Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning by Yongjie Ma, Lin Tian, Fuhang Hu, Jingyong Wang, Echuan Yan, Yanjun Zhang

“…Thermal conductivity prediction models were constructed using Support Vector Machine (SVM), Random Forest (RF), and Backpropagation Neural Network(BPNN). Results showed that data augmentation significantly improved model performance: the RF model exhibited the best improvement, with its coefficient of determination R² increasing from 0.7489 to 0.9765, Root Mean Square Error (RMSE) decreasing from 0.1870 to 0.1271, and Mean Absolute Error (MAE) reducing from 0.1453 to 0.0993. …”
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KESALAHAN BERBAHASA BIDANG MORFOLOGI PADA PLATFORM INSTAGRAM by Nadia Putri Prastikha, Pipin Sri Lestari, Ramadhan Ahmad Nuridayah, Markamah Markamah

“… This research aims to identify and analyze language errors in the field of morphology found on the Instagram platform. …”
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Polynomial estimates of measurand parameters for data from bimodal mixtures of exponential distributions by S.V. Zabolotnii, V.Yu. Kucheruk, Z.L. Warsza, А.K. Khassenov

“…The reduction coefficient depends on the values of the 4th and 6th order cumulant coefficients that characterize the degree of difference while the distribution of sample data from the Gaussian model. By means of multiple statistical tests (Monte Carlo method), the properties of the normalization of polynomial estimates are investigated and a comparative analysis of their accuracy with known estimates (mean, median and center of folds) is made. …”
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Forecasting Stock Value Based on Data from Social Media and Investment Instruments by Ömer Faruk Uyrun, İbrahim Sabuncu

“…This study aimed to predict stocks using different machine learning techniques with social media data and investment instrument data. Within the scope of the study, 236,764 tweets related to five different airline companies during the period October 2019 - February 2020, the stock value of those companies, the daily data of the stock market, dollar rate and gold prices were discussed. …”
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Automated generation of discharge summaries: leveraging large language models with clinical data by Matthias Ganzinger, Nicola Kunz, Pascal Fuchs, Cornelia K. Lyu, Martin Loos, Martin Dugas, Thomas M. Pausch

“…After de-identifying 25 patient datasets, we optimized the output of the LLaMA3 model through prompt engineering and evaluated it using error analysis, as well as quantitative and qualitative metrics. …”
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Identifying and Minimising Uncertainty for Experimental Journal Bearing Studies by G. D. Wale, D. Mba

“…Over the last few decades, different experimental methods, with varying forms of data analysis, have been employed on a wide range of journal bearing types. …”
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Enhancing Mars Gravity Field Solutions with China’s Tianwen-1 Tracking Data by Shangbiao Sun, Jianguo Yan, Shanhong Liu, Chongyang Wang, Denggao Qiu, Jean-Pierre Barriot

“…The range of gravity anomaly errors improves after incorporating TW1 data, with the maximum error decreasing from 53.4 to 46.4 mGal and the average error improving from 8.4 to 7.3 mGal. …”
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Aircraft Gas Turbine Engine Health Monitoring System by Real Flight Data by Mustagime Tülin Yildirim, Bülent Kurt

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A non-stationary panel data approach for examining convergence in South Africa by Stacey-Lee Marais

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Algorithms for big data mining of hub patent transactions based on decision trees by Zhukov Aleksandr, Pronichkin Sergey, Mihaylov Yuri, Kartsan Igor

“…One of the most promising methods for improving the accuracy of system analysis of big and semi-structured patent transaction data is the use of decision trees. …”
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BankNet: Real-Time Big Data Analytics for Secure Internet Banking by Kaushik Sathupadi, Sandesh Achar, Shinoy Vengaramkode Bhaskaran, Nuruzzaman Faruqui, Jia Uddin

“…This paper introduces BankNet, a predictive analytics framework integrating big data tools and a BiLSTM neural network to deliver high-accuracy transaction analysis. …”
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Myopia Prevalence and its Correlation with Demographic Characteristics Before the COVID-19 Pandemic among Acehnese School Children (6-19 years) in Indonesia by Yusni YUSNI, Firdalena MEUTIA

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Research on the Effect of Data Assimilation for Three‐Dimensional MHD Simulation of Solar Wind by Hanke Zhang, Fang Shen, Yi Yang

“…The numerical model generates two separate results, one without DA and one with DA directly performed on the model‐only results. Statistical analysis of observed, modeled and assimilated solar wind parameters at 1 AU reveals that assimilating simulations provide a more accurate forecast than the model‐only results with a sharp reduction in the root mean square error and an increase of correlation coefficient.…”
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Acquisition of Current and Vibration Data for Rewound Burnt Three-Phase Induction Motor by A.I. Abdullateef, O.S. Fagbolagun, M.F. Sanusi

“…The Mean Square Error value of the acquired and measured data is 0.00002. …”
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Bridge Cable Performance Warning Method Based on Temperature and Displacement Monitoring Data by Yan Shi, Yan Wang, Lu-Nan Wang, Wei-Nan Wang, Tao-Yuan Yang

“…Correlation analysis revealed a strong linear correlation between air temperature and quasi-static tower-girder displacements. …”
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Acquisition of Current and Vibration Data for Rewound Burnt Three-Phase Induction Motor by A.I. Abdullateef, O.S. Fagbolagun, M.F. Sanusi

“…The Mean Square Error value of the acquired and measured data is 0.00002. …”
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Reproduction of experimental data for stacked caffeine dimers using various computational methods by Maria Patricia Sanchez Gutierrez, Eduardo Gonzalez Jimenez, Alexandra Deriabina, Juan Carlos Sanchez Perez, Valeri Poltev

“…These methods are: the MP2 with Basis Set Superposition Error correction (MP2/CP), Poltev force field, along with PBE0-DH, SCAN and PBE-D3 functionals of DFT. …”
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Data Quality Improvement Method for Power Equipment Condition Based on Stacked Denoising Autoencoders Improved by Particle Swarm Optimization by JI Rong, HOU Huijuan, SHENG Gehao, ZHANG Lijing, SHU Bo, JIANG Xiuchen

“…However, equipment failures and personnel errors result in dirty data, having a negative effect on data quality and subsequent analysis results. …”
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Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

“…This study analyzes spatiotemporal CO patterns and builds accurate predictive models using five years (2018–2022) of data from ten monitoring stations, combined with meteorological variables. …”
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A spatial clustering-based approach to design monitoring networks of infectious diseases: a case study of hand, foot, and mouth disease by Shuting Li, Yuanhua Liu, Ke Li, Zengliang Wang, Michael P. Ward, Wei Tu, Jiayao Xu, Rui Yuan, Lele Zhang, Na Wang, Jidan Zhang, Yu Zhao, Henry S. Lynn, Zhaorui Chang, Zhijie Zhang

“…First, we used Spatial Kluster Analysis by Tree Edge Removal (SKATER) to stratify the data. …”
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