Intelligent Thermal Condition Monitoring for Predictive Maintenance of Gas Turbines Using Machine Learning by Sadiq T. Bunyan, Zeashan Hameed Khan, Luttfi A. Al-Haddad, Hayder Abed Dhahad, Mustafa I. Al-Karkhi, Ahmed Ali Farhan Ogaili, Zainab T. Al-Sharify

“…An Extreme Gradient Boosting (XGBoost)-based classification model was developed to distinguish between healthy and faulty operating conditions based on thermal load data. …”
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Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations by Badriah Alkalifah, Muhammad Tariq Shaheen, Johrah Alotibi, Tahani Alsubait, Hosam Alhakami

“…To support this an Artificial Neural Network (ANN), Binary Decision Tree (BDT), Linear Regression (LR), Boosting Regression Tree Ensemble (BSTE), Linear Regression with Stochastic Gradient Descent (LRSGD), Stepwise (SW), Support Vector Machine (SVM), and Gaussian process regression (GPR) were investigated. …”
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A review of machine learning and internet-of-things on the water quality assessment: Methods, applications and future trends by Gangani Dharmarathne, A.M.S.R. Abekoon, Madhusha Bogahawaththa, Janaka Alawatugoda, D.P.P. Meddage

“…Explainable AI (XAI) which can explain the decision making process of ML, is underutilised, appearing in only a few recent studies. …”
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Remote Sensing Image Semantic Segmentation Sample Generation Using a Decoupled Latent Diffusion Framework by Yue Xu, Honghao Liu, Ruixia Yang, Zhengchao Chen

“…The proportion-aware loss effectively mitigates the impact of minority classes, boosting segmentation performance on under-represented categories. …”
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Underlying-Dynamics Paradigm Shift of Global Digital Ecosystems: Characteristics and Enlightenment by Hong Zou, Fan Zhang, Yuting Shang, Jiangxing Wu

“…Nowadays, the world is embarking on a process of transformation in the underlying dynamics of the digital ecosystem. …”
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Development and validation of a machine learning‐based model of ischemic stroke risk in the Chinese elderly hypertensive population by Xiaoyue Lyu, Jie Liu, Yingying Gou, Shengli Sun, Jing Hao, Yali Cui

“…The final model, eXtreme gradient boosting, was identified as having superior performance than the other 9 classifers (random forest, Gaussian process, multilayer perceptron, logistic regression, support vector machine, K‐nearest neighbor, decision tree, Gaussian naive bayes, and ensemble model), with area under the receiver‐operating characteristic curves of 0.97 and 0.94 for the test and external validation sets, respectively. …”
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Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data by Maksut Kulzhanov, Alexander Wagner, Abylkair Skakov, Iliyas Mukhamejan, Saya Zhorabek, Ainur B. Qumar

“…An automated AI system was developed and tested using nine ML models, including XGBoost, Random Forest, Decision Tree, Gradient Boosting, etc. The dataset comprised 329,584 real records, including demographic and socio-economic parameters. …”
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Targeting tumor-associated macrophages to overcome immune checkpoint inhibitor resistance in hepatocellular carcinoma by Fen Liu, Xianying Li, Yiming Zhang, Shan Ge, Zhan Shi, Qingbin Liu, Shulong Jiang

“…M2-polarized TAMs secrete a range of immunosuppressive cytokines that inhibit T cell activation and promote tumor progression through processes such as angiogenesis and epithelial-mesenchymal transition. …”
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Unveiling Microbial Dynamics and Gene Expression in Legume–Buffel Grass Coculture Systems for Sustainable Agriculture by Xipeng Ren, Sung J. Yu, Philip B. Brewer, Nanjappa Ashwath, Yadav S. Bajagai, Dragana Stanley, Tieneke Trotter

“…Lablab and Wynn cassia exhibited similarities in modulating metabolic processes, butterfly pea contributed to mycotoxin detoxification, and desmanthus balanced cell death and growth. …”
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The Design of a Low-Power Pipelined ADC for IoT Applications by Junkai Zhang, Tao Sun, Zunkai Huang, Wei Tao, Ning Wang, Li Tian, Yongxin Zhu, Hui Wang

“…A prototype ADC was fabricated in a 180 nm CMOS process and the core size was 0.333 mm². …”
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Melatonin: dual players mitigating drought-induced stress in tomatoes via modulation of phytohormones and antioxidant signaling cascades by Shifa Shaffique, Anis Ali Shah, Sang-Mo Kang, Md. Injamum-Ul-Hoque, Raheem Shahzad, Tiba Nazar Ibrahim Al Azzawi, Byung-Wook Yun, In-Jung Lee

“…Melatonin is a vital hormone, signaling molecule, and bio-regulator of diverse physiological growth and development processes. Its role in boosting agronomic traits under diverse stress conditions has received considerable attention. …”
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Artificial intelligence driven platform for rapid catalytic performance assessment of nanozymes by Wenjie Xuan, Xiaofo Li, Honglei Gao, Luyao Zhang, Jili Hu, Liping Sun, Hongxing Kan

“…Artificial intelligence (AI) has the potential to simplify these processes, but there are very few dedicated nanozyme databases available, limiting the resources for research and application. …”
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Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach by Qiulin Li, Jinchao He, Dewei Mu, Hao Liu, Shicheng Li

“…Dissolved oxygen (DO) is a vital water quality index influencing biological processes in aquatic environments. Accurate modeling of DO levels is crucial for maintaining ecosystem health and managing freshwater resources. …”
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Prediction Model for the Chloride Ion Permeability Resistance of Recycled Aggregate Concrete Based on Machine Learning by Pengfei Gao, Yuanyuan Song, Jian Wang, Zhiyong Yang, Kai Wang, Yongyu Yuan

“…Based on the XGBoost model, the LIME method was adopted to solve the interpretability problem in the prediction process. The importance ranking of IFs on the electric flux was <i>r</i> > <i>t</i> > <i>f</i> > <i>T</i> > <i>L</i> > <i>YN</i>. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…Method: In this study, various models, such as SVM, decision tree, random forest, logistic regression, K-neighbor, Gaussian NB, AdaBoost classifier, MLP classifier, passive aggressive, ridge classifier, extra tree, bagging classifier, extra trees, gradient boosting, SGD classifier, linear SVC, voting classifier, and stacking classifier were used. …”
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A Study on Hyperspectral Soil Moisture Content Prediction by Incorporating a Hybrid Neural Network into Stacking Ensemble Learning by Yuzhu Yang, Hongda Li, Miao Sun, Xingyu Liu, Liying Cao

“…First, raw hyperspectral data are processed by removing edge noise and standardization. …”
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Estimated ultimate recovery prediction of shale gas wells based on stacked integrated learning algorithm by Min Pang, Zheyuan Zhang, Zhaoming Zhou, Wendi Zhou, Qiong Li

“…Conventional methods often lack sufficient transparency and clarity in the calculation process. As a result, machine learning (ML) algorithms have proven to be an effective alternative. …”
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Determination of high-confidence germline genetic variants in next-generation sequencing through machine learning models: an approach to reduce the burden of orthogonal confirmatio... by Muqing Yan, Qiandong Zeng, Zhenxi Zhang, Patricia Okamoto, Stanley Letovsky, Angela Kenyon, Natalia Leach, Jennifer Reiner

“…Laboratories interested in deploying such models should consider incorporating additional quality criteria and thresholds to serve as guardrails in the assessment process.…”
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Study on debris flow vulnerability of ensemble learning model based on spy technology A case study of upper Minjiang river basin by Yutao Chen, Ning Li, Fucheng Xing, Han Xiang, Zilong Chen

“…Its formation and movement are intricate processes. The investigation of debris flow susceptibility assessment is crucial for disaster warning and mitigation. …”
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Assessing urban renewal opportunities by combining 3D building information and geographic big data by Xin Zhao, Nan Xia, ManChun Li

“…However, conventional data sources often fall short in encompassing diverse urban characteristics in the evaluation process, such as urban three-dimensional (3D) building information and the intensity of human activities. …”
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