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Books on the topic 'Counter data'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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1

Thuraisingham, Bhavani. Web Data Mining and Applications in Business Intelligence and Counter-Terrorism. London: Taylor and Francis, 2003.

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2

Baccelli, F. Stationary ergodic Jackson networks: Results and counter-examples. Bristol [England]: Hewlett Packard, 1996.

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3

Natow, Annette B. The most complete food counter. 2nd ed. New York: Pocket Books, 2006.

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4

Miller, C. J. Euler analysis comparison with LDV data for a advanced counter-rotation propfan at cruise. [Washington, DC: National Aeronautics and Space Administration, 1990.

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5

Skoudis, Ed. Counter hack: A step-by-step guide to computer attacks and effective defenses. Upper Saddle River, N.J: Prentice Hall PTR, 2002.

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6

Ed, Skoudis, and Liston Tom, eds. Counter hack reloaded: A step-by-step guide to computer attacks and effective defenses. 2nd ed. Upper Saddle River, NJ: Prentice Hall Professional Technical Reference, 2006.

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7

Levy-Ryan, Ellen. Moored current meter data from the Atlantic north equatorial counter current near 6⁰ N 28⁰ W (March-October, 1984): Vol. XXXVII. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1985.

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8

Kotlar, Kim Leslie. Predicting actions taken to counter economic sanctions: An examination of U.S. government financial data collection and its usefulness in determining if foreign governments anticipate economic sanctions : a case study of Iraq. Monterey, Calif: Naval Postgraduate School, 1992.

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9

United States. Agency for International Development. Bureau for Africa. Office of Sustainable Development. Country data profile: Orphans : 14 focus countries. Washington, D.C.]: U.S. Agency for International Development, Bureau for Africa, Office of Sustainable Development, 2003.

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10

Bangsund, Dean A. North Dakota county government expenditures, 1977-1986 data sets. Fargo, N.D: Dept. of Agricultural Economics, Agricultural Experiment Station, North Dakota State University, 1990.

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11

Organisation for Economic Co-operation and Development. Development Centre., ed. Politics and economic growth: A cross-country data perspective. Paris: OECD, 1997.

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12

Honohan, Patrick. Measuring microfinance access: Building on existing cross-country data. [Washington, D.C: World Bank, 2005.

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13

Nana, Ganesh. The JOANI two country general equilibrium model: Data bases & equations. Wellington: Victoria University of Wellington, Research Project on Economic Planning, 1989.

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14

Moore, James Gregory. Mount Whitney quadrangle, Inyo and Tulare counties, California: Analytic data. Washington: U.S. G.P.O., 1987.

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15

Galvin, William Francis. Historical data relating to counties, cities, and towns in Massachusetts. Boston, MA: New England Historic Genealogical Society, 1997.

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16

Acton, Jan Paul. Telephone demand over the Atlantic: Evidence from country-pair data. Santa Monica, CA: Rand, 1990.

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17

Whitburn, Joel. Top country singles, 1944 to 2001: Chart data compiled from Billboard's country singles charts, 1944-2001. 5th ed. Menomonee Falls, Wis: Record Research, 2002.

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18

Whitburn, Joel. Joel Whitburn's top country singles, 1944-1997: Chart data compiled from Billboard's country singles charts, 1944-1997. 4th ed. Menomonee Falls, Wis., U.S.A: Record Research, 1998.

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19

Peters, Matthew P. Integrating fine-scale soil data into species distribution models: Preparing soil survey geographic (SSURGO) data from multiple counties. Newtown Square, PA: U.S. Dept. of Agriculture, Forest Service, Northern Research Station, 2013.

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20

Mingat, Alain. The mechanics of progress in education: Evidence from cross-country data. Washington, DC (1818 H St. NW, Washington 20433): World Bank, Human Development Dept., Education Group, 1998.

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21

Sisson, Thomas W. Triple Divide Peak quadrangle, Fresno and Tulare counties, California--: Analytic data. [Reston, Va.?]: U.S. Dept. of the Interior, U.S. Geological Survey, 1992.

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22

Allum, Peter. Economic data dissemination: What influences country performance on frequency and timeliness? [Washington, D.C.]: International Monetary Fund, Middle Eastern Department, 2001.

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23

Gerlach, Stefan. Testing the quantity theory using long-run averaged cross-country data. Basle: Bank for International Settlements, Monetary and Economic Department, 1995.

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24

Computers in education: An outline of country experiences. Bangkok: Unesco Regional Office for Education in Asia and the Pacific, 1985.

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25

Perkins, Jeanne B. Existing land use in 1995: Data for Bay Area counties and cities. Oakland, CA: ABAG, 1996.

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26

Perkins, Jeanne B. Existing land use in 1990: Data for bay area counties and cities. Oakland: Association of Bay Area Governments, 1994.

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27

Pellechio, Anthony J. Data consistency in IMF publications: Country Staff Reports versus International Financial Statistics. Washington, D.C: International Monetary Fund, Statistics Dept., 2005.

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28

G, Abdel-Kader Magdy, and Sherer Michael, eds. Enterprise resource planning: Implementation and management accounting change in a transitional country. New York: Palgrave Macmillan, 2008.

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29

Lohsse, Sebastian, Reiner Schulze, and Dirk Staudenmayer, eds. Data as Counter-Performance - Contract Law 2.0? Nomos Verlagsgesellschaft mbH & Co. KG, 2020. http://dx.doi.org/10.5771/9783748908531.

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This 5th volume in the “Münster Colloquia on EU Law and the Digital Economy” focuses on one of the most important challenges faced by private law in this era of digitalization: the effects of “data as counter-performance” on contract law; a phenomenon acknowledged by the EU legislator in the new “Digital Content Directive” 2019/770. In this volume, legal experts from across Europe examine various issues, in particular contract performance and restitution, and the relationship between contract law and data protection, central to the question: Contract law 2.0?
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30

Blokdyk, Gerardus. Over the Counter Data a Complete Guide - 2020 Edition. Emereo Pty Limited, 2020.

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31

Martin, Keith M. Data Integrity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198788003.003.0006.

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This chapter discusses cryptographic mechanisms for providing data integrity. We begin by identifying different levels of data integrity that can be provided. We then look in detail at hash functions, explaining the different security properties that they have, as well as presenting several different applications of a hash function. We then look at hash function design and illustrate this by discussing the hash function SHA-3. Next, we discuss message authentication codes (MACs), presenting a basic model and discussing basic properties. We compare two different MAC constructions, CBC-MAC and HMAC. Finally, we consider different ways of using MACs together with encryption. We focus on authenticated encryption modes, and illustrate these by describing Galois Counter mode.
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32

Web Data Mining and Applications in Business Intelligence and Counter-Terrorism. CRC, 2003.

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33

Thuraisingham, Bhavani. Web Data Mining and Applications in Business Intelligence and Counter-Terrorism. CRC Press, 2003. http://dx.doi.org/10.1201/9780203499511.

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34

Tzanou, Maria. Fundamental Right to Data Protection: Normative Value in the Context of Counter-Terrorism. Bloomsbury Publishing Plc, 2017.

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35

Tzanou, Maria. Fundamental Right to Data Protection: Normative Value in the Context of Counter-Terrorism Surveillance. Bloomsbury Publishing Plc, 2019.

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36

Godin, Seth. The Fat Calories Sodium Counter: Complete Data on Hundreds of Foods (Cader Flips Title). Andrews McMeel Pub, 1997.

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37

Skoudis, Ed. Counter Hack: A Step-by-Step Guide to Computer Attacks and Effective Defenses. Prentice Hall PTR, 2001.

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38

Skoudis, Ed. Counter Hack: A Step-by-Step Guide to Computer Attacks and Effective Defenses. Prentice Hall PTR, 2001.

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39

Kareiva, Peter, and Michelle Marvier. Uncomfortable questions and inconvenient data in conservation science. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808978.003.0001.

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This chapter outlines the problems of exaggeration, misuse of statistics, and publication bias that plague all scientific disciplines, but that may be especially acute in the mission-oriented field of conservation. Because conservation describes itself as a crisis discipline, its scientific publications tend to reinforce that view, even when the data are lacking. And when data run counter to accepted wisdom, out of fear such results might be misinterpreted or misused to counter conservation’s mission, the review process sometimes favors dogma over data. Black-box models, data gaps filled with expert opinion, and a general lack of easy access to key data make the testing of alternative hypotheses or interpretations extremely difficult. Self-correction and iteration are key to scientific progress. In conservation especially, with the fate of biodiversity in the balance, it is essential that conservationists get the science right, even if it means admitting mistakes.
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40

Heslin, Jo-Ann, and Annette B. Natow. The Most Complete Food Counter: 2nd Edition. 2nd ed. Pocket, 2005.

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41

T, Pollard R., Polarstern (Ship), and Southampton Oceanography Centre, eds. Optical plankton counter SeaSoar data collected on Polarstern Cruise ANT-XIII/2, 04 Dec 1995-24 Jan 1996. Southampton, UK : Southampton Oceanography Centre, 1996.

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42

Gunnar's Basic Internet Security Guide: Protecting Europe's Trade and State Secrets. Campione d'Italia, Italy: SPACEPOL Academic Publishers, 2015.

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43

Gunnar's Basic Internet Security Guide: Protecting Europe's Trade and State Secrets. Campione d'Italia, Italy: SPACEPOL Academic Publishers, 2015.

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44

Skoudis, Edward, and Tom Liston. Counter Hack Reloaded: A Step-by-Step Guide to Computer Attacks and Effective Defenses (2nd Edition) (The Radia Perlman Series in Computer Networking and Security). 2nd ed. Prentice Hall PTR, 2005.

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45

Skoudis, Edward, and Tom Liston. Counter Hack Reloaded: A Step-by-Step Guide to Computer Attacks and Effective Defenses (2nd Edition) (The Radia Perlman Series in Computer Networking and Security). Prentice Hall PTR, 2005.

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46

Bank of America. World Information Services., ed. Country data forecasts. San Francisco, Calif. (555 California St., San Francisco 94104): Bank of America, 1991.

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47

Country data papers: Africa. [Washington, D.C.]: USIA, 1989.

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48

Zarins, Sasha, and Sara Konrath. Changes Over Time in Compassion-Related Variables in the United States. Edited by Emma M. Seppälä, Emiliana Simon-Thomas, Stephanie L. Brown, Monica C. Worline, C. Daryl Cameron, and James R. Doty. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190464684.013.25.

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Compassion, or empathic concern, is an emotional response to another’s suffering, coupled with the desire to take action to alleviate that suffering. Throughout history, older generations have been critical of younger generations, often arguing that they are more self-focused than previous generations. However, it is important to examine actual data with respect to changes over time in such variables. Without doing so, we risk spreading potentially harmful and inaccurate stereotypes about young Americans. The goal of this chapter is to review research examining changes over time in compassion-related variables in the United States. Research suggests that compassion-related variables have indeed been declining over time, while self-focused variables have been increasing. However, we will also discuss counter-arguments and counter-evidence, and present possible implications of this research.
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49

K, Hilpert, and United States. National Aeronautics and Space Administration., eds. Mass spectrometric high temperature measurements of the barium oxide-zirconium dioxide system and the determination of thermodynamic data for barium zirconate: Clarification of the counter-stopping capacity of coated particles for solid fission products by zirconium dioxude addition. Washington, DC: National Aeronautics and Space Administration, 1988.

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50

Associates, William C. Overman, ed. Virginia counties and cities data book, 1986. Virginia Beach, Va. (380 Cleveland Place, Virginia Beach 23462): W.C. Overman, 1986.

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