Interactive Geographic Visualization and Unsupervised Learning for Optimal Assignment of Preachers to Appropriate Congregations by Rahmad Kurniawan, Ibnu Daqiqil ID, Abdul Somad Batubara, Fitra Lestari, Arisman Adnan, Fatayat Fatayat, Ilyas Husti

“…Traditional assignment methods often lead to inefficiencies due to misalignment between the preacher’s expertise and congregational needs, as well as logistical issues. This study integrates K-Means clustering and DBSCAN algorithms with interactive geographic visualization to optimize the assignment of preachers to mosques. …”
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Transforming Wind Data into Insights: A Comparative Study of Stochastic and Machine Learning Models in Wind Speed Forecasting by Türker Tuğrul, Sertaç Oruç, Mehmet Ali Hınıs

“…Based on this, in this study, prospective analyses were made with various machine learning algorithms, the long-short term memory (LSTM), the artificial neural network (ANN), and the support vector machine (SVM) algorithms, and one of the stochastic methods, the seasonal autoregressive integrated moving average (SARIMA), using the monthly wind data obtained from Bodo. …”
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Mapping Antarctic Blue Ice Areas With Sentinel-2A/B Images and LightGBM Model by Xiaolong Teng, Jiahui Xu, Xiangbin Cui, Guitao Shi, Zhengyi Hu, Qingyu Gu, Bailang Yu, Jianping Wu, Yan Huang

“…Random forest, XGBoost, and LightGBM integrated learning algorithms were used to model the extraction of Antarctic blue ice. …”
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GLOBAL TRENDS ON RESEARCH TOWARDS THE VALUATION PROCESS OF AN AGRICULTURE LAND by Silvia CHIOREAN, Iulia COROIAN, Tudor SĂLĂGEAN, Mircea Emil NAP, Jutka DEAK, Ioan LUPUȚ

“…The increased use of data analytics and machine learning algorithms enables better prediction of land values based on various factors such as soil quality, climate, and historical performance by processing large datasets. …”
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Grammar Practices in the Digital World by Mária Csernoh, Attila Imre

“…eaching and protecting Hungarian language and cultural values have become more and more challenging due to the fast spread of uncontrollable digital platforms In their text-based digital products (e-mail, chat, blog, etc), youngsters prefer elliptical expressions (digital slang) to grammatically correct sentences Schools, course books offer a wide variety of opportunities to practise grammar, but students find these exercises rather boring and consider them as school chores As students live in the digital world, teachers should consider alternatives to offering exclusively classical, paper-based exercises The present work provides a subject-integrated approach, where paper-based course book tasks are converted into data management problems to practise grammar This novel approach may enable students to become more engaged not only in solving the original grammar problems but also in finding digital solutions Building algorithms helps them understand grammar rules, as well as differences between handwritten and computer-stored characters It is also stipulated that our approach is open to generalization and suitable to solve similar problems in languages other than Hungarian.…”
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Assessment of Corporate Financial Flood Risks Due to Property Damage and Business Interruption Loss by Masahiro Abe, Peter Adriaens

“…Flood damage algorithms are then used to quantify both direct impacts on capital assets and indirect effects on business interruption loss (BIL). …”
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Machine learning-based predictive analysis of energy efficiency factors necessary for the HIFU treatment of adenomyosis by Ziyan Liu, Ziyi Liu, Yuan Wang, Xiyao Wan, Xiaohua Huang

“…The correlation coefficients were 0.768 and 0.777, and the R2 coefficients of the two models in the test set were 0.559 and 0.549, respectively.ConclusionThe joint model integrating T2WI radiomics and clinical data effectively predicted EEF values for HIFU ablation in adenomyosis. …”
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Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

“…Comparative assessments with competitive algorithms, such as the grey wolf optimizer and particle swarm optimization, reveal MGO’s superior performance. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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An advanced real-time crash prediction framework for combined hard shoulder running and variable speed limits system using transformer by Mohamed Abdel-Aty, Tarek Hasan, B M Tazbiul Hassan Anik

“…This research proposes an integrated and advanced real-time crash risk prediction framework for Variable Speed Limits (VSL) and Hard Shoulder Running (HSR) implemented freeways considering their operational periods. …”
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Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…This research represents the first comprehensive application of ML techniques to WDE incubation period prediction, establishing a methodological framework that integrates experimental data, statistical analysis, and advanced ML algorithms. …”
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Machine learning models for discriminating clinically significant from clinically insignificant prostate cancer using bi-parametric magnetic resonance imaging by Hakan Ayyıldız, Okan İnce, Esin Korkut, Merve Gülbiz Dağoğlu Kartal, Atadan Tunacı, Şükrü Mehmet Ertürk

“…Additionally, a third feature subset was created by combining the T2W and ADC images, enhancing the analysis with an integrated approach. Once the features were extracted, Pearson’s correlation coefficient and selection were performed using wrapper-based sequential algorithms. …”
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Evaluation of the predictors of tooth loss using artificial intelligence-based machine learning approach: A retrospective study by Amit Rajabhau Pawar, Sankari Malaiappan, Pradeep Kumar Yadalam, P R Ganesh

“…While challenges remain, such as data quality and privacy concerns, integrating machine learning algorithms in dentistry can revolutionize dental healthcare, improve patient outcomes, and reshape the future of periodontics.…”
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Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data by Munib Mesinovic, Peter Watkinson, Tingting Zhu

“…We compare standard supervised machine learning algorithms with novel tabular deep learning approaches and find that an integrated XGBoost model in our EHR time-series extraction framework (XMI-ICU) performs best. …”
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MODERN ANALYSIS METHODS USE IN ORDER TO ESTABLISH THE GEOGRAPHIC ORIGIN OF FOOD PRODUCTS by L. A. Oganesyants, A. L. Panasyuk, E. I. Kuzmina, D. A. Sviridov

“…The advantages of an integrated research approach, which includes the creation of data array of various indicators values and its in-depth analysis using chemometric algorithms and mathematical modeling methods, are shown.…”
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Fine-scale carbon stocks mapping in the mangrove forests of Tumaco, Colombia using machine learning and remote sensing approaches by Laura Lozano-Arias, Bryan Ernesto Gallego-Pérez, John Josephraj Selvaraj

“…This study presents an innovative approach that integrates remote sensing with field data, utilizing high-resolution imagery and evaluating two machine learning algorithms: Random Forest and Support Vector Regression. …”
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Active Vibration Control of Laminated Composite Beam Operating in Thermal Environment using PZT-5H Patches by Kuldeep Saini, Ravi Kiran Akumalla, Vinayak Kallannavar, Subhaschandra Kattimani

“…The adequate vibration attenuation of the glass-epoxy cantilever beam operating in various thermal environments is achieved using the proportional (P) and proportional-integral-derivative (PID) controllers. The vibration attenuation characteristics of the developed control algorithms are comprehensively investigated for a wide temperature range of –20 °C to 60 °C using PZT-5H patches. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…However, due to the low and sparse vegetation in alpine meadows, it is challenging to obtain pure vegetation pixels from Sentinel-2 imagery, resulting in errors in the FVC estimation using traditional pixel dichotomy models. This study integrated Sentinel-2 imagery with unmanned aerial vehicle (UAV) data and utilized the pixel dichotomy model together with four machine learning algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Deep Neural Network (DNN), to estimate FVC in an alpine meadow region. …”
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Exploring the capabilities of hyperspectral remote sensing for soil texture evaluation by Mohammad Hosseinpour-Zarnaq, Mahmoud Omid, Fereydoon Sarmadian, Hassan Ghasemi-Mobtaker, Reza Alimardani, Pouya Bohlol

“…The influence of spectral unmixing and vegetation effects on croplands significantly enhanced the prediction and mapping of soil texture using PRISMA data. Furthermore, integrating preprocessed hyperspectral data with DSM covariates resulted in improved predictive performance for sand and clay content, yielding R2 values of 0.64 and 0.51, respectively. …”
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Optimal Placement of Wind Power System Using Machine Learning by Abdul Karim, Muhammad Amir Raza, Darakhshan Ara, Muhammad Shahid, Shakir Ali Soomro

“…Hence, this study, proposed a plan for the installation of wind turbines in Doha Qatar, and forecasted the future temperature and wind speed for the optimal placement of large-scale wind turbines using the Pythons algorithms namely, Long Short-Term Memory (LSTM), Prophet (PT), Support Vector Regression (SVR), Linear Regression (LR), Seasonal Autoregressive Integrated Moving Average with External Factors (SARIMAX), and K-Nearest Neighbors (KNN). …”
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