This volume explores a diverse range of applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation.
Chapter 1 introduces an innovative device for automatically notifying and analyzing the impact of automobile accidents. Chapter 2 focuses on the detection of malaria using systematized image processing techniques. In Chapter 3, an intelligent technique based on LMEPOP and fuzzy logic for the segmentation of defocus blur is discussed. Predictive analytics is introduced in Chapter 4, providing an overview of this emerging field. Chapter 5 delves into discrete event system simulation, offering insights into its applications.
The performance analysis of different hypervisors in OS virtualization is explored in Chapter 6. Load balancing in cloud computing is the subject of investigation in Chapter 7. Chapter 8 presents a survey on a facial and fingerprint-based voting system utilizing deep learning techniques. Chapter 9 explores IoT-based automated decision-making with data analytics in agriculture. Biometric recognition through modality fusion is investigated in Chapter 10. Chapter 11 offers a new perspective on evaluating machine learning algorithms for predicting employee performance. Pre-process methods for cardiovascular diseases diagnosis using CT angiography images are discussed in Chapter 12. Chapter 13 presents the implementation of a smart wheelchair using ultrasonic sensors and LabVIEW.
Cryptography using the Internet of Things is the focus of Chapter 14. Chapter 15 explores machine learning applications for traffic sign recognition, and the book concludes with Chapter 16, which analyzes machine learning algorithms in healthcare.
The book is a resource for academics, researchers, educators and professionals in the technology sector who want to learn about current trends in intelligent technologies.
Table of Contents
CHAPTER 1 INNOVATIVE DEVICE FOR AUTOMATICALLY NOTIFYING AND
- INTRODUCTION
- LITERATURE SURVEY
- Prototyping an Automatic Notification Scheme for Traffic Accidents in Vehicular Networks 3
- Emergency Services in Future Intelligent Transportation Systems Based on Vehicular
- Communication Networks
- National Highway Traffic Safety Administration
- Geometry and Motion-based Positioning Algorithms for Mobile Tracking in NLOS
- Environments
- PROPOSED SYSTEM
- Block Diagram for Vehicle Section
- Block Diagram for Other Vehicle Section
- ARM
- Crash Sensor
- MEMS Sensor
- DC Motor
- Circuit Diagram for Vehicle Section
- Relay
- MAX 232
- GSM
- GSM Interfacing with ARM
- ZIGBEE
- BUZZER
- RESULTS AND DISCUSSION
- CONCLUSION
- ACKNOWLEDGEMENTS
- REFERENCES
CHAPTER 2 DETECTION OF MALARIAL USING SYSTEMATIZED IMAGE PROCESSING
- INTRODUCTION
- Clinical Malaria Diagnosis
- Laboratorial Malaria Diagnosis: Peripheral Blood Smear
- Serological Tests
- Quantitative Buffy Tests
- Rapid Diagnostic Tests
- OBJECTIVE
- Image Processing Techniques
- Grey Scale Image Conversion
- Image Enhancement Techniques
- Image Filtering Techniques
- Image Sharpening Techniques
- Image Thresholding Techniques
- Region Selection
- Corner Detection
- Gray Scale Image Conversion
- Image Enhancement Techniques
- Log Transformation
- Image Filtering Techniques
- Gauss Filters
- Box Filters
- Min Filters
- Max Filters
- Image Sharpening Techniques
- Image Thresholding Techniques
- Edge Detection
- Region Selection
- Corner Detection
- DESIGN OF THE SYSTEM
- System Work Flow
- Working of the System
- Image Pre-Processing
- Reading the Image
- Image Transformation
- Image Filtering
- Image Sharpening
- Image Thresholding
- Severity Calculation
- Edge Detection
- Corner Detection
- Region Selection
- Severity
- Stage Detection
- CONCLUSION
- REFERENCES
CHAPTER 3 LMEPOP AND FUZZY LOGIC BASED INTELLIGENT TECHNIQUE FOR SEGMENTATION OF DEFOCUS BLUR
- INTRODUCTION
- LITERATURE SURVEY
- Image Sharpness Assessment Based on Local Phase Coherence
- Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns
- An Image Recapture Detection Algorithm Based on Learning Dictionaries of Edge Profiles 38
- PROPOSED SYSTEM
- LOCAL MAXIMUM EDGE POSITION OCTAL PATTERN
- BLUR SEGMENTATION ALGORITHM
- FUZZY BASED MULTI SCALE INFERENCE SYSTEM
- Fuzzy Set Operations
- Defuzzification
- RESULT AND DISCUSSION
- CONCLUSION & FUTURE ENHANCEMENT
- ACKNOWLEDGEMENTS
- REFERENCES
CHAPTER 4 PREDICTIVE ANALYTICS - AN INTRODUCTION
- INTRODUCTION
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- MAIN TEXT: PREDICTIVE ANALYTICS
- Benefits and Drawbacks
- Advantages
- Disadvantages
- MODEL 1 OF PA: REGRESSION
- Regression Line of X on Y [X Depending on Y]
- Regression Line of Y on X [Y Depending on X]
- Regression Line of X on Y [X Depending on Y]
- Regression line of Y on X [Y depending on X]
- PA MODEL 2: MULTIPLE REGRESSION
- MLR -Method 1
- MLR -Method 2
- PA MODEL 3: LOGISTIC REGRESSION
- PA MODEL 4: KNN
- CONCLUSION
- REFERENCES
CHAPTER 5 DISCRETE EVENT SYSTEM SIMULATION
- INTRODUCTION
- MAIN TEXT: SIMULATION
- Advantages and Disadvantages
- System in a Simulation
- Model of a System
- Steps in a Simulation Study
- CASE STUDY: A TWO SERVER QUEUING SYSTEM
- Problem Description
- Purpose of Queuing Models: Obtain Two Aspects of a Queueing System
- Characteristics of a Queuing System
- Arrival
- Service
- System Capacity
- Size of Calling Population
- Queue Discipline
- Human Behavior
- Measures of Queues
- CONCLUSION
- REFERENCES
CHAPTER 6 PERFORMANCE ANALYSIS OF DIFFERENT HYPERVISORS USING MEMORY AND WORKLOADS IN OS VIRTUALIZATION
- INTRODUCTION
- Hypervisors have many Benefits
- Speed
- Efficiency
- Flexibility
- Portability
- CONTAINER VS HYPERVISOR
- Type 1 Hypervisors (Bare Metal)
- Type 2 Hypervisors (Hosted Hypervisor
- HYPER-V ARCHITECTURE
- VMWARE ARCHITECTURE
- XEN ARCHITECTURE
- MOTIVATION
- PROBLEM STATEMENT
- METHOD
- EXPERIMENTAL SETUP
- EXPERIMENT WORKLOADS AND ITS CLASSIFICATION
- RESULTS AND DISCUSSION
- Observation 1
- Observation 2
- OVERALL RESULT ANALYSIS
- CONCLUSION
- REFERENCES
CHAPTER 7 A STUDY ON LOAD BALANCING IN CLOUD COMPUTING
- INTRODUCTION
- CLOUD COMPUTING ARCHITECTURE
- LOAD BALANCING
- Graphical Distribution Node
- Virtual Machine Migration
- Algorithm Complexity
- Heterogeneousous Nodes
- Single Point of Failure
- Load Balancer Scalability
- METRICS FOR LOAD BALANCING IN THE CLOUD
- Throughput
- Response Time
- Makespan
- Scalability
- Fault Tolerance
- Migration Time
- Energy Consumption
- Carbon Emission
- LOAD BALANCING POLICIES
- Selection Policy
- Location Policy
- Transfer Policy
- Information Policy
- ISSUES IN LOAD BALANCING
- Data Gathering Rules
- Picking Rules
- Aggravating Rules
- Place Rules
- Migration Rules
Author
- S. Kannadhasan
- R. Nagarajan
- N. Shanmugasundaram
- Jyotir Moy Chatterjee
