EXPLANATORY METHODS OF MARKETING DATA ANALYSIS – THEORETICAL AND METHODOLOGICAL CONSIDERATIONS by Rozalia GABOR

“…Explanatory methods of data analysis – also named by some authors supervised learning methods - enable researchers to identify and analyse configurations of relations between two or several variables, most of them with a high accuracy, as there is possibility of testing statistic significance by calculating the confidence level associated with validation of relation concerned across the entire population and not only the surveyed sample. …”
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Topological Data Analysis in Natural Language Processing -- A Tutorial by Wlodek Zadrozny

“…Within the last two decades, TDA has been mostly examined in unsupervised machine learning tasks. TDA has been often considered an alternative to the conventional algorithms due to its capability to deal with highdimensional data. in different tasks including but not limited to clustering, This tutorial will focus on applications of topological data analysis to text data.…”
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Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle by Jawoon Gu, Dongwoo Kim, Chulmin Jun, Seungwoo Son

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scikit-fda: A Python Package for Functional Data Analysis by Carlos Ramos-Carreño, José Luis Torrecilla, Miguel Carbajo-Berrocal, Pablo Marcos, Alberto Suárez

“… The library scikit-fda is a Python package for functional data analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. …”
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A Cloud-Based Intelligence System for Asian Rust Risk Analysis in Soybean Crops by Ricardo Alexandre Neves, Paulo Estevão Cruvinel

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Detecting hate in diversity: a survey of multilingual code-mixed image and video analysis by Hafiz Muhammad Raza Ur Rehman, Mahpara Saleem, Muhammad Zeeshan Jhandir, Eduardo Silva Alvarado, Helena Garay, Imran Ashraf

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Comparative analysis and application of rockburst prediction model based on secretary bird optimization algorithm by Tengjie Yang, Tengjie Yang, Xinqiang Gao, Xinqiang Gao, Lichuan Wang, Yongqing Xue, Haobo Fan, Zhengguo Zhu, Zhengguo Zhu, Jingbo Zhao, Beiyi Dong, Beiyi Dong

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DATA ANALYSIS OF COMMERCIAL AIRCRAFT LANDING ON THE RUNWAY AIRPORTS IN INDONESIA by Rossi PASSARELLA, Siti NURMAINI, Muhammad Naufal RACHMATULLAH, Osvari ARSALAN, Rizki KURNIATI, Aditya ADITYA, Indra Gifari AFRIANSYAH, Rifqi FATHAN, Rani Silvani YOUSNAIDI, Harumi VENY

“…The approach utilized in this study is exploratory data analysis (EDA), in which we explored the dataset to find trusted data (128 tier-1 data points). …”
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Optimized Machine Learning-Augmented Hybrid Empirical Models for AlGaN/GaN HEMTs: A Comprehensive Analysis by Ahmad Khusro, Saddam Husain, Mohammad Hashmi

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ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYSIS IN CRIME PREVENTION AND COMBAT by George-Marius ȚICAL

“…Machine learning algorithms, neural networks, and natural language processing enable the rapid analysis of unstructured data, enhancing the ability to predict and prevent crimes. …”
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Analysis of selected methods of person identification based on biometric data by Marcin Rudzki, Paweł Powroźnik

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Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis by Andres Emilio Hurtado-Perez, Manuel Toledano-Ayala, Irving A. Cruz-Albarran, Alejandra Lopez-Zúñiga, Jesús Adrián Moreno-Perez, Alejandra Álvarez-López, Juvenal Rodriguez-Resendiz, Carlos A. Perez-Ramirez

“…The role of advanced processing techniques, including filtering and transformation methods, and the increasing integration of artificial intelligence (AI) and machine learning (ML) for data classification is also discussed. …”
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Exploratory and Exploitative Innovation Performance in the Artificial Intelligence Industry in China from the Perspective of a Collaboration Network: A Data-Driven Analysis by Liping Zhang, Hailin Li, Wenhao Zhou, Hanhui Qiu, Yenchun Jim Wu

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Leveraging Machine Learning to Forecast Neighborhood Energy Use in Early Design Stages: A Preliminary Application by Andrea Giuseppe di Stefano, Matteo Ruta, Gabriele Masera, Simi Hoque

“…This study identifies three key phases in a design process framework where machine learning can be applied to optimize energy consumption in early design stages. …”
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ChatAnalysis revisited: can ChatGPT undermine privacy in smart homes with data analysis? by Jüttner Victor, Fleig Arthur, Buchmann Erik

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BioBricks.ai: a versioned data registry for life sciences data assets by Yifan Gao, Zakariyya Mughal, Jose A. Jaramillo-Villegas, Jose A. Jaramillo-Villegas, Marie Corradi, Alexandre Borrel, Ben Lieberman, Suliman Sharif, John Shaffer, Karamarie Fecho, Karamarie Fecho, Ajay Chatrath, Alexandra Maertens, Marc A. T. Teunis, Nicole Kleinstreuer, Thomas Hartung, Thomas Hartung, Thomas Luechtefeld, Thomas Luechtefeld

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META-ANALYSIS THE EFFECT OF STEM INTEGRATED PROBLEM BASED LEARNING MODEL ON SCIENCE LEARNING OUTCOMES by Media Roza, Lufri Lufri, Asrizal Asrizal

“…The goal of the research is to analyze the impact of Science,   Technology, Engineering, and Mathematics (STEM) integrated Problem Based Learning methods on science learning. Research methods use meta-analysis. …”
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Learning in digital era: Analysis of civic education learning materials for students in junior high school by Lathifah Sandra Devi, Triana Rejekiningsih, Rusnaini Rusnaini

“…This study aims to find out obtain the results of analysis learning materials Civic education in junior high school at digital era. …”
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Analysis of Student Learning Interests Based on Peer Learning Interests According to Crowds Behavior Theory by Izza Luthfia, Basori Basori, Kurniasari Kurniasari

“…While the interview instrument employed multiple question items that were submitted to the informant, the class teacher, the observation instrument used an observation sheet with several statement items. The data analysis results indicate that students' learning interests are significantly influenced by their peers' learning interests. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

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