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Books on the topic 'Natural users interfaces'

Author: Grafiati

Published: 10 March 2023

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1

B, Anderson Alan, and Construction Engineering Research Laboratories (U.S.), eds. LCTA users interface program users manual: Version 1.0. Champaign, Ill: US Army Corps of Engineers, Construction Engineering Research Laboratories, 1995.

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2

Sabourin, Conrad. Natural language interfaces: Bibliography. Montréal, Qué: Infolingua, 1994.

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3

Sabourin, Conrad. Natural language interfaces: Bibliography. Montréal: Infolingua Inc., 1994.

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4

Ogiela, Marek R., and Tomasz Hachaj. Natural User Interfaces in Medical Image Analysis. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-07800-7.

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5

United States. National Aeronautics and Space Administration., ed. A natural language interface to databases. Huntsville, AL: University of Alabama in Huntsville, 1990.

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6

Developing natural language interfaces: Processing human conversations. New York: McGraw-Hill, 1997.

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7

Dennis, Wixon, ed. Brave NUI world: Designing natural user interfaces for touch and gesture. Burlington, Mass: Morgan Kaufmann, 2011.

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8

Practical Speech User Interface Design. Boca Raton, FL: CRC Press, 2011.

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9

Blake, Joshua. Natural user interfaces in .NET: WPF 4, Surface 2, and Kinect. Greenwich, Conn: Manning, 2011.

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10

Mihalcea, Rada. Graph-based natural language processing and information retrieval. Cambridge: Cambridge University Press, 2011.

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11

Spoken dialogue technology: Toward the conversational user interface. London: Springer, 2004.

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12

Sabourin, Conrad. Natural language interfaces: Interfaces to databases, to expert systems, to robots, to operating systems, and question-answering systems : bibliography. Montréal: Infolingua, 1994.

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13

G, Bès Gabriel, and Guillotin T, eds. A Natural language and graphics interface: Results and perspectives from the ACORD project. Berlin: Springer-Verlag, 1992.

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14

O, Mittal Vibhu, ed. Assistive technology and artificial intelligence: Applications in robotics, user interfaces, and natural language processing. Berlin: Springer, 1998.

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15

Nutter, J. Terry. Design for a fully transportable natural language front-end to database management systems. [Blacksburg, Va.]: Dept. of Computer Science, Virginia Polytechnic Institute and State University, 1989.

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16

Campbell, William J. The development of a prototype intelligent user interface subsystem for NASA's scientific database systems. Greenbelt, Md: Goddard Space Flight Center, 1987.

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17

Speech acts and prosodic modeling in service-oriented dialog systems. Hauppauge, N.Y: Nova Science Publishers, 2010.

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18

Burns, Bridget A. A critical appraisal of natural language as the preferred interface style for database information retrieval for novice managerial users. [S.l: The author], 1991.

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19

Steve, Sande, ed. Talking to Siri: Learning the language of Apple's intelligent assistant. Indianapolis, Ind: Que Pub., 2012.

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20

Twente, Workshop on Language Technology (5th 1993 Enchede Netherlands). Natural language interfaces: From laboratory to commercial and user environment : proceedings of the fifth Twent Workshop on Language Technology. Enchede: University of Twente, 1993.

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21

Rieser, Verena. Reinforcement Learning for Adaptive Dialogue Systems: A Data-driven Methodology for Dialogue Management and Natural Language Generation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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22

Olivier, Pietquin, and SpringerLink (Online service), eds. Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces. New York, NY: Springer New York, 2012.

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23

Heinroth, Tobias. Introducing Spoken Dialogue Systems into Intelligent Environments. New York, NY: Springer New York, 2013.

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24

Zhou, Ming. Natural Language Processing and Chinese Computing: First CCF Conference, NLPCC 2012, Beijing, China, October 31-November 5, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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25

Ashwin, Ittoo, Métais Elisabeth, Wortmann Hans, and SpringerLink (Online service), eds. Natural Language Processing and Information Systems: 17th International Conference on Applications of Natural Language to Information Systems, NLDB 2012, Groningen, The Netherlands, June 26-28, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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26

Pitt, Ian. Design of speech-based devices: A practical guide. London: Springer, 2003.

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27

Aleš, Horák, Kopeček Ivan, Pala Karel, and SpringerLink (Online service), eds. Text, Speech and Dialogue: 15th International Conference, TSD 2012, Brno, Czech Republic, September 3-7, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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28

A field study of natural language interaction: Can content-familiar, casual users "naturally" query a database? Ottawa: National Library of Canada, 1988.

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29

Preim, Bernhard, and Raimund Dachselt. Interaktive Systeme : Band 2: User Interface Engineering, 3D-Interaktion, Natural User Interfaces. Springer Berlin / Heidelberg, 2015.

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30

Aspman-O'Callaghan, Robin. In search of the natural user interface. 1987.

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31

Dahl, Deborah A. Multimodal Interaction with W3C Standards: Toward Natural User Interfaces to Everything. Springer London, Limited, 2016.

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32

Dahl, Deborah A. Multimodal Interaction with W3C Standards: Toward Natural User Interfaces to Everything. Springer, 2016.

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33

Dahl, Deborah A. Multimodal Interaction with W3C Standards: Toward Natural User Interfaces to Everything. Springer, 2018.

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34

Blokdyk, Gerardus. Natural User Interface a Complete Guide - 2020 Edition. Emereo Pty Limited, 2020.

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35

Wigdor, Daniel, and Dennis Wixon. Brave NUI World: Designing Natural User Interfaces for Touch and Gesture. Elsevier Science & Technology Books, 2011.

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36

Perry, Phoenix, Sean Kean, and Jonathan Hall. Meet the Kinect: An Introduction to Programming Natural User Interfaces. Springer, 2011.

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37

A natural language interface to databases: Final report. Marshall Space Flight Center, AL: System Software Branch, Information and Electronic Systems Lab, George C. Marshall Space Flight Center, National Aeronautics and Space Administration, 1988.

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38

Pfurtscheller, Gert, Clemens Brunner, and Christa Neuper. EEG-Based Brain–Computer Interfaces. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0047.

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A brain–computer interface (BCI) offers an alternative to natural communication and control by recording brain activity, processing it online, and producing control signals that reflect the user’s intent or the current user state. Therefore, a BCI provides a non-muscular communication channel that can be used to convey messages and commands without any muscle activity. This chapter presents information on the use of different electroencephalographic (EEG) features such as steady-state visual evoked potentials, P300 components, event-related desynchronization, or a combination of different EEG features and other physiological signals for EEG-based BCIs. This chapter also reviews motor imagery as a control strategy, discusses various training paradigms, and highlights the importance of feedback. It also discusses important clinical applications such as spelling systems, neuroprostheses, and rehabilitation after stroke. The chapter concludes with a discussion on different perspectives for the future of BCIs.

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39

Rahman, Mansib. Beginning Microsoft Kinect for Windows SDK 2.0: Motion and Depth Sensing for Natural User Interfaces. Apress, 2017.

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40

Ell, Basil. User Interfaces to the Web of Data Based on Natural Language Generation. Saint Philip Street Press, 2020.

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41

Gateway software and natural language interfaces: Options for online searching. Ann Arbor, Mich: Pierian Press, 1988.

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42

Mihalcea, Rada, and Dragomir Radev. Graph-Based Natural Language Processing and Information Retrieval. Cambridge University Press, 2011.

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43

Mihalcea, Rada, and Dragomir Radev. Graph-Based Natural Language Processing and Information Retrieval. Cambridge University Press, 2011.

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44

Bes, G. G. A Natural Language and Graphic Interface: Results and Perspectives from the Acord Project (Research Reports Espirit : Project 393 Acord, Vol 1). Springer, 1992.

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45

Wisniowski, Antoni. An assessment of the effectiveness of a natural language interface for information retrieval. 1995.

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46

Azzopardi, Leif, and Guido Zuccon. Economic Models of Interaction. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198799603.003.0012.

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This chapter provides a tutorial on how economics can be used to model the interaction between users and systems. Economic theory provides an intuitive and natural way to model Human-Computer Interaction which enables the prediction and explanation of user behaviour. A central tenet of the approach is the utility maximisation paradigm where it is assumed that users seek to maximise their profit/benefit subject to budget and other constraints when interacting with a system. By using such models it is possible to reason about user behaviour and make predictions about how changes to the interface or the users interactions will affect performance and behaviour. In this chapter, we describe and develop several economic models relating to how users search for information. While the examples are specific to Information Seeking and Retrieval, the techniques employed can be applied more generally to other human-computer interaction scenarios. Therefore, the goal of this chapter is to provide an introduction and overview of how to build economic models of human-computer interaction that generate testable hypotheses regarding user behaviour which can be used to guide design and inform experimentation.

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47

Ogiela, Marek R., and Tomasz Hachaj. Natural User Interfaces in Medical Image Analysis: Cognitive Analysis of Brain and Carotid Artery Images. Springer, 2014.

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48

Ogiela, Marek R. R., and Tomasz Hachaj. Natural User Interfaces in Medical Image Analysis: Cognitive Analysis of Brain and Carotid Artery Images. Springer, 2016.

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49

Ogiela, Marek R., and Tomasz Hachaj. Natural User Interfaces in Medical Image Analysis: Cognitive Analysis of Brain and Carotid Artery Images. Springer, 2014.

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50

Drews, Frank A., and Jonathan R. Zadra. The Human-Technology Interface. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199366149.003.0004.

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The goal of this chapter is to outline considerations that are critical for the development of effective human-technology interfaces (HTI) in anesthesiology. It first provides an introduction to the social aspects of human technology interaction (the socio-technical systems perspective). It describes some of the specific properties of monitoring natural systems (i.e., patients) and how they differ from the task of monitoring technical systems (i.e., airplanes). The chapter examines important human factors concepts that should be considered when developing an HTI (e.g., the controls for a new medical device) and describes the currently available types of interfaces in anesthesia by focusing on tasks and devices. It presents considerations of how automation impacts the practice of anesthesiology, with a detailed description of currently available automated systems, and discusses principles of user-centered design. . The chapter concludes with an outlook of how future technologies in anesthesia will pose new challenges for HTI development.

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