Edge Convolutional Networks for Style Change Detection in Arabic Multi-Authored Text by Abeer Saad Alsheddi, Mohamed El Bachir Menai

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Comparative study of intelligent sensory technologies combined multiple metabolomics in evaluating sensory attributes and health profiles across different grades and varieties of g... by Junhui Lin, Zhangchang Yang, Qian Li, Weifei Wang, Sentai Liao, Dongxu Xing, Ruohong Chen, Daorui Pang, Yuxiao Zou

“…This study compares the sensory attributes and health profiles of green tea-processed mulberry leaf tea, focusing on different grades and leaves exposed to frost. …”
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A systematic flood risk assessment of Bloemfontein Watershed, South Africa by Zachariah H. Mshelia, Johanes A. Belle

“…The analytical hierarchy process (AHP) and GIS-based multi-criteria decision-making were utilized to map and identify potential locations that are vulnerable to floods. …”
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Enhanced Gold Ore Classification: A Comparative Analysis of Machine Learning Techniques with Textural and Chemical Data by Fabrizzio Rodrigues Costa, Cleyton de Carvalho Carneiro, Carina Ulsen

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Exercise Semantic Embedding for Knowledge Tracking in Open Domain by Zhi Cheng, Jinlong Li

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Participative leadership effects on followers’ radical creativity: the role of psychological safety and collaborative relationship by Guo Song, Md. Nurun Nabi, Md. Abu Issa Gazi, Mohammad Bin Amin, Abdul Rahman Bin S. Senathirajah, Md. Atikur Rahaman, Zhang Min

“…This study applies the social information processing (SIP) theory as the theoretical background by bringing the dynamics between leaders and followers to the current scholarly discourse. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

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ENHANCED EEG SIGNAL CLASSIFICATION FOR AUTISM SPECTRUM DISORDER USING RIEMANNIAN GEOMETRY AND ENSEMBLE LEARNING TECHNIQUES by Hajir Alzubaydi, Zaid Alyasseri

“…We enhance in this work the P300 classification in electroencephalogram (EEG) signals for autism disease using Riemannian geometry along with various conventional classifiers and ensemble learning approaches like bagging and boosting techniques (AdaBoostM1, GentleBoost, and LogitBoost), and developing sophisticated pre-processing methods for feature extraction. …”
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A Framework to Predict the Quality of a Video for Popularity on Social Media by Abqa Javed, Nimra Abid, Muhammad Shoaib, Muhammad Farrukh Shahzad, Fahad Sabah, Raheem Sarwar

“…Four machine learning models—random forest, stochastic gradient descent classifier (SGDC), gradient boosting, and XGBoost—were evaluated for classification. …”
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Digital Twin-Aided Municipal Traffic Control by Reeti Pradhananga, Shelby Williams, Sercan Aygun, Li Chen, Yazhou Tu, Whitney Crow, Sathyanarayanan Aakur, Nian-Feng Tzeng

“…Swift advances in computing and artificial intelligence (AI) technologies of late have prompted the increasing applications of digital twins (DiTs) to various sectors for boosting effectiveness and productivity. DiTs have been envisioned to possess immense potential for transforming numerous domains and sectors in the recent report of National Academics due to their powerful real-time decision-making based on modeling and simulating physical systems. …”
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Prediction and optimization of surface quality and material removal rate in wire-EDM cutting of tungsten–copper alloy (W70Cu30) by Abdullah Eaysin, Muhammad Ali Zinnah, Md. Nayem, Hosney Ara Begum, Md.Injamamul Haque Protyai, Salahuddin Ashrafi, Adib Bin Rashid

“…Predictive modeling was conducted using Support Vector Regression (SVR) and gradient-boosted regression Trees (GBRT) to assess the accuracy of MRR and Ra predictions. …”
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A Review on Pre-, In-Process, and Post-Synthetic Strategies to Break the Surface Area Barrier in g-C₃N₄ for Energy Conversion and Environmental Remediation by Mingming Gao, Minghao Zhao, Qianqian Yang, Lan Bao, Liwei Chen, Wei Liu, Jing Feng

“…To break this surface area barrier, advanced strategies achieve SSA enhancement through three primary pathways: pre-treatment (molecular and supramolecular precursor design), in process (templating and controlled polycondensation), and post-processing (chemical exfoliation and defect engineering). …”
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An investigation into the cost-sharing mechanism of order agriculture with consideration for green investment by Honglin Hu, Ouyang Dai, Ligong Qin, Jun Li

“…Model analysis shows that such a mechanism boosts both processing companies’ and farmers’ profits. …”
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Advanced Noise-Resistant Electrocardiography Classification Using Hybrid Wavelet-Median Denoising and a Convolutional Neural Network by Aditya Pal, Hari Mohan Rai, Saurabh Agarwal, Neha Agarwal

“…The classification of ECG signals is a critical process because it guides the diagnosis of the proper treatment process for the patient. …”
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Supervised Machine Learning Models for Predicting SS304H Welding Properties Using TIG, Autogenous TIG, and A-TIG by Subhodwip Saha, Barun Haldar, Hillol Joardar, Santanu Das, Subrata Mondal, Srinivas Tadepalli

“…Six ML algorithms—Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting Regression (GBR), and Extreme Gradient Boosting (XGBoost)—were implemented to assess their predictive accuracy. …”
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Sensor-Based Rock Hardness Characterization in a Gold Mine Using Hyperspectral Imaging and Portable X-Ray Fluorescence Technologies by Saleh Ghadernejad, Kamran Esmaeili, Mariano P. Consens

“…Rock hardness significantly impacts comminution efficiency, one of mining’s most energy-intensive processes. Accurate, rapid, and non-invasive hardness characterization can enhance mine-to-mill optimization and energy management. …”
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Hybrid Prediction Model of Burn-Through Point Temperature with Color Temperature Information from Cross-Sectional Frame at Discharge End by Mengxin Zhao, Yinghua Fan, Jing Ge, Xinzhe Hao, Caili Wu, Xian Ma, Sheng Du

“…Iron ore sintering is a critical process in steelmaking, where the produced sinter is the main raw material for blast furnace ironmaking. …”
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Computational machine learning estimation of digitoxin solubility in supercritical solvent at different temperatures utilizing ensemble methods by Hadil Faris Alotaibi, Waqed H. Hassan, Ahmed Kateb Jumaah Al-Nussairi, Narinderjit Singh Sawaran Singh, Ahmed Salah Al-Shati, M. M. Rekha, Subhashree Ray, Aashna Sinha, Gunjan Garg

“…Several machine learning models along with optimizer were used for correlation of the dataset. Employing AdaBoost as an ensemble method, predictions from Bayesian Ridge Regression (BRR), Gaussian process regression (GPR), and K-nearest neighbors (KNN) are amalgamated. …”
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Experimental analysis of triangular solar distiller with a new form of absorber by Ridha Boudhiaf, Sameh Kessentini, Zied Driss, Mohamed Salah Abid, Abederrahmane Aissa

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DPU empowered intelligent congestion control mechanism for the intelligent computing center network by CHEN Jinqian, GUO Shaoyong, LIU Chang, QI Feng, QIU Xuesong

“…Moreover, the model was transformed into the efficient gradient-boosted decision tree through knowledge distillation method, allowing for precise matching of control actions with real-time network conditions. …”
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