Racial and Ethnic Disparities in Dietary Intake and Quality Among United States Veterans by Xuan-Mai T Nguyen, Yanping Li, Stacey B Whitbourne, Luc Djousse, Dong D Wang, Kerry Ivey, Walter C Willett, John Michael Gaziano, Kelly Cho, Frank B Hu

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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

“…For ARs, relevant patterns include elongated bands of high TMQ and eastward winds. …”
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Integration of Artificial Neural Network Regression and Principal Component Analysis for Indoor Visible Light Positioning by Negasa Berhanu Fite, Getachew Mamo Wegari, Heidi Steendam

“…Leveraging machine learning techniques, particularly regression-based artificial neural networks (ANNs), offer a promising alternative. ANNs excel at modeling the intricate relationships within data, making them well-suited for handling the complex dynamics of indoor lighting environments. …”
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vBerlinV2N: Recreating a Cellular Network Measurement Campaign With Simulations by Christian L. Vielhaus, Mauri Seidel, Vincent Latzko, Alexander Grob, Peter Sossalla, Martin Reisslein, Frank H. P. Fitzek

“…System-level simulations play a crucial role in evaluating the behaviors of cellular networks, yet most studies rely on synthetic simulation scenarios rather than reproducing realistic network deployments. …”
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Resilience evolution and optimization strategies of ecological networks in the Three Gorges Reservoir Area: A scenario-based simulation approach by Haohua Wang, Lulu Zhou, Kangchuan Su, Yun Zhou, Qingyuan Yang

“…This study focuses on the Three Gorges Reservoir Area (TGRA), addressing human-land relationship conflicts by constructing an EN system and analyzing its spatiotemporal evolution from 2001 to 2023. To evaluate network resilience, this study employs node attack simulation methods, we dynamically assessed EN resilience through four functional and structural indicators. …”
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Reinforced liquid state machines—new training strategies for spiking neural networks based on reinforcements by Dominik Krenzer, Martin Bogdan, Martin Bogdan, Martin Bogdan

“…While traditional Liquid State Machines often employ unsupervised approaches, we introduce strict feedback to improve network performance by not only reinforcing correct predictions but also penalizing wrong ones.ResultsStrict feedback is compared to another strategy known as forgiving feedback, excluding punishment, using evaluations on the Spiking Heidelberg data. …”
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Integrated deep network model with multi-head twofold attention for drug–target interaction prediction by Angelin Jeba P, Tamilpavai G

“…This model leverages convolutional and recurrent neural networks to extract both local and sequential features from drug molecular structures and target protein sequences. …”
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Real-Time Financial Fraud Detection Using Adaptive Graph Neural Networks and Federated Learning by Milad Rahmati

“…In this research, we introduce a real-time fraud detection framework that combines Adaptive Graph Neural Networks (GNNs) and Federated Learning (FL) to overcome these limitations. …”
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Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks by Ayan Chatterjee, Vajira Thambawita, Michael A. Riegler, Pal Halvorsen

“…The model uses a contrastive loss function to compare input sequences and adjusts network weights iteratively during training to recognize intricate patterns. …”
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Application of a Stochastic Model for Water Demand Assessment under Water Scarcity and Intermittent Networks by Stefania Piazza, Mariacrocetta Sambito, Gabriele Freni

“…The analysis was conducted using a short-term water demand forecast model that reproduces periodic patterns observed at an annual, weekly and daily level to evaluate the adaptation response of users concerning the scarcity of water resources through a comparison between the real pattern of the network and the pattern of local tanks.…”
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Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…Compared to other machine learning algorithms, the proposed models demonstrate superior performance in balancing accuracy, computational efficiency, and detection speed, making them ideal for real-time network security applications. This approach’s flexibility to adapt to various network conditions and datasets ensures consistent optimal performance as traffic patterns change.…”
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Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

“…Extensive research studies have been done to detect electricity theft by analyzing customer consumption patterns. Today, one of the most widely used methods is convolutional neural networks (CNNs). …”
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Comparative study on carbon emission spatial network and carbon emission reduction collaboration in urban agglomerations by Yongqiang Dong, Lanjian Liu

“…Mismatches exist between collaboration patterns and emission networks: central cities dominate cooperation, while peripheral cities lack initiative; intensity polarization and provincial-level mini-clubs prevail. …”
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Fractional Transfer Entropy Networks: Short- and Long-Memory Perspectives on Global Stock Market Interactions by Ömer Akgüller, Mehmet Ali Balcı, Larissa Margareta Batrancea, Lucian Gaban

“…These findings demonstrate that FTE uncovers nuanced dynamics overlooked by methods focusing solely on either current events or deep-rooted patterns. Although the method relies on price returns and does not differentiate specific shock types, it offers a versatile tool for investors, policymakers, and researchers to gauge financial stability, evaluate contagion risk, and better understand how ephemeral signals and historical legacies jointly govern global market connectivity.…”
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ChaMTeC: CHAnnel Mixing and TEmporal Convolution Network for Time-Series Anomaly Detection by Ibrahim Delibasoglu, Deniz Balta, Musa Balta

“…This paper introduces ChaMTeC (CHAnnel Mixing and TEmporal Convolution Network), a novel deep learning framework designed for time-series anomaly detection. …”
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Intrusion Alert Analysis Method for Power Information Communication Networks Based on Data Processing Units by Rui Zhang, Mingxuan Zhang, Yan Liu, Zhiyi Li, Weiwei Miao, Sujie Shao

“…Finally, the suffix tree models attack activities, capturing key behavioral paths of high-severity alerts and identifying attacker patterns. Experimental evaluations on the CPTC-2017 and CPTC-2018 datasets validate the proposed method’s effectiveness in reducing alert redundancy, extracting critical attack behaviors, and constructing attack activity sequences. …”
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COVID-19 Disruption Strategy for Redesigning Global Supply Chain Network across TPP Countries by Takaki Nagao, Hiromasa Ijuin, Tetsuo Yamada, Keisuke Nagasawa, Lei Zhou

“…This enables us to model and evaluate simultaneous considerations of supplier disruption, customs duty, and TPP in redesigning a global supply chain network. …”
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HFFC: A High-Fan-Out and Flexible-Cluster Optical Network Architecture for Data Centers by Aijun Liu, Zixuan Chen, Yucheng Zhang, Jun Qin

“…The performance of the HFFC architecture is evaluated by simulation using synthetic traffic patterns. …”
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Optimizing Fractional-Order Convolutional Neural Networks for Groove Classification in Music Using Differential Evolution by Jiangang Chen, Pei Su, Daxin Li, Junbo Han, Gaoquan Zhou, Donghui Tang

“…This study presents a differential evolution (DE)-based optimization approach for fractional-order convolutional neural networks (FOCNNs) aimed at enhancing the accuracy of groove classification in music. …”
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Deep learning based predictive models for real time accident prevention in autonomous vehicle networks by Ahmed Almutairi, Abdullah Faiz Al Asmari, Fayez Alanazi, Tariq Alqubaysi, Ammar Armghan

“…The use of autonomous vehicle (AV) networks is a potentially useful solution since they make it possible to react in real time to probable collisions. …”
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