A Machine Learning-Based Platform for Monitoring and Prediction of Hazardous Gases in Rural and Remote Areas by Edgar F. Ladeira, Bruno M. C. Silva

“…Without means to monitor or predict, healthcare and government stakeholders typically act too late when indoor incidents occur. Hence, this paper presents a digital decision support system that uses Machine Learning (ML) for monitoring and prediction of incidents related with indoor hazardous gases. …”
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Machine Learning and IoT-Based Solutions in Industrial Applications for Smart Manufacturing: A Critical Review by Paolo Visconti, Giuseppe Rausa, Carolina Del-Valle-Soto, Ramiro Velázquez, Donato Cafagna, Roberto De Fazio

“…In addition, the paper presents a descriptive and comparative overview of ML algorithms mainly used in smart manufacturing. …”
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Comparative Analysis of Reinforcement Learning Approaches for Multi-Objective Optimization in Residential Hybrid Energy Systems by Yang Xu, Yanxue Li, Weijun Gao

“…However, including highly permeable intermittent renewables and energy storage presents significant challenges for traditional home energy management systems (HEMSs). …”
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Comparative Analysis of Hybrid Deep Learning Models for Electricity Load Forecasting During Extreme Weather by Altan Unlu, Malaquias Peña

“…Extreme weather events present some of the most severe natural threats to the electric grid, and accurate load forecasting during those events is essential for grid management and disaster preparedness. …”
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Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search. by Jamil Ahmad, Khan Muhammad, Sung Wook Baik

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Toward Improving Human Training by Combining Wearable Full-Body IoT Sensors and Machine Learning by Nazia Akter, Andreea Molnar, Dimitrios Georgakopoulos

“…The framework incorporates novel work activity recognition using generative adversarial network (GAN) and machine learning (ML) models for recognising the types and sequences of work activities by analysing an individual’s kinematic model. …”
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A Transformer-Based Multi-Scale Deep Learning Model for Lung Cancer Surgery Optimization by Pengfei Zhu, Tingmin Wang, Fan Yang, Meng Wang, Yunjie Zhang

“…This study presents a Transformer-based multi-scale deep learning framework that integrates imaging, clinical, and genomic data to optimize decision-making surrounding surgery. …”
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The future is inclusive: An invitation for interdisciplinary collaboration between social emotional learning and special education researchers by Kristabel Stark, Jessica B. Koslouski, Julie Vadhan, Madison Vega

“…Then, to catalyze our vision for increased collaboration, we present four assertions about inclusion that we believe are foundational to future, collaborative efforts toward more inclusive schools and educational systems. …”
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Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration by Hao Zou, Haochen Zhao, Mingming Lu, Jiong Wang, Zeyu Deng, Jianxin Wang

“…Abstract Machine learning offers a promising avenue for expediting the discovery of new compounds by accurately predicting their thermodynamic stability. …”
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SELF-CONTROL FORMATION TECHNOLOGY FOR PRIMARY SCHOOL CHILDREN WITH MILD MENTAL RETARDATION IN LEARNING PROCESS by Vera A. Galkina

“…The developed technology allows qualitative enhancement of learning activities for primary school children with mild mental retardation. …”
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Motor learning processes: an electrophysiologic perspective Processos de aprendizagem motora: uma perspectiva eletrofisiológica by Bruna Velasques, Camila Ferreira, Silmar Silva Teixeira, Vernon Furtado, Elizabeth Mendes, Luis Basile, Mauricio Cagy, Roberto Piedade, Pedro Ribeiro

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Do Machine Learning and Business Analytics Approaches Answer the Question of ‘Will Your Kickstarter Project be Successful? by Murat Kılınç, Can Aydın, Çiğdem Tarhan

“…Thus, Kickstarter users will be able to see their shortcomings and have a prediction about success before presenting their projects to their backers.…”
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OPTIMIZATION AND MODELING OF E-LEARNING SYSTEM THROUGH PLATFORMS IBM WEBSPHERE BUSINESS MODELER AND ANYLOGIC by Anna Yu. Orlova, Alexander A. Sorokin

“…The article offers a view on the issues related to modeling the performance of the system e-learning employing the platforms IBM WebSphere Business Modeler and AnyLogic, as well as presents optimization of the system’s performance, which resulted in server relief leading to a decrease in the request loss.…”
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INTEGRATED INFORMATION LEARNING ENVIRONMENT AS A MEANS OF DEVELOPING FOREIGN LANGUAGE COMMUNICATIVE COMPETENCE OF THE LEARNERS by Svetlana U. Rzheutskaya, Marina V. Kharina

“…The article presents the architecture of integrated information environment for training of students of technical training areas, the proposed models and technologies of development of foreign language communicative competence of the learners in this environment, discusses the results of an experimental individualized learning a foreign language in close connection with other disciplines of engineering.…”
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A Bayesian inversion supervised learning framework for the enzyme activity in graphene field-effect transistors by Ehsan Khodadadian, Samaneh Mirsian, Shahrzad Shashaani, Maryam Parvizi, Amirreza Khodadadian, Peter Knees, Wolfgang Hilber, Clemens Heitzinger

“…We present a pseudocode to explain the implementation of machine learning Bayesian inversion framework.…”
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Machine learning-based mathematical equations for dengue positivity detection using elementary laboratory parameters by Shirin Dasgupta, Shuvankar Das, Debarghya Chakraborty

“…In addition, two predictive mathematical equations are presented to detect dengue positivity for each ML model.…”
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Future Smart Grids Control and Optimization: A Reinforcement Learning Tool for Optimal Operation Planning by Federico Rossi, Giancarlo Storti Gajani, Samuele Grillo, Giambattista Gruosso

“…AI methods offer powerful tools for planning electrical systems, including electrical distribution networks. This study presents a methodology based on reinforcement learning (RL) for evaluating optimal power flow with respect to various cost functions. …”
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Deep Learning for Ore Haulage Monitoring: Vibrational Analysis Using a VGG16 Network by Artur Skoczylas, Pawel Stefaniak, Sergii Anufriiev, Wioletta Koperska

“…The findings indicate that leveraging IMU sensor data through machine learning techniques presents a significant advancement in the field of ore haulage cycle detection, ultimately benefiting the mining industry by enhancing efficiency and reducing operational costs.…”
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Strategies for Reducing the Communication and Computation Costs in Cross-Silo Federated Learning: A Comprehensive Review by Vineetha Pais, Santhosha Rao, Balachandra Muniyal

“…Federated learning is an innovative approach that allows collaboration across distributed clients while maintaining data privacy. …”
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Efficient Visual-Aware Fashion Recommendation Using Compressed Node Features and Graph-Based Learning by Umar Subhan Malhi, Junfeng Zhou, Abdur Rasool, Shahbaz Siddeeq

“…Current recommendation systems often struggle to incorporate high-dimensional visual data into graph-based learning models effectively. This limitation presents a substantial opportunity to enhance the precision and effectiveness of fashion recommendations. …”
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