Transient Stability Assessment of Power Systems Built upon Attention-Based Spatial–Temporal Graph Convolutional Networks by Yu Nan, Weiping Niu, Yong Chang, Zhenzhen Kong, Huichao Zhao

“…However, existing methods fail to adequately exploit the spatiotemporal characteristics in power grid transient data, which constrains the evaluation performance of models. This paper proposes a TSA method built upon an Attention-Based Spatial–Temporal Graph Convolutional Network (ASTGCN) model. …”
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Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions by Mohamad Alkhalidi, Abdullah Al-Dabbous, Shoug Al-Dabbous, Dalal Alzaid

“…This analysis reveals that ERA5 effectively captures general wind speed patterns, with offshore stations demonstrating stronger correlations (up to 0.85) and higher Perkins Skill Score (PSS) values (up to 0.94). …”
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Bibliometric Analysis of microRNA: A Comprehensive Evaluation of Its Contribution to Acute Coronary Syndromes by Gao Y, Li T, Mu X, Ren X, Wang J, Fan J, Zhu H, Wang X

“…Visualization tools mapped collaboration networks, co-citation patterns, and keyword trends.Results: China contributed 60% of publications, followed by the United States (12.86%). …”
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Trade-off/Synergy Networks and Threshold Effects in Different Ecosystem Service Bundles of the Pearl River Delta Region by Li Ting, Li Zhiwen, Chen Dengshuai, Li Huixia, Xu Haofan

“…In this study, the Integrated Valuation of Ecosystem Services and Trade-Offs model was used to evaluate ecosystem services in the Pearl River Delta region. …”
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Assessment of Scientific Creative-Potential by Near-Infrared Spectroscopy Using Brain-Network-Based Deep-Fuzzy Classifier by Sayantani Ghosh, Amit Konar, Atulya K. Nagar

“…The work presents a novel approach to assess the scientific creative ability of subjects by analyzing their brain connectivity patterns through functional Near-Infrared Spectroscopy (fNIRS) during participation in an analogical reasoning test. …”
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Novel Quanvolutional Neural Network-Based COVID-19 Diagnosis From Raman Spectroscopic Signals of Human Serum by Shivanya Shomir Dutta, Sahil Sandeep, S. Sridevi, Rajiv Mistry, Jonathan Ortega, Gorkem Kar

“…The primary goal of this research is to accurately diagnose COVID-19 by analyzing Raman spectroscopic signals of serum samples with a novel quantum circuit-based Quanvolutional Neural Network (QNN). In this research, although the signals are initially in one dimension (1D), we applied wavelet transforms to convert Raman spectroscopic signals into 2D scaleogram images to capture intricate spectral patterns for efficient classification. …”
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Networks of care for optimizing Primary Health Care Service Delivery in Ethiopia: Enhancing relational linkages and care coordination. by Gizachew Tadele Tiruneh, Nebreed Fesseha, Temesgen Ayehu, Tamar Chitashvili, Mesele Damte Argaw, Biruhtesfa Bekele Shiferaw, Mikias Teferi, Agumasie Semahegn, Biruk Bogale, Yibeltal Kifle, Hillina Tadesse, Chala Tesfaye, Dessalew Emaway

“…Routine program monitoring data, NoCs process evaluation, and facility service statistics were utilized for this study. …”
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Exploring Solar Granulation: from IMaX/SUNRISE to DKIST by Reza Mansouri, Rafal Angryk, Kevin Reardon

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Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption. by Abrar Ahmed, Safdar Ali, Ali Raza, Ibrar Hussain, Ahmad Bilal, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The proposed model is capable of capturing complex temporal and spatial features to predict short-term and long-term energy consumption. CNNs discover patterns in data, LSTM identifies long-term dependencies and sequential patterns and Bi-LSTM identifies complex temporal relations within the data. …”
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Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models by Cong Lu, Jianjun She, Hezhi Pan, Zihao Guo, Xuanling Zhou, Zhijian Li

“…The PageRank algorithm is used to identify critical nodes by evaluating their network centrality, thereby highlighting key components within the system. …”
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Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification. by Daniel R Ripoll, Sidhartha Chaudhury, Anders Wallqvist

“…We combined large-scale sequence-based protein-structure predictions to generate ensembles of 3-D Ab models, reduced the Ab binding interface to a 2-D image (fingerprint), used pre-trained convolutional neural networks to extract features, and trained deep neural networks (DNNs) to classify Abs. …”
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Real-time analysis of soccer ball–player interactions using graph convolutional networks for enhanced game insights by Fahad Majeed, Maria Nazir, Kamilla Swart, Marco Agus, Jens Schneider

“…Our approach leverages the power of deep computer vision models, employing a CSPDarknet53 backbone for detection and a Graph Convolutional Network (GCN) for predictive analytics. The proposed approach intricately analyzes ball–player interactions by evaluating metrics such as inter-player distances, proximity to the ball, and hierarchical sorting based on shortest distances to the ball. …”
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Optimized predictive maintenance for streaming data in industrial IoT networks using deep reinforcement learning and ensemble techniques by K. Varalakshmi, J. Kumar

“…Abstract Predictive maintenance in Industrial IoT (IIoT) networks faces challenges due to dynamic conditions, device heterogeneity, and evolving data patterns. …”
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A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection by Han Zhuoxi

“…This research centers on the use of advanced machine learning methods, particularly Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), to improve the detection of network attack traffic. The UNSW-NB15 dataset, which includes various attack types and normal traffic patterns, is used to evaluate the performance of these two models. …”
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A Multi-Area Software-Defined Vehicular Network Control Plane Deployment Mechanism Oriented to Traffic Prediction by Hao Li, Hongming Li, Yuqing Ji, Ziwei Wang

“…A comprehensive comparison of various machine learning and deep learning algorithms is then conducted to evaluate their efficacy in forecasting SDVN traffic patterns, which is crucial for system efficiency. …”
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Prediction of land cover changes in an Urban City of Bangladesh using artificial neural network-based cellular automata by Tania Yeasmin, Sourav Karmaker, Md Shafiqul Islam, Irteja Hasan, Saifur Rahman, Mahmudul Hasan

“…Supervised classification algorithms and cellular automata model based on Artificial Neural Networks (ANN) were used to prepare LULC maps and future simulations. …”
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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…As cyber threats grow in complexity, ensuring robust network security has become increasingly critical. …”
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Air quality prediction using stacked bi- long short-term memory and convolutional neural network in India by S Karkuzhali, Thendral Puyalnithi, R Nirmalan

“…The study aims to offer valuable insights into the temporal and spatial patterns of air quality in India, thereby aiding environmental policymakers, urban planners, and researchers in formulating effective strategies for air quality management. …”
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Modeling Higher-Order Interactions in Graphs Through Combinatorial Arc-Transitive Structure Using Graph Convolutional Network by Qingwei Wen

“…Our experimental evaluations on various benchmark graph datasets—including both homogeneous and heterogeneous structures—demonstrate that HiGCN significantly outperforms state-of-the-art models in node classification and graph classification tasks, particularly in domains such as bioinformatics, social networks, and recommendation systems. …”
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Data driven fuel consumption prediction model for green aviation using radial basis function neural network by Yuandi Zhao, Zhongyi Wang, Xiaohui Wang, Ye Song, Yuzhe Han

“…Further analysis indicated that the model can be employed to evaluate the “fuel penalty for carrying additional fuel” patterns and enhance fuel efficiency. …”
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