Relevant bibliographies by topics / Statistical data processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistical data processing'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Statistical data processing"

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OHE, Shuzo. "Statistical Data Processing." Journal of the Japan Society of Colour Material 67, no. 9 (1994): 590–95. http://dx.doi.org/10.4011/shikizai1937.67.590.

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MILOSAN, Ioan. "STATISTICAL PROCESSING OF EXPERIMENTAL DATA USING ANALYSIS OF VARIANCE." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (2016): 489–96. http://dx.doi.org/10.19062/2247-3173.2016.18.1.67.

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Šķiltere, Daina, and Svetlana Jesiļevska. "Data quality evaluation in statistical data processing." Statistical Journal of the IAOS: Journal of the International Association for Official Statistics 30, no. 4 (2014): 425–30. https://doi.org/10.3233/sji-140806.

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National Statistical Offices (NSO's) need data for the production of statistics. Apart from data obtained through surveys, NSO's are increasingly using other data sources (for example, data collected by other organizations). Disadvantages here come from the fact that very often an NSO uses an administrative data source for a purpose different than the one for which the data was originally collected. As a result of this difference, the 'statistical' usability of a data source needs to be thoroughly studied by an NSO before its use. Some more possible problems of statistics are the following: da
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Neubauer, Jiří, Oldřich Kříž, and Marek Sedlačík. "Statistical Data Processing in STAT1 Application." Vojenské rozhledy 22, no. 3 (2013): 114–22. http://dx.doi.org/10.3849/2336-2995.22.2013.03.114-122.

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Smit, Suzanne, Huub C. J. Hoefsloot, and Age K. Smilde. "Statistical data processing in clinical proteomics." Journal of Chromatography B 866, no. 1-2 (2008): 77–88. http://dx.doi.org/10.1016/j.jchromb.2007.10.042.

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Shermukhamedov, A. T., and Yo Ilkhamova. "STATISTICAL DATA PROCESSING IN THE DIGITAL ECONOMY." Theoretical & Applied Science 94, no. 02 (2021): 177–79. http://dx.doi.org/10.15863/tas.2021.02.94.41.

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Vidal, David, and Annio Moreno. "Statistical parameter flexibility for processing navigation data." Leading Edge 29, no. 4 (2010): 414–16. http://dx.doi.org/10.1190/1.3378305.

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Pankov, A. R., and A. M. Skuridin. "Data Processing Under A Priori Statistical Uncertainty." IFAC Proceedings Volumes 19, no. 5 (1986): 213–17. http://dx.doi.org/10.1016/s1474-6670(17)59796-7.

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Atzeni, Paolo, Luigi Bellomarini, Francesca Bugiotti, and Marco De Leonardis. "Executable schema mappings for statistical data processing." Distributed and Parallel Databases 36, no. 2 (2017): 265–300. http://dx.doi.org/10.1007/s10619-017-7212-2.

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Norin, Veniamin, and Yurii Pukharenko. "Statistical processing of traffic flow characteristics data." E3S Web of Conferences 371 (2023): 04031. http://dx.doi.org/10.1051/e3sconf/202337104031.

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In the course of statistical processing of traffic flows characteristics data, the check for the presence of anomalous measurements in the sampling should be done at the very start of processing. If anomalous measurements are detected, they should be excluded from the sampling at an early stage of the processing and not taken into considerations in further calculations. Numerous criteria have been developed to detect outliers, their effectiveness depends on the sample size. In practice, for technical and economic reasons, it is impractical to obtain a large number of measurements, as a rule th
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Dissertations / Theses on the topic "Statistical data processing"

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Fernandez, Noemi. "Statistical information processing for data classification." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/3297.

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This thesis introduces new algorithms for analysis and classification of multivariate data. Statistical approaches are devised for the objectives of data clustering, data classification and object recognition. An initial investigation begins with the application of fundamental pattern recognition principles. Where such fundamental principles meet their limitations, statistical and neural algorithms are integrated to augment the overall approach for an enhanced solution. This thesis provides a new dimension to the problem of classification of data as a result of the following developments: (1
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Clapp, T. C. "Statistical methods for the processing of communications data." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597697.

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This thesis describes the use of methods derived from Bayesian statistics on the problem of blind equalisation of communications channels, although much of this work is applicable to the more general problem of blind deconvolution. In order to allow general models to be incorporated, numerical methods are used; the focus is on <I>Markov chain Monte Carlo </I>(MCMC) methods for processing of blocks of data and the use of <I>particle filters </I>for sequential processing. In order to obtain the best performance using MCMC, the choice of the Markov chain needs tailoring to the application in hand
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Khondoker, Md Mizanur Rahman. "Statistical methods for pre-processing microarray gene expression data." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/12367.

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A novel method is developed for combining multiple laser scans of microarrays to correct for “signal saturation” and “signal deterioration” effects in the gene expression measurement. A multivariate nonlinear functional regression model with Cauchy distributed errors having additive plus multiplicative scale is proposed as a model for combining multiple scan data. The model has been found to flexibly describe the nonlinear relationship in multiple scan data. The heavy tailed Cauchy distribution with additive plus multiplicative scale provides a basis for objective and robust estimation of gene
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Wang, Yun, and Wenxuan Jiang. "Statistical Processing of IEEE 802.15.4 Data Collected in Industrial Environment." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-19619.

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Wireless sensor network, which is constitute of autonomous sensors, is used for monitoring physical or environmental conditions like temperature, sound, pressure, and so on. The dispersed sensors or nodes will respectively pass their data through the network to the main location. Currently, several standards are ratified or in developing for wireless sensor network, like Wireless Hart, ISA, 100.11a, WIA-PAA, IEEE 802.15.4, etc. Among the standards, Zigbee is often used in industrial applications that require short-range and low-rate wireless transfer. In the research, all the data is collected
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Patel, Ankur. "3D morphable models : data pre-processing, statistical analysis and fitting." Thesis, University of York, 2011. http://etheses.whiterose.ac.uk/1576/.

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This thesis presents research aimed at using a 3D linear statistical model (known as a 3D morphable model) of an object class (which could be faces, bodies, cars, etc) for robust shape recovery. Our aim is to use this recovered information for the purposes of potentially useful applications like recognition and synthesis. With a 3D morphable model as its central theme, this thesis includes: a framework for the groupwise processing of a set of meshes in dense correspondence; a new method for model construction; a new interpretation of the statistical constraints afforded by the model and addres
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Deel, Troy A. "A statistical study of graph algorithms." Virtual Press, 1985. http://liblink.bsu.edu/uhtbin/catkey/424871.

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The object of this paper is to investigate the behavior of some important graph properties and to statistically analyze the execution times of certain graph are the average degree of a vertex, connectivity of a graph, the existence of Hamilton cycles, Euler tours, and bipartitions in graphs. This study is unique in that it is based on statistical rather than deterministic methods.
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He, Zhenyu. "Writer identification using wavelet, contourlet and statistical models." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/767.

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Chong, Wai Yu Ryan. "Statistical and analytic data processing based on SQL7 with web interface." Leeds, 2001. http://www.leeds.ac.uk/library/counter2/compstmsc/20002001/chong.pdf.

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ALMEIDA, Marcos Antonio Martins de. "Statistical analysis applied to data classification and image filtering." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/25506.

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Submitted by Fernanda Rodrigues de Lima (fernanda.rlima@ufpe.br) on 2018-08-03T20:52:13Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) TESE Marcos Antonio Martins de Almeida.pdf: 11555397 bytes, checksum: db589d39915a5dda1d8b9e763a9cf4c0 (MD5)<br>Approved for entry into archive by Alice Araujo (alice.caraujo@ufpe.br) on 2018-08-09T20:49:00Z (GMT) No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) TESE Marcos Antonio Martins de Almeida.pdf: 11555397 bytes, checksum: db589d39915a5dda1d8b9e763a9cf4c0 (MD5)<
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Chen, Li. "Statistical Machine Learning for Multi-platform Biomedical Data Analysis." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/77188.

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Recent advances in biotechnologies have enabled multiplatform and large-scale quantitative measurements of biomedical events. The need to analyze the produced vast amount of imaging and genomic data stimulates various novel applications of statistical machine learning methods in many areas of biomedical research. The main objective is to assist biomedical investigators to better interpret, analyze, and understand the biomedical questions based on the acquired data. Given the computational challenges imposed by these high-dimensional and complex data, machine learning research finds its new opp
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Books on the topic "Statistical data processing"

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Kiselev, I︠U︡. V. (I︠U︡riĭ Vasilʹevich), ed. Statistical methods of geophysical data processing. World Scientific, 2010.

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Hale, Robert L. MYSTAT: Statistical applications. Course Technology, 1992.

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McCuen, Richard H. Microcomputer applications in statistical hydrology. Prentice Hall, 1993.

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A, Aitkin Murray, ed. Statistical modelling in GLIM. Clarendon Press, 1989.

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Froeschl, Karl. Metadata management in statistical information processing: A unified framework for metadata-based processing of statistical data aggregates. Springer, 1997.

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Thisted, Ronald A. Elements of statistical computing. Chapman and Hall, 1988.

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1952-, Reimann Clemens, ed. Statistical data analysis explained: Applied environmental statistics with R. John Wiley & Sons, 2008.

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Goyal, M. Computer-based numerical & statistical techniques. Infinity Science Press, 2007.

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United States. Bureau of the Census. 1980 census of population and housing: History : Data processing : Data products. U.S. Department of Commerce, Bureau of the Census, 1989.

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National Institutes of Health (U.S.). Division of Research Resources and Bolt, Beranek, and Newman, inc, eds. PROPHET statistics: A user's guide to the statistical analysis on the PROPHET system. The Division, 1985.

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Book chapters on the topic "Statistical data processing"

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Kundu, Debasis, and Swagata Nandi. "Real Data Example." In Statistical Signal Processing. Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0628-6_6.

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Ratkó, István. "Statistical Data Processing by Microcomputer." In Medical Informatics Europe 85. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-93295-3_159.

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MÜHLBAUER, JOHANN A. "Processing Outliers in Statistical Data." In ACS Symposium Series. American Chemical Society, 1985. http://dx.doi.org/10.1021/bk-1985-0284.ch004.

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Babak, Vitalii, Serhii Babak, Volodymyr Eremenko, Yurii Kuts, and Artur Zaporozhets. "Statistical Processing of Measurement Data." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89406-0_5.

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Nandi, Swagata, and Debasis Kundu. "Real Data Example Using Sinusoidal-Like Models." In Statistical Signal Processing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8_7.

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Scharf, Louis L. "Signal Processing in the Linear Statistical Model." In Underwater Acoustic Data Processing. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_25.

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Rabinovich, Semyon G. "Statistical Methods for Experimental Data Processing." In Evaluating Measurement Accuracy. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6717-5_3.

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Rabinovich, Semyon G. "Statistical Methods for Experimental Data Processing." In Evaluating Measurement Accuracy. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1456-9_3.

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Rabinovich, Semyon G. "Statistical Methods for Experimental Data Processing." In Measurement Errors and Uncertainties. Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4757-3256-6_4.

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Rabinovich, Semyon G. "Statistical Methods for Experimental Data Processing." In Evaluating Measurement Accuracy. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60125-0_3.

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Conference papers on the topic "Statistical data processing"

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Evdokimova, S. A., and A. N. Jenkov. "METHODS OF STATISTICAL DATA PROCESSING." In Аспекты моделирования систем и процессов. Воронежский государственный лесотехнический университет им. Г.Ф. Морозова, 2022. http://dx.doi.org/10.58168/amsp2022_121-129.

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Mach, Pavel, Josef Thuring, and David Samal. "Transformation of Data for Statistical Processing." In 2006 29th International Spring Seminar on Electronics Technology. IEEE, 2006. http://dx.doi.org/10.1109/isse.2006.365112.

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Toth, Peter, Imre Fodor, Zoltan Lorincz, and Peter Nagy. "General approach to statistical data processing." In 2008 30th International Conference on Information Technology Interfaces (ITI). IEEE, 2008. http://dx.doi.org/10.1109/iti.2008.4588443.

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Zaliskyi, Maksym, Oleksandr Solomentsev, Olena Kozhokhina, and Tetyana Herasymenko. "Statistical Data Processing for Condition-based Maintenance." In 2019 Signal Processing Symposium (SPSympo). IEEE, 2019. http://dx.doi.org/10.1109/sps.2019.8882103.

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Ponomarenko, Alexey. "Reformatting statistical education in Russia: changes in classifications, standards, and programs." In Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17314.

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In the centrally planned economy the main function of official statistics was monitoring of plans’ execution. Hence, official statisticians had to be experts in economics and bookkeeping, like tax inspectors. Russian statistical education was oriented mostly to official needs and statistics was included in the same educational group as economics. Currently, professional requirements for statisticians have changed. Official statistics lost its control function, and the old reporting system is being replaced by sample surveys that are less onerous for respondents and also less expensive. The sta
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Kumar, Anil, V. K. Dadhwal, and S. K. Ghosh. "ASTER data processing using statistical learning algorithm." In Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications. SPIE, 2006. http://dx.doi.org/10.1117/12.693501.

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Rocha, A. C. "Statistical processing of radiometer data using MATLAB." In 11th International Conference on Antennas and Propagation (ICAP 2001). IEE, 2001. http://dx.doi.org/10.1049/cp:20010265.

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Solomentsev, Oleksandr, Maksym Zaliskyi, Oleksiy Zuiev, and Ivan Yashanov. "Truncated Sequential Procedure of Statistical Data Processing." In 2023 IEEE 4th KhPI Week on Advanced Technology (KhPIWeek). IEEE, 2023. http://dx.doi.org/10.1109/khpiweek61412.2023.10312909.

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Kozhokhina, O. V., V. M. Gribov, and L. V. Blahaia. "Processing statistical data about UAV operator errors." In 2015 IEEE International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD). IEEE, 2015. http://dx.doi.org/10.1109/apuavd.2015.7346578.

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Marhoum, Adil. "Plenary lecture: the teaching of statistics in morocco l’enseignement de la statistique au maroc." In Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17103.

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Discussing higher education in Morocco, particularly about statistics, the talk reflects on the following points: • Interest of statistics • Place of statistics in education programs in Morocco • Difficulties in teaching statistics • Teachers of statistics and teaching methods • Suggestions for further increasing the penetration of statistics into curricula Various reforms of Moroccan education have consistently placed more emphasis on the teaching of statistics. This teaching is currently being introduced in most of the training streams, such as economics, management sciences, and agronomic s
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Reports on the topic "Statistical data processing"

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Ranjan, Niloo, Jibonananda Sanyal, and Joshua Ryan New. In-Situ Statistical Analysis of Autotune Simulation Data using Graphical Processing Units. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1093099.

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Koopman, D. STATISTICAL EVALUATION OF PROCESSING DATA FROM THE RH RU HG MATRIX STUDY. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/952445.

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Boyd, Thomas J., and Richard B. Coffin. Isotope Ratio Spectrometry Data Processing Software: Multivariate Statistical Methods for Hydrocarbon Source Identification and Comparison. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada422798.

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Fuentes, Anthony, Michelle Michaels, and Sally Shoop. Methodology for the analysis of geospatial and vehicle datasets in the R language. Cold Regions Research and Engineering Laboratory (U.S.), 2021. http://dx.doi.org/10.21079/11681/42422.

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The challenge of autonomous off-road operations necessitates a robust understanding of the relationships between remotely sensed terrain data and vehicle performance. The implementation of statistical analyses on large geospatial datasets often requires the transition between multiple software packages that may not be open-source. The lack of a single, modular, and open-source analysis environment can reduce the speed and reliability of an analysis due to an increased number of processing steps. Here we present the capabilities of a workflow, developed in R, to perform a series of spatial and
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Mazorchuk, Mariia S., Tetyana S. Vakulenko, Anna O. Bychko, Olena H. Kuzminska, and Oleksandr V. Prokhorov. Cloud technologies and learning analytics: web application for PISA results analysis and visualization. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4451.

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This article analyzes the ways to apply Learning Analytics, Cloud Technologies, and Big Data in the field of education on the international level. This paper provides examples of international analytical researches and cloud technologies used to process the results of those researches. It considers the PISA research methodology and related tools, including the IDB Analyzer application, free R intsvy environment for processing statistical data, and cloud-based web application PISA Data Explorer. The paper justifies the necessity of creating a stand-alone web application that supports Ukrainian
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Bates, C. Richards, Melanie Chocholek, Clive Fox, John Howe, and Neil Jones. Scottish Inshore Fisheries Integrated Data System (SIFIDS): Work package (3) final report development of a novel, automated mechanism for the collection of scallop stock data. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23449.

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[Extract from Executive Summary] This project, aimed at the development of a novel, automated mechanism for the collection of scallop stock data was a sub-part of the Scottish Inshore Fisheries Integrated Data Systems (SIFIDS) project. The project reviewed the state-of-the-art remote sensing (geophysical and camera-based) technologies available from industry and compared these to inexpensive, off-the -shelf equipment. Sea trials were conducted on scallop dredge sites and also hand-dived scallop sites. Data was analysed manually, and tests conducted with automated processing methods. It was con
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van der Sloot, Bart. The Quality of Life: Protecting Non-personal Interests and Non-personal Data in the Age of Big Data. Universitätsbibliothek J. C. Senckenberg, Frankfurt am Main, 2021. http://dx.doi.org/10.21248/gups.64579.

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Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- crimin
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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Alwan, Iktimal, Dennis D. Spencer, and Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.

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Objective: To compare the performance of popular machine learning algorithms (ML) in mapping the sensorimotor cortex (SM) and identifying the anterior lip of the central sulcus (CS). Methods: We evaluated support vector machines (SVMs), random forest (RF), decision trees (DT), single layer perceptron (SLP), and multilayer perceptron (MLP) against standard logistic regression (LR) to identify the SM cortex employing validated features from six-minute of NREM sleep icEEG data and applying standard common hyperparameters and 10-fold cross-validation. Each algorithm was tested using vetted feature
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Kvasnytsia, Olha, Iryna Sniadanko, and Khrystyna Verbytska. THE ROLE OF SENSE OF LIFE ORIENTATIONS IN THE FORMATION OF EXISTENTIAL FULFILLMENT OF STUDENT-JOURNALISTS. Ivan Franko National University of Lviv, 2025. https://doi.org/10.30970/vjo.2025.56.13277.

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Aim. The purpose of the article is to analyse the relationship between the level of existential fulfillment, sense- of- life and value orientations of students majoring in “Journalism”. The results of the study will contribute to the psychological preparation of students majoring in journalism for future professional activities. The article is based on the analysis of the relationship between the level of existential fulfillment, sense-of -life and value orientations of students majoring in “Journalism”. The article reveals the content and significance of existential fulfillment, sense-of-life
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