Methodological Aspects of Data Management at the Enterprise by E. N. Sheremetyeva, A. K. Adgizalova, Yu. G. Popov

“…This article explores the formation of a unified methodological framework for data management within modern enterprises. The relevance of the topic stems from ongoing changes in economic and social structures, driven by digital transformation and the increasing importance of information as a critical resource. …”
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Research on Big Data Application for Security by Deli Yang, Tao Zhang

“…Several data sources of big data on security were described，a closer look was taken at the implementation of big data platform on security，the main points and steps during the implementation were also proposed.Specially，detail analysis on the overall architecture and system structure of the big data platform on security were provided，the relationship with the existing video surveillance platform was also described.The implementation of big data platform on security must be promoted on the scale of data characteristics and algorithm maturity.…”
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Big Data Driving Economic Transformation by Wenjian Liu, Sude Qing

“…Big data are widely woven into every sector and play an important role in the global economy as an essential factor of production.Big data can be brought together and analyzed to discern patterns,make better decisions so as to reduce production cost and increase the quality of products and services.A concise and comprehensive description that big data would have a significant influence on the structure of traditional industry including agriculture,industry and services,was given.Obviously,the big data industry is currently becoming a new economic growth point,promoting economic transformation and upgrading.…”
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Big Data Driving Economic Transformation by Wenjian Liu, Sude Qing

“…Big data are widely woven into every sector and play an important role in the global economy as an essential factor of production.Big data can be brought together and analyzed to discern patterns,make better decisions so as to reduce production cost and increase the quality of products and services.A concise and comprehensive description that big data would have a significant influence on the structure of traditional industry including agriculture,industry and services,was given.Obviously,the big data industry is currently becoming a new economic growth point,promoting economic transformation and upgrading.…”
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METHOD OF CONSTRUCTION OF GENETIC DATA CLUSTERS by N. A. Novoselova, I. E. Tom

“…In a comparative experiment with the analogs the proposed method shows the advantage in allocating statistically significant different-sized clusters, the ability to filter non- informative genes and to extract the biologically interpretable functional modules matching the real data structure.…”
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Application and practice of industrial big data by Aijin YUAN, Binnan YUE, Xin YAN, Jian HUANG

“…With the advent of the Internet of things and the era of Cyber Physical System,more data can be collected and analyzed,and industrial big data have become important driving force for industry innovation and transformation.Unlike traditional Internet big data,industrial big data are closely integrated with industrial logic.The difference between industrial big data and internet big data was compared in detail.Combined with the classical cases,the process of demand driven transformation of traditional manufacturing industry and the development path of industrial big data were expounded.The structure and working principles of industrial big data platform were introduced.At last,taking the excavator business as an example,it shows the application effect of the industrial big data platform,and that having a share in data and models will make data based application produce more value was put forward.…”
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Embedding With Preservation of Semantics of the Original Data by M. E. Vatkin, D. A. Vorobey, M. V. Yakovlev, M. G. Krivova

“…In the modern world, the data used to describe objects is often presented as sparse vectors with a large number of features. …”
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Data caching technologies in modern microprocessors by V. A. Egunov, V. A. Shabalovsky

“…The study presented in the paper is aimed at studying the methods for improving the efficiency of software in modern computing systems with a hierarchical memory structure. Method. The study is based on data caching technologies in microprocessors. …”
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Big data for imaging assessment in glaucoma by Douglas R. da Costa, Felipe A. Medeiros

“…This review evaluates the use of Big Data and AI in glaucoma research, providing an overview of most relevant topics and discussing various models for screening, diagnosis, monitoring disease progression, correlating structural and functional changes, assessing image quality, and exploring innovative technologies such as generative AI.…”
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Data Inconsistency Evaluation for Cyberphysical System by Hao Wang, Jianzhong Li, Hong Gao

“…To deal with the large dynamic data, we provide a compact structure based on B-tree for storing independent residual subgraph in order to update inconsistency efficiently. …”
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Efficient processing of raster and vector data. by Fernando Silva-Coira, José R Paramá, Susana Ladra, Juan R López, Gilberto Gutiérrez

“…More concretely, we present algorithms for solving a spatial join between a raster and a vector dataset imposing a restriction on the values of the cells of the raster; and an algorithm for retrieving K objects of a vector dataset that overlap cells of a raster dataset, such that the K objects are those overlapping the highest (or lowest) cell values among all objects. The raster data is stored using a compact data structure, which can directly manipulate compressed data without the need for prior decompression. …”
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The Logarithmic Derivative in Scientific Data Analysis by Ruediger Grunwald

“…The logarithmic derivative has been shown to be a useful tool for data analysis in applied sciences because of either simplifying mathematical procedures or enabling an improved understanding and visualization of structural relationships and dynamic processes. …”
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Data Domain Servitization for Microservices Architecture by Patricio Michael Paccha, Victor Vicente Velepucha

“…This article reports an empirical study based on a systematic literature review aimed at identifying modeling techniques for segmenting data structures during microservice design. The review found limited methods to address the appropriate level of data granularity per microservice. …”
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Digital Bibliography in the Age of Linked Data by Kate Ozment

“…The article argues that as data from the ESTC is reproduced through linked data structures, information is ‘authorized’ far beyond what a single resource would do alone or what its original authors imagined or designed. …”
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An Exploration of Consistency Learning with Data Augmentation by Connor Shorten, Taghi M. Khoshgoftaar

“…Nearly all of these successes require very large manually annotated datasets. Data augmentation has enabled Supervised Learning with less labeled data, while avoiding the pitfalls of overfitting. …”
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Data preparation in crowdsourcing for pedagogical purposes by Tanara Zingano Kuhn, Špela Arhar Holdt, Iztok Kosem, Carole Tiberius, Kristina Koppel, Rina Zviel-Girshin

“…The focus of this paper is on data preparation, given the crucial role that such a stage plays in any crowdsourcing project dealing with the creation of language learning resources. …”
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The Property Graph Data Format (PGDF) by Renzo Angles, Sebastian Ferrada, Ignacio Burgos

“…The simplicity of PGDF comes from its tabular-like structure, where each line in a PGDF file contains a single schema or data declaration. …”
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MANAGEMENT OF PERSONAL DATA PROCESSING AND PROTECTION by Elena COFAS

“…To address these worries, the European Union has implemented a comprehensive regulatory structure, widely recognized as the General Data Protection Regulation (GDPR). …”
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Technology for collecting and analyzing relational data by E. N. Fedorova, G. M. Ruzhnikov, R. K. Fedorov

“…System operation "Faramant" is based on a model document, which includes three components: description of the data structure; visualization; logic of form work. …”
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Selective Dynamical Imaging of Interferometric Data by Joseph Farah, Peter Galison, Kazunori Akiyama, Katherine L. Bouman, Geoffrey C. Bower, Andrew Chael, Antonio Fuentes, José L. Gómez, Mareki Honma, Michael D. Johnson, Yutaro Kofuji, Daniel P. Marrone, Kotaro Moriyama, Ramesh Narayan, Dominic W. Pesce, Paul Tiede, Maciek Wielgus, Guang-Yao Zhao, The Event Horizon Telescope Collaboration, Antxon Alberdi, Walter Alef, Juan Carlos Algaba, Richard Anantua, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Bradford A. Benson, Dan Bintley, Lindy Blackburn, Raymond Blundell, Wilfred Boland, Hope Boyce, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Sandra Bustamente, Do-Young Byun, John E. Carlstrom, Chi-kwan Chan, Koushik Chatterjee, Shami Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Thomas M. Crawford, Geoffrey B. Crew, Alejandro Cruz-Osorio, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, H. Alyson Ford, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, Charles F. Gammie, Roberto Garc’a, Olivier Gentaz, Ciriaco Goddi, Roman Gold, Arturo I. Gómez-Ruiz, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Daryl Haggard, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Alejandra Jimenez-Rosales, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Dong-Jin Kim, Jae-Young Kim, Jongsoo Kim, Junhan Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Carsten Kramer, Michael Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Aviad Levis, Yan-Rong Li, Zhiyuan Li, Rocco Lico, Greg Lindahl, Michael Lindqvist, Jun Liu, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Nicola Marchili, Sera Markoff, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Izumi Mizuno, Yosuke Mizuno, James M. Moran, Monika Moscibrodzka, Cornelia Müller, Alejandro Mus Mejas, Gibwa Musoke, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Gopal Narayanan, Iniyan Natarajan, Antonios Nathanail, Joey Neilsen, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Michael A. Nowak, Hiroki Okino, Héctor Olivares, Gisela N. Ortiz-León, Tomoaki Oyama, Feryal zel, Daniel C. M. Palumbo, Jongho Park, Nimesh Patel, Ue-Li Pen, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Felix M. Pötzl, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, He Sun, Fumie Tazaki, Alexandra J. Tetarenko, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Efthalia Traianou, Tyler Trent, Sascha Trippe, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, Derek Ward-Thompson, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Kaj Wiik, George N. Wong, Qingwen Wu, Doosoo Yoon, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Shan-Shan Zhao

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