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Bibliographies thématiques / Intelligent Instrumentaion

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Littérature scientifique sur le sujet « Intelligent Instrumentaion »

Auteur : Grafiati

Publié le 6 septembre 2023

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Articles de revues sur le sujet "Intelligent Instrumentaion"

1

Harper, A. M., and S. A. Liebman. "Intelligent instrumentation." Journal of Research of the National Bureau of Standards 90, no. 6 (1985): 453. http://dx.doi.org/10.6028/jres.090.041.

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2

Preece, C. "Intelligent Instrumentation." Electronics and Power 32, no. 3 (1986): 233. http://dx.doi.org/10.1049/ep.1986.0148.

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3

Clarke, D. W. "Intelligent instrumentation." Transactions of the Institute of Measurement and Control 22, no. 1 (2000): 3–27. http://dx.doi.org/10.1177/014233120002200102.

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4

Howell, S. K., and T. D. S. Hamilton. "Intelligent instrumentation." Measurement Science and Technology 1, no. 12 (1990): 1265–73. http://dx.doi.org/10.1088/0957-0233/1/12/001.

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5

Clarke, D. W. "Intelligent instrumentation." Transactions of the Institute of Measurement and Control 22, no. 1 (2000): 3–27. http://dx.doi.org/10.1191/014233100675191926.

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6

Jakuš, Vladimír. "Artificial Intelligence in Chemistry." Collection of Czechoslovak Chemical Communications 57, no. 12 (1992): 2413–51. http://dx.doi.org/10.1135/cccc19922413.

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The definition of artificial intelligence and the associated tasks of this branch of science are discussed. The tasks include pattern recognition, adaptation and learning, problem solving by means of expert systems or neural networks, and understanding the natural language and communication with a machine in it. The principles of problem solving are analyzed. It is demonstrated how artificial intelligence-based computer programs in which chemical expertise is encoded assist in structure elucidation, in the investigation of relations between structure and biological activity or chromatographic retention, etc.; problems emerging in the synthesis planning with a retrosynthetic analysis, or in the planning of experiments and intelligent consultations are dealt with. Several models used for structure elucidation and synthesis planning are evaluated. An overview is presented of additional expert systems which, along with artificial intelligence-based robotics, are used in intelligent instrumentation. Also discussed is the role of neural networks, which begin to be successfully employed in structure elucidation, synthesis planning, in intelligent instrumentation and in the treatment of natural languages. They are expected to be an important tool in the implementation of intelligent systems for the classification of chemical databases and prediction of properties of molecules.

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7

Beckman, R. J. "Intelligent instrumentation - Discussion." Journal of Research of the National Bureau of Standards 90, no. 6 (1985): 464. http://dx.doi.org/10.6028/jres.090.042.

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8

Kohoutek, H. J. "Intelligent instrumentation: a quality challenge." ACTA IMEKO 3, no. 1 (2014): 47. http://dx.doi.org/10.21014/acta_imeko.v3i1.195.

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<p>This is a reissue of a paper which appeared in ACTA IMEKO 1988, Proceedings of the 11th Triennial World Congress of the International Measurement Confederation (IMEKO), "Instrumentation for the 21st century", 16.-21.10.1988, Houston, pp. 337-345.</p><p>After a review and description of current trends in the design of electronic measurement and analytical instrumentation, changes in its application and use, and of associated quality issues, this paper deals with new quality issues emerging from the expected increase of artificial intelligence impact on system design and implementation strategies. The concept of knowledge quality in all its aspects (i.e. knowledge levels, representation, storage, and processing) is identified as the key new issue. Discussion of crucial knowledge quality attributes and associated assurance strategies suggests the need to enrich the assurance sciences and technologies by the methods and tools of applied epistemology. Described results from current research and investigation, together with first applications of artificial intelligence to particular analytical instruments, lead to conclusion that the conceptual framework of quality management is, in general, adequate for successful resolution of all quality issues associated with intelligent instrumentation.</p>

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9

Boettcher, J., and H. R. Traenkler. "Trends in Intelligent Instrumentation." IFAC Proceedings Volumes 22, no. 18 (1989): 241–48. http://dx.doi.org/10.1016/s1474-6670(17)52849-9.

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10

Yadova, N., and S. Osiko. "Artificial Intelligence: Application and Development Prospects on the Example of Rocket and Space Instrumentation." Scientific Research and Development. Economics of the Firm 11, no. 2 (2022): 54–59. http://dx.doi.org/10.12737/2306-627x-2022-11-2-54-59.

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The presented article deals with the implementation of artificial intelligence technologies in the instrument-making industry. The statistics of the use of systems with elements of artificial intelligence are analyzed. It presents the problems of legal regulation of artificial intelligence systems in the Russian Federation. In this regard, the purpose of the article is, on the one hand, to give the reader some information on state of intelligent systems in rocket and space instrumentation in the Russian Federation, and on the other hand, to identify the most promising areas of development in this area.

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