Decision modelling for the evaluation of diabetes outcomes by A. A. Mosikian, W. Zhao, T. L. Galankin, A. S. Kolbin

“…We searched through the PubMed database using the ResearchGate and Mendeley networks; we also collected data from the websites of the key opinion leaders in the field of pharmacoeconomics and decision modelling. …”
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A comparative study of machine learning and deep learning models in binary and multiclass classification for intrusion detection systems by Ayesha Alharthi, Meera Alaryani, Sanaa Kaddoura

“…Seven models, Random Forest, Decision Tree, K-Nearest Neighbors, XGBoost, Convolutional Neural Network, Gated Recurrent Unit, and Long Short-Term Memory, were trained and evaluated using precision, recall, and F1-score. …”
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Enhanced Wind Energy Forecasting Using an Extended Long Short-Term Memory Model by Zachary Barbre, Gang Li

“…The xLSTM model was validated using SCADA data from wind turbines, with rigorous preprocessing to remove anomalous measurements. …”
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ECP-IEM: Enhancing seasonal crop productivity with deep integrated models. by Ghulam Mustafa, Muhammad Ali Moazzam, Asif Nawaz, Tariq Ali, Deema Mohammed Alsekait, Ahmed Saleh Alattas, Diaa Salama AbdElminaam

“…The proposed methodology consists of different stages, like Data Collection, Preprocessing, Feature Extraction with Support Vector Machine (SVM), correlation with Normalized Google Distance (NGD), feature ranking with rising star. …”
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ResTUnet: A Novel Neural Network Model for Nowcasting Using Radar Echo Sequences by Ground-Based Remote Sensing by Lei Zhang, Ruoyang Zhang, Yu Wu, Yadong Wang, Yanfeng Zhang, Lijuan Zheng, Chongbin Xu, Xin Zuo, Zeyu Wang

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Early Fault Detection Method of Rolling Bearing Based on MCNN and GRU Network with an Attention Mechanism by Xiaochen Zhang, Yiwen Cong, Zhe Yuan, Tian Zhang, Xiaotian Bai

“…This method first inputs multiple time scales rolling bearing vibration signals into the convolutional neural network to train the model through multiscale data processing and then adds the gated recurrent unit network with an attention mechanism to make the model predictive. …”
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Enhancing Science Learning: The Role of Educational Games in Elementary Classrooms by Ida Puspita Sari, Rohmani

“…Researchers collected journal articles from Google Scholar, Research Gate, SINTA, and Web of Science in the time span from 2019 to 2023. …”
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Carbon Footprint Analysis in Hydrogen Production Technology from Coke Oven Gas with Life Cycle Approach: Case Studies for Eight Companies by Xiao Chenjiang, Li Wenqing, Wang Ce

“…This study provides a reference for carbon footprint accounting model of hydrogen in China and fills the current data gap in the carbon footprint of COG-based hydrogen processes. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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Implementing semiclassical Szegedy walks in classical-quantum circuits for homomorphic encryption by Sergio A Ortega, Pablo Fernández, Miguel A Martin-Delgado

“…As cloud services continue to expand, the security of private data stored and processed in these environments has become paramount. …”
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Digital Twin Approach for Fault Diagnosis in Photovoltaic Plant DC–DC Converters by Pablo José Hueros-Barrios, Francisco Javier Rodríguez Sánchez, Pedro Martín Sánchez, Carlos Santos-Pérez, Ariya Sangwongwanich, Mateja Novak, Frede Blaabjerg

“…The proposed method addresses both hardware faults such as open and short circuits in insulated-gate bipolar transistors (IGBTs) and diodes and sensor-level false data injection attacks (FDIAs). …”
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COVID-19 and problems of ophthalmology by V. V. Neroev, G. I. Krichevskaya, N. V. Balatskaya

“…The review presents current data on SARS-CoV-2, ways of contagion, transmission routes, detection time in the body, the role of asymptomatic virus carriers in the epidemic process. …”
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A VHDL Code for Offset Pulse Position Modulation Working with Reed Solomon System by Using ModelSim by Ahmed H. Albatoosh, Mohamed Ibrahim Shuja'a, Basman M. Al-Nedawe

“… Error correction codes, often known as ECC, play a significant part in the process of detecting and correcting data mistakes that occur through communication channels that are unreliable or noisy. …”
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Understudied targets of the ischemia-reperfusion injury pathogenesis in liver transplantation by P. O. Svishcheva, A. A. Kanibolotskiy, B. I. Yaremin, E. Yu. Anosova, Ya. S. Karina, Z. G. Kaziakhmedova, M. S. Novruzbekov

“…The search for literature data was carried out in international databases (PubMed/MedLine, ResearchGate, as well as in the scientific electronic library of Russia (eLibrary.RU) for the period from 2020-2024.Conclusion. …”
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Hybrid GIS-Transformer Approach for Forecasting Sentinel-1 Displacement Time Series by Lama Moualla, Alessio Rucci, Giampiero Naletto, Nantheera Anantrasirichai, Vania Da Deppo

“…To address this, a Time-Gated LSTM (TG-LSTM) was implemented. TG-LSTM outperformed standard LSTM for irregular data in one-step prediction but faced limitations in handling heteroscedasticity and computational cost during multi-step forecasting. …”
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Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete. Advances in Civil Engineering by Awoyera, Paul O., Adetola, Joshua, Nayeemuddin, Mohammed, Mewada, Hiren, George Fadugba, Olaolu

“…The construction industry significantly contributes to environmental degradation,with many structures exhibiting high carbon footprints throughout their construction processes and lifespans.Activities such as cement hydration and other commoncon-struction practices substantially influence environmental conditions overtime,necessitating a critical evaluation of material and design choices.This study reported the environmental impact of fly ash(FA),which is largely used to enhance concrete strength.A prediction of two end point indicators,that is,global warming potential(GWP)and CO2 emission using soft computing methods are presented,which are particularly effective for handling complex,non linear relationships in environmental data.To achieve this, two machine learning approaches,the random forest(RF)and decision tree(DT)models,are employed to assess the environ- mental impact of structural materials and designs.Two data sets were obtained from reputable databases,including ResearchGate, Science Direct, Semantic Scholar,and Mendeley Data.The models are trained to explore the potential for optimizing structural designs and material selection stominimize environmental impacts.Feature importance is analyzed using Shapley values,providing insights into the most influential factors affecting GWP and CO2 emission Model performance is evaluated using R2 and root mean square error(RMSE) metrics. …”
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GTN-GCN: Real-Time Traffic Forecasting Using Graph Convolutional Network and Transformer by Sadia Naj Jinia, Sumaiya Binte Azad, Rima Akter, Taivan Reza Dipto, Md. Khaliluzzaman

“…The experimental setup included normalization, graph construction using adjacency matrices, and preprocessing steps to ensure data quality and robustness. …”
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An efficient trustworthy cyberattack defence mechanism system for self guided federated learning framework using attention induced deep convolution neural networks by Louai A. Maghrabi, Alanoud Subahi, Nouf Atiahallah Alghanmi, Turki Althaqafi, Nahla J. Abid, Nasser N. Albogami, Mahmoud Ragab

“…The CDMFL-AIDCNN model presents an improved structure incorporating self-guided FL with attack intelligence to improve defence mechanisms across varied cybersecurity applications in distributed systems. Initially, the data preprocessing stage utilizes Z-score normalization to transform input data into a beneficial format. …”
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Imaging Algorithm for Sea-Surface Ship Targets Based on Block Sparsity by Zhang Lin, Jiang Yicheng

“…By only estimating the azimuth Doppler parameters of the targets within the range gates, the amount of process data was significantly reduced, and the data processing speed was enhanced. …”
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A Review of Ku-Band GaN HEMT Power Amplifiers Development by Jihoon Kim

“…The demand for high-frequency, high-power amplifiers is growing, driven by the global expansion of high-speed data communication and enhanced national security requirements. …”
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