FEATURE EXTRACTION AND ESTABLISHMENT BASED ON PUMPING UNIT WORKING CONDITIONS AND GLOBAL FAULT IDENTIFICATION by REN Taizhu, FAN Jun, JIANG Xiaxin

“…Then, two methods of obtaining valve opening and closing points and load variation characteristics were proposed, and 54 new features of global faults of pumping units were extracted, and the characteristic database of working conditions of the pumping unit was established.Finally, the algorithm of decision tree, logistic regression and support vector machine was used to verify that the feature database has good classification effect under different working conditions. …”
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Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

“…This review systematically examines advancements in AI-based fault diagnosis techniques, including machine learning (ML) and deep learning (DL), from 2019 to 2024, analyzing their evolution, efficacy, and practical challenges. …”
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Credit Scoring Prediction Using Deep Learning Models in the Financial Sector by Xi Shi, Dingfen Tang, Yike Yu

“…In the swiftly transforming domain of computational science, the incorporation of sophisticated machine learning algorithms has emerged as a critical driver in addressing these challenges. …”
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Internal Climate Variability Obscures Future Freezing Rain Changes Despite Global Warming Trend by Haoyu (Richard) Zhuang, Arthur T. DeGaetano, Flavio Lehner

“…Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. …”
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Development of Quantitative Structure–Anti-Inflammatory Relationships of Alkaloids by Cristian Rojas, Doménica Muñoz, Ivanna Cordero, Belén Tenesaca, Davide Ballabio

“…Then, we calibrated the QSAR models using well-known linear and non-linear machine learning classifiers, i.e., partial least squares discriminant analysis (PLSDA), random forests (RF), adaptive boosting (AdaBoost), <i>k</i>-nearest neighbors (<i>k</i>NN), <i>N</i>-nearest neighbors (N3) and binned nearest neighbors (BNN). …”
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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…This study, hence, introduces machine learning models utilizing K-nearest neighbors, decision tree, adaptive boosting, multilayer perceptron artificial neural network, convolutional neural network, support vector machine, random forest and ensemble learning algorithms to accurately forecast the dynamic viscosity of CO2-saturated PEG based on PEG molar mass, pressure, and temperature. …”
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Deep reinforcement learning Lane-Change Decision-Making for autonomous vehicles based on motion primitives library in hierarchical action space by Guizhe Jin, Zhuoren Li, Bo Leng, Minhua Shao

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FedQP: Large-Scale Private and Flexible Federated Query Processing by Hussain M. J. Almohri, Layne T. Watson

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Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

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A Type‐3 Fuzzy‐Based Model Predictive Control Approach for Management of Constant Energy by Man‐Wen Tian, Lixing Zhu, Mohammad Hosein Sabzalian, Jafar Tavoosi, Amirhosein Khosravi Sarvenoee, Pierpaolo D'Urso, Ebrahim Ghaderpour, Ardashir Mohammadzadeh

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Improved Coulomb collision operator for kinetic ion transport with EMC3-EIRENE simulating Nitrogen seeding in medium density ITER L-mode scenario by D. Harting, D. Reiser, S. Rode, J. Romazanov, P. Börner, Y. Feng, H. Frerichs, A. Knieps

“…In this work we will present the details of this newly implemented Coulomb collision operator for kinetic ions in EMC3-EIRENE and the implementation of the adaptive time step algorithm. We applied this new Coulomb collision operator in a kinetic ion simulation with EMC3-EIRENE for Nitrogen seeding, where we puffed Nitrogen from the top of the machine in an attached medium density ITER L-mode scenario (nsep = 1×1019 m−3, Psep = 20 MW). …”
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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

“…Images from the publicly available dataset were subjected to pre-processing and Region of Interest is obtained by adapting the proposed Multilevel Hierarchical Marker-Based Watershed Algorithm (MHMW). …”
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Informatics-driven unsupervised learning of comorbidity clusters for COVID-19 reinfection risk: A finite mixture modeling approach by Grant B. Morgan, Andreas Stamatis, Chelsea C. Yager, Ali Boolani

“…Methods: We analyzed 42,974 patient records containing COVID-19 diagnoses using an machine learning classification algorithm to identify comorbidity profiles. …”
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Automatic classification of fungal-fungal interactions using deep leaning models by Marjan Mansourvar, Jonathan Funk, Søren Dalsgård Petersen, Sajad Tavakoli, Jakob Blæsbjerg Hoof, David Llorente Corcoles, Sabrina M. Pittroff, Lars Jelsbak, Niels Bjerg Jensen, Ling Ding, Rasmus John Normand Frandsen

“…To overcome these challenges, we developed an AI-automated image classification approach using machine learning algorithm based on deep neural network. …”
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Cost-Efficient Distributed Learning via Combinatorial Multi-Armed Bandits by Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz

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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…As a subset of artificial intelligence, machine learning algorithms create a mathematical model based on sample data or "training data" in order to predict or make decisions without overt planning (Du et al., 2019). …”
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GeoTemporal clustering for aquifer delineation: a big data approach to synchronizing and analyzing variable-length groundwater time series by Khalid ElHaj, Dalal Alshamsi

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AUTOMATIC SYNTHESIS OF GAIT SCENARIOS FOR RECONFIGURABLE MECHATRONIC MODULAR ROBOTS IN THE MODIFICATION OF THE WALKING PLATFORM by S. V. Manko, E. I. Shestakov

“…One of the key issues in controlling the movement of robots of this type is the need to use original algorithms for each of the possible configurations. …”
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AI-assisted Pattern Generator for Garment Design by Michael Danner, Elena Brake, Gabriela Kosel, Yordan Kyosev, Katharina Rose, Matthias Rätsch, Holger Cebulla

“…Machine learning adapts to different garment styles (close-fitting, regular fit and loose-fitting), ensuring a broad applicability, while customization options allow a precise adaption to individual body measurements. …”
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An instruction dataset for extracting quantum cascade laser properties from scientific textDataverse by Deperias Kerre, Anne Laurent, Kenneth Maussang, Dickson Owuor

“…One of the main challenges in developing machine learning algorithms for extraction of QCL properties from text is lack of quality training data for these algorithms. …”
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