IDENTIFICATION OF SMALL LAKES IN KAZAKHSTAN USING REMOTE SENSING DATA by Akmaral Tolepbayeva, Dinara Abiyeva, Roza Karagulova, Aigerim Tanbayeva, Zhanerke Sharapkhanova

“…A technique for automated extraction of morphometric characteristics of small lakes has been developed, data on lake morphometry have been obtained. Verification against field measurements demonstrated a high degree of accuracy, with relative error rates of 12% for lake lengths and 13% for the widths. …”
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Radar Sensor Data Fitting for Accurate Linear Sprint Modelling by Daniel Geneau, Patrick Cormier, Ming-Chang Tsai, Dana Agar-Newman, Seth Lenetsky, Marc Klimstra

“…Results: Significant differences (<i>p</i> < 0.001) were identified across the models in terms of goodness-of-fit and most FV metrics, with the sigmoid and polynomial functions demonstrating superior fit to the radar-collected velocity data. Conclusions: The results suggest that radar sensors, combined with appropriate modelling techniques, can significantly improve the accuracy of sprint performance analysis, offering valuable insights for both researchers and coaches. …”
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MONITORING DATA AGGREGATION OF DYNAMIC SYSTEMS USING INFORMATION TECHNOLOGIES by Dmytro Shevchenko, Mykhaylo Ugryumov, Sergii Artiukh

“…Looking at the results in general, the autoencoders work effectively for the dimensionality reduction task and the data recovery quality metric shows that they recover the data well with an error of 3–4 digits after 0. …”
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Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…The research integrates multiple ensemble techniques to develop a robust and efficient framework for seismic data analysis. These models offer superior performance in handling large datasets, noise reduction, and feature extraction, making them ideal for this application. …”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…Typically, crop yield prediction relies on features derived from direct field observations, either gathered through sensor measurements or manual data collection. However, enhancing prediction models by incorporating new features extracted through regressions executed on the original dataset features can potentially improve predictive outcomes. …”
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Possibility of using remote sensing data for glaciological calculations and monitoring by V. G. Konovalov, V. A. Rudakov

“…Additional processing should be provided to exclude asynchronies in morphometric parameters. This will reduce errors in glaciological interpretation of satellite images and improve the quality of spatial extrapolation of meteorological data. …”
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The reliability of tax data for measuring disposable income inequality in Poland by Marcin Gorazda, Tomasz Kwarciński

“…The analysis draws on data from tax reports, national accounts, and a review of relevant literature on taxpayer behaviour. …”
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Artificial Intelligence and Ontologies for the Management of Heritage Digital Twins Data by Achille Felicetti, Franco Niccolucci

“…After providing an overview of the ontological model underlying the RHDT paradigm, this paper investigates the application of AI to improve data analysis and predictive capabilities of Heritage Digital Twins in synergy with the previously defined RHDTO semantic model. …”
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Performance Modeling of Data Storage Systems Using Generative Models by Abdalaziz R. Al-Maeeni, Aziz Temirkhanov, Artem Ryzhikov, Mikhail Hushchyn

“…High-precision systems modeling is one of the main areas of industrial data analysis. Models of systems, their digital twins, are used to predict their behavior under various conditions. …”
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Imputation for Missing Data in Statistical Matching Using Goal Programming by Abeer M. M. Elrefaey, Ramadan Hamed, Elham A. Ismail, Safia M. Ezzat

“…Nearly all common statistical approaches assume complete information for all variables involved in the analysis, which making missing data problematic. Imputation is the process of substituting a missing value with a specific value, and it is most likely the most popular method for compensating for missing item values in a survey. …”
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Enabling data-driven design of block copolymer self-assembly by Chiara Magosso, Irdi Murataj, Michele Perego, Gabriele Seguini, Debra J. Audus, Gianluca Milano, Federico Ferrarese Lupi

“…This approach has numerous advantages including ease of sharing, reusability of information and resilience against user errors. This database follows the digital International System of Units principles and is complemented by a graphical user interface for process metadata insertion and an automated algorithm for image analysis to retrieve structural properties of the nanostructures. …”
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Cardiac disease diagnosis based on GAN in case of missing data. by Xing Chen, Na Zhang, Xiaohui Yang, Chunyan Wang, Qi Na, Tianyun Luan, Wendi Zhu, Chenjie Zhang, Chao Yang

“…The presence of incomplete data significantly reduces the quality of the published data, hindering the timely analysis of data and the generation of reliable knowledge by epidemiologists, public health authorities, and researchers. …”
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Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

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Healthcare data governance assessment based on hospital management perspectives by Shinta Oktaviana R, Putu Wuri Handayani, Achmad Nizar Hidayanto, Bambang Budi Siswanto

“…These problems raise healthcare expenses, cause errors in patient treatment, and consume a lot of hospital IT personnel's work time for data extraction and synchronization. …”
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Orbital Parameters of 665 Double-lined Spectroscopic Binaries in the LAMOST Medium-resolution Survey by Sufen Guo, Mikhail Kovalev, Jiao Li, Guoliang Lü, Shi Jia, Zhenwei Li, Jiangdan Li, Jianping Xiong, Mingkuan Yang, Tongyu He, Xuefei Chen, Zhanwen Han

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Integrating the Prior Shape Knowledge Into Deep Model and Feature Fusion for Topologically Effective Brain Tumor Segmentation by Salma Asif, Ahmad Raza Shahid, Kiran Aftab, Syed Ather Enam

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Uncertainty-Based Fusion Method for Structural Modal Parameter Identification by Xiaoteng Liu, Zirui Dong, Hongxia Ji, Zhenjiang Yue, Jie Kang

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The Impact of Cloud Versus Local Infrastructure on Automatic IoT-Driven Hydroponic Systems by Cosmina-Mihaela Rosca, Adrian Stancu, Marian Popescu

“…The limitations of this research are associated with the exclusion of human errors and cybernetics simulations from the analysis. …”
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Morphosyntactic Study Of Urdu Esl Learners: A Derivation By Interface by Asad Ali, Aqsa Younis, Qaisar Jabbar, Sidra Niazi

“…The aim of this study is to analyze the interface of syntax/ morphology of L2 English of Urdu Learners. For the analysis of morphology/syntax interface, the data is collected from 15 students of Grammar Model high school through essay writing. …”
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