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Bibliographies thématiques / Feature management / Livres

Pour voir les autres types de publications sur ce sujet consultez le lien suivant : Feature management.

Livres sur le sujet « Feature management »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 10 mars 2023

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1

Ley, Michael. Ein Datenbankkern zur Speicherung variabel strukturierter Feature-Terme : Implementierungstechniken. Sank[t] Augustin : Infix, 1993.

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2

Huan, Liu. Feature selection for knowledge discovery and data mining. Boston : Kluwer Academic Publishers, 1998.

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3

Liu, Huan. Feature selection for knowledge discovery and data mining. Boston : Kluwer Academic, 1998.

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4

1958-, Liu Huan, et Motoda Hiroshi, dir. Feature extraction, construction and selection : A data mining perspective. Boston : Kluwer Academic, 1998.

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5

Liu, Huan. Feature Extraction, Construction and Selection : A Data Mining Perspective. Boston, MA : Springer US, 1998.

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6

Jensen, Richard. Computational intelligence and feature selection : Rough and fuzzy approaches. Oxford : Wiley, 2008.

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7

American Water Works Association. Illinois Section. Illinois Section AWWA, Illinois EPA and Illinois Rural Water Assoc. presents double feature seminars coming soon to a location near you. Springfield, Ill.] : [Illinois Environmental Protection Agency], 1993.

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8

Inc, ebrary, dir. Kentico CMS 5 website development : Beginner's guide : building professional and feature-rich websites with Kentico CMS 5. Birmingham [U.K.] : Packt Pub., 2010.

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9

Inc, ebrary, dir. JBoss portal server development : Create dynamic, feature-rich, and robust enterprise portal applications. Birmingham, U.K : Packt Pub., 2009.

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10

Second lives : Becoming a freelance writer. New York : St. Martin's Griffin, 1999.

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11

Second lives : Becoming a desktop publisher. New York : St. Martin's Griffin, 1999.

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12

Jones, Peter F. CAD/CAM : Features, Applications and Management. London : Macmillan Education UK, 1992. http://dx.doi.org/10.1007/978-1-349-22141-7.

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13

Jones, Peter F. CAD/CAM, features, applications and management. London : Macmillan, 1992.

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14

Hegstad, Sven Olaf. Management contracts : Main features and design issues. Washington, D.C : World Bank, 1987.

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15

Dabrowski, Christopher E. Object database management systems : Concepts and features. Washington, D.C : National Institute of Standards and Technology, 1990.

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16

Elizabeth, Fong, et Yang Deyuan, dir. Object database management systems : Concepts and features. Gaithersburg, MD : U.S. Dept. of Commerce, National Institute of Standards and Technology, 1990.

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17

Cascella, Marco, Arturo Cuomo et Daniela Viscardi. Features and Management of the Pelvic Cancer Pain. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33587-2.

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18

Ryzhikov, Sergey. Management : management methods. ru : INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1039875.

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The textbook contains questions that reveal the composition and nature of management methods. Methods of organizational dynamics, stages of evolution of management methods, characteristic features of modern techniques and methods of management are considered. The features of methods that promote self-organization are defined. The innovation in the described assessment methodology consists in the application of management methods. Meets the requirements of the Federal state educational standards of higher education of the latest generation. For undergraduate and graduate students 38.03.03 "personnel Management", 38.03.01 "Economics", 38.03.02 and 38.04.02" Management", 38.03.04 and 38.04.04" State and municipal management", teachers and practitioners in the field of management.

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19

Cascella, Marco, et Elvio De Blasio. Features and Management of Acute and Chronic Neuro-Covid. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86705-8.

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20

Otey, Michael. Microsoft SQL Server 2005 new features. New York : McGraw-Hill/Osborne, 2004.

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21

service), SpringerLink (Online, dir. Fisheries Management in Japan : Its institutional features and case studies. Dordrecht : Springer Science+Business Media B.V., 2011.

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22

American Bankers Association. Fiduciary and Securities Operations Division., dir. Risk management and control : Processing bond put and call features. Washington, D.C. (1120 Connecticut Ave., N.W., Washington 20036) : Fiduciary and Securities Operations Division, American Bankers Association, 1990.

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23

Goetzke, Sabine. Computerisation of the personnel management function : Motives, features and impacts. [s.l.] : typescript, 1987.

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24

Oracle Database 10g new features. New York : McGraw-Hill/Osborne, 2004.

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25

IBM Data Management Solutions Education Services. Working with IBM Informix XPS 8.40 features : Course 765, version 2. [United States?] : IBM, 2002.

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26

Stories of achievements : Narrative features of organizational performance. New Brunswick, NJ : Transaction Publishers, 1997.

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27

Belal, Tassi, dir. DB2 viper strikes again : New features in DB2 9.5. New York : McGraw Hill, 2008.

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28

Brown, C. K. Features of a participatory management information system for rural development projects. Cape Coast, Ghana : University of Cape Coast, Centre for Development Studies, 1991.

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29

Our Feature Presentation : Management. South-Western College Pub, 2003.

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30

Computational methods of feature selection. Boca Raton : Chapman & Hall/CRC, 2008.

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31

Loukas, Athanasios, et Luis Garrote, dir. Feature Papers of Water Resources Management, Policy and Governance. MDPI, 2022. http://dx.doi.org/10.3390/books978-3-0365-4946-0.

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32

Champoux, Joseph E. Our Feature Presentation : Human Resource Management (with Printed Access Card). South-Western College Pub, 2006.

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33

Tari, Zahir, Adil Fahad, Abdulmohsen Almalawi et Xun Yi. Network Classification for Traffic Management : Anomaly detection, feature selection, clustering and classification. Institution of Engineering and Technology, 2020. http://dx.doi.org/10.1049/pbpc032e.

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34

Tari, Zahir, Adil Fahad, Abdulmohsen Almalawi et Xun Yi. Network Classification for Traffic Management : Anomaly Detection, Feature Selection, Clustering and Classification. Institution of Engineering & Technology, 2020.

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35

Wang, Ran, et Jorge A. Chan-Lau. UnFEAR : Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification. International Monetary Fund, 2020.

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36

Wang, Ran, et Jorge A. Chan-Lau. UnFEAR : Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification. International Monetary Fund, 2020.

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37

Wang, Ran, et Jorge A. Chan-Lau. UnFEAR : Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification. International Monetary Fund, 2020.

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38

Feature Extraction, Construction and Selection : A Data Mining Perspective. Springer, 2011.

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39

Jensen, Richard, et Qiang Shen. Computational Intelligence and Feature Selection : Rough and Fuzzy Approaches. Wiley & Sons, Incorporated, John, 2008.

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40

Jensen, Richard, et Qiang Shen. Computational Intelligence and Feature Selection : Rough and Fuzzy Approaches. Wiley & Sons, Incorporated, John, 2008.

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41

(Editor), Isabelle Guyon, Steve Gunn (Editor), Masoud Nikravesh (Editor) et Lotfi A. Zadeh (Editor), dir. Feature Extraction : Foundations and Applications (Studies in Fuzziness and Soft Computing). Springer, 2006.

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42

Mishra, Kamta Nath, et Subhash Chandra Pandey. Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction : Emerging Research and Opportunities. IGI Global, 2020.

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43

Mishra, Kamta Nath, et Subhash Chandra Pandey. Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction : Emerging Research and Opportunities. IGI Global, 2020.

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44

Mishra, Kamta Nath, et Subhash Chandra Pandey. Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction : Emerging Research and Opportunities. IGI Global, 2020.

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45

(Editor), Huan Liu, et Hiroshi Motoda (Editor), dir. Feature Extraction, Construction and Selection : A Data Mining Perspective (The Springer International Series in Engineering and Computer Science). Springer, 1998.

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46

Latham, Gary P., Lorne M. Sulsky et Heather MacDonald. Performance Management. Sous la direction de Peter Boxall, John Purcell et Patrick M. Wright. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199547029.003.0018.

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A distinguishing feature of performance management relative to performance appraisal is that the former is an ongoing process whereas the latter is done at discrete time intervals (e.g. annually). Ongoing coaching is an integral aspect of performance management. Performance appraisal is the time period in which to summarize the overall progress that an individual or team has made as a result of being coached, and to agree on the new goals that should be set. Common to the performance management/appraisal process are the four following steps. First, desired job performance must be defined. Second, an individual's performance on the job must be observed. Is the person or team's performance excellent, superior, satisfactory, or unacceptable? Third, feedback is provided and specific challenging goals are set as to what the person or team should start doing, stop doing, or be doing differently. Fourth, a decision is made regarding retaining, rewarding, training, transferring, promoting, demoting, or terminating the employmemt of an individual.

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47

Niu, Gang. Data-Driven Technology for Engineering Systems Health Management : Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions. Springer London, Limited, 2016.

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48

Niu, Gang. Data-Driven Technology for Engineering Systems Health Management : Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions. Springer, 2018.

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49

Niu, Gang. Data-Driven Technology for Engineering Systems Health Management : Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions. Ingramcontent, 2016.

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50

Morrell, Kevin, et Mark Learmonth. Evidence-Based Management. Sous la direction de Adrian Wilkinson, Steven J. Armstrong et Michael Lounsbury. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198708612.013.21.

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This chapter outlines the case for “evidence-based management” then adopts a critical perspective. To do so, it focuses on a recurring feature of evidence-based writings: the management-as-medicine motif (MAMM). Advocates draw on MAMM in two ways. First, they promote the same model of knowledge production as in medicine, e.g. championing ‘systematic reviews’. Second, they rely on comparisons between management and medicine as professional practices. Identified here are consequent problems and a ‘systematic review’ is considered in the Cochrane Database of Systematic Reviews. This concerns a management phenomenon: nursing turnover and there are now five versions of the review. Bizarrely, these never actually review any evidence and the different versions are incompatible. This shows how the protocols of ‘systematic’ reviews do not necessarily lead to superior evidence, instead they can disguise inaccuracies and inconsistencies. It also exemplifies problems with MAMM.

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