Threat Vector–Hierarchical Attack Representation Model-Based Threat Modeling and Security Assessment for Satellite Networks by Junbeom Park, Taehoon Eom, Hyungeun Kim, Hyeonsu Park, Zizung Yoon, Jongsou Park

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Enhancing mixing efficiency in multi-impeller tanks through innovative CFD and artificial neural network approaches by Reza Beigzadeh, Saber Soltanian, Yousef Azizpour

“…This study introduces an innovative model for simulating fluid flow in multi-impeller tanks using Computational Fluid Dynamics (CFD) and Artificial Neural Networks (ANN). The effects of blade number, impeller diameter, and rotational speed on material distribution within the tank are investigated. …”
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ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction. by Yunyun Dong, Yuanrong Zhang, Yuhua Qian, Yiming Zhao, Ziting Yang, Xiufang Feng

“…In response to these challenges, this study introduces the Adaptive Sparse Graph Contrastive Learning Network (ASGCL), an innovative approach to unraveling latent interactions in the complex context of cancer cell lines and drugs. …”
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Lightweight graph convolutional network with multi-attention mechanisms for intelligent action recognition in online physical education by Yuhao You

“…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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Graph-based neural networks with neural ODEs for robust speech processing in environmental and human-centric systems by Mambetov Saken, Ormanbekova Ainur, Joldasbayev Serik, Duissembayeva Laura, Mailykhanova Bulgyn

“…This paper introduces H-STGNN-ODE-DA, a novel model for voice sentiment analysis that combines multi-scale acoustic feature extraction, hierarchical graph neural networks (GNNs), Neural Ordinary Differential Equations (Neural ODEs), and domain-adversarial adaptation. …”
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Epileptic Seizure Detection in Neonatal EEG Using a Multi-Band Graph Neural Network Model by Lihan Tang, Menglian Zhao

“…The proposed method is evaluated using the EEG recordings of 39 neonates from the Helsinki database. …”
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Detecting SARS-CoV-2 in CT Scans Using Vision Transformer and Graph Neural Network by Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

“…This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. …”
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Wi-Fi-Enabled Vision via Spatially-Variant Pose Estimation Based on Convolutional Transformer Network by Hyeon-Ju Lee, Seok-Jun Buu

“…To address these challenges, we propose a Convolutional Transformer Network. This architecture integrates convolutional layers for localized spatial feature extraction and transformer layers for global temporal dependency modeling. …”
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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

“…Notably, the Siamese Network’s architecture ensures that comparisons are made within the same feature space, allowing for more accurate assessments. …”
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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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Windows Malware Detection via Enhanced Graph Representations with Node2Vec and Graph Attention Network by Nisa Vuran Sarı, Mehmet Acı, Çiğdem İnan Acı

“…The dual role of GAT as a classifier and feature extractor is also analyzed to evaluate its impact on embedding quality and classification accuracy. …”
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Simulated Annealing-Based Hyperparameter Optimization of a Convolutional Neural Network for MRI Brain Tumor Classification by Sofia El Amoury, Youssef Smili, Youssef Fakhri

“…Recent advances in deep learning, particularly through the application of Convolutional Neural Networks (CNNs), have transformed medical image analysis by enabling automated, high-accuracy feature extraction. …”
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Dynamic Real-Time Anchor Selection for Accurate UWB Indoor Positioning-Based Deep Neural Networks by Ammar Fahem Majeed, Rashidah Arsat, Muhammad Ariff Baharudin, Nurul Mu'Azzah Abdul Latiff, Abbas Albaidhani

“…This paper proposes a lightweight sequential branching deep network for dynamic indoor positioning (LSB-DIP Net) is proposed to address these challenges. …”
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Transformer-based multiple instance learning network with 2D positional encoding for histopathology image classification by Bin Yang, Lei Ding, Jianqiang Li, Yong Li, Guangzhi Qu, Jingyi Wang, Qiang Wang, Bo Liu

“…To address this issue, we propose a new framework named TMIL (Transformer-based Multiple Instance Learning Network with 2D positional encoding), which leverages multiple instance learning for weakly supervised classification of histopathological images. …”
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GPU-Based Implementation of Pruned Artificial Neural Networks for Digital Predistortion Linearization of Wideband Power Amplifiers by Wantao Li, Raul Criado, William Thompson, Gabriel Montoro, Kevin Chuang, Pere L. Gilabert

“…This paper presents a feature selection technique based on <inline-formula><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> regularization to select the most relevant weights of artificial neural networks (ANNs) for digital predistortion (DPD) linearization of wideband radio-frequency (RF) power amplifiers (PAs). …”
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Strategies for enhancing deep video encoding efficiency using the Convolutional Neural Network in a hyperautomation mechanism by Xiaolan Wang

“…This method utilizes a multi-level feature fusion network to reconstruct coding units. …”
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Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data by Reza Ahmadi Lashaki, Zahra Raeisi, Nasim Razavi, Mehdi Goodarzi, Hossein Najafzadeh

“…Abstract Objective This study evaluates the performance of various classifiers and pre-trained models for dental implant state classification using preprocessed radiography images with masks. …”
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RAMAS-Net: a module-optimized convolutional network model for aortic valve stenosis recognition in echocardiography by Yejia Gan, Wanzhong Huang, Yan Deng, Xiaoying Xie, Yuanyuan Gu, Yaozhuang Zhou, Qian Zhang, Maosheng Zhang, Yangchun Liu

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ST-CapsNet: Linking Spatial and Temporal Attention With Capsule Network for P300 Detection Improvement by Zehui Wang, Chuangquan Chen, Junhua Li, Feng Wan, Yu Sun, Hongtao Wang

“…Then the obtained signals were fed into the capsule network for discriminative feature extraction and P300 det- ection. …”
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Evaluating Regional Variability in Road Closure Outcomes Due to Rainfall: a Logistic Regression Approach by H. Zhong, D. Liang, D. Liang

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