Long-Range Wide Area Network Intrusion Detection at the Edge by Gonçalo Esteves, Filipe Fidalgo, Nuno Cruz, José Simão

“…We considered two use cases for evaluating our work: one with a more traditional approach where the devices and network are static, and another where we assume that both the devices and the network are mobile; for example, when we need to report data back from sensors on a rail infrastructure to a mobile LoRaWAN gateway onboard a train.…”
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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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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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Crack-Based Estimation of Seismic Damage Level in Confined Masonry Walls in the Lima Metropolitan Area Using Deep Learning Techniques by Miguel Diaz, Luis Lopez, Michel Amancio, Italo Inocente, Jhianpiere Salinas, Sergio Isuhuaylas, Erika Flores, Edisson Moscoso

“…The measured crack patterns were normalized into an index, which was then correlated with the amplitude of the lateral deformation in each hysteretic loop. …”
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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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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

“…Structural covariance networks (SCN) describe the shared variation in morphological properties emerging from coordinated neurodevelopmental processes, This study evaluates the potential of SCNs as diagnostic biomarker for schizophrenia.MethodsWe compared the diagnostic value of two SCN computation methods derived from regional gray matter volume (GMV) in 154 patients with a diagnosis of first episode psychosis or recurrent schizophrenia (PAT) and 366 healthy control individuals (HC). …”
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Prevalence and prenatal diagnosis of major congenital anomalies in Dubai: first insights and emerging patterns in a multicenter cohort study by Anne F. Minsart, Hiba Adam, Nadirah Ghenimi, Muna Tahlak, Fadi G. Mirza, Anjum Akbar, Shanthi Sairam

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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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Neural connectivity biotypes: predictors of clinical outcomes and improvement patterns of iTBS treatment in adolescents and young adults with depression by Xiaoyu Chen, Min Zhang, Fan Zhang, Yanling Zhou, Yuping Ning, Roger S McIntyre, Hanna Lu, Haiyan Liu, Yiying Chen, Xiaofeng Lan, Chengyu Wang, Weicheng Li, Zhibo Hu, Siming Mai, Yanan Yin, Zerui You, Guanxi Liu, Zhanjie Luo, Yexian Zeng, Yifang Chen, Robin Shao

“…This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network (DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression (n=82) were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN. …”
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Spatiotemporal Land Use and Land Cover Changes and Their Impact on Landscape Patterns in the Colombian Coffee Cultural Landscape (2014–2034) by Anyela Piedad Rojas Celis, Jie Shen, Jose David Martinez Otalora

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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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Spatiotemporal patterns of wet–dry encounters between water source and receiving areas in the South-to-North water transfer project by Yuping Han, Jinhang Li, Mengdie Zhao

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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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Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations by Xuan Wang, Jialu Shi, Chengxin Wang, Xumin Jiao

“…We construct the evaluation index of GI network resilience. Using this index to evaluate the GI network resilience to changes under various disturbance scenarios. …”
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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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A Convolutional Neural Network as a Potential Tool for Camouflage Assessment by Erik Van der Burg, Alexander Toet, Paola Perone, Maarten A. Hogervorst

“…However, discrepancies emerged at close distances, where YOLO’s performance was particularly sensitive to high-contrast, shape-breaking elements of the camouflage pattern. CNNs such as YOLO have significant potential for assessing camouflage effectiveness for a wide range of applications, such as evaluating or optimizing one’s signature and predicting optimal hiding locations in each environment. …”
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Spatial Correlation Network Characteristics of Comprehensive Transportation Green Efficiency in China by Qifei Ma, Sujuan Li, Zhenchao Zhang

“…Furthermore, the standard deviational ellipse (SDE) model and social network analysis (SNA) method are adopted to delineate the spatiotemporal evolution patterns and spatial correlation network characteristics of CTGE, based on input–output data from the transportation industry across 30 provinces (municipalities and autonomous regions) between 2003 and 2020. …”
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Optimization of Flipped Classroom Teaching Model Based on Social Cognitive Network by Xinyue Wang

“…An evaluation model based on learners’ cognitive network analysis is designed and constructed by integrating cognitive visualization analysis techniques such as network analysis. …”
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