Machine learning in modeling, analysis and control of electrochemical reactors: A tutorial review by Wenlong Wang, Zhe Wu, Dominic Peters, Berkay Citmaci, Carlos G. Morales-Guio, Panagiotis D. Christofides

“…The complexity of these systems – arising from coupled electrochemical reactions with mass, heat and charge transport phenomena – poses significant challenges in modeling, analysis, and control. Machine learning (ML) has emerged as a promising tool for addressing these challenges by providing data-driven solutions to complex process modeling, optimization, and advanced control. …”
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Exploring machine learning trends in poverty mapping: A review and meta-analysis by Badri Raj Lamichhane, Mahmud Isnan, Teerayut Horanont

“…This study provides a comprehensive review and meta-analysis of 215 peer-reviewed articles published on Scopus from 2014 to 2023, underscoring the capacity of ML methods to enhance poverty mapping through satellite data analysis. …”
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Leveraging deep learning and graph analysis for enhanced course recommendations in online education by Xinxin Chen, Xiaojing Wang, Ying Wang, Dan Liu, Wei Zhang

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Analysis of the Inquiry-Infusion learning model to develop students' critical thinking ability by Beni Asyhar

“…Analysis of the data used is content analysis. The results of this study were obtained: 1) the syntax of the inquiry-infusion learning model that modifies the inquiry learning model at the orientation stage and formulates the problem; 2) social system; 3) the principle of reaction; 4) support system; and 5) instructional impact and companion effect.…”
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Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis by Liang Xu, Jing Li, Wei Gong

“…In recent years, machine learning (ML) technology in the medical field has gained momentum, which utilize various algorithms to analyze input data, identify potential patterns and trends, develop predictive models, and generate high-precision predictions of unknown data, demonstrating its clinical potential in disease diagnosis. …”
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Barriers and facilitators to learning health systems in primary care: a framework analysis by Jeffrey Braithwaite, Kate Churruca, Louise A Ellis, Genevieve Dammery, Maree Saba, Georgia Fisher, Janani Mahadeva, Darran Foo, Simon Wilcock

“…This study aimed to describe the barriers and facilitators to achieving an LHS in primary care and provide practical recommendations for general practices on their journey towards an LHS.Methods This study is a secondary data analysis from a qualitative investigation of an LHS in a university-based general practice in Sydney, Australia. …”
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Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

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Prevalence and Pattern of Learning Disability in India: A Systematic Review and Meta-Analysis by Johny Kutty Joseph, Babitha K. Devu

“…Aim of the Review: This systematic review aimed to identify the prevalence and pattern of learning disability among children of India. Methods: This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and is also registered under PROSPERO vide CRD Number: CRD42021286224. …”
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COMPARATIVE ANALYSIS THE PERFORMANCE OF CLIENT-SIDE AND SERVER-SIDE MACHINE LEARNING TECHNOLOGIES by I. Mysiuk, Roman Shuvar

“…The performance analysis of client-side and server-side machine learning technologies is important for understanding the optimal way to model optimization. …”
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Applications and Trends of Machine Learning in Building Energy Optimization: A Bibliometric Analysis by Jingyi Liu, Jianfei Chen

“…First, this paper delves into the role of ML in building performance prediction, intelligent energy management, and sustainable design, with particular emphasis on how smart building systems leverage real-time data analysis and prediction to optimize energy usage and significantly reduce carbon emissions dynamically. …”
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Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models by Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

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Robust Brain Tumour Classification: Comparative Deep Learning Analysis with Ensemble Modelling by Verma Aditya, Wankhede Disha

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Evaluation of the relationship between spatial learning and image maintenance through isovist analysis by Sinem Kırkan, Mina Hazal Taşcı, Orkan Zeynel Güzelci

“…However, spatial learning in low-visibility areas cannot always be predicted using the ‘image maintenance’ method or the data obtained from ‘spatial cues’.…”

Needs Analysis to Design an English Blended Learning Program: Teachers’ and Administrators’ Voices by Luis Hernando Tamayo Cano, Andrés Felipe Riascos Gómez, Jorge Eduardo Pineda Hoyos

“…This needs analysis study sought to identify the contextual requirements to design and implement a blended learning program in English at a Colombian public university. …”
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A convolutional deep reinforcement learning architecture for an emerging stock market analysis by Anita Hadizadeh, Mohammad Jafar Tarokh, Majid Mirzaee Ghazani

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Integrating empirical analysis and deep learning for accurate monsoon prediction in Kerala, India by Yajnaseni Dash, Ajith Abraham

“…Thus, by integrating empirical data analysis with advanced deep learning techniques, this research offers a robust framework for predicting rainfall in Kerala, making a significant contribution to the field of climate informatics and providing practical benefits for the region's economy and environmental management.…”
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Comparative Analysis of Supervised Learning Techniques for Forecasting PV Current in South Africa by Ely Ondo Ekogha, Pius A. Owolawi

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Learning-Based Testing Using SAL (Symbolic Analysis Laboratory) Model Checker by Anjum Ara Shah, Muddassar Azam Sindhu

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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

“…This paper revolves around, the analysis of energy consumption of a Federated learning-based utility supervision architecture for Zero-Touch Networks, by comparing it to a Cloud-Fog architecture. …”
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Predictive analysis of Somalia’s economic indicators using advanced machine learning models by Bashir Mohamed Osman, Abdillahi Mohamoud Sheikh Muse

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