Mathematical Modelling of Hybrid Powertrain Systems for Improved Energy Efficiency by Oleg Lyashuk, Victor Aulin, Roman Rohatynskiy, Ivan Gevko, Andriy Gypka, Dmytro Mironov, Volodymyr Martyniuk, Artur Lutsyk, Nadia Denysiuk

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Optimizing microchannel heat sinks with rhomboid vortex generators: An artificial neural network approach and its application in superconducting synchronous condensers by Jiacheng Zhang, Baojun Ge, Jiancheng Zhang, Shiyong Xiao, Abdullah Saeed, Khalid Faisal, Eli Murphy, Karthikeyan Ramanathan

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Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis by Bardia Hajikarimloo, Ibrahim Mohammadzadeh, Salem M. Tos, Mohammad Amin Habibi, Rana Hashemi, Ehsan Bahrami Hezaveh, Dorsa Najari, Arman Hasanzade, Mehdi Hooshmand, Sara bana

“…This systematic review and meta-analysis evaluated the predictive performance of machine learning (ML)-based models in EGFR status in NSCLC patients with brain metastasis. …”
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Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive ge... by Wounsuk Rhee, Sam Yeol Chang, Bong-Soon Chang, Hyoungmin Kim

“…Conclusions Advanced machine learning models have consistently shown greater performance and interpretability over conventional methodologies, implying their potential for a more individualized risk assessment of the aged population. …”
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Research on Machine Learning-Based Extraction and Classification of Crop Planting Information in Arid Irrigated Areas Using Sentinel-1 and Sentinel-2 Time-Series Data by Lixiran Yu, Hongfei Tao, Qiao Li, Hong Xie, Yan Xu, Aihemaiti Mahemujiang, Youwei Jiang

“…The optimal classification model selected was subjected to inter-annual transfer to obtain the planting structures over multiple years. …”
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Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

“…We applied several supervised ML algorithms and feature selection strategies to distinguish between DN and DA, including Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), Naive Bayes (BAYES), K-Nearest Neighbors (KNN), SelectKBest, Recursive Feature Elimination with Cross-Validation (RFECV), and SelectFromModel. …”
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DRSegNet: A cutting-edge approach to Diabetic Retinopathy segmentation and classification using parameter-aware Nature-Inspired optimization. by Sundreen Asad Kamal, Youtian Du, Majdi Khalid, Majed Farrash, Sahraoui Dhelim

“…This is achieved using Generative Adversarial Networks (GANs) to generate high-quality synthetic data and transfer learning for accurate feature extraction and classification, integrating these with Extreme Learning Machines (ELM). The substantial evaluation plan we have provided on the IDRiD dataset gives exceptional outcomes, where our proposed model gives 99.87% accuracy and 99.33% sensitivity, while its specificity is 99. 78%. …”
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Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods by Fernanda Cristina Barbosa Lana, Carolina Coimbra Marinho, Bruno Barbosa Miranda de Paiva, Lucas Rocha Valle, Guilherme Fonseca do Nascimento, Leonardo Chaves Dutra da Rocha, Marcelo Carneiro, Joanna d‘Arc Lyra Batista, Fernando Anschau, Pedro Gibson Paraiso, Frederico Bartolazzi, Christiane Corrêa Rodrigues Cimini, Alexandre Vargas Schwarzbold, Danyelle Romana Alves Rios, Marcos André Gonçalves, Milena Soriano Marcolino

“…Shapley additive explanation (SHAP) values derived from the predictions of a light gradient-boosting machine (LightGBM) model were used to assess potential risk factors for death, IMV and ICU. …”
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Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments by Pablo Valledor, Alberto Gomez, Paolo Priore, Javier Puente

“…The aim of this paper is to analyse, model, and solve the rescheduling problem in dynamic permutation flow shop environments while considering several criteria to optimize. …”
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Multi-Physics and Multi-Objective Design of an Axial Flux Permanent Magnet-Assisted Synchronous Reluctance Motor for Use in Electric Vehicles by Emre Gözüaçık, Mehmet Akar

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A New Paradigm in AC Drive Control: Data-Driven Control by Learning Through the High-Efficiency Data Set—Generalizations and Applications to a PMSM Drive Control System by Madalin Costin, Ion Bivol

“…Knowing a reasonable number of optimal efficiency operation points, an interpolation Radial Base Function (RBF) control was built. …”
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Classification of English Translation Teaching Models based on Multiple Intelligence Theory by Xiaoli Li

“…In order to improve the discrimination accuracy of the extreme learning machine algorithm, this paper applies the particle swarm optimization extreme learning machine algorithm to the research on the classification of English translation teaching samples and proposes an intelligent English classification teaching model based on the actual situation of English translation teaching. …”
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Aerodynamic performance enhancement of centrifugal compressor using numerical techniques [version 1; peer review: 2 approved] by Srinivas G, Shivani S, Amar Murthy A

“…To accomplish this, a comprehensive investigation of variables such as blade number and hub diameter, along with various turbulence models will be conducted. This approach will leverage numerical techniques to fill the significant gaps in the current literature regarding centrifugal compressor design and optimization. …”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence, particularly machine learning and deep learning, is revolutionizing agricultural practices by enabling data-driven, precise, and sustainable solutions. …”
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AI-driven wear monitoring of PVD TiAlN coated carbide insert in sustainable machining of Hastelloy C276: An industry 4.0 perspective by Binayak Sen, Subhankar Saha, Raman Kumar, Ramdevsinh Jhala, Nagaraj Patil, Abinash Mahapatro, Abhijit Bhowmik, A․Johnson Santhosh

“…This research explores the application of AI-based predictive models for monitoring wear on PVD TiAlN-coated carbide inserts during the sustainable machining of Hastelloy C276. …”
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Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms by Huanyu Li, Lixue Dai, Shaomei Guo, Hongluan Wang, Lei Lei, Jie Yu, Xiaoyun Li, Jun Wang

“…Five machine learning models, linear discriminant analysis (LDA), support vector machine (SVM), random forest, multilayer perceptron (MLP), and LightGBM, were optimized using FTIR spectral data (1800–900 cm−1 band). …”
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Models for sustainable management of livestock waste based on neural network architectures by Anatoliy Tryhuba, Krzysztof Mudryk, Inna Tryhuba, Marian Kotsylovskyi, Dmytro Sorokin, Olena Bezaltychna, Pawel Pysz, Taras Hutsol

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Dynamical counterfactual inference under time-series model for waterflooding oilfield by Guoquan Wen, Chao Min, Qingxia Zhang, Guoyong Liao

“…Compared with general machine learning and statistical models, our results not only show better performance in oil production flooding but also guide the specific optimization in improving production, which holds more practical application significance.…”
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Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis by Sujata Dash, Ajith Abraham, Ashish Kr Luhach, Jolanta Mizera-Pietraszko, Joel JPC Rodrigues

“…The efficiency of the model is tested on a voice measurement dataset that is collected from “UC Irvine Machine Learning Repository.” …”
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Six-Dimensional Spatial Dimension Chain Modeling via Transfer Matrix Method with Coupled Form Error Distributions by Lu Liu, Xin Jin, Huan Guo, Chaojiang Li

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