Considering the effect of non-landslide sample selection on landslide susceptibility assessment by Youchen Zhu, Deliang Sun, Haijia Wen, Qiang Zhang, Qin Ji, Changming Li, Pinggen Zhou, Jianjun Zhao

“…In this study, we utilized Extreme Gradient Boosting and Random Forest algorithms, and four methods (Whole-area random selection method, Buffer method, Frequency Ratio method, and Analysis Hierarchy Process) were employed to select non-landslide samples for constructing the landslide susceptibility assessment model. …”
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Machine learning insights for predicting density and hardness in centrifugal SHS synthesized ceramic coatings by N. Radhika, M. Sabarinathan, S. Sivaraman

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Increasing Production Capacity and Competitiveness of Bakery and Dairy SMEs in Babussalam Al-Firdaus Islamic Boarding School, Malang by Mochamad Nurcholis, Mokhamad Nur, Yoga Dwi Jatmiko, Feronika Heppy Sriherfyna, Jaya Mahar Maligan, Aldila Putri Rahayu

“…Assistance and training are provided to increase product diversity, packaging design, production capacity, product selling value, SPP-IRT and halal certificate/label processing, and offline and online marketing to boost these business units' income. …”
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Febrile disease modeling and diagnosis system for optimizing medical decisions in resource-scarce settings by Daniel Asuquo, Kingsley Attai, Okure Obot, Moses Ekpenyong, Christie Akwaowo, Kiirya Arnold, Faith-Michael Uzoka

“…The research investigated the most effective modeling approach for differentiating among 11 febrile illnesses that are prevalent in Nigeria using three intelligent techniques: Extreme Gradient Boost (XGBoost), Fuzzy Cognitive Map (FCM), and Analytic Hierarchy Process (AHP). …”
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Plantão de escuta: uma aplicação da Teoria Humanística no processo clínico de enfermagem [On-call listening: an application of Humanistic Theory in the clinical nursing process] [T... by Alexandre Vicente da Silva, Iraci dos Santos, Célia Caldeira Fonseca Kestenberg, Célia Pereira Caldas, Lina Marcia Miguéis Berardinelli, Lenilse Pereira de Souza Silva

“…Results: the second phase of the clinical process – in which the nurse intuitively knows the other – was most notable. …”
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Phase-type distribution models for performance evaluation of condition-based maintenance by Kai-Wen Tien, Vittaldas Prabhu

“…Employing machine health-index, the framework characterizes production performance by estimating effective process times. The model demonstrates how adjusting CBM thresholds influences process time variations and assesses the impact of changing maintenance frequency for TBM. …”
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Leveraging Digital Twin for operational resilience in the oil and gas industry by Giovanni Mazzuto, Ilaria Pietrangeli, Marco Ortenzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua

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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

“…Among the four ensemble ML models evaluated, CatBoost demonstrated the highest predictive performance. …”
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Techno-economic feasibility study of ammonia recovery from sewage sludge digestate in wastewater treatment plants by Mohammad Alrbai, Sameer Al-Dahidi, Bashar Shboul, Mosa Abusorra, Hassan Hayajneh

“…Increased air flow rates significantly boosted recovery, achieving 90% efficiency at 60 °C with 50,000 kg/h as air flow. …”
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The Technological Basis of Training Future Teachers of Agricultural Disciplines in Higher Education Institutions: Pedagogical Experience of Great Britain by Viktor Nagayev, Tetiana Gerliand

“…The implementation of a three-level pedagogical technology in the educational process management system allows for boosting students’ creative activity, increasing the level of their internal motivation, and deepening the level of independence and individualisation of learning, which eventually is determined by a high level of readiness for professional pedagogical activity. …”
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Predicting EHL film thickness parameters by machine learning approaches by Max Marian, Jonas Mursak, Marcel Bartz, Francisco J. Profito, Andreas Rosenkranz, Sandro Wartzack

“…We assume that this will boost the use of ML approaches to predict EHL parameters and traction losses in multibody system dynamics simulations.…”
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Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…This paper proposes and assesses three Gaussian Process-based hybrid models—GP-RBM (Random Boosting Machine), GP-LSTM (Long Short-Term Memory), and GP-CNN (Convolutional Neural Network)—for forecasting COVID-19 mortality cases in the USA, France, and India. …”
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TOOLS OF ACTIVIZATION OF INNOVATIVE AND INVESTMENT ACTIVITY IN THE CREATIVE ECONOMY by Oksana Dubskaya, Elena Dubskaya, Yuliya Marakulina

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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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Fabrication of ZnFe2O4@g-C3N4 for enhanced photo-fenton effect and visible light-driven organic dye degradation by Leyan Li, Wang Jianhua, Huihui Fang

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Predictive modeling of punchouts in continuously reinforced concrete pavement: a machine learning approach by Ghazi Al-Khateeb, Ali Alnaqbi, Waleed Zeiada

“…It is noteworthy that ensemble methods such as boosted trees and Gaussian process regression models exhibit promising predictive performance, with low root mean square error (RMSE) and high R-squared values. …”
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Drying of Nettle Using Concentrated Air Collector and Concentrated Photovoltaic Thermal Supported Drying System and Modeling with Machine Learning by Mehmet Onur Karaagac

“…This study examines the performance of a solar assisted drying system in the nettle drying process. The drying process works by using thermal energy obtained from solar air collectors and PV modules. …”
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ENHANCING STATE POLICY EFFECTIVENESS IN CINEMA THROUGH MACHINE LEARNING / Повышение эффективности государственной политики в сфере кинематографа с помощью машинного обучения... by DOZHDIKOV ANTON V. / ДОЖДИКОВ А.В.

“…The study utilized the ensemble machine learning model HistGradientBoostingClassifier and a sequential fully connected three-layer neural network based on the TensorFlow library, along with basic methods of natural language processing. …”
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Progress on the world’s primate hotspots and coldspots: modeling ensemble super SDMs in cloud-computers based on digital citizen-science big data and 200+ predictors for more susta... by Moriz Steiner, Falk Huettmann

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Integrating environmental and LULC drivers of groundwater droughts in groundwater-dependent ecosystems: a machine learning (XGBoost)-SEM analysis with ecosystem implications by Kawawa Banda, Christopher Shilengwe, Imasiku Nyambe

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