A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

“…A comparative study evaluated the performance of five well-known two-class classification algorithms: two-class boosted decision trees, two-class decision forests, two-class locally deep SVMs, two-class neural networks, and two-class logistic regression. …”
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Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation. by Bhavana Jonnalagadda, Stephen Becker

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Evaluating the effectiveness of the national elderly care program in Oman: A cross-sectional study by Idris Aal Jumaa, Mohammed Al Ghafri, Nahid Bait Jamil, Jokha Al Sa'idi, Sitwat Usman Langrial, Salah Al Awaidy

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Evaluation of the Effectiveness of the UNet Model with Different Backbones in the Semantic Segmentation of Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Julieta Raquel Hernandez Vidales

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Evaluating the impact of waste marble on the compressive strength of traditional concrete using machine learning by Kennedy C. Onyelowe, Viroon Kamchoom, Ahmed M. Ebid, Shadi Hanandeh, Susana Monserrat Zurita Polo, Rolando Fabián Zabala Vizuete, Rodney Orlando Santillán Murillo, Rolando Marcel Torres Castillo, Siva Avudaiappan

“…This research has focused on evaluating the impact of waste marble on the compressive strength of traditional concrete using machine learning (ML). …”
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Empirical evidence for a process-based model of health-related quality of life using network analysis by Nicolette Stogios, Nicolette Stogios, Troy Francis, Troy Francis, Rachel G. Peiris, Aleksandra Stanimirovic, Aleksandra Stanimirovic, Valeria Rac, Valeria Rac, Robert P. Nolan, Robert P. Nolan

“…In support of this approach, we developed a novel HRQL assessment tool called the EUROIA: EvalUation of goal-diRected activities to prOmote wellbeIng and heAlth, which uses self-report data to assess the frequency with which individuals engage in a sample of goal-directed activities in pursuit of living well.MethodsWe conducted a network analysis to evaluate the hypothesis that the EUROIA subscales would demonstrate a meaningful pattern of associations with an established HRQL measure and associated indices of psychosocial functioning and efficacy in self-managing a chronic medical condition.ResultsThe EUROIA is associated with established indices of HRQL in a manner that is theoretically consistent with our process-based model. …”
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Combining Generative Adversarial Networks (GANs) With Gaussian Noise for Anomaly Detection in Internet of Things (IoT) Traffic by Roya Morshedi, S. Mojtaba Matinkhah

“…To evaluate the model's performance, the CICIDS2017 dataset, which includes various attack types and normal network traffic, was used. …”
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Week-Ahead Water Demand Forecasting Using Convolutional Neural Network on Multi-Channel Wavelet Scalogram by Adithya Ramachandran, Hatem Mousa, Andreas Maier, Siming Bayer

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Evaluating the Impact of Frequency Decomposition Techniques on LSTM-Based Household Energy Consumption Forecasting by Maissa Taktak, Faouzi Derbel

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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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SAGEFusionNet: An Auxiliary Supervised Graph Neural Network for Brain Age Prediction as a Neurodegenerative Biomarker by Suraj Kumar, Suman Hazarika, Cota Navin Gupta

“…<b>Background:</b> The ability of Graph Neural Networks (GNNs) to analyse brain structural patterns in various kinds of neurodegenerative diseases, including Parkinson’s disease (PD), has drawn a lot of interest recently. …”
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A Spiking Neural Network With Adaptive Graph Convolution and LSTM for EEG-Based Brain-Computer Interfaces by Peiliang Gong, Pengpai Wang, Yueying Zhou, Daoqiang Zhang

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Learning a cross-scale cross-view decoupled denoising network by mining Omni-channel information by Song Qian, Yan Xue, Youbao Chang

“…Traditional denoising methods often fail to address the complex noise patterns in such scenarios, which can adversely affect feature encoding and subsequent processing tasks. …”
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Performance Evaluation of Numerical Weather Prediction Models in Forecasting Rainfall Events in Kerala, India by V. Nitha, S. K. Pramada, N. S. Praseed, Venkataramana Sridhar

“…The results reveal that all models captured rainfall patterns well for the lower threshold of 5 mm, but most of the models struggled to accurately forecast heavy rainfall, especially for longer lead times. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…Several motifs closely match experimentally validated RBP motifs, confirming the model’s capacity to learn biologically meaningful patterns. A downstream case study on YTHDF1 focuses on analyzing interpretable spatial binding patterns, using a large-scale prediction dataset and CLIP-seq peak alignment. …”
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Electroencephalography-Based Pain Detection Using Kernel Spectral Connectivity Network with Preserved Spatio-Frequency Interpretability by Santiago Buitrago-Osorio, Julian Gil-González, Andrés Marino Álvarez-Meza, David Cardenas-Peña, Alvaro Orozco-Gutierrez

“…To address these limitations, we propose a threefold DL-based framework for coding EEG-based pain detection patterns. (i) We employ the Kernel Cross-Spectral Gaussian Functional Connectivity Network (KCS-FCnet) to code pairwise channel dependencies for pain detection. …”
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Clustering coefficient reflecting pairwise relationships within hyperedges by Rikuya Miyashita, Shiori Hironaka, Kazuyuki Shudo

“…Clustering coefficients quantify local link density in networks and have been widely studied for both simple graphs and hypergraphs. …”
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Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks by Diaoulé Diallo, Jurij Schoenfeld, René Schmieding, Sascha Korf, Martin J. Kühn, Tobias Hecking

“…Additionally, sub-graph analyses confirm that different venue types display distinct network characteristics consistent with their real-world contact patterns. …”
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Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…We use machine learning (ML) algorithms, including Random Forest, Logistic Regression, and Support Vector Machine, to evaluate the diagnostic power of the brain features and network patterns in differentiating the PD subtypes and distinguishing PD from HC. …”
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BTCP: Binary Temporal Convolutional Network-Based Data Prefetcher for Low Inference Latency and Storage Overhead by Chang Ho Ryu, Tae Hee Han

“…BTCP aids in detecting memory patterns by processing addresses and program counters through bitwise XOR operations and feeding them into a neural network. …”
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