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1

Yu, Meng-Lin. Automatic random logic layout synthesis: A module generator approach. Urbana, Ill: Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1986.

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2

Automated password generator (APG). Gaithersburg, MD: Dept. of Commerce, National Institute of Standards and Technology, 1994.

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3

Zhang, Jian, Zhiqiang Zhang, and Feifei Ma. Automatic Generation of Combinatorial Test Data. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43429-1.

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4

Logunova, Oksana, Petr Romanov, and Elena Il'ina. Processing of experimental data on a computer. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1064882.

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The textbook provides information about the main methods and tools for automating computational processes used in data processing; methods for representing and generating models of experimental data; data models and classification of processing tasks; and the organization of the user interface in automated systems for processing experimental data. Contains structured chapters on the specifics of experimental research. The features of using software for processing experimental data are clearly and logically described. Theoretical material and basic algorithms for processing experimental data used in industrial statistics are presented. Examples of processing experimental data in the field of metallurgy and management in higher education are given. Meets the requirements of the Federal state educational standards of higher education of the latest generation. For students and postgraduates of higher educational institutions.
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5

Diamant, P. E. Automatic generation of mixed signal test programs from circuitsimulation data. Manchester: UMIST, 1994.

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6

Automatic mesh generation: Application to finite element methods. Chichester: J. Wiley, 1991.

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7

Strock, O. J. Telemetry computer systems: The new generation. Research Triangle Park, NC: Instrument Society of America, 1988.

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8

Keßler, Christoph W. Automatic Parallelization: New Approaches to Code Generation, Data Distribution, and Performance prediction. Wiesbaden: Vieweg+Teubner Verlag, 1994.

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9

Ponzetto, Simone Paolo. Knowledge acquisition from a collaboratively generated encyclopedia. Heidelberg: IOS Press, 2010.

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10

Ponzetto, Simone Paolo. Knowledge acquisition from a collaboratively generated encyclopedia. Heidelberg: IOS Press, 2010.

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11

Knowledge acquisition from a collaboratively generated encyclopedia. Heidelberg: IOS Press, 2010.

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12

Gun, I. A study of automated hypothesis generation for a large medical data set. Manchester: UMIST, 1997.

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13

Germert, Ed Van. Alternative machine-readable record generation systems. Madison, Wis: Council of Wisconcin Libraries, 1988.

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14

Juris for next generation systems: A guide for lawyers and their firms. Chicago: American Bar Association, Tort and Insurance Practice Section, 1999.

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15

Dolan, F. T. Circstat report: A descriptive study of the statistics produced and the reports generated by automated circulation systems at six large public libraries in Ontario. London, Ont: School of Library and Information Science, University of Western Ontario, 1988.

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16

Australian Data Fusion Symposium (1st 1996 Adelaide, Australia). First Australian Data Fusion Symposium: ADFS-96 Adelaide, Australia, November 21-22, 1996. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 1996.

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17

Varlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.
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18

Australian, Data Fusion Symposium (1st 1996 Adelaide Australia). First Australian Data Fusion Symposium: November 21-22, 1996, Stamford Plaza Hotel, Adelaide, Australia. [New York?]: IEEE, 1996.

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19

Andreas, Hotho, Jäschke Robert, Nanopoulos Alexandros, Rendle Steffen, Schmidt-Thieme Lars, Stumme Gerd 1967-, Symeonidis Panagiotis, and SpringerLink (Online service), eds. Recommender Systems for Social Tagging Systems. Boston, MA: Springer US, 2012.

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20

Soman, S. A. Computational methods for large sparse power systems analysis: An object oriented approach. Boston: Kluwer Academic Publishers, 2002.

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21

Automatic Generation of Combinatorial Test Data. Zhang Jian, 2014.

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22

Sthamer, Harmen-Hinrich. The automatic generation of software test data using genetic algorithims. 1995.

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23

Yang, Xile. Automatic software test data generation from z specifications using evolutionary algorithms. 1998.

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24

W, Kessler Christoph, ed. Automatic parallelization: New approaches to code generation, data distribution, and performance prediction. Wiesbaden: Vieweg, 1994.

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25

Williams, ER, AC Matheson, and CE Harwood. Experimental Design and Analysis for Tree Improvement. CSIRO Publishing, 2002. http://dx.doi.org/10.1071/9780643090132.

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Experimental Design and Analysis for Tree Improvement provides a set of practical procedures to follow when planning, designing and analysing tree improvement trials. Using many fully-worked examples, it outlines how to: design field, glasshouse and laboratory trials; efficiently collect data and construct electronic data files; pre-process data, screening for data quality and outliers; analyse data from single and across-site trials using either GenStat or SAS; and interpret the results from statistical analyses. The authors address the many practical issues often faced in forest tree improvement trials and describe techniques that will give conclusive results with the minimum expense. The techniques provided are applicable to the improvement of not only trees, but to crops in general. Building on the success of the first edition, this new edition has been fully revised and updated to relate to the latest commercially-available software packages for design generation (CycDesigN) and data pre-processing and automated generation of programs for statistical analysis (DataPlus). For analysis, it now provides both GenStat and SAS programs as generated by DataPlus.
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26

Dowd, Cate. Digital Journalism, Drones, and Automation. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190655860.001.0001.

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Advances in online technology and news systems, such as automated reasoning across digital resources and connectivity to cloud servers for storage and software, have changed digital journalism production and publishing methods. Integrated media systems used by editors are also conduits to search systems and social media, but the lure of big data and rise in fake news have fragmented some layers of journalism, alongside investments in analytics and a shift in the loci for verification. Data has generated new roles to exploit data insights and machine learning methods, but access to big data and data lakes is so significant it has spawned newsworthy partnerships between media moguls and social media entrepreneurs. However, digital journalism does not even have its own semantic systems that could protect the values of journalism, but relies on the affordances of other systems. Amidst indexing and classification systems for well-defined vocabulary and concepts in news, data leaks and metadata present challenges for journalism. By contrast data visualisations and real-time field reporting with short-form mobile media and civilian drones set new standards during the European asylum seeker crisis. Aerial filming with drones also adds to the ontological base of journalism. An ontology for journalism and intersecting ontologies can inform the design of new semantic learning systems. The Semantic CAT Method, which draws on participatory design and game design, also assists the conceptual design of synthetic players with emotion attributes, towards a meta-model for learning. The design of context-aware sensor systems to protect journalists in conflict zones is also discussed.
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27

AUTOCASK (AUTOmatic generation of 3-D CASK models): A microcomputer based system for shipping cask design review analysis. Washington, D.C: Division of Industrial and Medical Nuclear Safety, Office of Nuclear Material Safety and Safeguards, U.S. Nuclear Regulatory Commission, 1995.

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28

Kessler, Christoph W. Automatic Parallelization: New Approaches to Code Generation, Data Distribution, and Performance Prediction (Vieweg Advanced Studies in Computer Science). Friedr Vieweg & Sohn Verlagsgesellschaft, 1994.

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29

Oyez Scientific and Technical Services., ed. Third& Fourth generation PABXs: Preparing for the next five years : conference transcript, 22nd February 1985, London. London: Oyez Scientific & Technical Services, 1985.

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30

Knight, Andrew P. Innovations in unobtrusive methods. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198796978.003.0004.

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Andrew P. Knight explores developments in unobtrusive research methods using unconventional sources of data from computer-based systems and tools. These generate novel measures of behaviour based on the digital trace data that we all generate, online access to public and personal archives, wearable sensors, and the automatic coding of text, and audio and video recordings. Smartphones and wristbands are just two of the growing range of connected devices that are capable of capturing and sharing multimedia information in real-time. Devices such as these offer new ways in which researchers can gather data at low cost, avoiding reactance effects, allowing the study of how phenomena change over time, and expanding the scale of research, given the wide dissemination of the technology. Before adopting these methods, researchers need to consider whether they have the expertise, and the ethical issues raised by using information (which may be in the public domain) without informed consent.
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31

Institution of Mechanical Engineers (Great Britain). Steam Plant Committee. and Institution of Mechanical Incorporated Engineers., eds. The Application of expert systems in the power generation industry: Papers presented at a seminar. London: Published by Mechanical Engineering Publications for the Institution of Mechanical Engineers, 1993.

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32

Leitner, David L. The Law Firm's Quick Guide to Juris. Tort and Insurance Practice Section American, 1999.

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33

Application of Expert Systems in the Power Generation Industry: Papers Presented at a Seminar Organized by the Steam Plant Committee. Wiley, 1993.

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34

Meier, Dennis, Jan Seidel, Marty Gregg, and Ramamoorthy Ramesh. Domain Walls. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198862499.001.0001.

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Technological evolution and revolution are both driven by the discovery of new functionalities, new materials and the design of yet smaller, faster, and more energy-efficient components. Progress is being made at a breathtaking pace, stimulated by the rapidly growing demand for more powerful and readily available information technology. High-speed internet and data-streaming, home automation, tablets and smartphones are now ‘necessities’ for our everyday lives. Consumer expectations for progressively more data storage and exchange appear to be insatiable. In this context, ferroic domain walls have attracted recent attention as a completely new type of oxide interface. In addition to their functional properties, such walls are spatially mobile and can be created, moved, and erased on demand. This unique degree of flexibility enables domain walls to take an active role in future devices and hold a great potential as multifunctional 2D systems for nanoelectronics. With domain walls as reconfigurable electronic 2D components, a new generation of adaptive nano-technology and flexible circuitry becomes possible, that can be altered and upgraded throughout the lifetime of the device. Thus, what started out as fundamental research, at the limit of accessibility, is finally maturing into a promising concept for next-generation technology.
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35

Hong, Sun-ha. Technologies of Speculation. NYU Press, 2020. http://dx.doi.org/10.18574/nyu/9781479860234.001.0001.

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What counts as knowledge in the age of big data and smart machines? Technologies of datafication renew the long modern promise of turning bodies into facts. They seek to take human intentions, emotions, and behavior and to turn these messy realities into discrete and stable truths. But in pursuing better knowledge, technology is reshaping in its image what counts as knowledge. The push for algorithmic certainty sets loose an expansive array of incomplete archives, speculative judgments, and simulated futures. Too often, data generates speculation as much as it does information. Technologies of Speculation traces this twisted symbiosis of knowledge and uncertainty in emerging state and self-surveillance technologies. It tells the story of vast dragnet systems constructed to predict the next terrorist and of how familiar forms of prejudice seep into the data by the back door. In software placeholders, such as “Mohammed Badguy,” the fantasy of pure data collides with the old specter of national purity. It shows how smart machines for ubiquitous, automated self-tracking, manufacturing knowledge, paradoxically lie beyond the human senses. This data is increasingly being taken up by employers, insurers, and courts of law, creating imperfect proxies through which my truth can be overruled. This book argues that as datafication transforms what counts as knowledge, it is dismantling the long-standing link between knowledge and human reason, rational publics, and free individuals. If data promises objective knowledge, then we must ask in return, Knowledge by and for whom; enabling what forms of life for the human subject?
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36

Sotnyk, M. Power supply for educational institutions: efficiency and alternatives. Accent Graphics Communications & Publishing, 2020. http://dx.doi.org/10.29013/msotnyk.pseiea.2020.146.

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Proposed methodological approaches to modeling short-term forecasting and long-term planning of electrical consumption in educational institutions based on retrospective data. A logic-structural model and software of the circuit “object of monitoring of electric consumption — factors of influence — regulatory tools” of an automated system for controlling the efficiency of energy consumption in educational institutions have been developed. There are given practical recommendations of feasibility study of introduction of alternative power supply sources in educational institutions, in particular: solar generation, heat pumps, autonomous energy sources, etc. Proposed scientific and methodological approaches to the introduction of an organizational and economic mechanism for managing the development of renewable energy in educational institutions and a motivation system for employees of the energy management service. The monograph is a generalization of scientific research conducted by employees of Sumy State University during the state budget research work “Model of an efficiency management and forecasting system for the consumption of electric energy” (State Registration No. 0118U003583). The monograph is intended for researchers and specialists in the implementation of energy management systems
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37

Institute Of Electrical and Electronics Engineers and IEEE South Australian Section. Adfs-96: First Australian Data Fusion Symposium : November 21-22, 1996 Stamford Plaza Hotel Adelaide, Australia. Institute of Electrical & Electronics Enginee, 1997.

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38

Kenneth, Baldwin, American Society of Civil Engineers. Engineering Mechanics Division., and ASCE National Convention, eds. Modern methods for automating finite element mesh generation: Proceedings of a session sponsored by the Engineering Mechanics Division of the American Society of Civil Engineers in conjunction with the ASCE National Convention in Boston, Massachusetts, October 31, 1986. New York, N.Y: American Society of Civil Engineers, 1986.

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39

Nanopoulos, Alexandros, Steffen Rendle, Lars Schmidt-Thieme, Leandro Balby Marinho, Panagiotis Symeonidis, Gerd Stumme, Andreas Hotho, and Robert Jäschke. Recommender Systems for Social Tagging Systems. Springer, 2012.

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40

Soman, S. A., S. A. Khaparde, and Shubha Pandit. Computational Methods for Large Sparse Power Systems: An Object Oriented Approach (With CD-ROM) (Power Electronics and Power Systems). Springer, 2001.

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