Hide and seek in transaction networks: a multi-agent framework for simulating and detecting money laundering activities by Qianyu Wang, Wei-Tek Tsai, Tianyu Shi, Wang Tang, Bowen Du

“…Abstract Detecting money laundering within financial networks presents a complex challenge due to the elusive behavior patterns of laundering agents, often resulting in data gaps. …”
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Windows Malware Detection via Enhanced Graph Representations with Node2Vec and Graph Attention Network by Nisa Vuran Sarı, Mehmet Acı, Çiğdem İnan Acı

“…Finally, the enhanced embeddings are classified using Convolutional Neural Network (CNN) and Gated Recurrent Units (GRU)s, a custom hybrid CNN-GRU-3 deep learning-based model capable of effectively modeling sequential patterns. …”
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Study on the relationship between topological characteristics of vegetation ecospatial network and sand fixation function in the Mongolian Plateau

“…Using the minimum cumulative resistance (MCR) model and complex network theory, the regional-scale vegetation structure was abstracted into a vegetation ecospatial network (VEN), and its topological characteristics were analyzed. …”
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Translational approach for dementia subtype classification using convolutional neural network based on EEG connectome dynamics by Thawirasm Jungrungrueang, Sawrawit Chairat, Kasidach Rasitanon, Praopim Limsakul, Krit Charupanit

“…This study investigated dynamic features of resting-state electroencephalography (EEG) functional connectivity to identify characteristic patterns of dementia subtypes, such as Alzheimer’s disease (AD) and frontotemporal dementia (FD), and to evaluate their potential as biomarkers. …”
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mTanh: A Low-Cost Inkjet-Printed Vanishing Gradient Tolerant Activation Function by Shahrin Akter, Mohammad Rafiqul Haider

“…Building on this progress, this work has developed a nonlinear computational element coined as mTanh to serve as an activation function in neural networks. Activation functions are essential in neural networks as they introduce nonlinearity, enabling machine learning models to capture complex patterns. …”
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Hot question prediction in Stack Overflow by Li Xian Zhao, Li Zhang, Jing Jiang

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Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding by Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John

“…Nevertheless, there are few approaches available to directly represent the relationship between these two perspectives of the node property and the network topology. Approaches utilizing the reconstruction error rely on straightforward, simple mappings, which introduce a substantial risk of overfitting in high-dimensional data, wherein the model acquires patterns that are exclusive to the training data and fails to generalize to new data. …”
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Unbalanced Associations between Physical, Psychological, and Social Domains of the Leicester Cough Questionnaire: Network and Mediation Analyses by Jieun Kang, Jiyeon Kang, Sung Jun Chung, Hyung Koo Kang, Sung-Soon Lee, Yun-Jeong Jeong, Ji-Yong Moon, Deog Kyeom Kim, Jin Woo Kim, Seung Hun Jang, Jae-Woo Kwon, Byung-Jae Lee, Hyeon-Kyoung Koo

“…The mediation analysis findings were subsequently validated in an independent cohort. Results Network analysis of LCQ items identified distinct patterns for each domain. …”
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Employing Siamese Networks as Quantitative Biomarker for Assessing the Effect of Dolphin-Assisted Therapy on Pediatric Cerebral Palsy by Jesús Jaime Moreno Escobar, Oswaldo Morales Matamoros, Erika Yolanda Aguilar del Villar, Hugo Quintana Espinosa, Liliana Chanona Hernández

“…Testing on samples from four children yielded a high average similarity index of 0.9150, indicating consistent similarity metrics before and after therapy. The network is trained to learn patterns and similarities between pre- and post-therapy evaluations, in order to identify biomarkers indicative of therapy effectiveness. …”
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Efficacy of antimalarial drugs for treatment of uncomplicated falciparum malaria in Asian region: A network meta-analysis. by Cho Naing, Maxine A Whittaker, Norah Htet Htet, Saint Nway Aye, Joon Wah Mak

“…Moreover, one drug regimen is better than another is only if current drug-resistance patterns are at play. For example, the AL might be better than DHP in areas where both artemisinin and piperaquine resistance patterns are prevalent. …”
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Individual-level cortical morphological network analysis in idiopathic normal pressure hydrocephalus: diagnostic and prognostic insights by Yifeng Yang, Meijing Yan, Lianxi Sun, Xiao Liu, Xuhao Fang, Shihong Li, Guangwu Lin

“…This study investigates individual-level cortical morphological network patterns in iNPH, explores their diagnostic utility and prognostic value for postoperative outcomes. …”
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Lightweight graph convolutional network with multi-attention mechanisms for intelligent action recognition in online physical education by Yuhao You

“…Existing action recognition models are often computationally intensive and struggle to generalize across diverse skeletal patterns. To address this, we propose a lightweight graph convolutional network (GCN) that integrates an improved Ghost module with multi-attention mechanisms, including a global attention mechanism (GAM) and a channel attention mechanism (CAM), to enhance spatial and temporal feature extraction. …”
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The Settlement Structure Is Reflected in Personal Investments: Distance-Dependent Network Modularity-Based Measurement of Regional Attractiveness by Laszlo Gadar, Zsolt T. Kosztyan, Janos Abonyi

“…How can the structure of investment patterns characterize the attractiveness and development of economic regions? …”
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SNet: A novel convolutional neural network architecture for advanced endoscopic image classification of gastrointestinal disorders by Samra Siddiqui, Junaid A. Khan, Tallha Akram, Meshal Alharbi, Jaehyuk Cha, Dina A. AlHammadi

“…Therefore, multiple challenges exist regarding CAD (Computer-aided diagnosis) and endoscopy, including a lack of annotated images, a dark background, poor contrast, and an irregular pattern. The objective of this research is to develop a robust deep network, called SNet, that offers a solution to complex classification problems. …”
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Probabilistic Forecasting of Crude Oil Prices Using Conditional Generative Adversarial Network Model with Lévy Process by Mohammed Alruqimi, Luca Di Persio

“…Recent research highlights Generative Adversarial Networks (GANs) as a promising alternative approach for capturing intricate patterns in time series data, leveraging the adversarial learning framework. …”
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The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology by Yun Tian, Xiaojie Tang

“…This work proposes an analysis method based on the artificial neural network to predict tourist behavior patterns through big data analysis, thereby optimizing the allocation of tourism resources. …”
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Northern goshawk optimization for optimal reactive power compensation in photovoltaic low-voltage radial distribution networks by Shaikh Sohail Mohiyodin, Rajesh Maharudra Patil, Dr MS Nagaraj

“…Considering the PVs and CBs of the network, a modified IEEE 33-bus test system was used to evaluate the effectiveness of the suggested methodology.…”
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Toward connectivity of a disconnected cluster in partitioned wireless sensor network for time-critical data collection by Kashif Nasr, Noor Muhammad Khan

“…These networks have diverse communication patterns due to non-uniform sensing activities at various locations in the environment being monitored. …”
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Enhanced novelty approaches for resource allocation model for multi-cloud environment in vehicular Ad-Hoc networks by R. Augustian Isaac, P. Sundaravadivel, V. S. Nici Marx, G. Priyanga

“…The proposed method begins by the meticulous feature extraction from the Vehicular network model, with attributes such as mobility patterns, transmission medium, bandwidth, storage capacity, and packet delivery ratio. …”
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DTC-m6Am: A Framework for Recognizing N6,2′-O-dimethyladenosine Sites in Unbalanced Classification Patterns Based on DenseNet and Attention Mechanisms by Hui Huang, Fenglin Zhou, Jianhua Jia, Huachun Zhang

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