Semi-Supervised Machine Learning for Fault Detection and Diagnosis of a Rooftop Unit by Mohammed G. Albayati, Jalal Faraj, Amy Thompson, Prathamesh Patil, Ravi Gorthala, Sanguthevar Rajasekaran

“…This is mainly because the building owners do not previously have good tools to detect and diagnose these faults, determine their impact, and act on findings. …”
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Employing Data Mining Techniques and Machine Learning Models in Classification of Students’ Academic Performance. by Hussein, Alkattan, Alhumaima, Ali Subhi, Oluwaseun, Adelaja A., Abotaleb, Mostafa, Mijwil, Maad M., Pradeep, Mishra, Sekiwu, Denis, Bamwerinde, Wilson, Turyasingura, Benson

“…The research indicates that the use of machine learning models and data mining methods can reveal hidden patterns and relationships in big data, making them indispensable tools in the field of education analysis. …”
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A Machine Learning Approach to Adapt Local Land Use Planning to Climate Change by Julia Forster, Stefan Bindreiter, Birthe Uhlhorn, Verena Radinger-Peer, Alexandra Jiricka-Pürrer

“…Ex-ante evaluation of planning measures is insufficient owing to a lack of data and linear models capable of simulating the impacts of complex systemic relationships. Integrating machine learning (ML) into systemic planning increases awareness of impacts by providing decision-makers with predictive analysis and risk mitigation tools. …”
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Risk prediction tools for pressure injury occurrence: an umbrella review of systematic reviews reporting model development and validation methods by Bethany Hillier, Katie Scandrett, April Coombe, Tina Hernandez-Boussard, Ewout Steyerberg, Yemisi Takwoingi, Vladica Velickovic, Jacqueline Dinnes

“…All included reviews contributed to building a comprehensive list of risk prediction tools. …”
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Machine Learning Classification Techniques for Detecting the Impact of Human Resources Outcomes on Commercial Banks Performance by Sulaiman O. Atiku, Ibidun C. Obagbuwa

“…In this study, eight different machine learning algorithms were employed to build performance models to predict the prospective performance of commercial banks in Nigeria based on human resources outcomes (employee skills, attitude, and behavior) through the Python software tool with machine learning libraries and packages. …”
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Small- to Large-Scale Electron Beam Powder Bed Fusion of Functionally Graded Steels by Carlos Botero, William Sjöström, Emilio Jimenez-Pique, Andrey Koptyug, Lars-Erik Rännar

“…In this way, two pre-alloyed powders—a stainless steel (SS) powder and a highly alloyed cold work tool steel (TS) powder—were combined during processing in an S20 Arcam machine. …”
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An investigative study on the parameters optimization of the electric discharge machining of Ti6Al4V by Muhammad Mansoor Uz Zaman Siddiqui, Syed Amir Iqbal, Ali Zulqarnain, Adeel Tabassum

“…This investigative study explored the field of electrical discharge machining (EDM), with a particular focus on the machining of Ti6Al4V, a titanium alloy that finds widespread application in aerospace, airframes, engine components, and non-aerospace applications such as power generation and marine and offshore environments. …”
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Komparasi Machine Learning Berbasis Pso Untuk Prediksi Tingkat Keberhasilan Belajar Berbasis E-Learning by Elin Panca Saputra, Siti Nurajizah, Mawadatul Maulidah, Nadiyah Hidayati, Taufik Rahman

“…Support Vector Machine (SVM) with PSO. While the attributes that have an influence to determine the algorithm on the level of accuracy are Practice Questions, Quizzes, Mid-Semester Exams, and Final Exams. it is evident from our previous studies that the PSO-based neural network algorithm does have a very good advantage. based on ANN is a method that has calculations that build several units of interconnected connectivity, the ANN method with predictive accuracy can be an efficient and good tool for forecasting and classification research in the field of education. …”
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Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…The data was pre-processed, and 80% and 20% of the observations were used for training, and testing the model, respectively. Eight machine learning algorithms were included for consideration of model building and comparison. …”
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Specificity of the operator’s activity performing the work with the forecasting tools of technologically and chronologically interconnected events in the system of continuous forec... by V. V. Savluchinskij

“…Creation of an automated continuous forecasting system based on tracking information flows requires the development of a number of algorithms and machine programs to build a model of the forecast object based on the obtained identification features, to optimize a branched technologically and chronologically interconnected network of hierarchically coordinated events with an example of the work of the operator performing the work with the prediction tool in the system continuous forecasting and tracking information E flows.…”
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Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study by Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan, Laure Abensur Vuillaume

“…Aim The main objective of this study was to build and test a prediction tool for ED admissions using artificial intelligence. …”
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Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning by Jingjing Pan, Tao Guo, Haobo Kong, Wei Bu, Min Shao, Zhi Geng

“…Variables were screened using the Recursive Feature Elimination method. Five machine learning algorithms were used to build predictive models. …”
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POSSIBILITY OF APPLICATION OF SODIUM SILICATE IN MOULDING AND CORE SAND MIXTURES IN ART CASTING by S. S. Tkachenko, V. S. Krivitskiy, V. O. Yemelyanov, K V. Martynov

“…The possibilities of application of sodium silicate and phosphate binder for production of large forms and cores in machine-tool industry are considered in the article.…”
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Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress) by Ryan M. McGranaghan, Jack Ziegler, Téo Bloch, Spencer Hatch, Enrico Camporeale, Kristina Lynch, Mathew Owens, Jesper Gjerloev, Binzheng Zhang, Susan Skone

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Adaptability of the Cutter-Head of the Earth Pressure Balance (EPB) Shield Machine in Water-Rich Sandy and Cobble Strata: A Case Study by Chaodong Wan, Zhiyi Jin

“…The effect of increasing the central opening of the cutter-head is that large cobbles and boulders can be discharged through the central opening when they cannot be discharged through the opening near the original position of the cobbles and boulders. …”
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Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms by Billy Ogwel, Vincent H. Mzazi, Alex O. Awuor, Caleb Okonji, Raphael O. Anyango, Caren Oreso, John B. Ochieng, Stephen Munga, Dilruba Nasrin, Kirkby D. Tickell, Patricia B. Pavlinac, Karen L. Kotloff, Richard Omore

“…Abstract Background Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. …”
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What We Didn’t Know a Recipe Could Be: Political Commentary, Machine Learning Models, and the Fluidity of Form in Nineteenth-Century Newspaper Recipes by Avery Blankenship

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Optimizing the Prediction Accuracy of Friction Capacity of Driven Piles in Cohesive Soil Using a Novel Self-Tuning Least Squares Support Vector Machine by Doddy Prayogo, Yudas Tadeus Teddy Susanto

“…The hybrid approach uses LS-SVM as a supervised-learning-based predictor to build an accurate input-output relationship of the dataset and SOS method to optimize the σ and γ parameters of the LS-SVM. …”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…By integrating the MIMIC-IV database and machine learning algorithms, we developed an effective predictive model for HRS in liver cirrhosis patients, providing a robust tool for early clinical intervention.…”
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Calculer la sémantique avec le langage IEML by Pierre Lévy

“…The article explains its dictionary, its formal grammar, and its integrated tools for building semantic graphs. As far as its applications are concerned, IEML could be the vector of a fluid calculation and communication of meaning – semantic interoperability – capable of decompartmentalising the digital memory and feeding the progress of collective intelligence, artificial intelligence, and digital humanities. …”
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