ultra-high data rates through the utilization of wide bandwidths and large-scale antenna configurations. …”
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CNN-LSTM-Attention with PSO optimization for temperature and fault prediction in meat grinder motors by Yao Zhang, Pengfei Zhang, Wenchao Zhang, Mingwei Wang

“…Additionally, the PSO algorithm optimized the number of neurons and the learning rate in the model. …”
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A plug and play fuzzy mask extraction module for single image deraining by Mingdi Hu, Yao Song, Songxin Zhang, Zejian Xie, Bingyi Jing

“…The proposed fuzzy mask learning model is critically beneficial for either rain removal algorithms.…”
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The impact of artificial intelligence on financial auditing: the case of Algeria by Amira Benachour, Ramzi Kaddai, Hanane Abdelmalek, Fella Bochelgoum, Lamine Tarhlissia

“…It enables auditors to go beyond the limits of manual analysis, facilitating more accurate and data-driven decisions. AI algorithms can analyze vast volumes of transactions to detect anomalies that may indicate fraud, such as duplications, unexplained discrepancies, or unusual transaction patterns. …”
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DeepSARFlood: Rapid and automated SAR-based flood inundation mapping using vision transformer-based deep ensembles with uncertainty estimates by Nirdesh Kumar Sharma, Manabendra Saharia

“…Synthetic Aperture Radar (SAR) satellites can overcome these limitations, allowing for high-resolution flood mapping. However, SAR data remains underutilized due to less availability of training data, and reliance on labor-intensive manual or semi-automated change detection methods. …”
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ConsensuSV-ONT – A modern method for accurate structural variant calling by Antoni Pietryga, Mateusz Chiliński, Sachin Gadakh, Dariusz Plewczynski

“…The field has also been subject to revolution in machine learning techniques, especially deep learning. To address the aforementioned need and developments, we propose a novel, fully automated ConsensuSV-ONT algorithm. …”
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Threshold-free multi-attributes physical layer authentication based on expectation–conditional maximization channel estimation in Internet of Things by Tao Jing, Hongyan Huang, Yue Wu, Qinghe Gao, Yan Huo, Jiayu Sun

“…Simulation results demonstrate that the obtained attribute estimates are sufficient to provide a reliable source of data for authentication and the proposed threshold-free multi-attributes physical layer authentication scheme can effectively improve authentication accuracy, with the false alarm rate P f reduced to 0.0263% and the miss detection rate P m reduced to 0.3466%.…”
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Recent Progress in Ocean Intelligent Perception and Image Processing and the Impacts of Nonlinear Noise by Huayu Liu, Ying Li, Tao Qian, Ye Tang

“…When combined with image enhancement, data augmentation, and transfer learning methods, deep learning algorithms can be applied to effectively address the challenges of underwater image degradation and nonlinear noise interference. …”
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Anomaly-Aware Tropical Cyclone Track Prediction Using Multi-Scale Generative Adversarial Networks by He Huang, Difei Deng, Liang Hu, Nan Sun

“…To address these challenges, we propose a generative adversarial network (GAN) model with a multi-scale architecture that processes input data at four distinct resolution levels. The model is designed to handle diverse inputs, including satellite cloud imagery, vorticity, wind speed, and geopotential height, and it features an advanced center detection algorithm to ensure precise TC center identification. …”
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Advanced leukocyte classification using attention mechanisms and dual channel U-Net architecture by Gauri Kalnoor, Vijayalaxmi Kadrolli

“…This ADCU-Net model is particularly selected to effectively capture various features and preserve spatial data, achieving98.4% accuracy. Overall, this paper highlights the performance of integrated sophisticated deep-learning structures for accurate leukocyte classification and segmentation, enabling the path for improved diagnostic tools in clinical settings.…”
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Centrality nearest-neighbor projected-distance regression (C-NPDR) feature selection for correlation-based predictors with application to resting-state fMRI study of major depressi... by Elizabeth Kresock, Bryan Dawkins, Henry Luttbeg, Yijie Jamie Li, Rayus Kuplicki, B A McKinney

“…<h4>Background</h4>Nearest-neighbor projected-distance regression (NPDR) is a metric-based machine learning feature selection algorithm that uses distances between samples and projected differences between variables to identify variables or features that may interact to affect the prediction of complex outcomes. …”
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AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review by Xuanchi Guo, Yuhan Shao

“…This review will focus on the fusion of AI-driven multimodal data analysis (e.g., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. …”
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Assessment of Seismic Hazard Potential for a Geothermal Field: A Case Study in West Texas by Victor Salles, Guo-Chin Dino Huang, Katerine Vallejo, Peter Eichhubl, Shuvajit Bhattacharya, Alexandros Savvaidis

“…Application of the machine-learning (ML)-based EarthQuake Compact Convolutional Transformer (EQCCT) algorithm to seismic data from 2008 to 2011 resulted in the detection of 645 seismic events in the area, lowering the magnitude detection threshold compared to public catalogs (e.g., U.S. …”
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Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques by Fan Zhao, Zhiyan Ren, Jiaqi Wang, Qingyang Wu, Dianhan Xi, Xinlei Shao, Yongying Liu, Yijia Chen, Katsunori Mizuno

“…The findings pave the way for advanced, data-driven precision agriculture, integrating deep learning with remote sensing methodologies to improve floriculture management.…”
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AI approaches for phenotyping Alzheimer's disease and related dementias using electronic health records by Sara Knox, Stephanie Aghamoosa, Paul M. Heider, Maxwell Cutty, Andrew Wright, Dmitry Scherbakov, Gabriel Hood, Sara A. Nolin, Jihad S. Obeid

“…Several of the AI‐based models, including convolutional neural networks, also outperformed the CCW algorithm. DISCUSSION These findings highlight the potential of AI‐based text‐classification methods to optimize the automated identification of patients with ADRD using rich EHR data. …”
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