A Deep Learning-Based Diagnostic Framework for Shaft Earthing Brush Faults in Large Turbine Generators by Katudi Oupa Mailula, Akshay Kumar Saha

“…The proposed framework combines advanced signal processing and convolutional neural networks (CNNs) to automatically recognize fault-related patterns in shaft grounding current and voltage signals. …”
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Study on the spatial and temporal differentiation of intangible cultural heritage and its influencing factors in Shandong province by Linliang Zou, Pengfei Tai, Xinchun Wang, Junjie Jiao, Yingtian Wang

“…Abstract This study examines 357 sports-related intangible cultural heritage (ICH) items in Shandong Province, employing an integrated methodology combining GIS spatial analysis, geodetector modeling, and comparative approaches to investigate their multi-tiered spatial distribution patterns. Through six analytical dimensions—natural ecological environment, sociodemographic conditions, economic development level, regional cultural foundations, transportation accessibility, and policy frameworks—the research systematically evaluates differential influences on spatial configuration. …”
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Protection Boundary Development in Historical–Cultural Built Environments Using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) by Can Kara, Aminreza Iranmanesh

“…To cope with this, it is essential to frequently re-evaluate and redefine protective boundaries and strategies for developing them to reflect current and emerging urban patterns. …”
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Personalized trajectory inference framework integrating driving behavior recognition and temporal dependency learning. by Jinhao Yang, Junwen Cao, Mingyu Fang

“…The framework operates through three rigorously designed stages: (1)Data preprocessing involving kinematics feature extraction, (2)Driving style recognition utilizing acceleration variation rate and average time headway combined with K-Means++ traffic density clustering and K-neighbor Gaussian mixture model (K-GMM) analysis to classify driving behaviors into conservative, moderate, and radical categories, and (3)Personalized trajectory prediction employing a multi-level neural architecture with dedicated sub-networks for distinct driving styles. Experimental evaluations demonstrate DS-TCTM's superior performance across multiple dimensions. …”
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Smart Implementation and Expectations for Sustainable Buildings: A Scientometric Analysis by Yuxing Xie, Xianhua Sun

“…Amidst global efforts toward sustainable development, this research addresses underexplored academic dimensions by evaluating the transformative potential of intelligent, sustainable architecture. …”
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Risk analysis of wastewater reuse in agriculture by Jacques Ganoulis

“…Economic and technical factors should also be taken into consideration, such as the water and wastewater treatment costs, the cost of maintenance, the employment of rural labour, the structure of irrigation networks and crop patterns. In this paper, the concept of sustainability in wastewater reclamation and reuse is formulated by using a general risk analysis framework and by taking into account all the above factors. …”
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Environmental impacts shape the density-size relationship of benthic macroinvertebrates in Amazonian streams (Serra dos Carajás, Pará, Brazil) by Maria Eduarda Cabral Liberal, Camila Pinto Leão, Jaqueline Silva de Oliveira, Francisco Valente-Neto, Bruno Spacek Godoy

“…These changes suggest a simplification of trophic networks and decreased energy transfer efficiency. …”
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Temporal Dynamics in Short Text Classification: Enhancing Semantic Understanding Through Time-Aware Model by Khaled Abdalgader, Atheer A. Matroud, Ghaleb Al-Doboni

“…The model employs a hybrid architecture combining Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks, enriched with attention mechanisms to capture both local and global dependencies. …”
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Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes by Guillermo Edinson Guzman Gómez, Luis Eduardo Burbano Agredo, Veline Martínez, Oscar Fernando Bedoya Leiva

“…We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). …”
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A Bibliometric Analysis and Systematic Review of Research Advances in In Situ Gel Drug Delivery Systems from 2003 to 2023 by Huanyu Zhou, Mingqing Yuan, Tao Zhang

“…<b>Methods</b>: Studies from 2003 to 2023 were systematically obtained from the Web of Science database and analyzed using VOSviewer software to evaluate publication trends, citation patterns, and collaborative networks. …”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…By leveraging Explainable AI’s interpretability to analyze the features, the model elucidates the reasoning behind its classifications leading to a comprehension of hidden patterns associated with suicidal ideations. Our system is compared to cutting-edge methods on several social media datasets using experimental evaluations, demonstrating that it is superior, since it detects suicidal content more accurately than others. …”
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Robust fault detection and classification in power transmission lines via ensemble machine learning models by Tahir Anwar, Chaoxu Mu, Muhammad Zain Yousaf, Wajid Khan, Saqib Khalid, Ahmad O. Hourani, Ievgen Zaitsev

“…This research introduces a novel approach for fault detection and classification by analyzing voltage and current patterns across transmission line phases. Leveraging a comprehensive dataset of diverse fault scenarios, various machine learning algorithms—including Random Forest (RF), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) networks—are evaluated. …”
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Real-Time Coronary Artery Dominance Classification from Angiographic Images Using Advanced Deep Video Architectures by Hasan Ali Akyürek

“…These models were trained and evaluated on a large dataset derived from a publicly available source. …”
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Beef Carcass Grading with EfficientViT: A Lightweight Vision Transformer Approach by Hyunwoo Lim, Eungyeol Song

“…Unlike conventional two-stage methods that require prior segmentation of the loin region, our model directly predicts beef quality grades from raw RGB images, significantly simplifying the pipeline and reducing computational overhead. We evaluate the proposed model against representative convolutional neural networks (VGG-16, ResNeXt-50, DenseNet-121) as well as two-stage combinations of segmentation and classification models. …”
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A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…By constructing causal graphs and introducing the script event simulation method, the architecture combines graph neural networks (GNNs) with BERT to simplify the event prediction process. …”
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Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma by Glaucia Maria de Mendonça Fernandes, Wesley Wang, Saman Seyed Ahmadian, Daniel Jones, Jing Peng, Pierre Giglio, Monica Venere, José Javier Otero

“…Novel differences in N6-Methyladenosine (m6A) RNA methylation patterns between these groups are identified in the first biopsy. …”
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Comparative analysis of machine learning models and explainable AI for agriculture drought prediction: A case study of the Ta-pieh mountains by Lichang Xu, Shaowei Ning, Xiaoyan Xu, Shenghan Wang, Le Chen, Rujian Long, Shengyi Zhang, Yuliang Zhou, Min Zhang, Bhesh Raj Thapa

“…The framework employs four machine learning models: Extreme Gradient Boosting (XGBoost), Random Forest (RF), Long Short-Term Memory (LSTM) networks, and Backpropagation Neural Networks (BPNN). …”
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An Extended Firefly Algorithm for Enhanced Information Diffusion with Multi-Factor Considerations by Amjad Alloush, Ghaida Rebdawi:, Mohammad Saeed Abou Trab

“…Unlike classical models, which treat information diffusion uniformly, our approach adapts dynamically to the nature of content and the behavioral patterns of users. The proposed model is evaluated using multiple real-world datasets, including Twitter and Reddit, and compared against state-of-the-art optimization-based diffusion models such as PSO, ACO, and GWO. …”
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Finger Knuckle Print classification: Leveraging vision Mamba for low complexity and high accuracy by Chiron Bang, Ali Salem Altaher, Ahmed Altaher, Hawraa Moamin, Thamer Alshammari, Basmh Alkanjr, Hasan Altaher, Mohammed G. Al-Jassani, Hanqi Zhuang

“…Seventeen pretrained deep neural networks were evaluated for their effectiveness in classifying FKPs, with experimental results consistently demonstrating the superior performance of the ViM model. …”
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Potential multiple disease progression pathways in female patients with Alzheimer's disease inferred from transcriptome and epigenome data of the dorsolateral prefrontal cortex. by Kousei Honda, Akinori Awazu

“…An inference of adjacency networks among substages, evaluated via partition-based graph abstraction using the gene expression profiles of individuals, suggested the possibility of multiple typical disease progression pathways from NCI to different AD substages through various MCI substages. …”
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