Design and Optimization Strategy of a Net-Zero City Based on a Small Modular Reactor and Renewable Energy by Jungin Choi, Junhee Hong

“…This study proposes the SMR Smart Net-Zero City (SSNC) framework—a scalable model for achieving carbon neutrality by integrating Small Modular Reactors (SMRs), renewable energy sources, and sector coupling within a microgrid architecture. …”
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PD-Net: Parkinson’s Disease Detection Through Fusion of Two Spectral Features Using Attention-Based Hybrid Deep Neural Network by Munira Islam, Khadija Akter, Md. Azad Hossain, M. Ali Akber Dewan

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Comparative Study of VGG16, ResNet50, and YOLOv8 Models in Detecting Driver Distraction in Varying Lighting Conditions by Ali Nafaa Jaafar, Mustafa Nafea Alzubaidi

“…Observing driver distractions while driving gives valuable information to prevent accidents, so it is necessary to use effective monitoring methods. …”
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An empirical study of the effect of information technology expenditures on student achievement. Information technology, Productivity, Educational technology, Standardized testing,... by Alan R. Peslak

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Using participant or non-participant observation to explain information behaviour. Participant observation, Non-participant observation, Information behaviour, Hospital pharmacists... by Janet Cooper, Rachael Lewis, Christine Urquhart

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Metodologías para el desarrollo de Interfaces Visuales de Recuperación de Información: análisis y comparación by Víctor Herrero-Solana, Yusef Hassan

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Segmentation of CAD models using hybrid representation by Claude Uwimana, Shengdi Zhou, Limei Yang, Zhuqing Li, Norbelt Mutagisha, Edouard Niyongabo, Bin Zhou

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An Emergency Response Framework Design and Performance Analysis for Ship Fire Incidents in Waterway Tunnels by Jian Deng, Shaoyong Liu, Xiaohan Zeng

“…The framework is mapped into a Petri net model encompassing three key stages: detection and early warning, emergency response actions, and recovery. …”
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DeepInsulin-Net: A Deep Learning Model for Identifying Drug Interactions Leading to Specific Insulin-Related Adverse Events by Muhammed Ali Pala

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Automatic two-wheeler rider identification and triple-riding detection in surveillance systems using deep-learning models by Uttam U. Deshpande, Supriya Shanbhag, Rudragoud Patil, Ramchandra Alias Ameet Chate, Sufola Das Chagas Silva Araujo, Kevin Pinto, J. Arjun, Mayankraj Patil, Balagouda Nirwani

“…To address challenging environments like occlusions and precise vehicle detection from a long distance we use the ResNet18-based DetectNet_v2 model. To reliably predict triple riding from several riders sitting on a two-wheeler and extract license plate information, we employ a cutting-edge YOLOv8 object-detection algorithm that operates on the Darknet framework. …”
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DMA‐Net: A dual branch encoder and multi‐scale cross attention fusion network for skin lesion segmentation by Guangyao Zhai, Guanglei Wang, Qinghua Shang, Yan Li, Hongrui Wang

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Parkinson’s Disease Detection via Bilateral Gait Camera Sensor Fusion Using CMSA-Net and Implementation on Portable Device by Jinxuan Wang, Hua Huo, Wei Liu, Changwei Zhao, Shilu Kang, Lan Ma

“…Consequently, we developed a single-step segmentation method based on Savitzky–Golay (SG) filtering and a sliding window peak selection function, along with a Cross-Attention Fusion with Mamba-2 and Self-Attention Network (CMSA-Net). Additionally, we introduced a loss function based on Maximum Mean Discrepancy (MMD) to further enhance the fusion process. …”
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HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…This model employs a dual-path parallel feature extraction strategy: the TabNet path performs sparse feature selection to capture fine-grained local discriminative information, while the hierarchical soft decision tree (HSDT) path models global nonlinear relationships across hyperspectral bands. …”
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MSA-Net: a multi-scale and adversarial learning network for segmenting bone metastases in low-resolution SPECT imaging by Yusheng Wu, Qiang Lin, Yang He, XianWu Zeng, Yongchun Cao, ZhengXing Man, Caihong Liu, Yusheng Hao, Zhengqi Cai, Jinshui Ji, Xiaodi Huang

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MFDAFF-Net: Multiscale Frequency-Aware and Dual Attention-Guided Feature Fusion Network for UAV Imagery Object Detection by Shu Tian, Bingxi Zhang, Lin Cao, Lihong Kang, Jing Tian, Xiangwei Xing, Bo Shen, Chunzhuo Fan, Kangning Du, Chong Fu, Ye Zhang

“…Based on this observation, we devise a multiscale frequency-aware and dual attention-guided feature fusion network (MFDAFF-Net) for UAV imagery object detection. MFDAFF-Net integrates spatial domain multiscale feature fusion with frequency domain information augmentation, effectively improving the detection accuracy of objects with varying scales in UAV imagery. …”
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GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability by Zhiyu Dong, Le Zhao, Yajun Fan, Haihua Ma, Changle Shao, Yiran Zhang, Peng Li

“…Firstly, GA-TongueNet is built upon the transformer architecture, embedding the dilated feature pyramid (DiFP) module and the multi-dilated convolution (MDi) module proposed in this article. …”
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A robust tuned EfficientNet-B2 using dynamic learning for predicting different grades of brain cancer by A. A. Abd El-Aziz, Mohammed Elmogy, Sameh Abd El-Ghany

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ACGRHA-Net: Accelerated multi-contrast MR imaging with adjacency complementary graph assisted residual hybrid attention network by Haotian Zhang, Qiaoyu Ma, Yiran Qiu, Zongying Lai

“…This graph is then combined with a residual hybrid attention network, forming the adjacency complementary graph assisted residual hybrid attention network (ACGRHA-Net) for multi-contrast MR image reconstruction. …”
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Deep Pseudogene Categorization and Genome-Wide Transcription Prediction Using GANP-Based Feature Selection and TabNet Interpretability by Zeeshan Ahmed, Kashif Munir, Muhammad Usama Tanveer, Syed Rizwan Hassan, Ateeq Ur Rehman, Habib Hamam

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MolAttnNet: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention by Chenxu Wang, Yijun Feng, Zhejie Xu, Xiaohui Xu, Bangguo Peng

“…To address this issue, we propose MolAttnNet, an innovative deep learning framework that combines Graph Neural Networks, Transformer encoders, and Long Short-Term Memory networks to enhance solubility prediction accuracy. …”
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