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Статті в журналах з теми "Production of information"

Автор: Grafiati

Опубліковано: 29 березня 2025

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1

Klinenberg, Éric. "Information et production numérique." Actes de la recherche en sciences sociales 134, no. 1 (2000): 66–75. http://dx.doi.org/10.3406/arss.2000.2693.

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2

Ruth, Matthias, and Clark W. Bullard. "Information, production and utility." Energy Policy 21, no. 10 (October 1993): 1059–67. http://dx.doi.org/10.1016/s0301-4215(06)80009-1.

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3

Kasakow, Georg, and Jan Christian Aurich. "Reactive Production Control - Information to Control a Production." Applied Mechanics and Materials 869 (August 2017): 151–58. http://dx.doi.org/10.4028/www.scientific.net/amm.869.151.

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Анотація:

Sustainable protection and expansion of the competitiveness of the industrial location Germany is an important topic of current research. How can manufacturing companies in high wage countries counter the challenges of market turbulences? Crucial for the competitiveness of these companies is the compensation of wage and salary costs through highly efficient processes. A promising approach is to increase the responsiveness of a company. Responsiveness means, to react as quickly as possible to events or changes of the market, which are not yet evident and can not be foreseen at the time of production system planning. An increase of responsiveness enables companies to react quickly and flexible to market turbulences. The question arises, which market information are relevant, to which a company has to react as quickly as possible in order to handle market turbulence. This paper addresses this issue and identifies relevant information, that are already known during the phase of product development, and the unknown information of the market, to which an existing production system has to react in order to compensate market turbulences. The interplay of known and unknown information enables a responsive production control. The origin and usage of this information, which enables reactive production control, are a part of this article and are explained therein.

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4

Látečková, A., and M. Kučera. "Management of agricultural production in the conditions of information society." Agricultural Economics (Zemědělská ekonomika) 53, No. 8 (January 7, 2008): 354–58. http://dx.doi.org/10.17221/922-agricecon.

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Анотація:

Nowadays the development of information systems and technologies secures an effective solution of the production process. The implementation of a qualitative software solution is a competitive advantage for agricultural companies as well. In this article, we pay our attention to problematic fields which need to be respected in the process of automated management of agricultural production. We consider as the most important part the creation of adequate information infrastructure which respects the company organization structure and manager’s requirements for information accessibility; data monitoring in terms of environmental economy (nitrate directive) and we suggest selected aspects for automated company information system.

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5

Shukalov, A. V., I. O. Zharinov, and O. O. Zharinov. "Cyber-physical production information environment." Journal of Physics: Conference Series 1889, no. 4 (April 1, 2021): 042027. http://dx.doi.org/10.1088/1742-6596/1889/4/042027.

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6

Laux, Christian, and Volker Laux. "Performance Measurement and Information Production." Journal of Institutional and Theoretical Economics 162, no. 3 (2006): 412. http://dx.doi.org/10.1628/093245606778387384.

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7

Gray, Colin, and Salam Al-Bizri. "Modelling Trade Contractor Information Production." Architectural Engineering and Design Management 3, no. 1 (January 2007): 39–48. http://dx.doi.org/10.1080/17452007.2007.9684628.

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8

Bag, Bidhan Chandra, Jyotipratim Ray Chaudhuri, and Deb Shankar Ray. "Chaos and information entropy production." Journal of Physics A: Mathematical and General 33, no. 47 (November 17, 2000): 8331–50. http://dx.doi.org/10.1088/0305-4470/33/47/301.

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9

Pennings, Johannes M. "Information Technology in Production Organizations." International Studies of Management & Organization 17, no. 4 (December 1987): 68–89. http://dx.doi.org/10.1080/00208825.1987.11656468.

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10

Fjällström, Sabina, Kristina Säfsten, Ulrika Harlin, and Johan Stahre. "Information enabling production ramp‐up." Journal of Manufacturing Technology Management 20, no. 2 (February 6, 2009): 178–96. http://dx.doi.org/10.1108/17410380910929619.

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11

Kalinkin, B. N., and V. L. Shmonin. "Cumulative hadrons: production mechanism, information." Physica Scripta 42, no. 4 (October 1, 1990): 393–99. http://dx.doi.org/10.1088/0031-8949/42/4/003.

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12

LANDINI, FABIO. "Institutional change and information production." Journal of Institutional Economics 9, no. 3 (March 21, 2013): 257–84. http://dx.doi.org/10.1017/s1744137413000064.

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Анотація:

Abstract:The organization of information production is undergoing a deep transformation. Alongside corporations, which have been for long time the predominant institutions of information production, new organizational forms have emerged, e.g. free software communities, open-content on-line wikis, and collective blogs. The paper investigates the factors that favoured the emergence of these alternative systems, called peer production. Different from the previous literature, the paper considers technology as an endogenous variable in the process of organizational design. On this basis, the paper argues that the diffusion of digital technology is a necessary but not sufficient condition to explain the emergence of peer production. A similarly important role has been played by the set of ethics that motivated the early adherents to the free software movement. Such an ethics indeed operated as a ‘cultural subsidy’ that helped to overcome the complementarities existing among distinct institutional domains, and let a new organizational species to emerge.

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13

Lin, Chen, Lai Wei, and Wensi Xie. "Managerial Entrenchment and Information Production." Journal of Financial and Quantitative Analysis 55, no. 8 (September 3, 2019): 2500–2529. http://dx.doi.org/10.1017/s0022109019000693.

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Анотація:

In this article, we evaluate the effect of managerial entrenchment on corporate information production using the voting outcomes of shareholder-initiated proposals intended to mitigate managerial entrenchment. We focus on the proposals that are passed or rejected by a small margin of votes, which generate plausibly exogenous variations in managerial entrenchment. We find that a reduction in managerial entrenchment enhances corporate information production. The effects are stronger for firms with greater information asymmetries and severer agency frictions. Overall, the evidence is consistent with the view that reducing managerial entrenchment enhances corporate disclosure by aligning the incentives of managers and shareholders.

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14

Klemsa, Jaroslav, and Tony Perris. "Quality information for production management." Computers & Chemical Engineering 16 (May 1992): S507—S516. http://dx.doi.org/10.1016/s0098-1354(09)80060-4.

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15

Sonka, Steven T. "Information management in farm production." Computers and Electronics in Agriculture 1, no. 1 (October 1985): 75–85. http://dx.doi.org/10.1016/0168-1699(85)90007-9.

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16

Foster, Jonathan, Steve Benford, and Dominic Price. "Digital archiving as information production." Journal of Documentation 69, no. 6 (October 14, 2013): 773–85. http://dx.doi.org/10.1108/jd-04-2012-0047.

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17

Ekström, Mats, and Johan Östman. "Information, Interaction, and Creative Production." Communication Research 42, no. 6 (February 21, 2013): 796–818. http://dx.doi.org/10.1177/0093650213476295.

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18

Boggs, Roy A. "Implications of Formal Production Information Systems for Production Management." International Journal of Operations & Production Management 8, no. 4 (April 1988): 22–33. http://dx.doi.org/10.1108/eb054832.

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19

Korablyov, Mykola, and Sergey Lutskyy. "SYSTEM-INFORMATION MODELS FOR INTELLIGENT INFORMATION PROCESSING." Innovative Technologies and Scientific Solutions for Industries, no. 3 (21) (September 30, 2022): 26–38. http://dx.doi.org/10.30837/itssi.2022.21.026.

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Анотація:

The subject of the study is system-information models of processes and systems and their use for intelligent processing of information in production tasks. The use of intelligent information processing in production management systems is currently one of the key areas of development of informatics. The aim of the work is to develop system-information models of processes and systems for intelligent information processing allowing to analyze and solve production problems, in conditions of uncertainty. In the article the following tasks are solved: to analyze approaches to the definition of information characteristics of processes and systems; to develop the basis for modeling of system-information processes and systems for intelligent information processing; to develop system-information models and ways of their application for intelligent information processing in the tasks of production. The following methods are used: system-information approach to processes and systems; system-information modeling of processes and systems. The following results were obtained: the analysis of approaches to the definition of information characteristics of processes and systems; developed principles of modeling system-information processes and systems for intelligent processing of information; introduced the concepts of system information and information measure; developed system-information models and methods of their application for the intelligent processing of information in the tasks of production. Conclusions. The development of methods for solving various classes of practical problems using intelligent information processing is one of the key areas of research in computer science. The developed system-information models of processes and systems for intelligent information processing allow analyzing and solving problems. Thereby increase the efficiency of solving problems of analysis, synthesis and forecasting of production systems and technologies, as well as problems of production management. The system-information approach to processes and systems operates with new concepts – system information and information measure, it allowed developing system-information models for intelligent processing of information, as well as ways of their application at stages of product life cycle, which allowed solving problems of production. System-information models of processes and systems describe interaction between source and receiver on information level on the basis of sensitivity threshold. The communication channel between the source and the receiver of information operates, as a rule, under conditions of uncertainty, which can lead to the loss of information during transmission due to possible changes in the characteristics of the system. To describe their interaction, some models of intelligent information processing can be used, in particular, neural network models or fuzzy inference models. Their use will improve the efficiency of receiver state prediction, taking into account the state of the transmitter and the conditions of communication channel operation. The presented article has shown the relevance of developing system-information models for intelligent information processing at the levels of data reception, interpretation and communication, which allows expanding the class of solved production tasks.

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20

Kapitanov, Alexey, Aleksandra Kozlova, and Sergey Tyasto. "The information model of the modern digital production." MATEC Web of Conferences 224 (2018): 02065. http://dx.doi.org/10.1051/matecconf/201822402065.

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Анотація:

The article devoted the analysis and research of modern digital production technologies that ensure the transfer of digital design to a physical object. Five target criteria of production digitalization, such as economic efficiency, prototypiny, quality control, interaction, standardization. The article analyzes the dependence of the cost of implementing new tools at the initial stage of transition to digital production and saving of enterprise resources, as well as basic tools of digital production. The concept under consideration is based on integration of mechatronic technologies, computer systems, as well as engineering analysis and adaptation of the work of various equipment and technological equipment with programmatic control. In conclusion, the list of potential advantages, the creation of digital productions at engineering enterprises on the basis of the development and implementation of new critical and high technologies.

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21

Caplinskas, Albertas, Gintautas Dzemyda, Ferenc Kiss, and Audrone Lupeikiene. "Processing of Undesirable Business Events in Advanced Production Planning Systems." Informatica 23, no. 4 (January 1, 2012): 563–79. http://dx.doi.org/10.15388/informatica.2012.375.

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22

NAKAZAWA, Hiromu, and Hideo KONDOH. "Production scheduling method by information concept." Journal of the Japan Society for Precision Engineering 52, no. 3 (1986): 471–77. http://dx.doi.org/10.2493/jjspe.52.471.

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23

Klinenberg, Éric. "Information et production numérique." Actes de la recherche en sciences sociales 134, no. 4 (September 1, 2000): 66–75. http://dx.doi.org/10.3917/arss.p2000.134n1.0066.

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24

Gutsalenko, L. "Information system quality of organic production." Bioeconomics and agrarian business 10, no. 1 (June 11, 2019): 40–49. http://dx.doi.org/10.31548/bioeconomy2019.01.040.

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25

Zhou, Jian Jun, Xiao Fang Wang, Xiu Wang, and Ji Chen Cai. "Meat Pigeon Production Management Information System." Applied Mechanics and Materials 411-414 (September 2013): 518–22. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.518.

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Анотація:

A meat pigeon production management information system was developed. The system can carry through precision management for meat pigeon, which adopts RFID, computers and other IT technologies. Pigeon production management information system include two parts: breeding information collection handheld terminals and pigeon management information software system. The breeding information collection handheld terminal can collect production information of breeder pigeon. Breeding information collection terminals include electronic tag reader module, database storage module and human-machine interaction module. The pigeon management information software system can storage and statistics the data that collected by information collection terminal and can also generate standard breeder production record report for workers.

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26

Lata, Suman, and Ajmer Kundu. "Wheat Production Information Retrieval System (WPIRS)." International Journal of Computer Applications 58, no. 2 (November 15, 2012): 16–19. http://dx.doi.org/10.5120/9253-3422.

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27

Chua, Cecil, Lan Cao, Karlene Cousins, and Detmar Straub. "Measuring Researcher-Production in Information Systems." Journal of the Association for Information Systems 3, no. 1 (2002): 145–215. http://dx.doi.org/10.17705/1jais.00026.

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28

Likhacheva, L. B., L. I. Nazina, A. V. Lomanova, and N. A. Chernykh. "Information model of production system management." Proceedings of the Voronezh State University of Engineering Technologies 80, no. 4 (March 21, 2019): 128–32. http://dx.doi.org/10.20914/2310-1202-2018-4-128-132.

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Анотація:

Improvement of production systems of the organization is carried out through the introduction of quality management systems, changes in the model of production organization, the use of modern approaches to improve product quality and customer satisfaction. Measurement, evaluation and analysis of the production system allows to set the direction of activity to improve production processes and to develop activities aimed at ensuring the effectiveness of the whole system. The production system is an open system, it is connected and exchanged with the external environment information, resources, etc. the production system is Called the operating system, which consists of three subsystems: processing subsystem, directly related to the technological processes of raw materials and semi-finished products conversion into finished products; support subsystem, which performs auxiliary functions necessary for the implementation of the main technological processes; planning and control subsystems that receive and process information from the internal and external environment of the organization. The task of building an automated information system is connected with the need to integrate with the subsystem of data collection and analysis, visual representation of information for decision-making at all levels. Building an information management system of the production system is impossible without a powerful infrastructure, without a single information system support and process control. The proposed information system will help to automate the processes of management of the organization, quickly form the strategic and tactical goals of the organization. Within a given period of time, data will be collected and analyzed from the internal and external environment, timely analysis of deviations of the values of indicators from the planned values. The results of information processing will be timely visualized both for each employee and the production system of the organization as a whole.

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29

Egghe, L. "Dynamical aspects of Information Production Processes." Collnet Journal of Scientometrics and Information Management 7, no. 1 (June 2013): 35–44. http://dx.doi.org/10.1080/09737766.2013.802631.

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30

Irwin, Daniel, and David R. Mandel. "Improving information evaluation for intelligence production." Intelligence and National Security 34, no. 4 (February 6, 2019): 503–25. http://dx.doi.org/10.1080/02684527.2019.1569343.

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31

Palmer, Ralph C. "Assessing Information Alignment in Production Organizations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 16 (October 2007): 981–85. http://dx.doi.org/10.1177/154193120705101604.

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Анотація:

Alignment is defined as the proper positioning or adjustment of resources in relation to each other. Organization alignment involves aligning many different levels of an organization and its business segments to allow more accurate predictability of organization performance. To align an organization requires consideration of many different levels of vertical and lateral alignment of processes, resources, and information. Alignment research involves interaction implications, level of coordination implications, and geographic implications as well as resource and information need, and resource and information generation. One of the challenges of alignment is directly connecting deficiencies to their underlying issues. This is due to the weak link between organization metrics of performance and alignment factors. This study discusses issues that alignment alleviates in reference to process efficiency, procedure errors, operator errors, knowledge loss, and forecasting.

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32

Baláž, Vladimír. "Flexible Production Cell with Information Systems." Applied Mechanics and Materials 282 (January 2013): 252–56. http://dx.doi.org/10.4028/www.scientific.net/amm.282.252.

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Анотація:

The article describes one of the current approaches to classification of production systems. It is described the simplest production system – Single Flexible Machine to the complex production configurations, which represents Multi-Cell Flexible Manufacturing system. Transmission of the information in such systems can be addressed at different levels. The structure of information systems for such a production configurations is solved from the point of view of information transfer in the production system.

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33

Chick, Stephen E., Sameer Hasija, and Javad Nasiry. "Information Elicitation and Influenza Vaccine Production." Operations Research 65, no. 1 (February 2017): 75–96. http://dx.doi.org/10.1287/opre.2016.1552.

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34

Chai, Xiao-Jun. "Port Safety Production Management Information System." Engineering Technology Trends 2, no. 2 (2024): 0. http://dx.doi.org/10.37155/2972-483x-0202-44.

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35

SRIVASTAVA, Y. N., G. VITIELLO, and A. WIDOM. "QUANTUM MEASUREMENTS, INFORMATION AND ENTROPY PRODUCTION." International Journal of Modern Physics B 13, no. 28 (November 10, 1999): 3369–82. http://dx.doi.org/10.1142/s0217979299003076.

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Анотація:

In order to understand the Landau–Lifshitz conjecture on the relationship between quantum measurements and the thermodynamic second law, we discuss the notion of "diabatic" and "adiabatic" forces exerted by the quantum object on the classical measurement apparatus. The notion of heat and work in measurements is made manifest in this approach and the relationship between information entropy and thermodynamic entropy is explored.

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36

Hyytinen, Ari. "Information production and lending market competition." Journal of Economics and Business 55, no. 3 (May 2003): 233–53. http://dx.doi.org/10.1016/s0148-6195(03)00024-9.

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37

Skrastins, Janis, and Vikrant Vig. "How Organizational Hierarchy Affects Information Production." Review of Financial Studies 32, no. 2 (July 18, 2018): 564–604. http://dx.doi.org/10.1093/rfs/hhy071.

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Анотація:

AbstractWe exploit a variation in organizational hierarchy induced by a reorganization plan implemented in roughly 2,000 bank branches in India. We do so to investigate how organizational hierarchy affects the allocation of credit. We find that increased hierarchization of a branch induces credit rationing, reduces loan performance, and generates standardization in loan contracts. Additionally, we find that hierarchical structures perform better in environments characterized by a high degree of corruption, highlighting the benefits of hierarchies in restraining rent-seeking activities. Overall, our results are consistent with the view that valuable information may be lost in hierarchical structures.Received May 4, 2018; editorial decision April 30, 2018 by Editor Itay Goldstein. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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38

Sahar, Loukil, Jarboui Anis, and David McMillan. "Loan officers and soft information production." Cogent Business & Management 3, no. 1 (June 28, 2016): 1199521. http://dx.doi.org/10.1080/23311975.2016.1199521.

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39

Day, Theodore E. "Information, Production, and the Term Structure." Journal of Political Economy 94, no. 1 (February 1986): 167–84. http://dx.doi.org/10.1086/261367.

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40

Del Gaudio, Belinda L., Mark D. Griffiths, and Gabriele Sampagnaro. "SOFT INFORMATION PRODUCTION IN SME LENDING." Journal of Financial Research 43, no. 1 (November 14, 2019): 121–51. http://dx.doi.org/10.1111/jfir.12198.

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41

Sewell, G. "Management information systems for JIT production." Omega 18, no. 5 (January 1990): 491–503. http://dx.doi.org/10.1016/0305-0483(90)90005-t.

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42

Trauten, Andreas, and Thomas Langer. "Information production and bidding in IPOs." Zeitschrift für Betriebswirtschaft 82, no. 4 (February 28, 2012): 361–88. http://dx.doi.org/10.1007/s11573-012-0554-3.

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43

Li, Chao Kevin, Jin-hui Luo, and Naomi S. Soderstrom. "Air pollution and analyst information production." Journal of Corporate Finance 60 (February 2020): 101536. http://dx.doi.org/10.1016/j.jcorpfin.2019.101536.

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44

Nesen, Mariia, Viktoriia Liashevska, and Yelizaveta Fomina. "Management of information security of production." Economics: time realities 2, no. 54 (February 23, 2021): 39–46. http://dx.doi.org/10.15276/etr.02.2021.5.

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Анотація:

The article actualizes the problem of reliability of enterprise information. The methodological bases of construction and implementation of the information security management system of the company are considered. In accordance with the established purpose of this work, approaches to ensure safe management of information system mechanisms are identified. Solutions have been identified that make it possible to protect information transmitted in domestic and foreign markets. The systems that help automate the functioning of the organization's processes are considered. Based on international standards and the analysis of modern approaches to defining the essence of the information system management model, the key stages of creating an effective information security management system for business processes are proposed.

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45

Longo, Anna. "Computational Creativity or Automated Information Production?" Balkan Journal of Philosophy 15, no. 1 (2023): 13–22. http://dx.doi.org/10.5840/bjp20231513.

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Анотація:

Algorithms and automated learning systems have been successfully applied to produce images, pieces of music, or texts that are appealing to humans and that are often compared to artworks. Computational technologies are able to find surprising and original solutions–new patterns that humans cannot anticipate– but does this mean we ascribe to them the kind of creativity that is expressed by human artists? Even though AI can successfully detect humans’ preferences as well as select the objects that satisfy taste, can we ascribe to them the capacity of recognizing the intrinsic value of artworks? To answer these questions, I am first going to explain the kind of creativity that is expressed by contemporary predictive systems, then, in the second part of this paper, I will try to show the difference between the creativity of algorithms and the creativity of artists by expanding on Deleuze’s reflections.

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46

Psareva, Nadezhda Yu, and Dmitriy N. Kiselev. "Available information technologies in production management." Vestnik BIST (Bashkir Institute of Social Technologies), no. 1(62) (March 29, 2024): 25–32. http://dx.doi.org/10.47598/2078-9025-2024-1-62-25-32.

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Анотація:

This article considers the digital transformation of Russia's economy as a priority direction of the country's development, based on the active development of modern information technologies in the field of production management. In addition, the advantages of using information technologies in production management, basic production management systems, promising digital information technologies and their use to ensure the successful functioning of enterprises in a modern economic environment are described on the example of LLC "Zavod Moskabel".

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