Muutke küpsiste eelistusi

E-raamat: Emerging Extended Reality Technologies for Industry 4.0: Early Experiences with Conception, Design, Implementation, Evaluation and Deployment

5.00/5 (2 hinnangut Goodreads-ist)
Edited by , Edited by , Edited by
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 14-Apr-2020
  • Kirjastus: Wiley-Scrivener
  • Keel: eng
  • ISBN-13: 9781119654735
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 225,94 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Raamatukogudele
Emerging Extended Reality Technologies for Industry 4.0: Early Experiences with Conception, Design, Implementation, Evaluation and DeploymentSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 14-Apr-2020
  • Kirjastus: Wiley-Scrivener
  • Keel: eng
  • ISBN-13: 9781119654735
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

In the fast-developing world of Industry 4.0, which combines Extended Reality (XR) technologies, such as Virtual Reality (VR) and Augmented Reality (AR), creating location aware applications to interact with smart objects and smart processes via Cloud Computing strategies enabled with Artificial Intelligence (AI) and the Internet of Things (IoT), factories and processes can be automated and machines can be enabled with self-monitoring capabilities. Smart objects are given the ability to analyze and communicate with each other and their human co-workers, delivering the opportunity for much smoother processes, and freeing up workers for other tasks. Industry 4.0 enabled smart objects can be monitored, designed, tested and controlled via their digital twins, and these processes and controls are visualized in VR/AR. The Industry 4.0 technologies provide powerful, largely unexplored application areas that will revolutionize the way we work, collaborate and live our lives. It is important to understand the opportunities and impact of the new technologies and the effects from a production, safety and societal point of view.

List of Figures
xi
List of Tables
xv
Foreword xvii
Introduction xix
Preface xxiii
Acknowledgments xxv
Acronyms xxvii
Part I Extended Reality Education
1 Mixed Reality Use in Higher Education: Results from an International Survey
3(14)
J. Riman
N. Winters
J. Zelenak
I. Yucel
J. G. Tromp
1.1 Introduction
4(1)
1.2 Organizational Framework
4(1)
1.3 Online Survey About MR Usage
5(1)
1.4 Results
6(7)
1.4.1 Use in Classrooms
8(1)
1.4.2 Challenges
9(1)
1.4.3 Examples of Research in Action
10(1)
1.4.4 Hardware and Software for Use in Classrooms and Research
10(2)
1.4.5 Challenges Described by Researcher Respondents
12(1)
1.4.6 Anecdotal Responses about Challenges
12(1)
1.5 Conclusion
13(2)
References
15(2)
2 Applying 3D VR Technology for Human Body Simulation to Teaching, Learning and Studying
17(14)
Le Van Chung
Gia Nhu Nguyen
TungSanh Nguyen
Tri Huu Nguyen
Dac-Nhuong Le
2.1 Introduction
18(1)
2.2 Related Works
18(1)
2.3 3D Human Body Simulation System
19(6)
2.3.1 The Simulated Human Anatomy Systems
19(1)
2.3.2 Simulated Activities and Movements
20(3)
2.3.3 Evaluation of the System
23(2)
2.4 Discussion of Future Work
25(1)
2.5 Conclusion
26(1)
References
26(5)
Part II Internet Of Things
3 A Safety Tracking and Sensor System for School Buses in Saudi Arabia
31(14)
Samah Abbas
Hajar Mohammed
Laila Almalki Maryam Hassan
Maram Meccawy
3.1 Introduction
32(1)
3.2 Related Work
32(1)
3.3 Data Gathering Phase
33(3)
3.3.1 Questionnaire
34(1)
3.3.2 Driver Interviews
35(1)
3.4 The Proposed Safety Tracking and Sensor School Bus System
36(5)
3.4.1 System Analysis and Design
37(1)
3.4.2 User Interface Design
38(3)
3.5 Testing and Results
41(1)
3.6 Discussion and Limitation
42(1)
3.7 Conclusions and Future Work
42(1)
References
42(3)
4 A Lightweight Encryption Algorithm Applied to a Quantized Speech Image for Secure IoT
45(18)
Mourad Talbi
4.1 Introduction
46(1)
4.2 Applications of IoT
46(1)
4.3 Security Challenges in IoT
47(1)
4.4 Cryptographic Algorithms for IoT
47(1)
4.5 The Proposed Algorithm
48(2)
4.6 Experimental Setup
50(2)
4.7 Results and Discussion
52(5)
4.8 Conclusion
57(1)
References
58(5)
Part III Mobile Technology
5 The Impact of Social Media Adoption on Entrepreneurial Ecosystem
63(18)
Bodor Almotairy
Manal Abdullah
Rabeeh Abbasi
5.1 Introduction
64(1)
5.2 Background
65(1)
5.2.1 Small and Medium-Sized Enterprises (SMEs)
65(1)
5.2.2 Social Media
65(1)
5.2.3 Social Networks and Entrepreneurial Activities
66(1)
5.3 Analysis Methodology
66(1)
5.4 Understanding the Entrepreneurial Ecosystem
67(2)
5.5 Social Media and Entrepreneurial Ecosystem
69(4)
5.5.1 Social Media Platforms and Entrepreneurship
71(1)
5.5.2 The Drivers of Social Media Adoption
71(1)
5.5.3 The Motivations and Benefits for Entrepreneurs to Use Social Media
71(1)
5.5.4 Entrepreneurship Activities Analysis Techniques in Social Media Networks
71(2)
5.6 Research Gap and Recommended Solution
73(1)
5.6.1 Research Gap
73(1)
5.6.2 Recommended Solution
74(1)
5.7 Conclusion
74(1)
References
75(6)
6 Human Factors for E-Health Training System: UX Testing for XR Anatomy Training App
81(20)
Zhushun Timothy Cai
Oliver Medonza
Kristen Ray
Chung Van Le
Damian Schofield
Jolanda Tromp
6.1 Introduction
82(1)
6.2 Mobile Learning Applications
82(1)
6.3 Ease of Use and Usability
82(4)
6.3.1 Effectiveness
83(1)
6.3.2 Efficiency
83(1)
6.3.3 Satisfaction
83(3)
6.4 Methods and Materials
86(3)
6.5 Results
89(4)
6.5.1 Task Completion Rate (TCR)
89(1)
6.5.2 Time-on-Task (TOT)
90(1)
6.5.3 After-Scenario Questionnaire (ASQ)
91(2)
6.5.4 Post-Study System Usability Questionnaire (PSSUQ)
93(1)
6.6 Conclusion
93(1)
References
94(7)
Part IV Towards Digital Twins and Robotics
7 Augmented Reality at Heritage Sites: Technological Advances and Embodied Spatially Minded Interactions
101(20)
Lesley Johnston
Romy Galloway
Jordan John Trench
Matthieu Poyade
Jolanda Tromp
Hoang Thi My
7.1 Introduction
102(1)
7.2 Augmented Reality Devices
103(2)
7.3 Detection and Tracking
105(1)
7.4 Environmental Variation
106(3)
7.5 Experiential and Embodied Interactions
109(5)
7.6 User Experience and Presence in AR
114(1)
7.7 Conclusion
115(1)
References
116(5)
8 TELECI Architecture for Machine Learning Algorithms Integration in an Existing LMS
121(20)
V. Zagorskis
A. Gorbunovs
A. Kapenieks
8.1 Introduction
122(1)
8.2 TELECI Architecture
123(5)
8.2.1 TELECI Interface to a Real LMS
123(1)
8.2.2 First RS Steps in the TELECI System
124(1)
8.2.3 Real Student Data for VS Model
125(1)
8.2.4 TELECI Interface to VS Subsystem
126(2)
8.2.5 TELECI Interface to AI Component
128(1)
8.3 Implementing ML Technique
128(5)
8.3.1 Organizational Activities
128(1)
8.3.2 Data Processing
129(1)
8.3.3 Computing and Networking Resources
130(1)
8.3.4 Introduction to Algorithm
130(2)
8.3.5 Calibration Experiment
132(1)
8.4 Learners' Activity Issues
133(3)
8.5 Conclusion
136(1)
References
137(4)
Part V Big Data Analytics
9 Enterprise Innovation Management in Industry 4.0: Modeling Aspects
141(24)
V. Babenko
9.1 Introduction
142(2)
9.2 Conceptual Model of Enterprise Innovation Process Management
144(3)
9.3 Formation of Restrictions for Enterprise Innovation Management Processes
147(1)
9.4 Formation of Quality Criteria for Assessing Implementation of Enterprise Innovation Management Processes
148(1)
9.5 Statement of Optimization Task of Implementation of Enterprise Innovation Management Processes
148(2)
9.6 Structural and Functional Model for Solving the Task of Dynamic
150(2)
9.7 Formulation of the Task of Minimax Program Management of Innovation Processes at Enterprises
152(2)
9.8 General Scheme for Solving the Task of Minimax Program Management of Innovation Processes at the Enterprises
154(2)
9.9 Model of Multicriteria Optimization of Program Management of Innovation Processes
156(5)
9.10 Conclusion
161(1)
References
162(3)
10 Using Simulation for Development of Automobile Gas Diesel Engine Systems and their Operational Control
165(24)
Mikhail G. Shatrov
Vladimir V. Sinyavski
Audrey Y. U. Dunin
Ivan G. Shishlov
Sergei D. Skorodelov
Andrey L. Yakovenko
10.1 Introduction
166(1)
10.2 Computer Modeling
167(1)
10.3 Gas Diesel Engine Systems Developed
168(4)
10.3.1 Electronic Engine Control System
168(1)
10.3.2 Modular Gas Feed System
169(1)
10.3.3 Common Rail Fuel System for Supply of the Ignition Portion of Diesel Fuel
169(3)
10.4 Results and Discussion
172(11)
10.4.1 Results of Diesel Fuel Supply System Simulation
172(9)
10.4.2 Results of Engine Bed Tests
181(2)
10.5 Conclusion
183(1)
References
184(5)
Part VI Towards Cognitive Computing
11 Classification of Concept Drift in Evolving Data Stream
189(18)
Mashail Althabiti
Manal Abdullah
11.1 Introduction
190(1)
11.2 Data Mining
190(1)
11.3 Data Stream Mining
191(2)
11.3.1 Data Stream Challenges
191(2)
11.3.2 Features of Data Stream Methods
193(1)
11.4 Data Stream Sources
193(1)
11.5 Data Stream Mining Components
193(1)
11.5.1 Input
194(1)
11.5.2 Estimators
194(1)
11.6 Data Stream Classification and Concept Drift
194(6)
11.6.1 Data Stream Classification
194(1)
11.6.2 Concept Drift
194(2)
11.6.3 Data Stream Classification Algorithms with Concept Drift
196(1)
11.6.4 Single Classifier
196(1)
11.6.5 Ensemble Classifiers
197(3)
11.6.6 Output
200(1)
11.7 Datasets
200(1)
11.8 Evaluation Measures
200(1)
11.9 Data Stream Mining Tools
201(1)
11.10 Data Stream Mining Applications
202(1)
11.11 Conclusion
202(1)
References
202(5)
12 Dynamical Mass Transfer Systems in Buslaev Contour Networks with Conflicts
207(16)
Marina Yashina
Alexander Tatashev
Ivan Kuteynikov
12.1 Introduction
208(2)
12.2 Construction of Buslaev Contour Networks
210(1)
12.3 Concept of Spectrum
211(1)
12.4 One-Dimensional Contour Network Binary Chain of Contours
212(2)
12.5 Two-Dimensional Contour Network-Chainmail
214(4)
12.6 Random Process with Restrictions on the Contour with the Possibility of Particle Movement in Both Directions
218(1)
12.7 Conclusion
218(1)
References
219(4)
13 Parallel Simulation and Visualization of Traffic Flows Using Cellular Automata Theory and QuasigasDynamic Approach
223
Antonina Chechina
Natalia Churbanova
Pavel Sokolov
Marina Trapeznikova
Mikhail German
Alexey Ermakov
Obidzhon Bozorov
13.1 Introduction
224(1)
13.2 The Original CA Model
224(1)
13.3 The Slow-to-Start Version of the CA Model
225(1)
13.4 Numerical Realization
225(4)
13.5 Test Predictions for the CA Model
229(1)
13.6 The QGD Approach to Traffic Flow Modeling
230(2)
13.7 Parallel Implementation of the QGD Traffic Model
232(1)
13.8 Test Predictions for the QGD Traffic Model
232(3)
13.9 Conclusion
235(1)
References
236
Jolanda G. Tromp is a Human-Computer Interaction expert for User-Centered design and evaluation of new technologies (VR/AR/AI/IoT), with 20 years' experience as principal Usability investigator. She has a PhD in Systematic Usability Design and Evaluation for Collaborative Virtual Environments, 2001, University of Nottingham, United Kingdom, a BSc in Psychology (with honors) University of Amsterdam, Holland (1995). She is a research consultant for the Center of Visualization and Simulation at Duy Tan University, Vietnam; for the Mixed Reality Task Group of the State University of New York; and for the global Simulations Working Group.

Dac-Nhuong Le is PhD Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. His areas of research include: evolutionary computation, specialized with evolutionary multiobjective optimization, approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, image processing in biomedical. His core work in evolutionary multi-objective optimization, network security, wireless, mobile computing and virtual reality. He has edited several books for the Wiley-Scrivener imprint.

Chung Van Le is Vice-Director Center of Visualization and Simulation. He has a MSc in Computer Science from Duy Tan University, 2011, Vietnam and a BSc in Computer Science at Da Nang University, 2004, Vietnam. He is currently pursuing a PhD at Duy Tan University, Vietnam. He researches medical image processing, e-Health, virtual simulation in medicine. He is Duy Tan University Lead Software Developer for 3D virtual body system for teaching anatomy and virtual endoscopic techniques for medical students.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97811196547356e.html
Märksõnad: