2D Spatiotemporal Hypergraph Convolution Network for Dynamic OD Traffic Flow Prediction by Cheng Fang, Li Wang

“…Initially, temporal characteristics of traffic flow between OD pairs are captured using a 1D convolution neural network (1D-CNNs). Subsequently, a 2D hypergraph convolutional network is introduced to uncover spatial correlations in OD flow patterns. …”
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The Impact of Microscopic Pore Network Characteristics on Movable Fluid Properties in Tight Oil Reservoir by Jie Gao, Hu Wang, Xiaojun Ding, Qingxiao Yuchi, Qiang Ren, Bo Ning, Junxiang Nan

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Self-Supervised Neural Networks for Precoding in MIMO Rate Splitting Multiple Access Systems by Dheeraj Raja Kumar, Carles Anton-Haro, Xavier Mestre

“…The intention is to explore several alternatives to conventional iterative precoding benchmarks like Weighted Minimum Mean Square Error (WMMSE) which are computationally intensive algorithms. We evaluate the different precoding policies learnt by the neural network architectures by closely studying the respective radiation patterns. …”
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Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…Advanced deep learning architectures such as convolutional neural networks (CNNs), deep CNNs (DCNNs), and recurrent neural networks (RNNs) are utilized to identify critical spatial and temporal patterns in the data. …”
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Integrating Recurrent Neural Networks and Loss Function Optimization for Efficient Indoor Camera Positioning by Shamsul Alam, Farhan Mohamed, Bellal Hossain

“…This study proposed an integrated design that combines recurrent neural networks (RNNs) and a loss function modification approach to improve the accuracy of indoor camera location. …”
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The Expression Pattern of Prostaglandin-Endoperoxide Synthase-2 in Immature Oocytes and Surrounding Cumulus Cells May Explain A Disrupted Oocyte Maturation Process by Goktan Kuspinar, Berrin Avcı

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The two-mode network approach to digital skills and tasks among technology park employees by Anna Ujwary-Gil, Bianka Godlewska-Dzioboń

“…Contribution & Value Added: The article shows digital skills (information management, information evaluation, communication sharing, communication building, communication networking, collaboration, critical thinking, creativity, problem solving) in connection with the tasks performed in the workplace in terms of dyads and two-mode networks (actors and digital skills; actors and tasks performed). …”
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Adaptive distributed honeypot detection network for enhanced cybersecurity against DoS and DDoS attacks by V. Selva Kumar, K.R. Mohan Raj, S. Gopalakrishnan, G. Vennila, D. Dhinakaran, P. Kavitha

“…This study introduces the Adaptive Distributed Honeypot Detection Network (ADHDN), a novel framework that leverages deep learning and probabilistic modeling to address the limitations of existing solutions. …”
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Radio Spectrum Sensing Framework for Large-Scale, High-Density IoT Sensor Networks by Partemie-Marian Mutescu, Alexandru Lavric, Adrian-Ioan Petrariu, Alin-Mihai Cailean, Valentin Popa

“…The rapid growth of the Internet of Things (IoT) requires innovative solutions to address the challenges posed by constrained radio spectrum resources in Wireless Sensor Networks (WSNs). This paper presents an Artificial Intelligence (AI) based spectrum sensing framework designed to detect and classify various IoT communication technologies and generate advanced communication channel analytics, such as the technology in use, central frequency and the bandwidth of the radio channel, time-on-air parameter, channel usage patterns, and radio spectrum occupancy degree. …”
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Enhanced-Dueling Deep Q-Network for Trustworthy Physical Security of Electric Power Substations by Nawaraj Kumar Mahato, Junfeng Yang, Jiaxuan Yang, Gangjun Gong, Jianhong Hao, Jing Sun, Jinlu Liu

“…Empirical evaluation using synthetic data derived from historical incident patterns demonstrates the significant advantages of EDDQN over other standard DQN variations, yielding an average reward of 7.5, a threat prevention success rate of 91.1%, and a notably low false alarm rate of 0.5%. …”
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Multimodal lightweight neural network for Alzheimer's disease diagnosis integrating neuroimaging and cognitive scores by Bhoomi Gupta, Ganesh Kanna Jegannathan, Mohammad Shabbir Alam, Kottala Sri Yogi, Janjhyam Venkata Naga Ramesh, Vemula Jasmine Sowmya, Isa Bayhan

“…To address these challenges, we propose Light-Mo-DAD, a lightweight multimodal diagnostic neural network designed to integrate MRI, PET imaging, and neuropsychological assessment scores for enhanced AD detection. …”
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Construction and Overall Protection of Ecological and Marine Cultural Composite Landscape Network in Quanzhou, Fujian by Dongfang LU, Yaru ZHENG, Tianteng HAN, Shunhe CHEN

“…Based on the evaluation results of the gravity model, these corridors are classified into first-class, second class, and third-class corridors, forming the spatial pattern of the Quanzhou ecological network. …”
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Formulating a Blue Ocean Strategy in the Banking Services Industry: Enhancing Customer Satisfaction through Improved Demand Fulfillment and Presenting an Optimal Pattern by Manuchehr Ghanbari, Ali Sabzali Yameqani, Yousef Rabbani, Kobra Sabzali Yamaqani

“…Additionally, it endeavors to achieve an optimal pattern through the utilization of optimization techniques.   …”
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Exploring the role of electrode density in capturing spatiotemporal dynamics of resting-state networks with EEG by Matheus Mangini Bertuzzo, Rodrigo P Rocha, Ricardo Spyrídes Boabaid Pimentel Gonçalves, Adair Roberto Soares Dos Santos, Odival Cezar Gasparotto

“…Using exact low-resolution electromagnetic tomography, we estimated the cortical current density in regions of interest linked to resting state networks. Point process analysis was employed to identify regions of high activity over time, revealing dynamic brain salient activity patterns, or brain maps. …”
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Triplet-Style Dynamic Graph Network With Transformer Encoder for Scam Detection in Cryptocurrency Transactions by Min-Woo Nam, Hyeon-Ju Lee, Seok-Jun Buu

“…Evaluations on a real-world Bitcoin transaction network demonstrate TD-GCN’s superior scam detection performance. …”
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Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach by Xi Zhang, Lan Yang, Jiayu Lu, Yuting Yuan, Dandan Li, Hui Zhang, Rong Yao, Jie Xiang, Bin Wang

“…This study employed hidden Markov model (HMM) analysis to delve deeper into the moment-to-moment temporal patterns of brain activity in BD. We utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 43 BD patients and 51 controls to evaluate the altered dynamic spatiotemporal architecture of the whole-brain network and identify unique activation patterns in BD. …”
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Causal inference-based graph neural network method for predicting asphalt pavement performance by CHEN Kai;WANG Xiaohe;SHI Xinli;CAO Jinde

“…The local feature extraction module utilizes dilated convolutional neural networks(CNN) with various kernel sizes to extract short-term temporal patterns at different scales. …”
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Real-time ocean wave prediction in time domain with autoregression and echo state networks by Karoline Holand, Henrik Kalisch

“…This study evaluates the potential of applying echo state networks (ESN) and autoregression (AR) for dynamic time series prediction of free surface elevation for use in wave energy converters (WECs). …”
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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

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Terrain and Atmosphere Classification Framework on Satellite Data Through Attentional Feature Fusion Network by Antoni Jaszcz, Dawid Połap

“…Hence, in this paper, we propose a neural classifier architecture that analyzes different features by the parallel processing of information in the network and combines them with a feature fusion mechanism. …”
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