Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…Furthermore, we have incorporated a tailored Differential Evolution (DE) algorithm designed to navigate the complex hyperparameter space with finesse. …”
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Prediction models for COVID-19 disease outcomes by Cynthia Y. Tang, Cheng Gao, Kritika Prasai, Tao Li, Shreya Dash, Jane A. McElroy, Jun Hang, Xiu-Feng Wan

“…We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). …”
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Fault diagnosis technology for three-level inverter based on ICEEMDAN-FE and SVM by CAO Ruijun, GUO Qiyi

“…In order to improve the accuracy to diagnose complex open-circuit faults for three-level inverters, a new fault diagnosis method of three-level inverters was proposed, combining improved complete ensemble empirical mode decomposition with adaptive noise-fuzzy entropy (ICEEMDAN-FE) and support vector machine (SVM). …”
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Optimizing space heating efficiency in sustainable building design a multi criteria decision making approach with model predictive control by Zheng Qi, Nan Zhou, Xianwei Feng, Sama Abdolhosseinzadeh

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Microbiology in the era of artificial intelligence: transforming medical and pharmaceutical microbiology by Virna-Maria Tsitou, Dimitrios Rallis, Mariana Tsekova, Nikolay Yanev

“…In this mini-review, we delve into the transformative impact of artificial intelligence (AI) and machine learning (ML) in the field of microbiology. …”
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Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach by Mehdi Fasihi, Mirko Sodini, Alex Falcon, Francesco Degano, Paolo Sivilotti, Giuseppe Serra

“…To ensure the robustness of the proposed Pseudo-labelling strategy, we integrated it into eight machine-learning algorithms. We evaluated its performance across seven diverse datasets, each exhibiting varying percentages of missing values. …”
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Hybrid AI and semiconductor approaches for power quality improvement by Ravikumar Chinthaginjala, Asadi Srinivasulu, Anupam Agrawal, Tae Hoon Kim, Sivarama Prasad Tera, Shafiq Ahmad

“…The research addresses key power quality challenges - including voltage sags, swells, harmonics, and transient disturbances - through a data-driven framework that combines traditional control techniques with adaptive learning models. A variety of algorithms, including Support Vector Machines (SVM), Random Forests, Neural Networks, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks, were tested using real-time data. …”
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Transient Equivalent Modelling of a Wind Farm Based on QPSO-Based Wind Turbine Fault Ride-Through Control by Jianan He, Shenbing Ma, Xu Zhang, Meiling Luo, Lei Li, Jian Niu, Haitao Liu, Ping Jin, Yabo Liang

“…Based on the control mechanism of direct-drive wind turbines, this method first analyzes the fault ride-through operating characteristics of wind turbines and establishes a single-machine fault transient model; then, taking the fault ride-through control characteristics of wind turbines as the criteria for subgroups, it calculates the relevant parameters of the group through weighted aggregation and QPSO algorithm, and constructs the fault transient equivalent model of each group; finally, combining with the principle of loss conservation, it integrates and obtains the fault transient equivalent model of the whole wind power field. …”
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Integrating data-driven and physics-based approaches for robust wind power prediction: A comprehensive ML-PINN-Simulink framework by Rajaperumal T. A, Christopher Columbus Chinnappan

“…Using a complete annual dataset of 8,760 hourly wind speed observations from the MERRA-2 platform, ten machine learning algorithms were systematically evaluated, including Random Forest, XGBoost, and an advanced Stacking ensemble model. …”
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LULC-SegNet: Enhancing Land Use and Land Cover Semantic Segmentation with Denoising Diffusion Feature Fusion by Zongwen Shi, Junfu Fan, Yujie Du, Yuke Zhou, Yi Zhang

“…The LULC-SegNet incorporates DDPM decoder features into the LULC segmentation task, utilizing machine learning clustering algorithms and spatial attention to extract continuous DDPM semantic features. …”
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Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears by Jhonathan Sora-Cardenas, Wendy M. Fong-Amaris, Cesar A. Salazar-Centeno, Alejandro Castañeda, Oscar D. Martínez-Bernal, Daniel R. Suárez, Carol Martínez

“…Using a dataset of 1000 clinically diagnosed images, we applied feature extraction techniques, including histogram bins and texture analysis with the gray level co-occurrence matrix (GLCM), alongside support vector machines (SVMs), for image quality assessment. Leukocyte detection employed optimal thresholding segmentation utility (OTSU) thresholding, binary masking, and erosion, followed by the connected components algorithm. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…AI’s ability to enhance learning outcomes is evident, yet concerns around algorithmic bias, data privacy and the digital divide must be addressed to ensure equitable access to AI-powered education worldwide. …”
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Predicting Energy and Emissions in Residential Building Stocks: National UBEM with Energy Performance Certificates and Artificial Intelligence by Carlos Beltrán-Velamazán, Marta Monzón-Chavarrías, Belinda López-Mesa

“…Using the XGBoost machine learning algorithm, the model analyzes the physical and geometrical characteristics of residential buildings in Spain. …”
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Analyzing the Impact of Geoenvironmental Factors on the Spatiotemporal Dynamics of Forest Cover via Random Forest by Hendaf N. Habeeb, Yaseen T. Mustafa

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Chamber shape optimization for ultra-high-pressure water-jet nozzle based on computational fluid dynamics method and a data-driven surrogate model by Wen-Tao Zhao, Zheng-Shou Chen, Yuan-Jie Chen, Jiang-Long Li

“…Firstly, to ensure optimization accuracy, an improved whale optimization algorithm (IWOA) was developed. It combines the chaotic opposition-based learning (COBL) and the Cauchy-Gaussian mutation simulated annealing algorithms, incorporating a nonlinear convergence and adaptive inertia weight mechanism. …”
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Design and operation experiences of a multi-wire detector under high beam power environment by FENG Yongchun, CHEN Yucong, KANG Xincai, LI Weilong, TANG Kai, ZHAO Zulong, ZHAO Tiecheng, XU Zhiguo, MAO Ruishi, XIAO Guoqing

“…However, wire deformation and even wire broken have also happened frequently during the MW operation due to beam power deposition on the wire under high beam power environment.PurposeThis study aims to investigate the influences of the beam parameters and detector design, especially wire tension structure, on the wire temperature and wire deformation arising therefrom.MethodsFirstly, based on the backward Euler method with adaptive steps, a numerical algorithm was developed to conduct temperature simulation of MW. …”
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Tools for forecasting regional economic growth using big data and business intelligence technologies by Afanasev Kirill, Kalinin Aleksandr

“…The research methodology includes modified machine learning algorithms specifically adapted for regional data analysis, using both structured and unstructured information sources. …”
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A Reinforcement Learning Approach to Personalized Asthma Exacerbation Prediction Using Proximal Policy Optimization by Dahiru Adamu Aliyu, Emelia Akashah Patah Akhir, Maryam Omar Abdullah Sawad, Jameel Shehu Yalli, Yahaya Saidu

“…Traditional predictive models rely on static machine learning approaches, which lack adaptability to evolving patient conditions and environmental changes. …”
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Insight Thoughts for Intelligent Traffic Management-Based SDN by Sara Sadiq Jawad, Dheyaa Jasim Kadhim, Yusmadi Yah Bt Jusoh

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The Evolving Role of Copyright Law in the Age of AI-Generated Works by J. Hutson

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