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1

Derbel, Nabil, and Olfa Kanoun, eds. Advanced Methods for Human Biometrics. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81982-8.

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2

Harvey, Schuster, and Metzger Wilfred, eds. Biometrics: Methods, applications and analyses. Hauppauge, N.Y: Nova Science Publishers, 2009.

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3

Biometrics: Methods, applications and analyses. New York: Nova Science Publishers, 2010.

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4

Biometrics: Theory, methods, and applications. Piscataway, N.J: IEEE Press, 2010.

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5

Ranta, Esa. Biometria: Tilastotiedettä ekologeille. 4th ed. Helsinki: Yliopistopaino, 1992.

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6

Schuckers, Michael E. Computational Methods in Biometric Authentication. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-202-5.

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7

Schuckers, Michael E. Computational methods in biometric authentication: Statistical methods for performance evaluation. London: Springer, 2010.

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8

Bilan, Stepan, Mohamed Elhoseny, and D. Jude Hemanth, eds. Biometric Identification Technologies Based on Modern Data Mining Methods. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-48378-4.

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9

Pejaś, Jerzy, and Andrzej Piegat, eds. Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/b101135.

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10

1928-, Searle S. R., ed. Proceedings of the conference in honor of Shayle R. Searle: August 9-10, 1996, Biometrics Unit, Cornell University. Ithaca, NY: Biometrics Unit, Cornell University, 1998.

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11

Exposure-response modeling: Methods and practical implementation. Boca Raton: CRC Press, Taylor & Francis, 2016.

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12

Statistical methods for disease clustering. New York: Springer, 2010.

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13

J, Berry Kenneth, ed. Permutation methods: A distance function approach. 2nd ed. New York: Springer, 2007.

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14

Bayesian methods for repeated measures. Boca Raton: CRC Press, Taylor & Francis Group, 2016.

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15

Biostatistics and epidemiology: A primer for health professionals. 2nd ed. New York: Springer-Verlag, 1995.

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16

Biostatistics and epidemiology: A primer for health professionals. New York: Springer-Verlag, 1990.

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17

1968-, Jacqmin-Gadda Hélène, ed. Dynamical biostatistical models. Boca Raton: CRC Press/Taylor & Francis, 2016.

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18

Christoph, Lange, ed. The fundamentals of modern statistical genetics. New York: Springer Science, 2011.

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19

Sutradhar, Brajendra C. Dynamic mixed models for familial longitudinal data. New York: Springer, 2011.

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20

service), SpringerLink (Online, ed. Multivariate nonparametric methods with R: An approach based on spatial signs and ranks. New York, N.Y: Springer, 2010.

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21

Gacovski, Zoran. Biometrics Authentication Methods. Arcler Education Inc, 2019.

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22

Gacovski, Zoran. Biometrics Authentication Methods. Arcler Education Inc, 2019.

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23

Kanoun, Olfa, and Nabil Derbel. Advanced Methods for Human Biometrics. Springer International Publishing AG, 2022.

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24

Kanoun, Olfa, and Nabil Derbel. Advanced Methods for Human Biometrics. Springer International Publishing AG, 2021.

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25

Computational Intelligence Methods For Biometrics Applications. IEEE Computer Society Press, 2009.

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26

Drahanský, Martin, ed. Hand-Based Biometrics: Methods and Technology. Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/pbse008e.

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27

Hand-Based Biometrics: Methods and technology. The Institution of Engineering and Technology, 2018.

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28

Drahanský, Martin. Hand-Based Biometrics: Methods and Technology. Institution of Engineering & Technology, 2018.

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29

Zhang, David. Medical Biometrics. Springer, 2008.

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30

Schuckers, Michael E. Computational Methods in Biometric Authentication: Statistical Methods for Performance Evaluation. Springer London, Limited, 2012.

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31

Sinha, G. R. Advances in Biometrics: Modern Methods and Implementation Strategies. Springer, 2019.

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32

Sinha, G. R. Advances in Biometrics: Modern Methods and Implementation Strategies. Springer International Publishing AG, 2021.

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33

Boubchir, Larbi. Biometric Recognition and Security: Theory, Methods and Applications. Elsevier, 2019.

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34

Boubchir, Larbi. Biometric Recognition and Security: Theory, Methods and Applications. Elsevier, 2019.

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35

Hemanth, D. Jude, Mohamed Elhoseny, and Stepan Bilan. Biometric Identification Technologies Based on Modern Data Mining Methods. Springer, 2020.

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36

Hemanth, D. Jude, Mohamed Elhoseny, and Stepan Bilan. Biometric Identification Technologies Based on Modern Data Mining Methods. Springer International Publishing AG, 2021.

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37

Medical Biometrics: Computerized TCM Data Analysis. World Scientific Publishing Co Pte Ltd, 2016.

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38

Piegat, Andrzej, and Jerzy Pejas. Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems. Springer, 2010.

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39

Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems. Springer, 2006.

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40

(Editor), Jerzy Pejas, and Andrzej Piegat (Editor), eds. Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems. Springer, 2004.

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41

Talbot, P. Amaury, and H. Mulhall. The Physical Anthropology of Southern Nigeria: A Biometric Study in Statistical Method. Cambridge University Press, 2013.

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42

Nacke, Lennart E. Introduction to biometric measures for Games User Research. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198794844.003.0016.

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This chapter presents the physiological metrics used in Games User Research (GUR). Aimed at GUR professionals in the games industry, it explains what methods are available to researchers to measure biometric data while subjects are engaged in play. It sets out when it is appropriate to use biometric measures in GUR projects, the kind of data generated, and the differing ways it can be analysed. The chapter also discusses the trade-offs required when interpreting physiological data, and will help games researchers to make informed decisions about which research questions can benefit from biometric methodologies. As the equipment needed to collect biometric data becomes more sophisticated as well as cheaper, physiological testing of players during a game’s development will become more common. At the same time, Games User Researchers will become more discriminating in its use. Where in the past professionals in the games industry have used biometric testing to generate quick, actionable feedback about player responses to elements of a game, and have been less concerned with the scientific robustness of their methodology, as GUR develops a new breed of games industry professionals are attempting to deploy good academic practice in their researches.
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43

Bilan, Stepan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov. Biometric Data in Smart Cities: Methods and Models of Collective Behavior. Taylor & Francis Group, 2021.

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44

Bilan, Stepan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov. Biometric Data in Smart Cities: Methods and Models of Collective Behavior. Taylor & Francis Group, 2021.

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45

Bilan, Stepan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov. Biometric Data in Smart Cities: Methods and Models of Collective Behavior. Taylor & Francis Group, 2021.

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46

Objective Biometric Methods for the Diagnosis and Treatment of Nervous System Disorders. Elsevier, 2018. http://dx.doi.org/10.1016/c2015-0-00380-x.

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47

Torres, Elizabeth B. Objective Biometric Methods for the Diagnosis and Treatment of Nervous System Disorders. Elsevier Science & Technology Books, 2018.

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48

Wilson, Gregory, David H. Olwell, and Alyson Wilson. Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication. Springer London, Limited, 2007.

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49

(Editor), Alyson G. Wilson, Gregory D. Wilson (Editor), and David H. Olwell (Editor), eds. Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication. Springer, 2006.

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50

Torres, Elizabeth B. Objective Biometric Methods for the Diagnosis and Treatment of Nervous System Disorders. Elsevier Science & Technology Books, 2018.

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