Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks by Miljenko Švarcmajer, Denis Ivanović, Tomislav Rudec, Ivica Lukić

“…This paper investigates the application of graph theory and variants of greedy graph coloring algorithms for the optimization of distributed peer-to-peer networks, with a special focus on private blockchain networks. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The high penetration of renewables into the active distribution network (ADN) brings voltage deviation and difficulties to the optimal power flow (OPF) problem. …”
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Graph Neural Networks for Pressure Estimation in Water Distribution Systems by Huy Truong, Andrés Tello, Alexander Lazovik, Victoria Degeler

“…Abstract Pressure and flow estimation in water distribution networks (WDNs) allows water management companies to optimize their control operations. …”
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Optimal Transport Based Graph Kernels for Drug Property Prediction by Mohammed Aburidi, Roummel Marcia

“…<italic>Objective:</italic> The development of pharmaceutical agents relies heavily on optimizing their pharmacodynamics, pharmacokinetics, and toxicological properties, collectively known as ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity). …”
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Optimal Network Analysis through Vertex Order Coloring of Intuitionistic Fuzzy Graph Operations by A. Meenakshi, S. Dhanushiya, Hong Qin, Muniyandy Elangovan

“…We analyzed multiple IFG products to determine the most optimal network based on some important metrics, including the weight and total number of α˜str vertices, the chromatic number, and the weight of the graph’s minimum spanning tree. …”
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Hyperspectral Anomaly Detection by Spatial&#x2013;Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization by Song Zhao, Yali Lv, Wen Zhang, Lijun Wang, Zhiru Yang, Gaofeng Ren, Bin Wang, Xiaobin Zhao, Tongwei Lu, Jiayao Wang, Wei Li

“…Second, to enhance the model&#x2019;s adaptability to non-Gaussian backgrounds and maximize spectral information utilization, we propose a Cauchy graph distance-optimized RX anomaly detection approach. …”
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Efficient network attack path optimization method based on prior knowledge-based PPO algorithm by Qiuxiang Li, Jianping Wu

“…To address this issue, we propose a bi-objective attack path optimization problem based on attack graphs, aiming to maximize attack gains while minimizing the attack path length. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…ObjectiveScene graph generation is an important task in the field of computer vision, aimed at achieving a comprehensive and deep understanding of visual scenes. …”
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Constructing ancestral recombination graphs through reinforcement learning by Mélanie Raymond, Marie-Hélène Descary, Cédric Beaulac, Fabrice Larribe

“…Among these methods, many rely on the assumption that the most likely graph is among those with the fewest recombination events. …”
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A graph-based sensor recommendation model in semantic sensor network by Yuanyi Chen, Yihao Lin, Peng Yu, Yanyun Tao, Zengwei Zheng

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Fast Nonparametric Inference of Network Backbones for Weighted Graph Sparsification by Alec Kirkley

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Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors by Zhenqiang Guo, Guojun Duan, Yinxing Zhang, Yong Sun, Weifeng Zhang, Xiaohan Li, Haowan Shi, Pengfei Li, Zhen Zhao, Jikang Xu, Biao Yang, Yousef Faraj, Xiaobing Yan

“…Here, robust and epitaxial Gd: HfO2‐based film memristors are reported and construct a weighted echo state graph neural network (WESGNN). Benefiting from the optimized epitaxial films, the high switching speed (20 ns), low energy consumption (2.07 fJ), multi‐value storage (4 bits), and high endurance (109) outperform most memristors. …”
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A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition by Li Chen, Jing Yang, Yuzhen Zhou, Yanxiang Ling, Jialong Zhang

“…Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. The most critical point of the agent is the introduction and application of a thermal distribution grid graph (TDGG) and virtual grid dictionary (VGD), where the former is used to identify the formation information of air targets, and the latter is used to optimize the storage space and simplify the access process for the large-scale and real-time combat information. …”
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Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…MFF-DANet employs convolutional kernels of various scales to extract feature information across multiple frequency bands, followed by a channel attention-based average pooling operation to retain the most critical frequency domain features. Additionally, MFF-DANet integrates a graph attention convolutional network to capture spatial topological features across different electrode channels, utilizing electrode positions as prior knowledge to construct and update the graph adjacency matrix. …”
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Federated SPARQL query performance evaluation for exploring disease model mouse: combining gene expression, orthology, and disease knowledge graphs by Tatsuya Kushida, Tarcisio Mendes de Farias, Ana C. Sima, Christophe Dessimoz, Hirokazu Chiba, Frederic B. Bastian, Hiroshi Masuya

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Enhancing Urban Heatwave Response Planning via a Graph-Based Digital Twin Approach: Spatial Dependency Risk Analysis in Vienna City by George Stergiopoulos, Sozon A. Leventopoulos, Michalis Karamousadakis, Benjamin Schuster, Dimitris Gritzalis

“…Using Vienna&#x2019;s city center as a case study, we integrate (i) high-resolution spatial data from Google on heat hazard, (ii) spatial population distribution from Vienna Open Data and (iii) META&#x2019;s Vienna population datasets alongside (iv) critical road infrastructure from OpenStreetMaps, into a graph network model that captures cumulative risk paths that help determine the most critical city blocks needing intervention and the optimal allocation of resources for routing first responders to reach critical locations of sensitive populations. …”
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OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS by O. S. Khalyutina

“…The reduction in the accuracy characteristics of HRG is caused by the presence of defects in the distribution of mass in the volume of its design. The synthesis of control system for optimal damping of the distortion parameters of the standing wave due to the influence of the mass defect resonator is adapted. …”
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Methodology of Determining the Location of the Distribution Center of Material Flows in a Combined Scheme of Goods Delivery by Svetlana A. Zhestkova

“…Despite the sufficient number of existing ways to solve this problem, they have some disadvantages: they are not entirely realistic and do not completely meet the requirements of logistical optimization. Namely, existing algorithms do not take into account the need to visit the branches of the transport graph several times and the curvature of the movement trajectory.The developed technique has greater practical application because it deals with determining the optimal location of the distribution center based on the criterion of full vehicle loading, using piecewise linear approximation to account for the curvature of routes, forming delivery routes using the accurate fictitious nodes and branches’ method (FNB) to optimize transportation and minimize overall logistical costs. …”
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Latency-optimal virtual backbone construction with acoustic communication in underwater sensor networks by Xin Bai, Xiaohui Wei, Sen Bai

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Optimal Joint Defense and Monitoring for Networks Security under Uncertainty: A POMDP-Based Approach by Armita Kazeminajafabadi, Mahdi Imani

“…This paper develops two security policies based on the optimal stationary defense policy for the underlying POMDP state process (i.e., a network with known compromises): the estimation-based policy that performs the defense actions corresponding to the optimal minimum mean square error state estimation and the distribution-based policy that utilizes the posterior distribution of network compromises to make defense decisions. …”
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