Intelligent Computing for Interactive System Design : Statistics, Digital Signal Processing, and Machine Learning in Practice / Parisa Eslambolchilar, Andreas Komninos, Mark Dunlop.

Format:

Book

Author/Creator:

Eslambolchilar, Parisa, author.

Series:

ACM books - Collection 2 ; #34.

ACM books, 2374-6777 ; #34

Language:

English

Subjects (All):

Intelligent Computing (Computer Science).

Genre:

Electronic books.

Physical Description:

1 online resource (xvi, 455 pages) LuaTEX

Edition:

First Edition

Place of Publication:

[New York, NY, USA] : Association for Computing Machinery; [2021].

System Details:

Mode of access: World Wide Web

System requirements: Adobe Acrobat Reader

Contents:

Preface

Introduction

Ubiquitous HCI

Data-driven Opportunities and Challenges in Novel HCI

Statistics, DSP, and ML as Tools for HCI Design and Evaluation

Aims and Scope of this Book

Structure of this Book

References

Ethical Issues in Digital Signal Processing and Machine Learning

Ethical Frameworks

Professional Ethics and Computer Science

Summary

1 Internet of Everything

1.1 Introduction

1.2 The Importance of DSP and ML in IoE Applications

1.3 Elements and Enabling Technologies for DSP and ML in IoE Applications

1.4 Computing Paradigms for IoE Data Analysis

1.5 Security, Privacy, and Data Confidentiality

1.6 Challenges and Future Directions

1.7 Follow-up Questions

1E The Internet of Everything

Introducing Privacy

2 Statistical Grounding

2.1 Terminologies

2.2 Sample and Population

2.3 Level of Measurement

2.4 Data Collection and Logging

2.5 Descriptive Statistics

2.6 Outliers

2.7 Hypothesis Testing

2.8 Parametric Tests

2.9 Non-parametric Tests

2.10 Case Study

2.11 Further Reading

2E Ethics and Statistics

3 DSP Basics

3.1 Introduction

3.2 Signals

3.3 Analog-to-digital Conversion

3.4 Digital-to-analog Conversion

3.5 Discrete Fourier Transform

3.6 Autocorrelation

3.7 LTI Systems

3.8 Use Case Example

3.9 Follow-up Questions

3.10 Summary

3E Ethical Issues of Digital Signal Processing

4 Machine Learning Basics

4.1 Probability Primer

4.2 Supervised Learning

4.3 Unsupervised Learning: Clustering

4.4 Practical Aspects

4.5 Summary and Links

4.6 Follow-up Questions

4E Ethical Issues in Machine Learning

5 Combining Infrastructure Sensor and Tourism Market Data in a Smart City Project-Case Study 1

5.1 Tourism Analytics

5.2 Making Sense of the Available Glasgow Data

5.3 Predicting Business Indicators

5.4 Multivariate Predictions

5.5 Simple Visualization

5.6 Summary

Acknowledgments

Author Contributions

5E Ethics and Smart Cities

6 Brain-Computer Interfacing with Interactive Systems

Case Study 2

6.1 Introduction

6.2 Interfacing with the Brain

6.3 Interacting with VR

6.4 Conclusions

6.5 Follow-up Questions

6.6 Further Reading

References

6E Ethical Issues in Brain

Computer Interfaces

7 Probabilistic Text Entry

Case Study 3

7.1 Uncertain Text Input

7.2 Statistical Formulation

7.3 Input Modeling

7.4 Language Modeling

7.5 Decoding

7.6 User Interface Issues

7.7 Case Study: Typing on a Smartwatch

7.8 Discussion and Conclusions

7.9 Follow-up Questions

7.10 Further Reading

7E Ethical Issues in Probabilistic Text Entry

8 Secure Gestures

Case Study 4

8.1 What Are Secure Gestures?

8.2 Background: The Problem of Recognition

8.3 Recognition Approaches

8.4 Metrics for Evaluating Recognition Approaches

8.5 Attacks Against Gesture-based Authentication

8.6 Summary

8.7 Follow-up Question

8.8 Further Reading

8E Ethics and Secure Gestures

9 Personal Context from Mobile Phones

Case Study 5

9.1 What Is Personal Context?

9.2 Example: Inferring Phone Placement

9.3 Inferring Social Relationships from Communication Behavior

9.4 Conclusion

9.5 Follow-up Questions

9E Ethics and Personal Context

10 Building Adaptive Touch Interfaces

Case Study 6

10.1 Motivation for Adaptive, Probabilistic Touch Interfaces

10.2 Three Key Challenges for Developing Adaptive Touch Interfaces

10.3 The ProbUI Framework

10.4 Development Examples

10.5 Reflection from a Developer Perspective

10.6 Conclusion and Outlook

10.7 Follow-up Questions

10.8 Further Reading

Acknowledgment

10E Ethics and Adaptive Touch Interfaces

11 Driver Cognitive Load Classification Based on Physiological Data

Case Study 7

11.1 Motivation for Driver State Estimation

11.2 Driver Cognitive Load Detection Methods

11.3 Case Study: Cognitive Load Classification Using Driver Physiological Data

11.4 Conclusion

11.5 Further Reading

11.6 Follow-up Questions

11E Ethics in Automotive User Interface

Author's Biography

Index

Other Format:

Print version:

ISBN:

3447404

9781450390279

9781450390286

Access Restriction:

Restricted for use by site license.