Effects of Multisession High-Definition Transcranial Direct Current Stimulation on Resting-State Brain Network Connectivity and Efficiency Under Running-Induced Fatigue by Changxiao Yu, Jianglong Zhan, Bin Shen, Junhong Zhou, Weijie Fu

“…Resting-state electroencephalography (EEG) signals from 28 channels were recorded before the intervention and after fatigue was induced. Brain network connectivity was characterized using average functional connectivity measured using the phase locking value, and network efficiency was assessed using graph theoretical indices. …”
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Visual Point Cloud Map Construction and Matching Localization for Autonomous Vehicle by Shuchen Xu, Kedong Zhao, Yongrong Sun, Xiyu Fu, Kang Luo

“…We fuse multi-source information from vehicle-mounted sensors and the regional road network to establish the geographically high-precision VPCM. …”
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A network analysis of the propagation of evidence regarding the effectiveness of fat-controlled diets in the secondary prevention of coronary heart disease (CHD): Selective citatio... by Rhodri Ivor Leng

“…<h4>Design</h4>Claim-specific citation network analysis was used to study the network of citations between reviews and RCTs over a defined period (1969-1984). …”
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Determination of the amount of water consumed by various water users of the residential sector by A. G. Zhulin, A. Kh. Aminova, L. V. Belova

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Using Entropy Metrics to Analyze Information Processing Within Production Systems: The Role of Organizational Constraints by Frits van Merode, Henri Boersma, Fleur Tournois, Windi Winasti, Nelson Aloysio Reis de Almeida Passos, Annelies van der Ham

“…Degree centrality of nodes outside of zero-entropy situations exhibits higher average and maximum values in andon coordination networks, compared to those with adjacent coordination in TPS. …”
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Assessment and Optimization of Hydrological Connectivity for Effective Management of Water Resources in the Samian Watershed by Zeinab Hazbavi, Nazila Alaei

“…The assessment and optimization of the structural hydrological connectivity in the Samian Watershed were based on remote sensing, geographic information systems, graph theory, and binary theory. After constructing the hydrological network of the Samian Watershed, several connectivity indices were calculated to capture the internal complexity of the water flow transfer path network:River chain node ratio (β): Calculated to represent the degree of branching in the river networkActual bonding degree (γ): Determined to show the level of connectivity in the river networkIndex of Integration of Connectivity (IIC): Extracted based on binary theory using Conefor Sensinode 2.6 software to represent the overall connectivity of the transmission path networkProbability of Connectivity (PC): Also derived from binary theory to indicate the overall connectivity of the transmission path networkThe cost of water connection resistance was determined based on topographical, hydrological, and anthropogenic factors. 5 optimization levels were then defined according to the priority of optimization. …”
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Aberrant Whole-Brain Resting-State Functional Connectivity Architecture in Obsessive-Compulsive Disorder: An EEG Study by Bo Tan, Jing Yan, Junjun Zhang, Zhenlan Jin, Ling Li

“…Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder characterized by intrusive thoughts (obsessions) and repetitive behaviors (compulsions), and few studies have assessed the whole-brain functional connectivity architecture of OCD with electroencephalogram (EEG) during different resting states. Graph theory and network-based statistics (NBS) were employed to examine the neural synchronization and the whole-brain functional connectivity (FC) based on the phase-locking value (<italic>PLV</italic>) of OCD patients and healthy controls (HCs) during eyes-closed (EC) and eyes-open (EO) states. …”
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Bearing fault diagnosis for variable operating conditions based on KAN convolution and dual branch fusion attention by Qibing Wang, Chuanjie Yin, Kun She, Qinfeng Tong, Guoxiong Lu, Hongbing Zhang, Jiawei Lu

“…Abstract This paper proposes a bearing fault diagnosis method based on Kolmogorov–Arnold Convolutional Network: Adaptive Context-aware Graph Channel Attention with Squeeze-and-Excitation Networks (KANConv-ACGCA-SENet). …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…Statistical criteria, margin of deviation plots, violin graphs, and external experimental datasets are utilized to assess the developed optimized models. …”
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Attention-Enhanced Hybrid Automatic Modulation Classification for Advanced Wireless Communication Systems: A Deep Learning-Transformer Framework by Sam Ansari, Khawla A. Alnajjar, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny, Abir Hussain, Soliman Mahmoud

“…The proposed framework is rigorously compared against six representative models&#x2014;recurrent neural networks (RNN), long short-term memory (LSTM), gated recurrent units (GRU), convolutional neural networks-transformer graph neural network (CTGNet), MobileViT, and DeepsigNet&#x2014;across multiple evaluation criteria. …”
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Stopover regions, phenology, and spatiotemporal group dynamics of adult and juvenile common terns Sterna hirundo from inland lakes in North America by Annie Bracey, Fred Strand, Alexis Grinde, Francesca Cuthbert, Ann E. McKellar, David Moore, Elizabeth Craig, Simeon Lisovski

“…Although adult female arrival to and departure from Lake Erie was similar to adult males, female schedules became significantly earlier than males as southward migration progressed. Using a graph network to describe the spatiotemporal associations among adults from the same inland lake, individuals appeared to be highly connected, meeting up in different regions throughout the non‐breeding season, suggesting that social interactions may play an important role in maintaining spatial connectivity. …”
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G2Grad-CAMRL: An Object Detection and Interpretation Model Based on Gradient-Weighted Class Activation Mapping and Reinforcement Learning in Remote Sensing Images by Shoulin Yin, Liguo Wang, Muhammad Shafiq, Lin Teng, Asif Ali Laghari, Muhammad Faizan Khan

“…First, ResNet is used as the main backbone network to extract the features of RSIs and generate feature graphs. …”
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Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects by Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim

“…We categorize the models into four main types: Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers, and Diffusion Models. …”
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Garbage prediction using regression analysis for municipal corporations of Indian cities by Raj Kumar Sharma, Manisha Jailia

“…This research initiates a variety of regression models, including multiple linear regression (MLR), artificial neural network (ANN), decision tree regression (DTR), and random forest regression (RFR). …”
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Unreliable communication in high-performance distributed multi-agent systems: A ingenious scheme in high computing by Ali Mustafa, Muhammad Najam ul Islam, Salman Ahmed, Muhammad Ahsan Tufail

“…This study established a consensus for a dynamically changing interaction topology among agents, for addition of agents in the network with dynamically switching topology at any instant in communication, for removal of agents from the network with dynamically switching topology at any instant in communication, and for a fixed topology with link failure and a reconnection with the same agent after each iteration. …”
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Distance Measurements Related to Cartesian Product of Cycles by Xiaoli Qiang, Saima Nazeer, Yu-Ming Chu, Muhammad Awais Umar, Imrana Kousar, Ammara Sehar

“…Making the graph of computer networks and analyzing it with aid of graph theory are extensively studied and researched in the literature. …”
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Steiner eccentricity: Predictions and applications by Xingfu Li, Zongbo Yang, Siyi Lin, Jialu Wang

“…The average Steiner 3-eccentricity, a fundamental graph invariant, has demonstrated efficacy in network similarity assessment and anti-HIV activity prediction. …”
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An improve fraud detection framework via dynamic representations and adaptive frequency response filter by Juncheng Yang, Shuxia Li, Zijun Huang, Junhang Wu

“…On the Sichuan Telecom, Sichuan-mini Telecom, and YelpChi datasets, using AUC, Recall, and F1-score as evaluation metrics, DPGFD outperforms GCN, GraphSAGE, FRAUDRE, BWGNN, and GAGA by an average of 5%.…”
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Joint QoS prediction for Web services based on deep fusion of features by Jianxun LIU, Linghang DING, Guosheng KANG, Buqing CAO, Yong XIAO

“…In order to solve the problem of insufficient accuracy of Web service QoS prediction, a joint QoS prediction method for Web services based on the deep fusion of features was proposed with considering of the hidden environmental preference information in QoS and the common features of multi-class QoS.First, QoS data was modeled as a user-service bipartite graph and multi-component graph convolution neural network was used for feature extraction and mapping, and the weighted fusion method was used for the same dimensional mapping of multi-class of QoS features.Subsequently, the attention factor decomposition machine was used to extract the first-order features, second-order interactive features, and high-order interactive features of the mapped feature vector.Finally, the results of each part were combined to achieve the joint QoS prediction.The experimental results show that the proposed method is superior to the existing QoS prediction methods in terms of root mean square error (RMSE) and average absolute error (MAE).…”
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A Dual-View Approach for Multistation Short-Term Passenger Flow Prediction in Bus Transit Systems by Gang Luo, Haoxuan Kuang, Dongran Zhang, Kunxiang Deng, Jun Li

“…Simultaneously, in addition to considering the adjacency graph, the similarity of all the stations of the entire transit network is also considered and uses multigraph convolution and graph fusion modules. …”
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