Information Technology - New Generations

14th International Conference on Information Technology
 
 
Springer (Verlag)
  • erschienen am 15. Juli 2017
  • |
  • XIX, 985 Seiten
 
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
E-Book | PDF mit Wasserzeichen-DRM | Systemvoraussetzungen
978-3-319-54978-1 (ISBN)
 

This volume presents a collection of peer-reviewed, scientific articles from the 14 th International Conference on Information Technology - New Generations, held at the University of Nevada at Las Vegas on April 10-12, at Tuscany Suites Hotel in Las Vegas. The Book of Chapters addresses critical areas of information technology including web technology, communications, computing architectures, software engineering, security, and data mining.


1st ed. 2018
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • 144
  • |
  • 200 farbige Tabellen, 455 farbige Abbildungen, 144 s/w Abbildungen
  • |
  • 144 schwarz-weiße und 455 farbige Abbildungen, 200 farbige Tabellen, Bibliographie
  • 52,99 MB
978-3-319-54978-1 (9783319549781)
10.1007/978-3-319-54978-1
weitere Ausgaben werden ermittelt
Shahram Latifi, PhD, P.E., is Professor of Electrical and Computer Engineering and Co-director of Center for Information Technology, College of Engineering at the University of Nevada at Las Vegas.
  • Intro
  • Contents
  • ITNG 2017 Organization
  • General Chair and Editor
  • Vice General Chair
  • Publicity Chair
  • Track Chairs and Associate Editors
  • Track Co-chairs and Session Chairs
  • Conference Secretary
  • Industry Partnership
  • Chair Message
  • Reviewers List
  • Part I: Networking and Wireless Communications
  • Chapter 1: Performance Enhancement of OMP Algorithm for Compressed Sensing Based Sparse Channel Estimation in OFDM Systems
  • 1.1 Introduction
  • 1.2 System Model
  • 1.3 Compressed Sensing for Sparse Channel Estimation
  • 1.4 Enhanced LMMSE-OMP Channel Estimation
  • 1.5 Simulation Results
  • 1.6 Conclusion
  • References
  • Chapter 2: CARduino: A Semi-automated Vehicle Prototype to Stimulate Cognitive Development in a Learning-Teaching Methodology
  • 2.1 Introduction
  • 2.2 Related Works
  • 2.3 CARduino Development
  • 2.3.1 Setting the Bluetooth Module Integrated with Arduino
  • 2.3.2 Physical Prototype (Hardware) Automated Vehicle
  • 2.3.3 Development of Software in Boarded Arduino
  • 2.3.4 Controller Software Development in Android CARduino
  • 2.4 Vehicle Operation of Automated Simulation
  • 2.5 Analysis of Costs CARduino
  • 2.6 Conclusion
  • References
  • Chapter 3: ICI Mitigation for High-Speed OFDM Communications in High-Mobility Vehicular Channels
  • 3.1 Introduction
  • 3.2 System Model
  • 3.3 Channel Estimation and ICI Cancellation
  • 3.4 Simulation Results
  • 3.5 Conclusion
  • References
  • Mobile Payment Protocol 3D (MPP 3D) by Using Cloud Messaging
  • 4.1 Introduction
  • 4.2 Background
  • 4.3 Proposed Protocol
  • 4.4 Performance Evaluation
  • 4.5 Conclusion
  • References
  • Chapter 5: Event-Based Anomalies in Big Data
  • 5.1 Introduction
  • 5.2 Related Work
  • 5.3 Anomaly Detection Techniques
  • 5.4 Anomaly Detection Model
  • 5.5 Event Detection and Analysis Examples Using R
  • 5.6 Conclusions
  • References
  • ACO-Discreet: An Efficient Node Deployment Approach in Wireless Sensor Networks
  • 6.1 Introduction
  • 6.2 The Problem of GCLC
  • 6.3 Proposed Framework
  • 6.3.1 Phase-I of Proposed Framework
  • 6.3.2 Phase-II of Proposed Framework
  • 6.4 Simulations and Results
  • 6.5 Conclusion
  • References
  • Chapter 7: Golden Linear Group Key Agreement Protocol
  • 7.1 Introduction
  • 7.2 Related Works
  • 7.2.1 Key Agreement Protocol
  • 7.2.2 Group Key Agreement Protocols
  • 7.3 Golden Linear Group Key Agreement Protocol
  • 7.3.1 Golden Key Agreement Protocol (GKA)
  • 7.3.2 Secure Channel Sub-protocol
  • 7.3.3 Initiation Sub-protocol
  • 7.4 Join Protocol
  • 7.5 Leave Protocol
  • 7.6 Complexity
  • 7.7 Comparison
  • 7.8 Experiment
  • 7.9 Conclusion
  • References
  • Implementing an In-Home Sensor Agent in Conjunction with an Elderly Monitoring Network
  • 8.1 Introduction
  • 8.1.1 Background and Motivation for Elderly Monitoring Networks
  • 8.1.2 Research Purpose and Outline
  • 8.2 Requirements Analysis in Conjunction with the Bed Monitor and Pillow Sensors
  • 8.2.1 Requirements Analysis of Our Watch-Over Network
  • 8.2.2 Collaboration with a Bed Monitor and Pillow Sensor
  • 8.3 Functions and Specifications of a Sensor Agent in the Home
  • 8.3.1 Features of the In-Home Agent
  • 8.3.2 Specifications
  • 8.4 Design and Implementation of the Home Sensor Agent
  • 8.4.1 Hardware Design and Implementation
  • 8.4.2 Software Design and Implementation
  • 8.4.3 Prototyping and Load Testing
  • 8.5 Collection and Analysis of Multi-fusion Sensors and Trigger Information
  • 8.6 Conclusions and Future Work
  • References
  • Chapter 9: How Risk Tolerance Constrains Perceived Risk on Smartphone Users´ Risk Behavior
  • 9.1 Introduction
  • 9.2 Hypotheses Development
  • 9.3 Data Collection, Analysis and Results
  • 9.4 Conclusions
  • References
  • When Asteroids Attack the Moon: Design and Implementation of an STK-Based Satellite Communication Simulation for the NASA-Led ...
  • 10.1 Introduction
  • 10.2 AGI STK Components
  • 10.3 MWSU Communication Satellites Federate
  • 10.3.1 Satellite Constellation and Lunar Visualization Module
  • 10.3.2 Communication Server Module
  • 10.4 Lessons Learned and Recommendations for Future Development
  • 10.5 Conclusion
  • References
  • Chapter 11: Wireless Body Sensor Network for Monitoring and Evaluating Physical Activity
  • 11.1 Introduction
  • 11.2 Related Work
  • 11.3 Ubiquitous Computing Environment for Monitoring and Evaluating Physical Activity
  • 11.4 Wireless Body Sensor Network
  • 11.5 WBSN Simulation and Evaluation
  • 11.6 Conclusion
  • References
  • Chapter 12: Techniques for Secure Data Transfer
  • 12.1 Introduction
  • 12.2 Advanced Encryption Standard
  • 12.3 AES Attacks
  • 12.4 Steganography
  • 12.5 Related Work
  • 12.6 Implementation and Results
  • 12.7 Conclusion
  • References
  • Chapter 13: Rate Adjustment Mechanism for Controlling Incast Congestion in Data Center Networks
  • 13.1 Introduction
  • 13.2 Related Work
  • 13.3 Proposed Algorithm
  • 13.4 Working Rationale of Proposed Algorithm
  • 13.5 Performance Evaluation
  • 13.6 Conclusion
  • References
  • Performance Analysis of Transport Protocols for Multimedia Traffic Over Mobile Wi-Max Network Under Nakagami Fading
  • 14.1 Introduction
  • 14.2 Related Work
  • 14.3 Transport Protocols
  • 14.3.1 Multi-path Transport Protocol (MPTCP)
  • 14.3.2 Datagram Congestion Control Protocol (DCCP)
  • 14.3.3 Stream Control Transmission Protocol (SCTP)
  • 14.3.4 Real-Time Transport Protocol (RTP)
  • 14.3.5 User Datagram Protocol (UDP)
  • 14.3.6 Transmission Control Protocol (TCP)
  • 14.4 Nakagami Fading Channel
  • 14.5 Mobile Wi-Max Technology and MPEG-4 Video Traffic
  • 14.6 Simulations
  • 14.6.1 Multiple Mobile Stations Scenario
  • 14.6.1.1 Mobile Nodes at a Speed of 3Km/h
  • 14.6.1.2 Mobile Nodes at a Speed of 3Km/h
  • 14.7 Conclusion
  • References
  • Part II: Cybersecurity
  • Chapter 15: CyberSecurity Education and Training in a Corporate Environment in South Africa Using Gamified Treasure Hunts
  • 15.1 Introduction
  • 15.2 Research Methodology
  • 15.3 Treasure Hunts in Education
  • 15.4 Gamified Treasure Hunts
  • 15.5 Security Topics Covered
  • 15.5.1 Cryptography
  • 15.5.2 GnuPG
  • 15.5.3 Jasypt and Bouncy Castle
  • 15.5.4 SSL
  • 15.5.5 Wireshark
  • 15.5.6 HTTPS vs HTTP
  • 15.5.7 Various Attack Strategies
  • 15.5.8 Steganography
  • 15.5.9 Going Forward
  • 15.6 Results
  • 15.7 Conclusion
  • References
  • Chapter 16: Router Security Penetration Testing in a Virtual Environment
  • 16.1 Introduction
  • 16.2 Review of Literature
  • 16.2.1 Distributed Denial of Service (DDoS)
  • 16.2.2 Configuration-Based Vulnerabilities
  • 16.2.3 NAT Vulnerabilities
  • 16.3 Establish Metrics for Router Testing
  • 16.4 Virtualization Methodology
  • 16.4.1 Security Benefits of Virtualization
  • 16.4.2 Penetration Tests
  • 16.4.2.1 NMap
  • 16.4.2.2 MSF Console
  • 16.5 Findings
  • 16.6 Conclusion and Suggestions
  • References
  • Chapter 17: Advanced Machine Language Approach to Detect DDoS Attack Using DBSCAN Clustering Technology with Entropy
  • 17.1 Introduction
  • 17.2 Literature Review
  • 17.3 Selected Detection Schemes for This Research
  • 17.4 Proposed System
  • 17.4.1 Research Questions and Hypothesis
  • 17.4.2 Theoretical Framework and Research Methodologies
  • 17.4.2.1 Introduction
  • 17.4.3 The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm
  • 17.4.4 How DBSCAN Is Applied with Our Research
  • 17.4.5 The Application of Entropy for This Research
  • 17.5 Conclusion
  • References
  • A Novel Regular Format for X.509 Digital Certificates
  • 18.1 Introduction
  • 18.2 An Analysis of X.509
  • 18.3 Specification of the New Digital Certificate Format
  • 18.4 Implementation Strategies and Experimental Validation
  • 18.5 Conclusion
  • References
  • Chapter 19: A Software-Defined Networking (SDN) Approach to Mitigating DDoS Attacks
  • 19.1 Introduction
  • 19.2 Literature Review
  • 19.3 SDN Model for DDoS Mitigation
  • 19.4 Case Study: Verizon Networks
  • 19.5 Conclusions
  • References
  • Chapter 20: Integrated Methodology for Information Security Risk Assessment
  • 20.1 Introduction
  • 20.2 OCTAVE Method
  • 20.3 CORAS Method
  • 20.4 IS Risk Analysis Method
  • 20.5 ISRAM Method
  • 20.6 Proposal: Integrated Method
  • 20.7 Conclusion
  • References
  • Chapter 21: Techniques for Detecting and Preventing Denial of Service Attacks (a Systematic Review Approach)
  • 21.1 Introduction
  • 21.2 Methodology
  • 21.2.1 Methods of the Review
  • 21.3 Denial-of-Service-Resistant Intrusion Detection Architecture
  • 21.3.1 Active IDS Response
  • 21.3.2 Separate Communication Channel and Decentralized Non-hierarchical IDSs
  • 21.3.3 Mobile Recoverable Components
  • 21.4 Analyzing Well-Known Countermeasures Against Distributed DoS Attacks
  • 21.4.1 Location Where the Attack Is Detected
  • 21.4.2 Response Mechanism
  • 21.4.3 Places That a Response Mechanism Applies
  • 21.4.4 Decision Center Place
  • 21.5 DDoS Defense Techniques
  • 21.5.1 Source-End Defense Technique
  • 21.5.2 D-WARD
  • 21.6 Core-end Defense Technique-Gossip Mechanism
  • 21.7 Victim-end Defense
  • 21.7.1 Distributed Defense Technique
  • 21.7.2 Well-Known Detection Methods
  • 21.8 Chi-square Method
  • 21.9 DoS Attacks and Countermeasures in 802.11 Wireless Networks
  • 21.10 Detecting MAC Layer Attacks
  • 21.11 Conclusion
  • References
  • Chapter 22: Open Source Intelligence: Performing Data Mining and Link Analysis to Track Terrorist Activities
  • 22.1 Introduction
  • 22.2 Data Collection Using Open Source Intelligence
  • 22.3 Open Source Software for Intelligence Analysis
  • 22.4 Links and Transforms
  • 22.5 Data Analysis Using R and Python
  • 22.6 Findings
  • 22.7 Discussion and Recommendation
  • 22.8 Conclusion
  • References
  • Chapter 23: A Description of External Penetration Testing in Networks
  • 23.1 Introduction
  • 23.2 Process and Technology
  • 23.3 Evaluation
  • 23.3.1 Weaknesses
  • 23.3.2 Strengths
  • 23.4 Conclusion
  • References
  • Chapter 24: SCORS: Smart Cloud Optimal Resource Selection?
  • 24.1 Introduction
  • 24.2 Background
  • 24.3 SCORS Scheme Objectives
  • 24.4 SCORS Scheme Design
  • 24.5 Experiments and Results
  • 24.5.1 Solving Problem 31
  • 24.5.2 Solving Problem 29
  • 24.5.3 Solving Problem 25
  • 24.6 Acknowledgments
  • 24.7 Conclusion
  • References
  • Chapter 25: Towards the Memory Forensics of MS Word Documents
  • 25.1 Introduction
  • 25.2 Background and Related Work
  • 25.3 Methodology
  • 25.4 Experiments
  • 25.4.1 Experimentation Setup
  • 25.4.2 Experimentation Steps
  • 25.5 Results
  • 25.6 Discussion and Future Work
  • 25.7 Conclusion
  • References
  • Chapter 26: Two Are Better than One: Software Optimizations for AES-GCM over Short Messages?
  • 26.1 Introduction
  • 26.2 Preliminaries
  • 26.2.1 Efficient AES-GCM Computations on Modern Processors
  • 26.2.2 Processing Multiple Packets in Parallel
  • 26.3 Further Optimization via Sorting by Packet Sizes
  • 26.4 Conclusions
  • References
  • Chapter 27: BYOD Security Risks and Mitigations
  • 27.1 Introduction
  • 27.2 Legal Considerations
  • 27.2.1 U.S. Privacy Laws: The Privacy of an Individual
  • 27.2.2 Comingled Data
  • 27.2.3 Device Ownership
  • 27.2.4 Spoliation of Evidence
  • 27.2.5 Variety of BYODs
  • 27.2.6 Cloud Services
  • 27.2.7 Mobile Solutions: MDMs and MAMs
  • 27.3 Risk Mitigation
  • 27.3.1 Define a Strong BYOD Policy
  • 27.3.2 Awareness and Training
  • 27.4 Case Study: Verizon Wireless
  • 27.5 Conclusion
  • References
  • Chapter 28: Evaluation of Cybersecurity Threats on Smart Metering System
  • 28.1 Introduction
  • 28.2 Related Studies
  • 28.3 Smart Metering Functional Architecture
  • 28.4 Cybersecurity Challenges in Smart Metering
  • 28.4.1 Smart Metering Cyber Attack
  • 28.4.2 Attack Vectors
  • 28.4.2.1 Device Attack
  • 28.4.2.2 Application Service Attack
  • 28.4.2.3 Network Attack
  • 28.4.2.4 Web Interface Attack
  • 28.4.2.5 Data Integrity Attack
  • 28.5 Experimental Evaluation of Cyberattacks against Smart Metering
  • 28.5.1 Discussion
  • 28.6 Conclusion
  • References
  • Chapter 29: A Layered Model for Understanding and Enforcing Data Privacy
  • 29.1 Introduction
  • 29.2 Privacy Metrics and Their Flaws
  • 29.2.1 Deterministic Models
  • 29.2.2 Probabilistic Models
  • 29.2.3 Framework-based Models
  • 29.3 Need for a Different Perspective
  • 29.4 Proposed Layered Model
  • 29.4.1 The Read/Write Layer
  • 29.4.2 The EPA Layer
  • 29.4.3 Trust Layer
  • 29.5 Conclusion
  • References
  • Chapter 30: BYOD: A Security Policy Evaluation Model
  • 30.1 Introduction
  • 30.2 Literature Review and Underlying Theories
  • 30.2.1 Risks and Vulnerabilities Associated with BYODs
  • 30.2.2 Methodologies for Building Security Policies
  • 30.2.3 Non-ambiguous Evaluating Process for Policies
  • 30.3 Overview of Model Design
  • 30.3.1 The Reference Policy
  • 30.3.2 The Policy Evaluation Process
  • 30.4 Model Demonstration and Evaluation
  • 30.4.1 Artifact Demonstration
  • 30.4.2 Artifact Evaluation
  • 30.5 Conclusion and Future Work
  • 30.5.1 Conclusion
  • 30.5.2 Future Work
  • References
  • Chapter 31: A Novel Information Privacy Metric
  • 31.1 Introduction
  • 31.2 Privacy Metrics
  • 31.3 EPA-Based Privacy Model
  • 31.3.1 Specification of Embedded Privacy Agreement
  • 31.3.1.1 Fundamental Axiom of Privacy
  • 31.3.1.2 Operation Concatenation
  • 31.3.1.3 Lemma 1
  • 31.3.2 Embedded Privacy Agreement (EPA) Matrix
  • 31.3.2.1 Theorem 1
  • 31.3.3 Privacy Violation
  • 31.4 Privacy and Trust
  • 31.4.1 Trust in Parallel
  • 31.4.2 Trust in Tandem
  • 31.4.3 Example of Privacy Given Trust
  • 31.4.4 Imperfect Channel
  • 31.5 Conclusion
  • References
  • Chapter 32: An Integrated Framework for Evaluating the Security Solutions to IP-Based IoT Applications
  • 32.1 Introduction
  • 32.2 Background
  • 32.3 An Integrated Framework
  • 32.4 Discussion
  • 32.5 Conclusion and Future Work
  • References
  • Chapter 33: Towards the Security of Big Data: Building a Scalable Hash Scheme for Big Graph
  • 33.1 Introduction
  • 33.2 Related Works and Background
  • 33.2.1 Merkle-Hash-Tree
  • 33.2.2 Graph
  • 33.3 Scheme Design and ImplementationM
  • 33.3.1 Attacker Assumption
  • 33.3.2 Review of Standard Hash Scheme
  • 33.3.3 Graph Traversal
  • 33.3.4 Edge Labels
  • 33.3.5 Procedure of Hashing Graph
  • 33.3.6 Birthday Attack Resistance Hash for Graph
  • 33.3.7 MHT Construction Scheme for Graph query
  • 33.3.8 Data Operations and Corresponding MHT Updates
  • 33.4 Security and Performance Analyze
  • 33.4.1 Correctness
  • 33.4.2 Security
  • 33.4.3 Performance Reslut Analysis
  • 33.5 Conclusion and Future Work
  • References
  • Chapter 34: A Cluster Membership Protocol Based on Termination Detection Algorithm in Distributed Systems
  • 34.1 Introduction
  • 34.2 Computing System Model, Definition and Assumption
  • 34.3 Cluster Luster Membership Specification
  • 34.4 Cluster Luster Membership Protocol
  • 34.4.1 Cluster Membership in a Wired Network
  • 34.5 Conclusion
  • References
  • Part III: Information Systems and Internet Technology
  • Chapter 35: An Adaptive Sensor Management System
  • 35.1 Introduction
  • 35.2 Related Work
  • 35.3 System Architecture
  • 35.4 Sensor Control Management
  • 35.5 System Prototype
  • 35.6 Experimental Results
  • 35.7 Conclusions
  • References
  • Chapter 36: A Cloud Service for Graphical User Interfaces Generation and Electronic Health Record Storage
  • 36.1 Introduction
  • 36.2 Background and Related Work
  • 36.2.1 Archetypes
  • 36.2.2 Related Works
  • 36.3 Proposed Cloud Service
  • 36.3.1 Architecture and Overview
  • 36.3.2 Polyglot Persistence
  • 36.3.3 Generating Graphical User Interfaces
  • 36.4 Results and Discussion
  • 36.5 Conclusion
  • References
  • Chapter 37: A Petri Net Design and Verification Platform Based on The Scalable and Parallel Architecture: HiPS
  • 37.1 Introduction
  • 37.2 Petri Net
  • 37.3 The Petri Net Design Tool: HiPS
  • 37.4 On-the-Fly Model Checking
  • 37.4.1 Nested Depth First Search
  • 37.5 Model Checking for LTS in HiPS
  • 37.5.1 Tester Automaton
  • 37.5.2 Graph Contraction
  • 37.6 Implements
  • 37.6.1 User Interface
  • 37.6.2 LTL2BA
  • 37.6.3 Interprocess Connection Between the Model Checking Process and State-Space Generator
  • 37.6.4 Verification Example
  • 37.7 Conclusion
  • References
  • Chapter 38: Optimally Compressed Digital Content Delivery Using Short Message Service
  • 38.1 Introduction
  • 38.2 Related Work
  • 38.3 Proposed Methodology
  • 38.4 Experiments and Evaluations
  • 38.5 Conclusion
  • References
  • Chapter 39: The Method of Data Analysis from Social Networks using Apache Hadoop
  • 39.1 Introduction
  • 39.2 Distributed Platform Apache Hadoop
  • 39.3 Data Processing with Social Networks Using Apache Hadoop
  • 39.4 Conclusion
  • References
  • Chapter 40: Using Web Crawlers for Feature Extraction of Social Nets for Analysis
  • 40.1 Introduction
  • 40.2 Crawling the OSN
  • 40.2.1 Crawler Design
  • 40.3 Preprocessing Layer
  • 40.4 Visualization of Network
  • 40.5 Conclusion
  • References
  • Chapter 41: Detecting Change from Social Networks using Temporal Analysis of Email Data
  • 41.1 Introduction
  • 41.2 Temporal email Network Analysis
  • 41.3 Proposed Methodology
  • 41.3.1 Network Extraction and Data Preparation
  • 41.3.2 Segmentation of Network
  • 41.3.3 Network Measure Extraction
  • 41.3.4 Feature Vector Generation
  • 41.4 Conclusion
  • References
  • Chapter 42: The Organisational Constraints of Blending E-Learning Tools in Education: Lecturers´ Perceptions
  • 42.1 Introduction
  • 42.2 The Problem Statement
  • 42.3 Related Work
  • 42.4 Methodology
  • 42.5 Theoretical Model
  • 42.6 Findings
  • 42.6.1 Top-Down Approach
  • 42.6.2 User Support
  • 42.6.3 Lack of a ICT Budget
  • 42.6.4 Lack of ICT Policy
  • 42.6.5 Lackof Consultation
  • 42.6.6 Academic Freedom Violation
  • 42.7 Conclusion
  • References
  • Chapter 43: A Rule-Based Relational XML Access Control Model in the Presence of Authorization Conflicts
  • 43.1 Introduction
  • 43.2 Motivation
  • 43.3 Related Work
  • 43.4 Proposed Authorization Model
  • 43.5 XML-To-Relational Security Policy Conversion
  • 43.6 Illustrative Case Study
  • 43.7 Conclusions
  • References
  • Part IV: Entertainment Technology and Education
  • Chapter 44: A Practical Approach to Analyze Logical Thinking Development with Computer Aid
  • 44.1 Introduction
  • 44.2 Related Works
  • 44.3 Methodology
  • 44.3.1 Tools
  • 44.3.2 Target Audience
  • 44.3.3 Strategy
  • 44.3.4 Activities
  • 44.4 Result
  • 44.4.1 Comparative Analyses Between Classes
  • 44.4.2 Comparative Analysis Between Tools
  • 44.5 Conclusion
  • References
  • Chapter 45: A Transversal Sustainability Analysis of the Teaching-Learning Process in Computer Students and Groups
  • 45.1 Introduction
  • 45.2 Information Technology and Sustainability
  • 45.3 Method
  • 45.4 Results
  • 45.5 Conclusions
  • References
  • Chapter 46: Cloud Computing: A Paradigm Shift for Central University of Technology
  • 46.1 Introduction
  • 46.2 What Is Cloud Computing?
  • 46.3 Literature Review
  • 46.4 Current Situation at Cut
  • 46.5 Benefits of Cloud Computing for Cut Staff and Students
  • 46.6 Implementation of Cloud Computing in Cut
  • 46.7 Conclusion
  • 46.8 Recommendations
  • References
  • Chapter 47: Peer Music Education for Social Sounds in a CLIL Classroom
  • 47.1 Introduction
  • 47.2 Motivation to Learning
  • 47.3 Why Open SoundS
  • 47.4 Application and Analysis /Research Method
  • 47.5 Discussion and Conclusions
  • References
  • Chapter 48: Teaching Distributed Systems Using Hadoop
  • 48.1 Introduction
  • 48.2 Related Works
  • 48.3 Course Architecture
  • 48.3.1 Course Topics
  • 48.3.1.1 Scale-Up Architecture
  • 48.3.1.2 Scale-Out Architecture
  • Client-Server Model
  • Client-Server with Master-Slave Model
  • 48.3.2 Hadoop Framework
  • 48.4 Proposed Methodology
  • 48.4.1 Case Study
  • 48.5 Conclusions
  • References
  • Chapter 49: MUSE: A Music Conducting Recognition System
  • 49.1 Introduction
  • 49.2 Background
  • 49.2.1 Conducting Patterns and the Ictus
  • 49.2.2 Sensors for Gesture Recognition
  • 49.3 System Architecture and Functionality
  • 49.3.1 Overview of the Architecture
  • 49.3.1.1 Presentation Layer
  • 49.3.1.2 Midi Processor Layer
  • 49.4 Machine Learning Module Theory and Results
  • 49.5 Discussion
  • 49.6 Conclusions and Future Work
  • References
  • Part V: Agile Software Testing and Development
  • Chapter 50: Using Big Data, Internet of Things, and Agile for Crises Management
  • 50.1 Introduction
  • 50.2 Background
  • 50.2.1 Problem-Based Learning (PBL)
  • 50.2.2 The Scrum Agile Method and Practices
  • 50.2.3 Big Data
  • 50.2.4 Internet of Things (IoT)
  • 50.2.5 The Hadoop Ecosystem
  • 50.2.6 Cloud Computing and Security
  • 50.2.7 The Management of Emergency Monitoring, Warning, and Prevention in Big Events Situations
  • 50.3 The Project Overview
  • 50.3.1 The Project Vision Artifact
  • 50.3.2 The BD-ITAC Project Architecture
  • 50.4 The Project Development
  • 50.4.1 Sprint 0
  • 50.4.2 Sprint 1
  • 50.4.3 Sprint 2
  • 50.4.4 Sprint 3
  • 50.5 Conclusion
  • 50.6 Future Works
  • References
  • Chapter 51: An Agile and Collaborative Model-Driven Development Framework for Web Applications
  • 51.1 Introduction
  • 51.2 Related Works
  • 51.2.1 The AMDD High-Level Life Cycle
  • 51.2.2 The Sage Process
  • 51.2.3 The MDD-SLAP Process
  • 51.3 The AC-MDD Framework
  • 51.4 The Web-ACMDD Method
  • 51.5 Applying the Web-ACMDD Framework to an Academic Case Study
  • 51.6 Conclusion
  • References
  • Chapter 52: Generating Control Flow Graphs from NATURAL
  • 52.1 Introduction
  • 52.2 Software Testing
  • 52.2.1 Agile Testing Quadrants
  • 52.2.2 White-Box Testing
  • 52.2.3 Control Flow Technique
  • 52.2.4 Test Cases
  • 52.3 Proposed Tool
  • 52.4 The Main Results
  • 52.4.1 First Experiment
  • 52.4.2 Second Experiment
  • 52.5 Analyses and Discussions
  • 52.6 Conclusion
  • References
  • Chapter 53: Requirements Prioritization in Agile: Use of Planning Poker for Maximizing Return on Investment
  • 53.1 Introduction
  • 53.2 Existing Techniques and Challenges
  • 53.3 Multi-phase Solution
  • 53.3.1 Prioritizing Customer Facing Requirement
  • 53.3.2 Prioritizing Technical Debt
  • 53.4 Industrial Case Study
  • 53.5 Threats to Validity
  • 53.6 Future Work
  • 53.7 Conclusion
  • References
  • Chapter 54: EasyTest: An Approach for Automatic Test Cases Generation from UML Activity Diagrams
  • 54.1 Introduction
  • 54.2 Related Works
  • 54.3 EasyTest Approach
  • 54.3.1 Phase 1: Importing Activity Diagrams in XMI
  • 54.3.2 Phase 2: Test Cases Generation
  • 54.3.2.1 Activity Dependency Table (ADT) Generation
  • 54.3.2.2 Activity Dependency Graph (ADG) Generation
  • 54.3.2.3 Test Paths Generation
  • 54.3.2.4 Test Cases Generation
  • 54.3.3 Phase 3: Applying Test Cases
  • 54.3.3.1 Before Coding Stage: Test Driven Development (TDD)
  • 54.3.3.2 After Coding Stage: Exporting Generated Test Cases
  • 54.4 EasyTest Tool
  • 54.5 Conclusion and Future Work
  • References
  • Chapter 55: An Integrated Academic System Prototype Using Accidents and Crises Management as PBL
  • 55.1 Introduction
  • 55.2 Background
  • 55.2.1 Real-Time Embedded System
  • 55.2.2 Accidents and Crises Management
  • 55.2.3 Scrum Framework
  • 55.2.4 SCADE
  • 55.2.5 Arduino and Raspberry Pi Boards
  • 55.3 The ACMIS Project Setup
  • 55.4 The ACMIS Project Sprints
  • 55.4.1 Sprint 0
  • 55.4.2 Sprint 1
  • 55.4.3 Sprint 2
  • 55.4.4 Sprint 3
  • 55.5 The ACMIS Project Compliance with Safety Standards
  • 55.6 Conclusion
  • 55.6.1 Future Works
  • References
  • Chapter 56: Agile Testing Quadrants on Problem-Based Learning Involving Agile Development, Big Data, and Cloud Computing
  • 56.1 Introduction
  • 56.2 Background
  • 56.2.1 The BD-ITAC Project
  • 56.2.2 The Problem-Based Learning (PBL)
  • 56.2.3 The Scrum Agile Method and Practices
  • 56.2.4 The Agile Testing Quadrants
  • 56.3 The Agile Software Testing and Development in the Project
  • 56.3.1 The Sprint #0
  • 56.3.2 The Sprint #1
  • 56.3.3 The Sprint #2
  • 56.3.4 The Sprint 3
  • 56.4 The Main Results
  • 56.5 Conclusion
  • 56.6 Future Works
  • References
  • Chapter 57: Integrating NoSQL, Relational Database, and the Hadoop Ecosystem in an Interdisciplinary Project involving Big Dat...
  • 57.1 Introduction
  • 57.2 Background
  • 57.2.1 NoSQL Concept
  • 57.2.2 Apache Cassandra
  • 57.2.3 Big Data and Hadoop
  • 57.2.4 Hadoop Ecosystem
  • 57.2.4.1 Hadoop Common
  • 57.2.4.2 HDFS (Hadoop Distributed File System)
  • 57.2.4.3 MapReduce
  • 57.2.4.4 Apache Hive
  • 57.3 The Project Overview
  • 57.4 The Project Development
  • 57.4.1 Sprint 1: Moving Data into Hadoop
  • 57.4.1.1 Denormalizing the Dataset
  • 57.4.2 Sprint 2: Accessing the Dataset
  • 57.4.3 Sprint 3: Performance Improvements
  • 57.4.4 Testing Architecture
  • 57.5 Results and Discussion
  • 57.6 Conclusion
  • 57.7 Future Works
  • References
  • Chapter 58: Enhancing Range Analysis in Software Design Models by Detecting Floating-Point Absorption and Cancellation
  • 58.1 Introduction
  • 58.2 Floating-Point Basics
  • 58.3 Related Work
  • 58.4 Detecting Absorption and Cancellation in Range Analysis
  • 58.4.1 Absorption
  • 58.4.2 Cancellation
  • 58.5 Results
  • 58.6 Conclusion and Future Work
  • References
  • Chapter 59: Requirements Prioritization Using Hierarchical Dependencies
  • 59.1 Introduction
  • 59.2 Related Work
  • 59.3 Approach
  • 59.4 Running Example
  • 59.5 Conclusion and Future Work
  • References
  • Part VI: Data Mining
  • Chapter 60: An Optimized Data Mining Method to Support Solar Flare Forecast
  • 60.1 Introduction
  • 60.2 Method Description
  • 60.3 Experiments
  • 60.4 Conclusions
  • References
  • Chapter 61: A New Approach to Classify Sugarcane Fields Based on Association Rules
  • 61.1 Introduction
  • 61.2 Related Work
  • 61.3 Proposed Method
  • 61.3.1 Step 1: Learning Model
  • 61.3.2 Step 2: Rule Matches Counter
  • 61.3.3 Step 3: Classification
  • 61.4 Experiment and Results
  • 61.4.1 About the Data
  • 61.4.2 Describing the Experiment and Obtained Results
  • 61.5 Conclusions and Future Works
  • References
  • Chapter 62: Visualizing the Document Pre-processing Effects in Text Mining Process
  • 62.1 Introduction
  • 62.2 Theoretical Foundation
  • 62.2.1 Document Pre-processing
  • 62.2.2 Multidimensional Projection
  • 62.3 Visual Analysis of Document Pre-processing Effects
  • 62.4 Experiments
  • 62.5 Conclusions and Future Works
  • References
  • Chapter 63: Complex-Network Tools to Understand the Behavior of Criminality in Urban Areas
  • 63.1 Introduction
  • 63.2 Related Work
  • 63.3 Proposed Methodology
  • 63.3.1 Background and Datasets
  • 63.3.2 Mapping of Urban Crimes
  • 63.3.3 Criminal Community Identification
  • 63.3.4 Crime Analysis
  • 63.3.4.1 Measuring the Similarity of Communities
  • 63.3.4.2 Identifying the Behavior of Crimes
  • 63.4 Results and Discussions
  • 63.5 Conclusion
  • References
  • Chapter 64: Big Data: A Systematic Review
  • 64.1 Introduction
  • 64.2 Big Data
  • 64.3 Methodology
  • 64.4 Results and Discussion
  • 64.5 Conclusions
  • References
  • Chapter 65: Evidences from the Literature on Database Migration to the Cloud
  • 65.1 Introduction
  • 65.2 Methodology
  • 65.3 Evidences from the Literature
  • 65.3.1 Strategies for Database Migration
  • 65.3.2 Issues
  • 65.3.3 Service Providers
  • 65.4 Results and Discussions
  • 65.5 Conclusions
  • References
  • Chapter 66: Improving Data Quality Through Deep Learning and Statistical Models
  • 66.1 Introduction
  • 66.2 Related Work
  • 66.2.1 Outlier Detection Technologies
  • 66.2.2 Statistical Quality Control
  • 66.2.3 Deep Learning
  • 66.3 Overview Architecture
  • 66.4 Data Source
  • 66.5 Data Preparation
  • 66.5.1 Transferring String Type
  • 66.5.2 Transferring Date Type
  • 66.5.3 Data Cleaning
  • 66.6 Deep Learning
  • 66.7 Statistical Quality Control Model
  • 66.8 Conclusion
  • 66.9 Future Work
  • References
  • Chapter 67: A Framework for Auditing XBRL Documents Based on the GRI Sustainability Guidelines
  • 67.1 Introduction
  • 67.2 Literature Review
  • 67.3 A Service Framework for Sustainability Reports
  • 67.3.1 Integration Process Flow
  • 67.3.2 Corporate Setting Architecture of Continuous Audit
  • 67.3.3 Analysis of the Compliance of Sustainability Reports
  • 67.3.4 Operators for the Assessment of Compliance
  • 67.3.5 Sustainability Analysis
  • 67.4 A Sample of Sustainability Analysis
  • 67.5 Conclusion and Future Work
  • References
  • Part VII: Software Engineering
  • Chapter 68: Mining Historical Information to Study Bug Fixes
  • 68.1 Introduction
  • 68.2 Related Work
  • 68.3 Dataset and Characteristics
  • 68.4 Results
  • 68.5 Threats to Validity
  • 68.6 Conclusion
  • References
  • Chapter 69: An Empirical Study of Control Flow Graphs for Unit Testing
  • 69.1 Introduction
  • 69.2 Control Structures in Bytecode
  • 69.2.1 Running Example
  • 69.2.2 Extracting Control Structures
  • 69.3 Bytecode CFG Construction
  • 69.3.1 Identifying the Vertices
  • 69.3.2 Identifying Edges
  • 69.3.3 Compound Conditions in CFG
  • 69.4 An Extended Force-Based CFG Visualizer
  • 69.4.1 Extended Force-Based CFG Visualization Algorithm
  • 69.4.2 Positioning Source and Sink Vertices
  • 69.4.3 Positioning Loops and Jump Edges
  • 69.5 Empirical Study
  • 69.6 Related Work
  • 69.7 Conclusion
  • References
  • Chapter 70: A New Approach to Evaluate the Complexity Function of Algorithms Based on Simulations of Hierarchical Colored Petr...
  • 70.1 Introduction
  • 70.2 Related Works
  • 70.3 Theoretical Foundations
  • 70.3.1 Asymptotic Notation
  • 70.3.2 Algorithm Minimax
  • 70.3.3 Hierarchical Colored Petri Net
  • 70.4 Modeling Command Structures
  • 70.4.1 Assignment Command
  • 70.4.2 Conditional and Iterative Commands
  • 70.4.3 Recursive Command
  • 70.4.3.1 Modeling Recursive Call
  • 70.4.3.2 Modeling Recursive Return
  • 70.5 Calculating Complexity Functions Through Model Simulations
  • 70.5.1 Modeling the Minimax
  • 70.5.1.1 Modeling the Minimax Control Policies
  • 70.5.2 Simulation Model: Estimating the Runtime of Minimax
  • 70.6 Conclusions and Future Works
  • References
  • Chapter 71: Detection Strategies for Modularity Anomalies: An Evaluation with Software Product Lines
  • 71.1 Introduction
  • 71.2 Background
  • 71.3 Study Settings
  • 71.3.1 Goal and Research Questions
  • 71.3.2 Study Steps
  • 71.3.3 Selected Artifacts
  • 71.4 Comparison of Existing Strategies
  • 71.5 Comparison with Novel Strategies
  • 71.6 Threats to Validity
  • 71.7 Related Work
  • 71.8 Conclusion and Future Work
  • References
  • Chapter 72: Randomized Event Sequence Generation Strategies for Automated Testing of Android Apps
  • 72.1 Introduction
  • 72.2 Related Work
  • 72.3 Dynamic Event Sequence Generation
  • 72.4 Frequency-Based Event Selection Strategies
  • 72.4.1 Frequency Weighted Selection
  • 72.4.2 Minimum Frequency Selection
  • 72.5 Evaluation
  • 72.5.1 Research Questions
  • 72.5.2 Subject Apps
  • 72.5.3 Implementation
  • 72.5.4 Experimental Setup and Design
  • 72.5.5 Results
  • 72.6 Discussion and Implications
  • 72.6.1 Potential Correlations and Factors Affecting Effectiveness
  • 72.6.2 Practical Implications for Testers
  • 72.7 Threats to Validity
  • 72.8 Conclusions and Future Work
  • References
  • Chapter 73: Requirement Verification in SOA Models Based on Interorganizational WorkFlow Nets and Linear Logic
  • 73.1 Introduction
  • 73.2 Theoretical Background
  • 73.2.1 Interorganizational WorkFlow Net
  • 73.2.2 Linear Logic
  • 73.2.3 Branching Bisimilarity
  • 73.3 Requirement Verification in SOA Models
  • 73.3.1 Proposed Method
  • 73.3.2 Method Application
  • 73.4 Discussion and Conclusion
  • References
  • Chapter 74: Cambuci: A Service-Oriented Reference Architecture for Software Asset Repositories
  • 74.1 Introduction
  • 74.2 Related Work
  • 74.3 Establishment of Cambuci
  • 74.4 Evaluation of Cambuci
  • 74.5 Conclusion and Future Work
  • References
  • Chapter 75: Extending Automotive Legacy Systems with Existing End-to-End Timing Constraints
  • 75.1 Introduction
  • 75.2 Related Work
  • 75.3 Background and Component Model
  • 75.3.1 Component Model
  • 75.3.1.1 Timing Model for DL-SWCs
  • 75.3.1.2 Communication Mechanism
  • 75.3.2 End-to-End Delay
  • 75.3.3 Implementation Level
  • 75.3.4 Calculating the End-to-End Delays
  • 75.3.5 Job-Level Dependencies
  • 75.4 Challenges of Extending Legacy Systems
  • 75.4.1 Implications of the Period Selection
  • 75.4.2 Exhaustive Search
  • 75.5 Synthesize Periods for Partial Component Chains
  • 75.5.1 Algorithm Description
  • 75.5.2 Timing Analysis Variants
  • 75.6 Industrial Case Study
  • 75.6.1 Required Execution Time
  • 75.7 Conclusions and Future Work
  • References
  • Chapter 76: Modeling of Vehicular Distributed Embedded Systems: Transition from Single-Core to Multi-core
  • 76.1 Introduction
  • 76.1.1 Motivation
  • 76.1.2 Paper Layout
  • 76.2 Research Challenges and Paper Contribution
  • 76.3 Background: RCM and Rubus-ICE
  • 76.4 Structural Hierarchy in the Component Models Supporting Single-Core ECUs
  • 76.5 Proposed Extensions to the Structural Hierarchy
  • 76.6 Summary of Ongoing Work
  • References
  • Chapter 77: On the Impact of Product Quality Attributes on Open Source Project Evolution
  • 77.1 Introduction
  • 77.2 Background and Related Work
  • 77.3 Exploratory Study
  • 77.3.1 Data Collection
  • 77.3.2 Target OSS Projects
  • 77.3.3 The Study Protocol
  • 77.3.4 Participants Selection
  • 77.4 Data Analysis
  • 77.4.1 Participant 1
  • 77.4.2 Participant 2
  • 77.4.3 Participant 3
  • 77.4.4 Participant 4
  • 77.4.5 Participant 5
  • 77.4.6 Participant 6
  • 77.5 Conclusions
  • 77.5.1 Threats to Validity
  • 77.5.2 Future Works
  • References
  • Chapter 78: AD-Reputation: A Reputation-Based Approach to Support Effort Estimation
  • 78.1 Introduction
  • 78.2 Background
  • 78.3 AD-Reputation
  • 78.3.1 Reputation Calculation Model
  • 78.3.2 Developer Ranking Reputation View
  • 78.3.3 Estimating Effort
  • 78.4 Experimental Study
  • 78.5 Final Considerations
  • References
  • Chapter 79: Pmbench: A Micro-Benchmark for Profiling Paging Performance on a System with Low-Latency SSDs
  • 79.1 Introduction
  • 79.2 Background
  • 79.3 Design and Implementation
  • 79.4 Evaluation
  • 79.4.1 Experimental Setup
  • 79.4.2 Analyzing Pmbench Result
  • 79.4.3 Paging Performance Comparison
  • 79.5 Related Works
  • 79.6 Conclusion
  • References
  • Chapter 80: Design Observer: A Framework to Monitor Design Evolution
  • 80.1 Introduction
  • 80.2 Related work
  • 80.3 Overview of the Framework
  • 80.4 Checking Design Violations
  • 80.4.1 PatternPreserver
  • 80.4.2 MetricEnforcer
  • 80.4.3 CostMeasurer
  • 80.5 Identifying Designers
  • 80.5.1 DesignHandler
  • 80.5.2 Contributor
  • 80.6 Consistency Between Code and Design
  • 80.7 Preliminary Evaluation
  • 80.8 Conclusions and Future work
  • References
  • Chapter 81: Generating Sequence Diagram and Call Graph Using Source Code Instrumentation
  • 81.1 Introduction
  • 81.2 Related Work
  • 81.3 Overview of the Framework
  • 81.4 Case Study and Descussion
  • 81.5 Conclusion
  • References
  • Part VIII: High Performance Computing Architectures
  • Chapter 82: Data Retrieval and Parsing of Form 4 from the Edgar System using Multiple CPUs
  • 82.1 Introduction
  • 82.1.1 Form 4: Insider Trading
  • 82.1.2 Form 4: Potential Uses
  • 82.2 Prior Works
  • 82.3 Data Source and Format
  • 82.3.1 File Transfer Protocol (FTP) Server
  • 82.3.1.1 Indexes
  • 82.4 System Overview
  • 82.4.1 FTP
  • 82.4.2 System Updating
  • 82.4.3 Index Retrieval
  • 82.4.4 Data Retrieval
  • 82.4.5 Data Parsing Class
  • 82.5 Hardware and Language
  • 82.6 Profiling: Parallel Justification
  • 82.7 Sequential Execution
  • 82.8 Parallel Execution
  • 82.8.1 Set-up
  • 82.9 Results
  • 82.10 Conclusion and Future Work
  • References
  • Chapter 83: A New Approach for STEM Teacher Scholarship Implementation
  • 83.1 Introduction
  • 83.2 Literature Review
  • 83.3 Three-Tiered Noyce Partnership Structure and Implementation
  • 83.4 Survey and Interview Results
  • 83.5 Conclusion
  • References
  • Chapter 84: Improving the Performance of the CamShift Algorithm Using Dynamic Parallelism on GPU
  • 84.1 Introduction
  • 84.1.1 MeanShift
  • 84.1.2 CamShift
  • 84.1.3 Compute Il and Adjust Search Window Size in CamShift
  • 84.1.4 Graphics Processing Unit (GPU)
  • 84.2 Existing Work and Their Limitations
  • 84.3 Our Contributions
  • 84.3.1 Dynamic Parallelism (DP)
  • 84.3.2 Our Design and Advantage
  • 84.4 Implementation
  • 84.4.1 Preprocessing
  • 84.4.2 Parent Kernel for Processing One Video Frame
  • 84.5 Experimental Results
  • 84.6 Conclusion and Future Work
  • References
  • Chapter 85: Sumudu Transform for Automatic Mathematical Proof and Identity Generation
  • 85.1 Introduction
  • 85.2 Application in Coefficient Calculation
  • 85.3 Automatic Proof of Identities
  • 85.4 Automatic Generation of New Identities
  • 85.5 Conclusions
  • References
  • Chapter 86: A Multiobjective Optimization Method for the SOC Test Time, TAM, and Power Optimization Using a Strength Pareto Ev...
  • 86.1 Introduction
  • 86.1.1 Related Work
  • 86.1.2 Strength Pareto Evolutionary Algorithm
  • 86.2 Problem Formulation
  • 86.2.1 Chromosomal Representation
  • 86.2.2 Initial Population
  • 86.2.3 Archive
  • 86.2.4 Fitness Function
  • 86.2.5 Selection and Reproduction
  • 86.2.6 Genetic Operators
  • 86.2.6.1 Mutation
  • 86.2.6.2 Crossover
  • 86.3 Annealing Bin Packing Algorithm
  • 86.4 Hierarchical Test Scheduling Algorithm
  • 86.5 Experimental Results
  • 86.6 Conclusion
  • References
  • Part IX: Computer Vision, HCI and Image Processing/Analysis
  • Chapter 87: Handwritten Feature Descriptor Methods Applied to Fruit Classification
  • 87.1 Introduction
  • 87.2 Feature Descriptor Methods
  • 87.2.1 New Feature Descriptor Approaches
  • 87.3 Experiments
  • 87.4 Detailed Inspection with Image Visualization
  • 87.5 Conclusions and Future Works
  • References
  • Chapter 88: A No-Reference Quality Assessment Method of Color Image Based on Visual Characteristic
  • 88.1 Introduction
  • 88.2 Quality Assessment Model of Color Image
  • 88.3 Experimental results and analysis
  • 88.3.1 Quantitative Analysis of Expand Region
  • 88.3.2 Contrast Optimization Analysis Under Visual Masking Effect
  • 88.3.3 Comparative Analysis of Related Methods
  • 88.3.4 Performance Analysis on Other Image Databases
  • 88.4 Conclusion
  • References
  • Chapter 89: Approaches for Generating Empathy: A Systematic Mapping
  • 89.1 Introduction
  • 89.2 Method
  • 89.2.1 Research Questions
  • 89.2.2 Search and Selection Strategy
  • 89.2.3 Selection Criteria
  • 89.3 Results and Discussion
  • 89.4 Threats to Validity
  • 89.5 Conclusion
  • References
  • Chapter 90: Multi-camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains
  • 90.1 Introduction
  • 90.2 Visual Tracking System and Hidden Markovian Model
  • 90.3 Recursive Bayesian Estimation
  • 90.4 Experimental Result
  • 90.5 Conclusion
  • References
  • Chapter 91: Store Separation Analysis Using Image Processing Techniques
  • 91.1 Introduction
  • 91.2 Store Separation
  • 91.3 Application Architecture
  • 91.3.1 Determine the Optical System
  • 91.3.2 Determine the Track Target
  • 91.3.3 Determine the Position and Attitude of Cameras
  • 91.3.4 Measurement of Store and Aircraft Track Targets
  • 91.3.5 Calibration of the Principal Point of the Cameras and the Focal Length of the Cameras
  • 91.4 Synthetic Scenario Test
  • 91.5 Pit Drop Testing
  • 91.6 Conclusions
  • References
  • Chapter 92: Ballistic Impact Analysis Using Image Processing Techniques
  • 92.1 Introduction
  • 92.2 Ballistic Protection
  • 92.3 Application Architecture
  • 92.3.1 Warm-Up
  • 92.3.2 Camera Calibration
  • 92.4 Experiments and Data Analysis
  • 92.4.1 Tests
  • 92.4.2 Data Analysis
  • 92.5 Conclusions
  • References
  • Chapter 93: iHelp HEMOCS Application for Helping Disabled People Communicate by Head Movement Control
  • 93.1 Introduction
  • 93.2 Proposed iHelp HEMOCS System
  • 93.2.1 What Is Head Movement Control Systems
  • 93.2.2 Head Pose Gesture Control Function
  • 93.2.3 Method for Detecting Head Pose Movement
  • 93.3 Implementation and Evaluation
  • 93.3.1 Implementation of iHelp HEMOCS
  • 93.3.2 Accuracy Evaluation
  • 93.3.3 Usability Evaluation
  • 93.4 Conclusion and Future Works
  • References
  • Part X: Signal Processing, UAVs
  • Chapter 94: Evaluation of Audio Denoising Algorithms for Application of Unmanned Aerial Vehicles in Wildlife Monitoring
  • 94.1 Introduction
  • 94.2 Denoising Algorithms
  • 94.2.1 Wiener Filter
  • 94.2.2 Least Mean Square Algorithm
  • 94.2.3 Block Thresholding
  • 94.2.4 Discrete Wavelet Transform
  • 94.2.5 Implementation of Denoising Algorithms
  • 94.2.6 Results
  • 94.2.6.1 Denoising Results
  • 94.2.6.2 Classification Results
  • 94.3 Conclusions
  • References
  • Chapter 95: Development of a Portable, Low-Cost System for Ground Control Station for Drones
  • 95.1 Introduction
  • 95.2 Background
  • 95.3 Materials and Methods
  • 95.4 Results and Discussion
  • 95.5 Conclusion
  • References
  • Chapter 96: Collision Avoidance Based on Reynolds Rules: A Case Study Using Quadrotors
  • 96.1 Introduction
  • 96.2 Background and Related Work
  • 96.3 Materials and Methods
  • 96.3.1 Swarm Robotics
  • 96.3.2 Quadrotor Dynamics
  • 96.3.3 Pixhawk
  • 96.3.4 Robots
  • 96.3.5 Mission Description
  • 96.4 Results and Discussion
  • 96.4.1 System Architecture
  • 96.4.2 Algorithm Implementation
  • 96.4.3 Simulation
  • 96.5 Conclusion
  • References
  • Chapter 97: PID Speed Control of a DC Motor Using Particle Swarm Optimization
  • 97.1 Introduction
  • 97.2 PMDC Motor Model
  • 97.3 PID-PSO Algorithm
  • 97.4 Application to the PMDC Motor
  • 97.5 Improvement of Pid-Pso Performance
  • 97.5.1 Effect of Varying the Acceleration Constants
  • 97.5.2 Effect of Varying the Inertia Weight
  • 97.5.3 Effect of Varying the Number of Particles
  • 97.5.4 Effect of Varying the Number of Iterations
  • 97.5.5 Comparison of Initial and Improved Control System Responses
  • 97.6 Conclusion
  • References
  • Chapter 98: Use of Intelligent Water Drops (IWD) for Intelligent Autonomous Force Deployment
  • 98.1 Introduction
  • 98.2 Background
  • 98.2.1 Troop Deployment
  • 98.2.2 Need in the Context of Autonomous Warfighters
  • 98.2.3 Intelligent Water Drops
  • 98.3 Intelligent Water Drops Troop Deployment Algorithm
  • 98.4 IWD Bifurcation and Distributaries
  • 98.5 IWD Bifurcation and Troop Deployment
  • 98.6 Qualitative Evaluation
  • 98.7 Research Methods, Evaluation Scenario and Results
  • 98.8 Analysis of Results
  • 98.9 Discussion
  • 98.10 Conclusions and Future Work
  • References
  • Chapter 99: Match-the-Sound CAPTCHA
  • 99.1 Introduction
  • 99.2 Related Work
  • 99.3 Proposed MS-CAPTCHA Scheme
  • 99.4 Experimentation and Results
  • 99.5 Conclusions and Future Work
  • References
  • Part XI: Health, Bioinformatics, Pattern Detection and Optimization
  • Chapter 100: Information Technology - Next Generation: The Impact of 5G on the Evolution of Health and Care Services
  • 100.1 Introduction
  • 100.2 Empiric Evidence for the Rapid Evolution of eHealth as a 5G Application Domain
  • 100.3 The Emergence of Low Power Wide Area Technology and Its Implications for Health Care
  • 100.4 Smart Phones, 4G and mm Waves
  • 100.5 Advanced 5G Functionalities
  • 100.6 The Role of Mobile Edge Clouds
  • 100.7 Next Generation Network Abilities
  • 100.8 5G Service Examples and Bandwidth Requirements
  • 100.9 Conclusions
  • References
  • Chapter 101: Testing Cloud Services Using the TestCast Tool
  • 101.1 Introduction
  • 101.2 Motivation and Background
  • 101.3 Testing Methodology of Cloud Services
  • 101.4 General overview of the TestCast TTCN-3 Tool
  • 101.5 Lessons Learned
  • 101.6 Conclusions
  • References
  • Chapter 102: Evaluation of High-Fidelity Mannequins in Convulsion Simulation and Pediatric CPR
  • 102.1 Introduction
  • 102.2 Methodology
  • 102.3 Results and Discussions
  • 102.3.1 Convulsion
  • 102.3.2 Need of CPR
  • 102.3.3 Mannequin´s Response to the Execution of Pediatric CPR Maneuvers
  • 102.4 Conclusion
  • References
  • Chapter 103: wCReF - A Web Server for the CReF Protein Structure Predictor
  • 103.1 Introduction
  • 103.2 Implementation
  • 103.2.1 Preparing the CReF Environment
  • 103.2.2 Deciding the Architectural Model
  • 103.2.3 Conducting the Usability Evaluations
  • 103.2.4 Algorithm
  • 103.2.5 User Interface
  • 103.3 Discussion
  • 103.3.1 Availability and Requirements
  • 103.4 Conclusion
  • References
  • Chapter 104: Automating Search Strings for Secondary Studies
  • 104.1 Introduction
  • 104.2 Background
  • 104.2.1 Secondary Studies
  • 104.2.2 Hill Climbing and Fitness Function
  • 104.3 The SBSG Approach
  • 104.3.1 Proof-of-Concept Implementation
  • 104.4 Empirical Evaluation
  • 104.4.1 Research Questions
  • 104.4.2 Goals
  • 104.4.3 Experimental Design and Execution
  • 104.5 Results and Discussion
  • 104.5.1 Sensibility and Precision
  • 104.5.2 Efficiency
  • 104.5.3 Threats to Validity
  • 104.6 Conclusion and Future Work
  • References
  • Chapter 105: Visual Approach to Boundary Detection of Clusters Projected in 2D Space
  • 105.1 Introduction
  • 105.2 Background
  • 105.3 Boundary Detection Approach
  • 105.4 Experiments
  • 105.5 Conclusions and Future Works
  • References
  • Chapter 106: Opposition-Based Particle Swarm Optimization Algorithm with Self-adaptive Strategy
  • 106.1 Introduction
  • 106.2 A Brief Overview of the PSO Algorithm
  • 106.3 The SAOPSO Algorithm
  • 106.3.1 Adaptive Inertia Weight
  • 106.3.2 Opposite-Based Learning
  • 106.3.3 Dynamic Adjustment of Cauchy Mutation Probability
  • 106.3.4 The SAOPSO Algorithm
  • 106.4 Simulation Experiment and Result Analysis
  • 106.4.1 Benchmark Function
  • 106.4.2 Parameter Settings
  • 106.4.3 Experimental Results and Performance Comparison
  • 106.5 Conclusion
  • References
  • Part XII: Education, Applications and Systems
  • Chapter 107: Recruitment Drive Application
  • 107.1 Introduction
  • 107.2 System Analysis and Design
  • 107.2.1 Output Design
  • 107.2.2 Input Design
  • 107.2.3 Logical Design
  • 107.3 Developing the Application
  • 107.4 Software Modules
  • 107.5 Conclusions
  • References
  • Chapter 108: Evaluating Assignments Using Grading App
  • 108.1 Introduction
  • 108.2 Background
  • 108.3 Software Design
  • 108.4 Using GradingApp
  • 108.5 Conclusions and Future Work
  • References
  • Chapter 109: A Heuristic for State Power Down Systems with Few States
  • 109.1 Introduction
  • 109.2 The Power Down Problem
  • 109.3 Optimizing the Online Algorithm
  • 109.4 Power Down Heuristic
  • 109.5 Conclusion
  • References
  • Chapter 110: Internet Addiction in Kuwait and Efforts to Control It
  • 110.1 Introduction
  • 110.2 Review of Related Literature
  • 110.3 Internet Addiction in Kuwait
  • 110.4 Efforts to Control Internet Addiction
  • 110.5 Conclusion and Recommendations
  • References
  • Chapter 111: Approaches for Clustering Polygonal Obstacles
  • 111.1 Introduction
  • 111.2 Preliminaries
  • 111.3 Clustering Obstacles
  • 111.3.1 Problem Formulation
  • 111.3.2 Proximity Graph Approach
  • 111.3.3 Visibility Graph Approach
  • 111.4 Discussion
  • References
  • Part XIII: Short Papers
  • Chapter 112: Usability in Computer Security Software
  • 112.1 Introduction
  • 112.2 Related Jobs
  • 112.3 Usability and Heuristic Evaluation
  • 112.4 Computer Security Tools
  • 112.5 Results Obtained
  • 112.6 Conclusions
  • References
  • Chapter 113: Techniques for Detecting, Preventing and Mitigating Distributed Denial of Service (DDoS) Attacks
  • 113.1 Introduction
  • 113.2 DDoS Detection
  • 113.2.1 Around-the-Clock Monitoring
  • 113.2.2 Pattern and Third-Party Detection
  • 113.2.3 Dynamic Deterministic Marking and NIDS
  • 113.3 Prevention
  • 113.3.1 Kona Site Defender Technology from IBM/Akamai
  • 113.3.2 Security Awareness and Multifactor Authentication
  • 113.3.3 Antimalware Software
  • 113.3.4 Disabling Unused Services and Other Security Best Practices
  • 113.4 Mitigation
  • 113.4.1 OWASP Guidance in DDoS Mitigations
  • 113.4.2 Class Based Queuing Queues and SLA/ IMPERVA and CISCO Mitigations
  • 113.5 Conclusion
  • References
  • Chapter 114: Next-Generation Firewalls: Cisco ASA with FirePower Services
  • 114.1 Introduction
  • 114.2 Cisco ASA Technology
  • 114.3 FirePower Services Technology
  • 114.4 Strengths of FirePower Services
  • 114.5 Limitations of FirePower Services
  • 114.6 Conclusion
  • References
  • Chapter 115: DDoS Attacks: Defending Cloud Environments
  • 115.1 Introduction
  • 115.2 Summary: DDoS Defense Mechanisms
  • 115.2.1 Selective Blackholing
  • 115.2.2 Consecutive Packet Entropy
  • 115.2.3 Chi-Square Statistic
  • 115.3 Summary: Catch Me If You Can: A Cloud-Enabled DDoS Defense
  • 115.3.1 Shuffling
  • 115.3.2 Replication
  • 115.3.3 Entropy
  • 115.4 Summary: DDoS Attack Protection in the Era of Cloud Computing and Software-Defined Networking
  • 115.4.1 DaMask
  • 115.4.2 Graphical Model Detection
  • 115.4.3 Bayesian Approach
  • References
  • Chapter 116: Cyber Security Policies for Hyperconnectivity and Internet of Things: A Process for Managing Connectivity
  • 116.1 Introduction
  • 116.2 Internet of Things
  • 116.3 Managing Risks
  • 116.4 Hyperconnectivity
  • 116.5 Testing
  • 116.6 Conclusion
  • References
  • Chapter 117: DDoS Countermeasures
  • 117.1 Introduction
  • 117.2 Hybrid Intrusion Detection Techniques
  • 117.3 Distributed Filtering
  • 117.4 Prevention Mechanisms
  • 117.5 DDoS Determinations
  • 117.6 Conclusion
  • References
  • Chapter 118: Removal of Impulsive Noise From Long Term Evolution Handset
  • 118.1 Introduction
  • 118.1.1 Long Term Evolution
  • 118.1.2 Impulsive Noise
  • 118.1.3 MIMO
  • 118.1.4 Alamounti Transmission
  • 118.2 Background
  • 118.2.1 Addition of IN
  • 118.2.1.1 Space Time Block Coding and Space Frequency Block Coding
  • 118.2.1.2 Space Time Block Coding and IN
  • 118.3 Methodology
  • 118.3.1 Threshold Detection and Blanking Method
  • 118.3.2 Blanking Versus Clipping
  • 118.3.3 Using Receive Diversity to Eliminate IN
  • 118.3.4 Selection of Threshold
  • 118.3.5 Conservative Threshold
  • 118.3.6 Aggressive Threshold
  • 118.4 Results
  • 118.5 Conclusion
  • References
  • Chapter 119: A Synchronization Rule Based on Linear Logic for Deadlock Prevention in Interorganizational WorkFlow Nets
  • 119.1 Introduction
  • 119.2 Theoretical Background
  • 119.3 Synchronization Rule
  • 119.4 Conclusion
  • References
  • Chapter 120: Summary Report of Experimental Analysis of Stemming Algorithms Applied to Judicial Jurisprudence
  • 120.1 Introduction
  • 120.2 Related Work
  • 120.3 Definition and Experiment Planning
  • 120.3.1 Goal Definition
  • 120.3.2 Planning
  • 120.4 Results
  • 120.4.1 Analysis and Interpretation
  • 120.4.2 Threats to Validity
  • 120.5 Conclusion and Future Work
  • References
  • Chapter 121: Applying Collective Intelligence in the Evolution of a Project Architecture Using Agile Methods
  • 121.1 Introduction
  • 121.2 The Case Study
  • 121.3 Result Analysis
  • 121.4 Conclusion
  • References
  • Chapter 122: Development of Human Faces Retrieval in a Big Photo Database with SCRUM: A Case Study
  • 122.1 Introduction
  • 122.2 Implemented Fraud-Prevention Case
  • 122.3 The Deliverables
  • 122.4 The Agile Methodology
  • 122.5 Conclusion
  • References
  • Chapter 123: An Agile Developed Interdisciplinary Approach for Safety-Critical Embedded System??
  • 123.1 Introduction
  • 123.2 Accidents and Crises
  • 123.3 The Case Study
  • 123.4 Conclusion
  • References
  • Chapter 124: The Implementation of the Document Management System ``DocMan´´ as an Advantage for the Acceleration of Adminis...
  • 124.1 Introduction
  • 124.2 System for Document Management ``DocMan´´
  • 124.3 The Advantages of Using the DMS ``DocMan´´
  • 124.4 Questionnaire
  • 124.5 Conclusion
  • References
  • Index

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