Integrating Recurrent Neural Networks and Loss Function Optimization for Efficient Indoor Camera Positioning by Shamsul Alam, Farhan Mohamed, Bellal Hossain

“…This study proposed an integrated design that combines recurrent neural networks (RNNs) and a loss function modification approach to improve the accuracy of indoor camera location. …”
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The two-mode network approach to digital skills and tasks among technology park employees by Anna Ujwary-Gil, Bianka Godlewska-Dzioboń

“…Findings: The results show that there is a relationship between selected digital skills and tasks shared among employees; digital skills influence behavior patterns, thus increasing or decreasing tasks shared in the workplace; moreover, dyad embedded in an intra-organizational social network is more appropriate for anticipating inherently relational tasks sharing between employees in a knowledge-intensive organization. …”
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Enhanced-Dueling Deep Q-Network for Trustworthy Physical Security of Electric Power Substations by Nawaraj Kumar Mahato, Junfeng Yang, Jiaxuan Yang, Gangjun Gong, Jianhong Hao, Jing Sun, Jinlu Liu

“…Empirical evaluation using synthetic data derived from historical incident patterns demonstrates the significant advantages of EDDQN over other standard DQN variations, yielding an average reward of 7.5, a threat prevention success rate of 91.1%, and a notably low false alarm rate of 0.5%. …”
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Multimodal lightweight neural network for Alzheimer's disease diagnosis integrating neuroimaging and cognitive scores by Bhoomi Gupta, Ganesh Kanna Jegannathan, Mohammad Shabbir Alam, Kottala Sri Yogi, Janjhyam Venkata Naga Ramesh, Vemula Jasmine Sowmya, Isa Bayhan

“…To address these challenges, we propose Light-Mo-DAD, a lightweight multimodal diagnostic neural network designed to integrate MRI, PET imaging, and neuropsychological assessment scores for enhanced AD detection. …”
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Adaptive distributed honeypot detection network for enhanced cybersecurity against DoS and DDoS attacks by V. Selva Kumar, K.R. Mohan Raj, S. Gopalakrishnan, G. Vennila, D. Dhinakaran, P. Kavitha

“…Traditional detection techniques often fall short in addressing the complexities posed by dynamic traffic patterns, diverse attack types, and real-time processing demands. …”
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Radio Spectrum Sensing Framework for Large-Scale, High-Density IoT Sensor Networks by Partemie-Marian Mutescu, Alexandru Lavric, Adrian-Ioan Petrariu, Alin-Mihai Cailean, Valentin Popa

“…The rapid growth of the Internet of Things (IoT) requires innovative solutions to address the challenges posed by constrained radio spectrum resources in Wireless Sensor Networks (WSNs). This paper presents an Artificial Intelligence (AI) based spectrum sensing framework designed to detect and classify various IoT communication technologies and generate advanced communication channel analytics, such as the technology in use, central frequency and the bandwidth of the radio channel, time-on-air parameter, channel usage patterns, and radio spectrum occupancy degree. …”
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A Representation-Learning-Based Graph and Generative Network for Hyperspectral Small Target Detection by Yunsong Li, Jiaping Zhong, Weiying Xie, Paolo Gamba

“…The mini-batch-training pattern of the GCN decreases the high computational cost of building an adjacency matrix for high-dimensional data sets. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…To address these limitations, this study proposes a novel seepage field solution method based on Physics-Informed Neural Networks (PINNs).MethodsThe core of the proposed method lies in transforming the free-boundary seepage problem into a fixed-boundary optimization problem. …”
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Exploring the role of electrode density in capturing spatiotemporal dynamics of resting-state networks with EEG by Matheus Mangini Bertuzzo, Rodrigo P Rocha, Ricardo Spyrídes Boabaid Pimentel Gonçalves, Adair Roberto Soares Dos Santos, Odival Cezar Gasparotto

“…Using exact low-resolution electromagnetic tomography, we estimated the cortical current density in regions of interest linked to resting state networks. Point process analysis was employed to identify regions of high activity over time, revealing dynamic brain salient activity patterns, or brain maps. …”
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Triplet-Style Dynamic Graph Network With Transformer Encoder for Scam Detection in Cryptocurrency Transactions by Min-Woo Nam, Hyeon-Ju Lee, Seok-Jun Buu

“…To address these intertwined challenges, we introduce the Triplet-style Dynamic Graph Convolutional Network (TD-GCN). TD-GCN is specifically engineered to model the dynamic nature of cryptocurrency transaction networks and to disentangle subtle distinctions between scam and benign transaction patterns. …”
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Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach by Xi Zhang, Lan Yang, Jiayu Lu, Yuting Yuan, Dandan Li, Hui Zhang, Rong Yao, Jie Xiang, Bin Wang

“…This study employed hidden Markov model (HMM) analysis to delve deeper into the moment-to-moment temporal patterns of brain activity in BD. We utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 43 BD patients and 51 controls to evaluate the altered dynamic spatiotemporal architecture of the whole-brain network and identify unique activation patterns in BD. …”
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Causal inference-based graph neural network method for predicting asphalt pavement performance by CHEN Kai;WANG Xiaohe;SHI Xinli;CAO Jinde

“…The local feature extraction module utilizes dilated convolutional neural networks(CNN) with various kernel sizes to extract short-term temporal patterns at different scales. …”
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Real-time ocean wave prediction in time domain with autoregression and echo state networks by Karoline Holand, Henrik Kalisch

“…This study evaluates the potential of applying echo state networks (ESN) and autoregression (AR) for dynamic time series prediction of free surface elevation for use in wave energy converters (WECs). …”
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Synergized security framework: revolutionizing wireless sensor networks through comparative methodological analysis by Guodong Su, Boliang Zhang

“…Finally, comprehensive evaluations using OMNeT++ with networks of 1–500 nodes demonstrate that our framework outperforms existing protocols (LEAP, SPINS, ESK) by 17–32% in network throughput and 12–26% in node connectivity, while maintaining comparable latency to quantum-based methods (QKD, BB84). …”
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Providing a model of purchase intention and customer experience on customer behavior in virtual networks by Kazem Tolooee, Hossein budaghi Khajeh Noubar, Hossein Gharehbiglo, Mojtaba Ramazani

“…The collection tool in this research includes a questionnaire of purchase intention pattern based on customers' experience in designed virtual networks. …”
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An efficient emerging network and secured hopping scheme employed over the unsecured public channels by Aamir Shahzad, Kaiwen Zhang, René Landry, Neal Xiong, Young-Gab Kim

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Wordline Input Bias Scheme for Neural Network Implementation in 3D-NAND Flash by Hwiho Hwang, Gyeonghae Kim, Dayeon Yu, Hyungjin Kim

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Synergistic Enhancement of Carbon Sinks and Connectivity: Restoration and Renewal of Ecological Networks in Nanjing, China by Renfei Zhang, Hongye Li, Zhicheng Liu

“…This study used Nanjing, China, as a case to construct an ecological network by applying Morphological Spatial Pattern Analysis (MSPA) and the Linkage Mapper (LM) tool based on circuit theory. …”
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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

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A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

“…The filter bank common spatial pattern (FBCSP) algorithm filters the MI-based EEG signals in the spatial domain to extract features. …”
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