Artificial Intelligence : Fundamentals and Applications / edited by Cherry Bhargava and Pradeep Kumar Sharma.

Format:

Book

Contributor:

Bhargava, Cherry, editor.

Sharma, Pradeep Kumar, editor.

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (271 pages)

Edition:

First edition.

Place of Publication:

Boca Raton, FL : CRC Press, 2021.

Summary:

This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.

Contents:

Cover

Half Title

Title Page

Copyright Page

Table of Contents

Preface

Editors

Contributors

Chapter 1 Artificial Intelligence and Nanotechnology: A Super Convergence

1.1 Introduction

1.2 Utility of Artificial Intelligence

1.2.1 AI in Scanning Probe Microscopy

1.2.2 Nanosystem Design

1.2.3 Nanoscale Simulation

1.2.4 Nanocomputing

1.3 Food Science

1.4 Nanobots in Medicine

1.5 Summary

References

Chapter 2 Artificial Intelligence in E-Commerce: A Business Process Analysis

2.1 Introduction

2.2 Artificial Intelligence

2.2.1 AI Mimicking Human Intelligence

2.2.2 AI Exceeding Human Intelligence

2.3 E-Commerce Business Processes and Artificial Intelligence

2.3.1 Marketing

2.3.1.1 Market Research

2.3.1.2 Market Stimulation

2.3.2 Transaction Processing

2.3.2.1 Terms Negotiation

2.3.2.2 Order Selection and Priority

2.3.2.3 Order Receipt

2.3.2.4 Order Billing/Payment Management

2.3.3 Service and Support

2.3.3.1 Order Scheduling/Fulfillment Delivery

2.3.3.2 Customer Service and Support

2.4 Concluding Remarks

Chapter 3 ABC of Digital Era with Special Reference to Banking Sector

3.1 Introduction

3.2 Artificial Intelligence in Banking Sector

3.3 ABC of Digital Era in Banking Sector

3.3.1 A as Artificial Intelligence

3.3.2 B as Big Tech

3.3.3 C as Core Banking and Cloud

3.4 Opportunities and Challenges in Banking Sector Due to Digitalization

3.4.1 Opportunities

3.4.2 Challenges

3.5 Artificial Intelligence Used by Four BIG Banks of India

3.5.1 State Bank of India

3.5.2 HDFC Bank

3.5.3 ICICI Bank

3.5.4 AXIS Bank

3.6 Conclusion

Chapter 4 Artificial Intelligence in Predictive Analysis of Insurance and Banking

4.1 Introduction

4.2 Predictive Analysis and Its Applications.

4.2.1 Predictive Analysis of Stock Prices Using DCC GARCH Model in R

4.3 Genetic Algorithms

4.3.1 Genetic Algorithms in Portfolio Optimization

4.3.2 Genetic Algorithms in Bank Profit Maximization

4.4 Anomaly Detection

4.4.1 Anomaly Detection to Identify Credit Card Frauds using Python

4.4.1.1 Python Libraries

4.4.1.2 Anomaly Detection in Credit Card Data set

4.4.2 A Demonstration of Anomaly Detection in Ethereum Prices Using R

4.4.2.1 Ethereum

4.4.2.2 Tidy verse

4.4.2.3 Anomaly Detection

4.5 Conclusion

Chapter 5 Artificial Intelligence in Robotics and Automation

5.1 Introduction

5.2 History

5.3 Automation and Application Bots

5.4 Robots vs. Chatbots vs. Bots

5.4.1 Types of Bots

5.5 Natural Language Processing (NLP)

5.5.1 Natural Language Understanding (NLU)

5.5.2 Natural Language Generation

5.6 Robotics Process Automation (RPA)

5.6.1 Challenges in Implementation of RPA

5.7 Financial Impact of AI and Automation

5.8 Features of Automated Bots

5.9 Effect of AI and Automation

5.9.1 Human Resource

5.9.2 Drones and Self-Driving Cars

5.9.3 Education

5.9.4 Cybersecurity

5.9.5 Defense Forces

5.9.6 Home

5.9.7 Health Care

5.10 Challenges in implementing Automation

5.10.1 Business Case Issues

5.10.2 Analysis of Process

5.10.3 Post-Implementation Adoption

5.10.4 Choosing Right Vendor

5.11 Myths of Automated Bots

5.11.1 Robots are Humanoid

5.11.2 Automation Will Replace the Human Workforce

5.11.3 Accuracy

5.11.4 Expensive

5.11.5 Internal Environment of Organization

5.11.6 Robots Can Be Left Unattended

5.12 Platform Used for Implementation

5.12.1 Python

5.12.2 Tensor Flow

5.12.3 R

5.12.4 Scikit-Learn

5.12.5 Automation Anywhere

5.12.6 UiPath

5.13 Conclusion

References.

Chapter 6 Artificial Intelligence: An Emerging Approach in Healthcare

6.1 Introduction

6.2 Scope &amp

Relevance of Various Types of AI in Healthcare

6.3 AI's Timeline in Healthcare

6.4 Implementation of AI Concepts in the Medical World

6.5 Current Researches that Contribute to the Advancement of AI

6.6 Key Issues &amp

Challenges Ahead in AI

6.7 Conclusion

Chapter 7 Artificial Intelligence and Personalized Medicines: A Joint Narrative on Advancement in Medical Healthcare

7.1 Introduction

7.2 Need for Personalized Medicines

7.2.1 Contributors to Personalized Medicines

7.3 Application of AI in Healthcare for Development of Precision Medicines

7.4 In Intensive Care Unit (ICU)

7.4.1 In Intensive Care Unit (ICU)-To Predict the Fluid Requirement

7.4.2 To Solve Issues of Personalized Medicines

7.4.3 Revolutionizing Cloud of AI and Healthcare

7.5 Conclusion

Chapter 8 Nanotechnology and Artificial Intelligence for Precision Medicine in Oncology

8.1 Introduction

8.1.1 Fundamentals of Nanotechnology

8.2 Role of Nanotechnology in Medicine and Healthcare

8.2.1 Nanodrug Design by AI

8.2.2 Artificial Intelligence

8.2.2.1 AI in Medicine

8.2.3 Precision Medicine

8.2.3.1 Applications of Precision Medicine

8.2.4 Deep Learning

8.2.4.1 Application

8.2.4.2 Implementation of Deep Learning in Medicine

8.2.4.3 Convolutional Neural Networks

8.2.4.4 CNN in Precision Medicine

8.5 Conclusion

Chapter 9 Applications of Artificial Intelligence in Pharmaceutical and Drug Formulation

9.1 Introduction

9.2 Genetic Algorithm

9.3 Fuzzy Logic

9.4 Integrated Software

9.5 Applications of Artificial Intelligence in Pharmaceuticals

9.6 Recognition of Pattern and Modeling the Data of Analysis

9.7 Modeling the Response Surface.

9.8 In Assessment of Controlled-Release and Immediate-Release Formulations

9.9 In Product Development

9.10 In Predictive Toxicology

9.11 Proteins' Function and Structure Prediction

9.12 Pharmacokinetics

9.13 Conclusion

Chapter 10 Role of Artificial Intelligence for Diagnosing Tuberculosis

10.1 Introduction

10.1.1 History of TB

10.1.2 Global Impact of TB

10.1.3 TB: India's Silent Epidemic

10.1.4 Classification of TB

10.2 Technological Interventions for Diagnosis of TB

10.2.1 Artificial Intelligence (AI)

10.2.2 AI Techniques

10.2.3 Role of AI in the Diagnosis of TB-Comparative Analysis

10.2.4 Limitations of Retrieved Literature

10.3 Conclusion

Chapter 11 Applications of Artificial Intelligence in Detection and Treatment of COVID-19

11.1 Introduction

11.2 Inception of Artificial Intelligence in Healthcare

11.2.1 Applications of AI in Healthcare

11.3 Artificial Intelligence in the Management of COVID-19

11.3.1 AI in Early Detection and Alert Systems

11.4 Role of AI in Tracking and Prediction of COVID-19

11.4.1 Machine Learning

11.4.2 BlueDot Technology

11.4.3 Spatial Analysis

11.4.4 Enter Telco Analytics

11.4.5 Social Media

11.5 AI in COVID-19 Diagnosis

11.5.1 Real-Time Reverse Transcriptase Polymerase Chain Reaction (rRT-PCR

11.5.2 Antibody Detection Test

11.5.3 Isothermal Nucleic Acid Amplification

11.5.4 CT Imaging Analysis

11.5.5 Detection Using the Sensors of Smartphones

11.6 AI in the Treatment of COVID-19

11.7 AI in Maintenance of the Affected Areas and Dashboard

11.7.1 Johns Hopkins University Centre for Systems Science and Engineering Dashboard (JHU CSSE)

11.7.2 The World Health Organization (WHO) Dashboard

11.8 AI in Social Safety/Surveillance/Prevention of COVID-19

11.9 Conclusion

Chapter 12 Internet of Things-Powered Artificial Intelligence Using Microsoft Azure Platform

12.1 Introduction

12.2 Computing Requirements

12.3 Real-Time Data Analysis

12.4 AIoT: Integration of IoT &amp

AI on Microsoft Azure Platform

12.5 Steps to Write a Program in Rpi Computer

12.5.1 Working with Microsoft Azure

12.6 Application Areas of AIoT

12.7 Conclusion

Chapter 13 Load Balancing in Wireless Heterogeneous Network with Artificial Intelligence

13.1 Introduction

13.2 Different Types of Artificial Intelligence

13.2.1 Reactive Machines AI

13.2.2 Limited Memory AI

13.2.3 Theory of Mind AI

13.2.4 Self-Knowledge AI

13.2.5 Artificial Narrow Intelligence (ANI)

13.2.6 Artificial General Intelligence (AGI)

13.2.7 Artificial Strong Intelligence (ASI)

13.3 Advantages of Artificial Intelligence

13.4 Disadvantages of Artificial Intelligence

13.5 Artificial Intelligence: Methods and Applications

13.6 AI in Wireless Heterogeneous Networks (WHN)

13.7 Importance of Load Balancing In AI

13.6.1 Machine Learning in a Wireless Heterogeneous Network

13.6.2 Neural Network in a Wireless Heterogeneous Network

13.6.3 Fuzzy Logic for a Wireless Network

13.6.4 Genetic Algorithm

13.6.5 Particle Swarm Optimization (PSO)

13.6.6 Artificial Bee Colony (ABC)

13.6.7 Markov Models and Bayesian-Based Games

13.8 Conclusion

Chapter 14 Applications of Artificial Intelligence Techniques in the Power Systems

14.1 Introduction

14.1.1 Need of Artificial Intelligence in Power System

14.2 Types and Classification of Artificial Intelligent Techniques

14.2.1 Artificial Neural Network

14.2.1.1 Classification of Artificial Neural Network

14.2.1.2 Advantages and Disadvantages of Artificial Neural Network

14.2.1.3 Applications of ANN in Power System.

14.2.2 Fuzzy Logic.

Notes:

Description based on print version record.

ISBN:

1-00-309591-7

1-000-40646-6

1-003-09591-7

1-000-40648-2

9781003095910

OCLC:

1257666231