Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting by Vandana Singh, Sudip Kumar Sahana, Vandana Bhattacharjee

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Novel Deep Learning-Based Facial Forgery Detection for Effective Biometric Recognition by Hansoo Kim

“…Furthermore, a binary classification approach combined with supervised contrastive learning addresses data imbalance and strengthens generalization capabilities. …”
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Explicit Learning Triggers Sensory Motor Competence: An Experimental Study Of Pakistani Esl Learners by Sidrah Niaz, Asad Ali

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Aortic pressure and forward and backward wave components in children, adolescents and young-adults: Agreement between brachial oscillometry, radial and carotid tonometry data and a... by Agustina Zinoveev, Juan M Castro, Victoria García-Espinosa, Mariana Marin, Pedro Chiesa, Daniel Bia, Yanina Zócalo

“…Non-invasive devices used to estimate central (aortic) systolic pressure (cSBP), pulse pressure (cPP) and forward (Pf) and backward (Pb) wave components from blood pressure (BP) or surrogate signals differ in arteries studied, techniques, data-analysis algorithms and/or calibration schemes (e.g. calibrating to calculated [MBPc] or measured [MBPosc] mean pressure). …”
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SPATIALLY INFORMED INSIGHTS: MODELING PERCENTAGE POVERTY IN EAST JAVA PROVINCE USING SEM WITH SPATIAL WEIGHT VARIATIONS by Ashabul Akbar Maulana, Achmad Fauzan

“…A strategic approach employed to comprehend and redress this issue involves the application of spatial analysis, wherein spatial factors are intricately integrated into the modeling and cartographic representation of poverty data. …”
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An EWS-LSTM-Based Deep Learning Early Warning System for Industrial Machine Fault Prediction by Fabio Cassano, Anna Maria Crespino, Mariangela Lazoi, Giorgia Specchia, Alessandra Spennato

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Evaluasi Kinerja Alat Ukur Tinggi Muka Air Otomatis Menggunakan Kalibrator Di Laboratorium by Isnan Fauzan Akrom, Hany Agustiani

“…Water resources infrastructure development requires a careful planning, one of which requires hydrological analysis. The accuracy of hydrological data is influenced by the method, operator/observer, and the performance of the measuring instrument. …”
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Online Estimation Method and Verification of Sampling Mass for Lunar Drilling in the Chang’E-6 Mission by Gao Zhang, Lei Guo, Weiwei Zhang, Shengyuan Jiang, Xiangjin Deng, Nai Zhang, Zongquan Deng

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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The primary goal is to address challenges in multiclass data preparation and evaluate the best machine learning models using both micro and macro accuracy metrics derived from baseline comparisons. …”
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Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete by Ala’a R. Al-Shamasneh, Arsalan Mahmoodzadeh, Faten Khalid Karim, Taoufik Saidani, Abdulaziz Alghamdi, Jasim Alnahas, Mohammed Sulaiman

“…Among the tested models, GPR consistently outperformed all others, achieving a maximum coefficient of determination (R²) of 0.93 and the lowest root mean square error (RMSE) of 16.54, thereby demonstrating superior capability in capturing the underlying nonlinear relationships within the data. …”
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A novel comprehensive metric balancing imaging dose and setup accuracy in image-guided radiotherapy: concept proposal and clinical validation by Jiang Liu, Xinhui Fu, Xinhui Fu, Zhiyao Luo, Chuou Yin, Qiao Li, Xigang Fan, Tian Li, Chen Lin, Shouping Xu, Yibao Zhang, Yibao Zhang

“…Using w1=w2 = 0.5 as an example, the smallest mean, standard deviation, and IQR of DAPw were observed on the 100 kV CBCT, indicating optimal balance between dose and accuracy than the other two methods. Analysis of variance (ANOVA) showed statistically significant differences in DAPw among the different imaging methods (P<0.01, F=50.57).ConclusionUsing registration consistency as a surrogate indicator of image quality, this study proposed and validated a novel “DAPw” parameter based on real patient data, providing a purpose-specific tool for balancing setup accuracy and radiation dose in clinic.…”
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LAYERED DEFENSE IN COMMUNICATION SYSTEMS: JOINT USE OF VPN PROTOCOLS AND LINEAR BLOCK CODES by Vladyslav Sharov, Olena Nikulina

“…In contrast, error correction codes—such as Hamming codes—are well-established tools for detecting and correcting random errors in physical channels, but they do not address intentional threats like interception, modification, or traffic analysis. …”
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CONSEQUENCES FOR HEALTH AFTER THE CHERNOBYL ACCIDENT: MAIN RESULTS AND UNSOLVED PROBLEMS by A. K. Gus’kova, V. I. Krasniuk

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Characteristics and risk factors for medical malpractice among obstetric and gynecologic physicians in China by Shuwen Zhang, Lei Li, Fangfang Wang, Hongyan Wang, Kan Wang, Xiaomin Zhang, Yang Cao, Congcong Ma, Guohong Li, Lan Zhu

“…Malpractice claims were categorized by the type of medical error. Univariate and multivariate analyses were conducted to assess associations between medical errors and personal, administrative, and professional factors. …”
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Data Mining of 24-Hour Cumulative Precipitation Data in Iran Using Machine Learning: Multilayer Perceptron Neural Network and Decision Tree by mozaffar faraji, Majid Rezaii Banafsheh Daragh, Behroz sarisarraf, Ali Mohammad Khorshid Dust

“…Research Topic: This study examines 24-hour cumulative precipitation data in Iran and predicts rainfall amounts over various time periods using data mining and machine learning. …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…XGBoost, a gradient descent-based tree algorithm, outperforms the commonly used Feedforward Neural Networks (FNN) in terms of training speed and resource utilization for binary-classifications, as well the performance criterion in ROC-AUC score (classification), Median Absolute Error (regression) and R2 value. Principal Component Analysis (PCA) effectively reduces the dimensionality of the data and overfitting, while retaining vital variances and significantly reducing noise. …”
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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

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A Historical Review of the Technology Used for the Study of Freshness in Red Meats by Julieta Nava-Granados, Maria T. Orvananos-Guerrero, Claudia N. Sanchez, Julieta Dominguez-Soberanes

“…In contrast, advanced non-destructive technologies—supported by data-driven analysis—offer efficient, accurate, and objective alternatives. …”
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A New 5-D Hyperchaotic System With a Line Equilibrium, Its Bifurcation Analysis, Circuit Simulation, FPGA Implementation, and Data Prediction Using Long-Term-Short Memory by Talal Bonny, Sundarapandian Vaidyanathan, Wafaa Al Nassan, Aceng Sambas, Fareh Hannachi, Maher Alrahhal, Chittineni Aruna

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Analysis of the health status of patients with type 1 and type 2 diabetes mellitus living in urban and rural areas of the Saratov region (according to the data of the federal regis... by A. D. Ponomarev, G. Yu. Sazanova, M. A. Kunitsyna, L. M. Terina, A. A. Vojteshak

“…The significance level was determined at t>2 and p<005. Data were presented as P ± m, where P is the relative value and m is its standard error, and M ± m, where M is the mean value and m is its standard error.RESULTS: A higher average life expectancy was noted for people with type 2 diabetes, regardless of place of residence, in comparison with the same indicator in the Saratov region. …”
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