An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction by Zhiguo Xiao, Qi Shen, Changgen Li, Dongni Li, Qian Liu

“…Abstract Traffic prediction, as a core technology of Intelligent Transportation Systems, plays a pivotal role in dynamic road network optimization and urban travel planning. However, the complex spatiotemporal characteristics of transportation networks pose significant challenges to precisely capturing their dynamic patterns. …”
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Physics-Informed Graph Neural Networks for Attack Path Prediction by Marin François, Pierre-Emmanuel Arduin, Myriam Merad

“…The automated identification and evaluation of potential attack paths within infrastructures is a critical aspect of cybersecurity risk assessment. …”
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Analyzing key users’ behavior trends in volunteer-based networks by Nofar Piterman, Tamar Makov, Michael Fire

“…The insights gained from our analysis not only shed light on the behavioral patterns of key users in volunteer-driven networks but also highlight the potential of machine learning in enhancing community engagement and building strategies for the future. …”
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Cooperator and Defector-Based Dynamic Community Detection in Social Networks by Hui Jiang, Chenlin Zhao, Zhexi Guo, Tangyu Wang

“…Dynamic community detection in social networks requires advanced methods to capture the intricate patterns of user interactions. …”
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The influence of correlated features on neural network attribution methods in geoscience by Evan Krell, Antonios Mamalakis, Scott A. King, Philippe Tissot, Imme Ebert-Uphoff

“…Correlated features may also cause inaccurate attributions because XAI methods typically evaluate isolated features, whereas networks learn multifeature patterns. …”
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Towards a methodology for validation of centrality measures in complex networks. by Komal Batool, Muaz A Niazi

“…Whereas Betweenness Centrality varied according to network topology and did not demonstrate any noticeable pattern. …”
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Mechanisms underlying the spontaneous reorganization of depression network after stroke by Yirong Fang, Xian Chao, Zeyu Lu, Hongmei Huang, Ran Shi, Dawei Yin, Hao Chen, Yanan Lu, Jinjing Wang, Peng Wang, Xinfeng Liu, Wen Sun

“…Stepwise functional connectivity (SFC) was used to examine topological changes in the depression network over time to identify patterns of network reorganization. …”
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Evolution, Growth, and Maturity of the Thematic Network in the field of Citation Bias by Elaheh Hosseini, Maral Alipour-Tehrani, Najmeh Salemi

“…Understanding the growth patterns of the thematic network can enhance our comprehension of the mechanisms underlying its connections and links. …”
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Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…Then, we designed a multi-scale spatiotemporal evolution module to obtain the spatiotemporal evolution patterns of weather using inter- and intra-frame computations. …”
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SEEG-Based Bilateral Seizure Network Analysis for Neurostimulation Treatment by Genchang Peng, Mehrdad Nourani, Jay Harvey

“…Network nodes are selected subset of SEEG contact points, and network edges are directed signal correlations calculated from directed transfer function. …”
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Optimizing Artificial Neural Networks Using Mountain Gazelle Optimizer by Muhammed Abdulhamid Karabiyik, Bahaeddin Turkoglu, Tunc Asuroglu

“…In this study, we introduce a novel approach to optimizing neural network parameters using the Mountain Gazelle Optimizer (MGO), a nature-inspired metaheuristic algorithm that mimics the social hierarchy and behavioral patterns of wild mountain gazelles. …”
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Long-Range Wide Area Network Intrusion Detection at the Edge by Gonçalo Esteves, Filipe Fidalgo, Nuno Cruz, José Simão

“…This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN) algorithm, within an Intrusion Detection System (IDS) for LoRaWAN networks. Through behavioural analysis based on previously observed packet patterns, the system can detect potential intrusions that may disrupt critical tracking services. …”
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Transfer learning with XAI for robust malware and IoT network security by Ahmad Almadhor, Shtwai Alsubai, Natalia Kryvinska, Abdullah Al Hejaili, Belgacem Bouallegue, Mohamed Ayari, Sidra Abbas

“…We demonstrated the effectiveness of the proposed model in handling diverse heterogeneous cybersecurity threats across memory-based malware analysis, IoT security, and traditional network intrusion detection. The effectiveness of the proposed methodology is evaluated using several key metrics to demonstrate its advantages over conventional methods. …”
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Machine Learning Algorithms Performance Evaluation for Intrusion Detection by Shyla ., Kapil Kumar, Vishal Bhatnagar

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Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…Therefore, a more widely applicable network is needed for sleep staging.MethodsThis paper introduces MSDC-SSNet, a novel deep learning network for automatic sleep stage classification. …”
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Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals. by Reihaneh Hassanzadeh, Rogers F Silva, Anees Abrol, Mustafa Salman, Anna Bonkhoff, Yuhui Du, Zening Fu, Thomas DeRamus, Eswar Damaraju, Bradley Baker, Vince D Calhoun

“…Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. …”
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Exploring the predictive value of structural covariance networks for the diagnosis of schizophrenia by Clara S. Vetter, Clara S. Vetter, Clara S. Vetter, Annika Bender, Dominic B. Dwyer, Dominic B. Dwyer, Dominic B. Dwyer, Max Montembeault, Anne Ruef, Katharine Chisholm, Lana Kambeitz-Ilankovic, Linda A. Antonucci, Stephan Ruhrmann, Joseph Kambeitz, Marlene Rosen, Theresa Lichtenstein, Anita Riecher-Rössler, Rachel Upthegrove, Raimo K. R. Salokangas, Jarmo Hietala, Christos Pantelis, Christos Pantelis, Rebekka Lencer, Rebekka Lencer, Eva Meisenzahl, Stephen J. Wood, Stephen J. Wood, Paolo Brambilla, Paolo Brambilla, Stefan Borgwardt, Peter Falkai, Peter Falkai, Alessandro Bertolino, Nikolaos Koutsouleris, Nikolaos Koutsouleris, Nikolaos Koutsouleris, PRONIA Consortium

“…All model decisions were driven by widespread structural covariance alterations involving the somato-motor, default mode, control, visual, and the ventral attention networks. Risk estimates derived from KLS-SCNs and regional GMV, but not REF-SCNs, could be predicted from clinical variables, especially driven by body mass index (BMI) and affect-related negative symptoms.DiscussionThese patterns of results show that different SCN computation approaches capture different aspects of the disease. …”
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Evaluation of Meshed Reference Planes for High Performance Applications by N. D. Codreanu, P. Svasta, V. Golumbeanu, L. Gál

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Evaluating the effects of volume censoring on fetal functional connectivity by Jung-Hoon Kim, Josepheen De Asis-Cruz, Kevin M. Cook, Catherine Limperopoulos

“…Fetuses’ FC profiles significantly predicted average FD (r = 0.09 ± 0.08; p < 10–3) after regression, suggesting a lingering effect of motion on whole-brain patterns. To dissociate head motion and the FC, we used volume censoring and evaluated its efficacy in correcting motion at different thresholds. …”
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Neural Network VS Genetic and Particle Swarm Optimization Algorithms in Bankruptcy by Alireza Azarberahman

“…Neural networks (NNs) choose the optimal network with the least error in training and evaluating patterns in the second phase. …”
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