Reliable models for calculating the condensation heat transfer inside smooth helical tubes of different flow directions utilizing smart computational techniques by Chou-Yi Hsu, Nikunj Rachchh, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Ahmad Alkhayyat, Prabhat Kumar Sahu, Abhinav Kumar, Satvik Vats, F. Ranjbar

“…Two machine learning (ML) techniques, namely Support Vector Machine (SVM) and Gaussian Process Method (GPM) were implemented to accomplish this target. …”
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A bio-inspired framework for apple leaf disease detection: Integrating lesion localization, ant colony optimization, and machine learning by Xiaolong Li, Feifan Huang, Haotian Sun, Jiayu He, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang

“…To address the growing need for rapid, accurate, and scalable solutions in precision disease detection and management, this study presents a novel framework integrating image processing, artificial intelligence (AI), and ant colony optimization (ACO) for automated disease classification in apple leaves. …”
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A Novel Tool Wear Identification Method Based on a Semi-Supervised LSTM by Xin He, Meipeng Zhong, Chengcheng He, Jinhao Wu, Haiyang Yang, Zhigao Zhao, Wei Yang, Cong Jing, Yanlin Li, Chen Gao

“…These pseudo-labeled samples are combined with the original labeled samples to retrain the MR–LSTM model iteratively to improve its performance. This process continues until a termination condition is met. …”
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Analysis of the influence of the daily regulation of power stations on navigable flow conditions at river confluences using the LSTM model by Hongcheng Xue, Shihao Cui, Qian Ma, Zhongyong Li, Pengyu Zhou, Yuanyuan Li, Lingyun Xie

“…The simulated results for water levels and velocity vector fields are in good agreement with experimental data. …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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MICRO-SCALE STUDY OF RESIDUAL STRESSES IN CR2O3 COATINGS SPRAYED BY APS by Franck Decroos, Cécile Langlade, Eric Bourillot, Geoffrey Darut, Manuel Francois

“…Whichever the application field, every material forming process generates residual stresses on the surface. …”
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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Machine learning models, including Backpropagation Neural Network (BPNN), Support Vector Machines (SVM), and particle swarm optimization algorithms (PSO-BPNN, PSO-SVR), were applied for regression analysis. …”
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A Systematic Analysis of Meteorological Parameters in Predicting Rainfall Events by Muhammad Salman Pathan, Pardhu Nadella, Yasin Ul Haq, Soumini Chaudhury, Jiantao Wu, Avishek Nag, Soumyabrata Dev

“…The study also conducts a thorough assessment of prediction performance of various ML and deep learning (DL) techniques such as Classification and Regression Trees (CART), Support Vector Machine (SVM) and Dense Neural Networks (DNN).The findings show that the models using only the important meteorological features in the dataset perform better than using all the features. …”
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A Comprehensive Review of Crop Chlorophyll Mapping Using Remote Sensing Approaches: Achievements, Limitations, and Future Perspectives by Xuan Li, Bingxue Zhu, Sijia Li, Lushi Liu, Kaishan Song, Jiping Liu

“…Machine learning methods, such as random forest and support vector regression, exhibit excellent performance, with determination coefficients (R²) typically exceeding 0.9, although overfitting remains an issue. …”
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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…Furthermore, we adapt AEMGO to its binary version (bAEMGO) and combine it with a Support Vector Machine (SVM) to create the bAEMGO-SVM method. …”
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Enhancing Immoral Post Detection on Social Networks Using Knowledge Graph and Attention-Based BiLSTM Framework by Bibi Saqia, Khairullah Khan, Atta Ur Rahman, Sajid Ullah Khan, Mohammed Alkhowaiter, Wahab Khan, Ashraf Ullah

“…Various Natural Language Processing (NLP) approaches are being employed to detect subtle immoral posts; however, there remains a research gap due to the semantic and contextual complexity of natural language. …”
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The transcription factor PITX1 cooperates with super-enhancers to regulate the expression of DUSP4 and inhibit pyroptosis in pulmonary artery smooth muscle cells by Jingya Zhang, Yuyu Song, Xinru Wang, Xu Wang, Songyue Li, Xinyue Song, Chong Zhao, Jing Qi, Yunyun Tian, Baoshan Zhao, Xiaodong Zheng, Yan Xing

“…However, whether SEs are involved in the pathological process of pyroptosis in PAH and the specific mechanism involved remain unclear. …”
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Graph-Based COVID-19 Detection Using Conditional Generative Adversarial Network by Imran Ihsan, Azhar Imran, Tahir Sher, Mahmood Basil A. Al-Rawi, Mohammed A. Elmeligy, Muhammad Salman Pathan

“…These reconstructed features serve as input to a classification module, comprising a multi-layer neural network, GCN, adept at processing graph-structured data, alongside conventional machine learning classifiers such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), facilitating categorization of chest X-ray images into COVID-19, pneumonia, and normal cases. …”
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Metabolomics Biomarker Discovery to Optimize Hepatocellular Carcinoma Diagnosis: Methodology Integrating AutoML and Explainable Artificial Intelligence by Fatma Hilal Yagin, Radwa El Shawi, Abdulmohsen Algarni, Cemil Colak, Fahaid Al-Hashem, Luca Paolo Ardigò

“…The TreeSHAP approach, which is a type of XAI, was used to interpret the model by assessing each metabolite’s individual contribution to the categorization process. <b>Results:</b> TPOT had superior performance in distinguishing between HCC and cirrhosis compared to other AutoML approaches AutoSKlearn and H2O AutoML, in addition to traditional machine learning models such as random forest, support vector machine, and k-nearest neighbor. …”
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Effective Scheme of Sequential Application of Electrical Stimulation Courses in Dorsopathies: Comparative Study Results by Tatiana V. Konchugova, Lev G. Agasarov, Tatiana V. Apkhanova, Tatiana V. Marfina, Tatiana P. Miloykovich, Anastasia A. Mukhina

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The Fermentation Degree Prediction Model for Tieguanyin Oolong Tea Based on Visual and Sensing Technologies by Yuyan Huang, Jian Zhao, Chengxu Zheng, Chuanhui Li, Tao Wang, Liangde Xiao, Yongkuai Chen

“…The fermentation of oolong tea is a critical process that determines its quality and flavor. Current fermentation control relies on tea makers’ sensory experience, which is labor-intensive and time-consuming. …”
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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics by Jinghong Pei BD, Jing Yu BD, Ping Ge BD, Liman Bao BD, Haowen Pang MS, Huaiwen Zhang MS

“…Through stringent feature selection process, we identified 18 pivotal radiomic features for classification of cervical cancer and normal uterine tissue. …”
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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…Furthermore, decision tree, random forest, support vector machine (SVM), logistic regression, XGBoost, blending ensemble, and convolutional neural network (CNN) algorithms with corresponding optimized hyperparameters and synthetic minority oversampling technique (SMOTE) have been applied for learning behavior classification. …”
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Enhancing EEG-Based Emotion Detection with Hybrid Models: Insights from DEAP Dataset Applications by Badr Mouazen, Ayoub Benali, Nouh Taha Chebchoub, El Hassan Abdelwahed, Giovanni De Marco

“…Extensive experimentation was conducted using K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Decision Tree (DT), Random Forest (RF), Bidirectional Long Short-Term Memory (BiLSTM), Gated Recurrent Units (GRUs), Convolutional Neural Networks (CNNs), autoencoders, and transformers. …”
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Pemodelan Text Mining dalam Pengkodean Penyakit Pasien Berdasar Kode ICD 10 by Parjono Parjono, Sri Kusumadewi

“…Metode pendekatan yang diterapkan adalah Clinical Text Mining dengan Natural Language Processing dimana metode ini dirasa paling tepat untuk mengekstraksi informasi dari diagnosis dokter yang tidak terstruktur. …”
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