A Vision-Based Procedure with Subpixel Resolution for Motion Estimation by Samira Azizi, Kaveh Karami, Stefano Mariani

“…By employing Complexity Pursuit, a blind source separation method for output-only modal analysis, structural mode shapes and vibration frequencies are finally extracted from video data. …”
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Boundary-Aware Transformer for Optic Cup and Disc Segmentation in Fundus Images by Soohyun Wang, Byoungkug Kim, Doo-Seop Eom

“…We enhance data diversity while preserving vascular and tissue structures through truncated Gaussian-based sampling and colormap transformations. …”
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Analysis of retirees' knowledge return in the supply chain of Isfahan Refinery with a combined approach of interpretive structural modeling and structural equation modeling by Mehran Ziaeian, Somayeh Ahmadzadeh, Abdolrasoul Yazdi

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Diverse Counterfactual Explanations (DiCE) Role in Improving Sales and e-Commerce Strategies by Simona-Vasilica Oprea, Adela Bâra

“…Traditional pricing models rely on historical data and statistical methods but often lack interpretability and adaptability. …”
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Machine learning-based estimation of crude oil-nitrogen interfacial tension by Safia Obaidur Rab, Subhash Chandra, Abhinav Kumar, Pinank Patel, Mohammed Al-Farouni, Soumya V. Menon, Bandar R. Alsehli, Mamata Chahar, Manmeet Singh, Mahmood Kiani

“…In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil – nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs. …”
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Prediction of Remaining Useful Life of Packing Sets in a Plunger-Type High-Pressure Compressor Based on the PCA/SVD Analysis and NN Model by Jin-Wei Liang, Shyh-Chin Huang, Chun-Ling Lin

“…The results showed that the maximum prediction RUL error of the model is less than 15 days, and an averaged prediction RUL error is 7.23 days for 13 run-to-failure events. …”
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Design and Analysis of a Sowing Depth Detection and Control Device for a Wheat Row Planter Based on Fuzzy PID and Multi-Sensor Fusion by Yueyue Li, Bing Qi, Encai Bao, Zhong Tang, Yi Lian, Meiyan Sun

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Effects of Coverage Area Treatment, Spatial Analysis Unit, and Regression Model on the Results of Station-Level Demand Modeling of Urban Rail Transit by Hongtai Yang, Chaojing Li, Xuan Li, Jinghai Huo, Yi Wen, Emma G. P. Sexton, Yugang Liu

“…The influence of different basic spatial analysis unit on the model results is marginal. Therefore, the selection of basic area unit can use existing data. …”
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Seismic Attribute Extraction and Application Based on the Gabor Wavelet Transform by Ran Xiong, Xuri Huang, Liang Guo, Xuan Zou, Haonan Tian

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A Novel Model for Accurate Daily Urban Gas Load Prediction Using Genetic Algorithms by Xi Chen, Feng Wang, Li Xu, Taiwu Xia, Minhao Wang, Gangping Chen, Longyu Chen, Jun Zhou

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Prediction of Milk Yield and Lactation Curve of Dairy Cows: A Comparative Analysis of Three Mathematical Models in Tropical Smallholder Dairy Farm by Aswah Ridhowi, Trianti Djoharjani, Sucik Maylinda

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Application of Three-Dimensional Hierarchical Density-Based Spatial Clustering of Applications with Noise in Ship Automatic Identification System Trajectory-Cluster Analysis by Shih-Ming Wang, Wen-Rong Yang, Qian-Yi Zhuang, Wei-Hong Lin, Mau-Yi Tian, Te-Jen Su, Jui-Chuan Cheng

“…Clustering algorithms are widely used in statistical data analysis as a form of unsupervised machine learning, playing a crucial role in big data mining research for Maritime Intelligent Transportation Systems. …”
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SEISMIC PICTURE OF A FAULT ZONE. WHAT CAN BE GAINED FROM THE ANALYSIS OF FINE PATTERNS OF SPATIAL DISTRIBUTION OF WEAK EARTHQUAKE CENTERS? by Gevorg G. Kocharyan, Svetlana B. Kishkina, Aleksey A. Ostapchuk

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Refractive outcomes after intravitreal injection of antivascular endothelial growth factor versus laser photocoagulation for retinopathy of prematurity: a meta-analysis by Wai-kit Ming, Qihang Kong, Xue-Song Mi

“…Objective To determine the effects of the intraocular injection of antivascular endothelial growth factor (anti-VEGF) drugs on the refractive status of infants with retinopathy of prematurity (ROP).Design Systematic review and meta-analysis of the refractive status of infants with ROP who receive anti-VEGF drugs.Data sources The PubMed, Web of Science and Embase databases and the ClinicalTrials.gov website were searched up to June 2020.Eligibility criteria when selecting studies We included randomised controlled trials (RCTs) and observational studies that compared refractive errors between anti-VEGF drug and laser therapies.Data extraction and synthesis Data extraction and risk-of-bias assessments were conducted by two independent reviewers. …”
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Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning by Sangwoo Park, Osvaldo Simeone

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Monitoring and Prediction of the Real-Time Transient Thermal Mechanical Behaviors of a Motorized Spindle Tool by Tria Mariz Arief, Wei-Zhu Lin, Jui-Pin Hung, Muhamad Aditya Royandi, Yu-Jhang Chen

“…Multivariate regression analysis was then applied to identify optimal combinations of sensor data for accurate deformation prediction. …”
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Aerodynamic Drag Coefficient Analysis of Heavy-Duty Vehicle Platoons: A Hybrid Approach Integrating Wind Tunnel Experiments and CFD Simulations by Xiao Liang, Xiaohui Gao, Tianjiao Gu, Xudong Jia

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A Wearable Internet of Things-Based Device for the Quantitative Assessment of Hand Tremors in Parkinson’s Disease: The ELENA Project by Yessica Saez, Cristian Ureña, Julia Valenzuela, Antony García, Edwin Collado

“…Named in honor of a 67-year-old woman who has lived with Parkinson’s since 2011 and inspired the project, the ELENA system integrates an MPU6050 accelerometer, an ESP32 microcontroller, and cloud-based data analysis and MATLAB. The ELENA system was calibrated and validated against an Apple Watch, demonstrating high accuracy with frequency deviations under 0.5% and an average percentage error of −0.37%. …”
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Extraction of Clinically Relevant Temporal Gait Parameters from IMU Sensors Mimicking the Use of Smartphones by Aske G. Larsen, Line Ø. Sadolin, Trine R. Thomsen, Anderson S. Oliveira

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LiMMCov: An interactive research tool for efficiently selecting covariance structures in linear mixed models using insights from time series analysis. by Perseverence Savieri, Lara Stas, Kurt Barbé

“…The correct specification of covariance structures in linear mixed models (LMMs) is critical for accurate longitudinal data analysis. These data, characterised by repeated measurements on subjects over time, demand careful handling of inherent correlations to avoid biased estimates and invalid inferences. …”
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