The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science.
Artificial Intelligence Methods and Applications in Computer Engineering illuminates how today's computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.
Author(s): Kaddoura Sanaa
Publisher: Engineering Science Reference
Year: 2023
Language: English
Pages: 659
Cover
Title Page
Copyright Page
Book Series
Mission
Coverage
Editorial Advisory Board
Preface
Acknowledgment
Chapter 1: Introduction to Artificial Intelligence
ABSTRACT
INTRODUCTION
BACKGROUND
TYPES OF ARTIFICIAL INTELLIGENCE
KNOWLEDGE-BASED SYSTEMS
ALGORITHMS AND BIG DATA
MACHINE LEARNING
TYPES OF MACHINE LEARNING
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 2: Artificial Intelligence Accountability in Emergent Applications
ABSTRACT
INTRODUCTION
IMPORTANCE OF ACCOUNTABILITY
EXPLAINABLE AI IN EMERGENT APPLICATIONS
FAIRNESS
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
ENDNOTE
Chapter 3: The Rising Trend of Artificial Intelligence in Social Media
ABSTRACT
INTRODUCTION
BACKGROUND
UTILIZING AI IN DIVERSE APPLICATIONS
AI APPLICATIONS IN SOCIAL MEDIA
ARTIFICIAL INTELLIGENCE OPPORTUNITIES
ARTIFICIAL INTELLIGENCE CHALLENGES
CONCLUSION
FUTURE PROSPECTS
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 4: Artificial Intelligence-Based Intelligent Human-Computer Interaction
ABSTRACT
INTRODUCTION
LITERATURE SURVEY
CURRENT RESEARCH WORK ON HCI WITH AI
HUMAN-COMPUTER INTERACTION
COMPONENTS OF HCI
AI AND HCI
VARIOUS SECTORS OF HCI WITH AI
RESEARCH AREAS OF HCI USING ARTIFICIAL INTELLIGENCE
RECENT ADVANCES IN HCI
CONCLUSION
REFERENCES
Chapter 5: Artificial Intelligence in Navigation Systems
ABSTRACT
INTRODUCTION
NAVIGATION SYSTEMS
ARTIFICIAL INTELLIGENCE SYSTEMS
NAVIGATION SYSTEMS: ARTIFICIAL INTELLIGENCE APPLICATION
FUTURE RESEARCH DIRECTIONS
CONCLUSION
FUNDING
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 6: Artificial Intelligence Methods and Applications in Aviation
ABSTRACT
INTRODUCTION
BACKGROUND
INTELLIGENT DECISION SUPPORT SYSTEMS IN AIR NAVIGATION SYSTEM
CONCLUSION
FUTURE RESEARCH DIRECTIONS
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 7: The Impact of Artificial Intelligence on Search Engine
ABSTRACT
INTRODUCTION
BACKGROUND
SEARCH ENGINE AND INFORMATION RETRIEVAL
ARTIFICIAL INTELLIGENCE AND SEO
CRAWLING, INDEXING, AND RANKING
SEARCH ENGINE EVALUATION
CONCLUSION
RECOMMENDATIONS FOR FUTURE RESEARCH DIRECTIONS
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 8: A Survey About the Application of Artificial Intelligence in Search Engines
ABSTRACT
INTRODUCTION
WHAT IS EXACTLY A SEARCH ENGINE?
WHAT IS ARTIFICIAL INTELLIGENCE (AI)?
OPPORTUNITIES AND CHALLENGES OF AI IN SEARCH ENGINE CONTEXT
CONCERNS RELATED TO THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN SEARCH ENGINES
CONCLUSION
REFERENCES
Chapter 9: Artificial Intelligence Applications in Cybersecurity
ABSTRACT
INTRODUCTION
CYBERSECURITY
BACKGROUND
APPLICATIONS
FRAUD DETECTION
ADVANTAGES OF AI IN CYBERSECURITY
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 10: Text to Image Synthesis Using Multistage Stack GAN
ABSTRACT
INTRODUCTION
RELATED WORK
BACKGROUND
STACKED GENERATIVE ADVERSARIAL NETWORKS (STACK GAN)
IMPLEMENTATION DETAILS
QUANTITATIVE AND QUALITATIVE RESULTS
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 11: The Application of Machine Learning for Predicting Global Seismicity
ABSTRACT
INTRODUCTION
EARTHQUAKE
SOLAR ACTIVITY
EARTHQUAKES AND SOLAR ACTIVITY
MACHINE LEARNING
EXPERIMENT METHOD
CONCLUSION
ORGANIZATION BACKGROUND
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 12: Convergence of Blockchain to Artificial Intelligence Applications
ABSTRACT
INTRODUCTION
BACKGROUND
ARCHITECTURE OF BLOCKCHAIN
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITION
Chapter 13: Machine Learning Approach in Human Resources Department
ABSTRACT
INTRODUCTION
HUMAN RESOURCES DEPARTMENT AND RECRUITMENT PROCESS
MACHINE LEARNING
DECISION MAKING PROBLEM
CLASSIFICATION
MACHINE LEARNING IN HR DEPARTMENT
CONCLUSION
REFERENCES
Chapter 14: Artificial Intelligence in Higher Education
ABSTRACT
INTRODUCTION
BACKGROUND
LEARNING ANALYTICS, COMPUTER-BASED INSTRUCTION, EDUCATIONAL DATA MINING, AND ARTIFICIAL INTELLIGENCE IN EDUCATION
RECOMMENDATIONS
FUTURE RESEARCH DIRECTIONS
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 15: Smart Farming
ABSTRACT
INTRODUCTION
BACKGROUND
LITERATURE REVIEW
SUGGESTED METHOD
ANALYSIS OF THE RESULTS
ANALYSIS OF THE CLASSIFICATION INTO FOUR CLASSES BY THE KNN METHOD
VERIFICATION OF THE STATISTICAL VALIDITY BY THE NEURAL NETWORK
CONCLUSION AND FUTURE RESEARCH DIRECTIONS
ACKNOWLEDGMENT
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 16: A Comprehensive Overview of Artificial Intelligence in Healthcare
ABSTRACT
INTRODUCTION
AI APPLICATIONS IN HEALTHCARE
AI BEST PRACTICES IN HEALTHCARE
ASSOCIATED TECHNOLOGIES
ETHICAL ASPECTS OF AI IN HEALTHCARE
CHALLENGES
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 17: Potential Integration of Artificial Intelligence and Biomedical Research Applications
ABSTRACT
1.0 INTRODUCTION
2.0 LITERATURE SURVEY
3.0 AI APPLICATIONS IN HEALTHCARE
4.0 BIOMEDICAL ENGINEERING APPLICATIONS IN HEALTHCARE
5.0 BENEFITS OF AI AND BIOMEDICAL ENGINEERING IN HEALTHCARE
6.0 AI ENHANCED HEALTHCARE WITH BIOMEDICAL ENGINEERING
7.0 RISKS OF AI IN HEALTHCARE
8.0 HEALTHCARE TRANSFORMATIONS WITH AI
9.0 FUTURE PROSPECTS
10.0 CONCLUSION
REFERENCES
Chapter 18: Using Graph Neural Network to Enhance Quality of Service Prediction
ABSTRACT
INTRODUCTION
BACKGROUND
EXPERIMENT DESCRIPTION
FUTURE RESEARCH DIRECTIONS
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 19: Rifle Detection and Performance Evaluation Using Deep Learning Frameworks
ABSTRACT
INTRODUCTION
BACKGROUND
LITERATURE REVIEW AND GAPS
RESEARCH METHODOLOGY AND APPROACH
RESULT, ANALYSIS, AND DISCUSSION
CONCLUSION
REFERENCES
Chapter 20: A Transfer Learning Approach for Smart Home Application Based on Evolutionary Algorithms
ABSTRACT
1. INTRODUCTION
2. RELATED WORKS
3. PROPOSED APPROACH FOR INDOOR WAYFINDING ASSISTANCE NAVIGATION
4. EXPERIMENTS AND RESULTS
5. CONCLUSION
DECLARATIONS
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 21: Artificial Intelligence Approaches in Diabetic Prediction
ABSTRACT
1. INTRODUCTION
2. DIABETES MELLITUS
3. ARTIFICIAL INTELLIGENCE IN HEALTHCARE
4. ARTIFICIAL INTELLIGENCE IN DIABETES
5. AI APPLICATIONS IN DIABETES
5. DATASET
6. ARTIFICIAL INTELLIGENCE TECHNIQUES IN DIABETES
7. PERFORMANCE METRICS
8. LIMITATION OF ARTIFICIAL INTELLIGENCE
9. CONCLUSION
REFERENCES
Chapter 22: Lightweight Neural Networks for Pedestrian Detection in Intelligent Vehicles
ABSTRACT
INTRODUCTION
RELATED WORKS
PROPOSED METHOD
EXPERIMENTS AND RESULTS
CONCLUSION
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 23: Towards Predicting the Life of an Engine
ABSTRACT
INTRODUCTION
BACKGROUND
TIME SERIES
MACHINE LEARNING ALGORITHMS
TIME SERIES ANALYSIS
EVALUATION METRICS
PRACTICAL IMPLEMENTATION
CONCLUSION
REFERENCES
ADDITIONAL READING
KEY TERMS AND DEFINITIONS
Chapter 24: Nighttime Object Detection
ABSTRACT
1. INTRODUCTION
2. RELATED WORK
3. DATASET
4. BACKGROUND
5. PROPOSED MODEL
6. RESULTS
7. CONCLUSION
ACKNOWLEDGMENT
REFERENCES
KEY TERMS AND DEFINITIONS
Chapter 25: Identification of Avascular Necrosis or Osteoporosis Using Deep Belief Convolutional Neural Networks
ABSTRACT
INTRODUCTION
RESULTS AND ANALYSIS
FUTURE RESEARCH DIRECTIONS
CONCLUSION
ACKNOWLEDGMENT
REFERENCES
Compilation of References
About the Contributors
