A novel asymmetric form of the power half-logistic distribution with statistical inference and real data analysis by Amal S. Hassan, Najwan Alsadat, Mohammed Elgarhy, Laxmi Prasad Sapkota, Oluwafemi Samson Balogun, Ahmed M. Gemeay

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Copula-Based Reliability Analysis of Vehicles Based on Censored Failures Data Using Reliability Importance Measures by Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski

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Three-dimensional atomic-scale characterization of titanium oxyhydroxide nanoparticles by data-driven lattice correlation analysis by Kohei Aso, Koichi Higashimine, Masanobu Miyata, Hiroshi Kamio, Yoshifumi Oshima

“…However, characterizing the atomic-scale structures of the metal oxyhydroxides has still been challenging due to their diverse structural types, nanometer-scale sizes, and beam sensitivity. Here, we developed a data-driven analysis approach for atom-resolved transmission electron microscopy images of titanium oxyhydroxide (metatitanic acid) nanoparticles. …”
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3-Dimensional Spatial Analysis of Parking Lot Wall Scratch Using Mobile Point Cloud Data by Y. Li, C. Ye, Y. Zhang, Z. Kang

“…A novel approach integrating YOLOv10 object detection and PTv3 point cloud processing algorithms is developed to detect and localize scratches, while spatial analysis evaluates design factors affecting scratch distribution. …”
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Data-driven thermal safety threshold analysis of friction component based on macro-micro interaction model by Jianpeng Wu, Ao Ding, Chengbing Yang, Hanshu Zhang, Liyong Wang, Heyan Li

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Optimized aspect level sentiment analysis of tweet data using deep learning and rule-based techniques by S. N. Enemuo, O. N. Akande, M. O. Lawrence, I. C. Saidu

“…Towards coming up with a localized sentiment analysis system, this research explored the use of rules and optimized Convolutional Neural Network (CNN) Deep Learning (DL) technique for aspect-level sentiment analysis of users’ tweets. …”
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Predictive exploratory data analysis of shopfloor CNC machine operation through a machine learning model by Tarique Ameer, Omid Fatahi Valilai

“…The research explores the capabilities of exploratory data analysis in the manufacturing shop floor at the machine level. …”
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CircPac: A web-based analysis toolset for exploring circular RNA dataGitHub by Amir Hossein Foroutan, Sadra Salehi-Mazandarani, Maryam Lotfi-Shahreza, Parvaneh Nikpour

“…However, a comprehensive analysis tool for analyzing circRNA data is still required. …”
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Topological Data Analysis and Wavelet- Unsupervised Machine Learning Approaches to Identifying the Flooding and Non-Flooding Zones by Md Raqibul Hasan, Md. Jamal Hossain, Md. Waliullah, Abdul Hannan, Md. Mijanoor Rahman

“…The intertwined weather patterns known as the atmospheric river (AR) of Bangladesh make use of topological data analysis (TDA) in connection with wavelet decomposition and unsupervised machine learning (k-means clustering) methods to pave the way for enhanced flood detection. …”
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A meta fusion model combining geographic data and twitter sentiment analysis for predicting accident severity by Areeba Naseem Khan, Yaser Ali Shah, Wasiat Khan, Amaad Khalil, Jebran Khan

“…Building on these developments, this study introduces an innovative approach ConvoseqNet to improve traffic accident prediction by integrating traditional traffic data with real-time social media insights, specifically using geographic data and Twitter sentiment analysis. …”
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Phenolic content discrimination in Thai holy basil using hyperspectral data analysis and machine learning techniques. by Apichat Suratanee, Panita Chutimanukul, Tanapon Saelao, Supachitra Chadchawan, Teerapong Buaboocha, Kitiporn Plaimas

“…The neural network model demonstrated high performance, achieving an area under the receiver operating characteristic curve of 0.8113, highlighting its effectiveness in predicting phenolic content levels based on the spectral data. Comparative analysis with other machine learning techniques confirmed the superior performance of the neural network approach. …”
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Therapies for Advanced Parkinson’s Disease in Sweden: A Cost-Effectiveness Analysis Using Real-World Data by Dag Nyholm, Simon Eggington, Astrid Holm

“…This study sought to use this real-world evidence to determine the cost-effectiveness profile of specific DATs in Sweden. Methods We developed a state transition (Markov) model to represent disease progression over time and used published clinical data to represent short- and long-term disease outcomes. …”
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Design of an Efficient Model for Psychological Disease Analysis and Prediction Using Machine Learning and Genomic Data Samples by Alparthi Kumuda, Saroj Kumar Panigrahy

“…Therefore, this study developed the Psychological Disorders Machine Learning Genomic (PDMLG) model as an amalgamation of genetic algorithms and machine learning techniques in a predictive analysis model using genomic data samples. …”
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Transforming Systematic Literature Synthesis into Meta-Data Analysis: The Impact of Lean Six Sigma in the Healthcare Sector by James KOMALING, Octavia D. M. TUEGEH, Fitty Valdi ARIE, Johan R. TUMIWA

“…Through co-occurrence analysis and keyword correlation, the research develops robust indicators for each construct and proposes a data-driven path model for future quantitative analysis using PLS-SEM. …”
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Two Novel Multidimensional Data Analysis Approaches Using InSAR Products for Landslide Prone Areas by Hamit Beran Gunce, Bekir Taner San

“…Multi-temporal InSAR analysis of Sentinel-1 data (2015–2020) is performed using LiCSAR–LiCSBAS, followed by two novel approaches: multi-dimensional InSAR research and analysis (MIRA) and Crosta’s InSAR application (InCROSS). …”
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Comprehensive analysis of coastal flood susceptibility, drought severity, and crop water stress using data fusion by Hyeong-Joo Kim, Mahfuzur Rahman, Zulfiqar Hammad, Hyeong-Soo Kim, Seok-Jae Lee, Tae-Eon Kim, So-Hyi Jung

“…This study examines environmental susceptibilities in coastal regions by integrating geospatial indices to evaluate flood susceptibility, drought severity, and crop water stress. A data fusion framework was developed using the composite coastal flood susceptibility index (CCFSI), composite drought index (CDI), and crop water stress index (CWSI), validated against 70 ground truth points. …”
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Defining health and lifestyle characteristics of the age 50+ population: cluster analysis of data from the PROTECT study by Emily Kontaris, Ian Wakeling, Helen Brooker, Anne Corbett, Clive Ballard, Dag Aarsland, Anne Churchill

“…Chronological age is typically used to segment older consumers however, given the diversity of ageing, a multi-dimensional approach considering other factors contributing to this behavior change is important. Using data from the PROTECT study in the UK, this research aimed to identify clusters of older people with distinct characteristics and investigate whether chronological age was fundamental in defining these groups.MethodsTwelve variables, covering measures related to physical capabilities, mental health and lifestyle choices, were derived from the baseline questionnaire data from the PROTECT study and subjected to a k-means cluster analysis. …”
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Denoising Diffusion Probabilistic Model for Realistic and Fast Generated Euclid-like Data for Weak Lensing Analysis by Diana Scognamiglio, Jake H. Lee, Eric Huff, Sergi R. Hildebrandt, Shoubaneh Hemmati

“…Understanding and mitigating measurement systematics in weak lensing (WL) analysis requires large data sets of realistic galaxies with diverse morphologies and colors. …”
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Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data by Xue Qin Yu, David Goldsbury, Sarsha Yap, Mei Ling Yap, Dianne L O'Connell

“…Introduction Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only limited relevant data are generally available. …”
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Leveraging Cross-Project Similarity for Data Augmentation and Security Bug Report Prediction by Jinfeng Ji, Geunseok Yang

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