Class Balancing for Soil Data: Predictive Modeling Approach for Crop Recommendation Using Machine Learning Algorithms by Sapkal Kranti G., Kadam Avinash B.

“…Traditional soil analysis methods often require extensive labor and time, prompting the need for more efficient and accurate techniques. This research investigates the potential of machine learning algorithms in transforming soil data analysis. …”
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A Data-Driven Monitoring System for a Prescriptive Maintenance Approach: Supporting Reinforcement Learning Strategies by Joaquín Ordieres-Meré, Antonio Sánchez-Herguedas, Ángel Mena-Nieto

“…The aim of this study was to evaluate machine learning algorithms’ capacity to improve prescriptive maintenance. …”
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A Tailored Compliance Solution for Securing Personal Data privacy under Law 18-07 in Algeria by Mohamed kamel Benkaddour, Redouane Guettal, Ph.D

“…The rapid flow of information and the ubiquity of technology pose significant challenges to data security and privacy. In response to these concerns, the Algerian state enacted Law 18-07 on June 10, 2018, aimed at protecting individuals concerning the processing of their data. …”
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Misrepresentation of Overall and By-Gender Mortality Causes in Film Using Online, Crowd-Sourced Data: Quantitative Analysis by Calla Glavin Beauregard, Christopher M Danforth, Peter Sheridan Dodds

“…MethodsUsing crowd-sourced data on over 68,000 film deaths from Cinemorgue Wiki, we employ natural language processing techniques to analyze shifts in representation of deaths in movies versus the 2021 National Vital Statistics Survey top 10 mortality causes. …”
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Predicting Accident Severity on Taiwan Highways Using Machine Learning and Electronic Toll Collection (ETC) Data by Pei-Chun Lin, Kuan-Yen Chen, Jenhung Wang

“…This study aims to develop a machine learning-based framework for predicting the severity of highway traffic accidents by leveraging high-resolution data from Taiwan’s Electronic Toll Collection (ETC) system. …”
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Big Data Insights into Coastal Tourism: Analyzing Customer Satisfaction at Egyptian Red Sea Dive Resorts by Yinai Zhong, Angellie Williady, Narariya Dita Handani, Hak-Seon Kim

“…This research aims to explore the relationship between customer satisfaction and various extracted factors at dive resorts in the Red Sea, Egypt, utilizing a hybrid methodology of descriptive and diagnostic analytics applied to online review data. …”
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Predicting Alzheimer's Disease onset: A machine learning framework for early diagnosis using biomarker data by Shehu Mohammed, Neha Malhotra

“…The main goal is to combine multiple biomarkers: neuroimaging, CSF, genetic, and longitudinal cognitive data and develop a robust model for accurate early AD diagnosis. …”
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Exploring home-based reminder systems for daily routine support: usability, data insights, and future directions by Alyssia A. Sanchez, Joy Lai, Alexander Tighe, Alex Mihailidis

“…Data-driven techniques, including predictive modeling and anomaly detection, were applied to explore opportunities for optimizing reminder timing and identifying unusual usage patterns. …”
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Kriminalisasi Deepfake Di Indonesia Sebagai Bentuk Pelindungan Negara by Chiquita Thefirstly Noerman, Aji Lukman Ibrahim

“…The author uses descriptive data analysis techniques by presenting data and information as an overview of the subject and object of research that is arranged systematically so that it can be understood. …”
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? by Nouf Alturayeif, Jameleddine Hassine

“…In this article, we aim to explore ML-based approaches for limited annotated datasets to detect code-level data leakage in ML code. …”
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Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties by Fredi Alegría, Eladio Martínez, Claudia Cortés-García, Quirino Estrada, Andrés Blanco-Ortega, Mario Ponce-Silva

“…This study introduces an innovative computational method aimed at minimizing data requirements, reducing instrumentation costs, and functioning with fewer vibration modes. …”
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An Interpretable Machine Learning Framework for Analyzing the Interaction Between Cardiorespiratory Diseases and Meteo-Pollutant Sensor Data by Vito Telesca, Maríca Rondinone

“…The aim of this study is the development and verification of an interpretable machine learning framework applied to environmental and health data to assess the relationship between environmental factors and daily emergency room admissions for cardiorespiratory diseases. …”
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Privacy-Preserving Poisoning-Resistant Blockchain-Based Federated Learning for Data Sharing in the Internet of Medical Things by Xudong Zhu, Hui Li

“…However, the private nature of medical data, coupled with strict compliance requirements, has resulted in the separation of information repositories in the IoMT network, severely hindering protected inter-domain data cooperation. …”
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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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Qualitative and quantitative interpretations of high-resolution aeromagnetic data of Saki-East area, for basement and structural framework by E. O. Adeniyi, L. A. Sunmonu, Olagoke Peter Oladejo, Charles Olubunmi ogunkoya, O. M. Adedokun, K. N. Alao

“…This research work is aimed at qualitatively and quantitatively interpret high resolution aeromagnetic data of Saki-East area to provide basement and structural framework of the study area. …”
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Artificial Intelligence Algorithms in Asthma Management: A Review of Data Engineering, Predictive Models, and Future Implications by Shayma Alkobaisi, Muhammad Farhan Safdar, Piotr Pałka, Najah Abed Abu Ali

“…Additionally, the integration of multi-modal data through advanced pre-processing and feature selection techniques has emerged as a critical innovation in developing more effective and robust models. …”
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Multi-Mode Face-to-Face and Telephone Approach to Data Collection in Health Surveys: A Scoping Review by Paulo Henrique Guerra, Letícia Aparecida Calderão Sposito, Daniel Umpierre, Alex Antonio Florindo

“…<b>Background/Objectives</b>: The present study aims to identify information from health research studies that have used a mixed-methods data collection approach, considering the combination of face-to-face and telephone interviews (referred to as the MMFT approach), specifically focusing on identifying themes, objectives, designs, populations involved, and implementation processes. …”
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Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining by Dilara Gerdan, Abdullah Beyaz, Mustafa Vatandaş

“…For this aim the colour change of the damaged pears were determined, in another term, colour change value from red to green and yellow to blue at the damaged pears were determined with lightness values by using image analysis technique and analysed with data mining methods. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Educational Data Mining, leveraging machine learning and data mining techniques, aims to predict student performance using available datasets. …”
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Revolutionizing Nursing and Midwifery Informatics Curriculum Evaluation in Ghana: A Data-Driven Machine Learning Approach by Iven Aabaah, Japheth Kodua Wiredu, Bakaweri Emmanuel Batowise, Nelson Abuba Seidu

“…Data was gathered from 1,500 students across C.K. …”
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