Study on Dust Distribution Law in Open-Pit Coal Mines Based on Depth Variation by Dongmei Tian, Xiyao Wu, Jian Yao, Weiyu Qu, Jimao Shi, Kaishuo Yang, Jiayun Wang

“…The research team developed a three-dimensional geological model updating algorithm with depth gradient as the characteristic parameter, enabling dynamic monitoring of mining depth with a model iteration accuracy of 0.5 m per update. …”
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The Heavy‐Tailed Inverse Power Lindley Type‐I Model: Reliability Inference and Actuarial Applications by Amal S. Hassan, Diaa S. Metwally, Mohammed Elgarhy, Rokaya Elmorsy Mohamed

“…ABSTRACT The analysis and modeling of asymmetric data present an interesting and important area of research across various applied sciences, particularly in lifetime studies, medical research, and financial analysis. …”
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Automatic detection and prediction of epileptic EEG signals based on nonlinear dynamics and deep learning: a review by Shixiao Tan, Zhen Tang, Qiang He, Ying Li, Yuliang Cai, Jiawei Zhang, Di Fan, Zhenkai Guo

“…These methods reveal dynamic patterns in signals, thereby substantially improving epilepsy detection and prediction accuracy. …”
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A multimodal approach for ADHD with coexisting ASD detection for children by Jungpil Shin, Sota Konnai, Md. Maniruzzaman, Yoichi Tomioka, Yong Seok Hwang, Akiko Megumi, Akira Yasumura

“…This study proposes a novel approach that increase the detection rate and provides new insights for further research.…”
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Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios by HU Heng, QIN Jianru, LI Haibo, LIU Jiefeng

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Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit by Joaquin Gonzalez, Liliana Avelar Sosa, Gabriel Bravo, Oliverio Cruz-Mejia, Jose-Manuel Mejia-Muñoz

“…<i>Methods</i>: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

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”My AI is Lying to Me”: User-reported LLM hallucinations in AI mobile apps reviews by Rhodes Massenon, Ishaya Gambo, Javed Ali Khan, Christopher Agbonkhese, Ayed Alwadain

“…Using a mixed-methods approach, a heuristic-based User-Reported LLM Hallucination Detection algorithm were applied to identify  20,000 candidate reviews, from which 1,000 are manually annotated. …”
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Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…To accomplish better preservation of the geometry of high-dimensional data and more effective feature extraction, the HLLE algorithm is applied. These features are then inputted into a GNN, which utilizes the graph structure to identify and analyze metastatic patterns. …”
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Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data by Seunghui Kim, Jae Eun Ko, Seungbin Baek, Daechang Kim, Sungmin Kim

“…To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. …”
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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…To classify the reviews, we introduce a personalized multicentroid K-means algorithm, which improves traditional K-means by allowing a more precise clustering of false and genuine reviews. …”
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Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

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Hydroecological limitations of the use of water resources of transboundary rivers of the steppe zone (through the example of the Ural and Tobol Rivers, Russia) by Zh. T. Sivohip, V. M. Pavleichik, A. A. Chibilev, Yu. A. Padalko, M. A. Kozlova, O. B. Popova

“…As a result, an urgent task is to develop an algorithm for a comprehensive assessment of hydroecological restrictions on water use and their consequences for the population and economy of the regions of the steppe zone.…”
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INTEGRATED ASSESSMENT AND MAPPING OF ANTHROPOGENIC IMPACT ON THE NATURAL ENVIRONMENT OF RUSSIAN REGIONS by V. S. Tikunov, S. K. Belousov

“…Based on the obtained set of indicators for the study, a two-stage evaluation algorithm developed by one of the authors was chosen [Tikunov, 1997]. …”
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Transformer attention fusion for fine grained medical image classification by Danyal Badar, Junaid Abbas, Raed Alsini, Tahir Abbas, Wang ChengLiang, Ali Daud

“…This model uses self-attention mechanics to improve spatial connections between single scales and cross-attention to automatically match feature patterns across multiple scales, thereby developing a comprehensive information structure. …”
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Two Decades of Coastal Development across the Arabian Gulf: Insights from Remote Sensing and Machine Learning by B. Dahy, R. Sousa, M. Sultan, J. A. Burt

“…These findings emphasize the complex interactions between urbanization and environmental processes, underscoring the need for sustainable planning strategies. Future research will focus on detailed analyses of vegetation, urbanization trends, and long-term inundation patterns to better support climate adaptation and regional resilience planning in the Arabian Gulf.…”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…By structuring insights from the extensive literature, this paper aims to establish ANNs as a foundational tool in next-generation battery management systems, ultimately supporting safer and more efficient EVs through real-time fault detection, accurate SOC estimation, and robust safety protocols. Future research directions include refining dataset quality, optimizing algorithm selection, and enhancing diagnostic precision, thereby broadening ANNs’ role in ensuring reliable battery management in electric vehicles.…”
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Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation by Yuan Meng, Rong Hu, Song-Bin Guo, Deng-Yao Liu, Zhen-Zhong Zhou, Hai-Long Li, Wei-Juan Huang, Xiao-Peng Tian

“…Using an unsupervised clustering algorithm, we identified six dominant research clusters, among which Cluster 1 (standardizing response assessment criteria for NAI to minimize its adverse reactions; average citation=34.86±95.48) had the highest impact and Cluster 6 (efficacy and safety of multiple therapy patterns combination) was an emerging research cluster (temporal central tendency=2022.43, research effort dispersion=0.52), with “irAEs” (s=0.4242 (95% CI: 0.01142 to 0.8371), R2=0.4125, p=0.0453), “ICIs” (immune checkpoint inhibitors) (s=1.127 (95% CI: 0.5403 to 1.714), R2=0.7103, p=0.0022), and “efficacy and safety” (s=0.5455 (95% CI: 0.1145 to 0.9764), R2=0.5157, p=0.0193) showing significant overall growth. …”
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Low Illumination Video Image Enhancement by Zhi Li, Zhenhong Jia, Jie Yang, Nikola Kasabov

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