Table of Contents
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PREFACE
List of Contributors
A Comprehensive Study and Analysis on Prediction of Rainfall Across Multiple Countries using Machine Learning
Abstract
INTRODUCTION
RELEVANT WORK
DISCUSSION
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
A Novel Approach for Clustering Large-scale Cloud Data using Computational Mechanism
Abstract
INTRODUCTION
REVIEW OF LITERATURE
IMPLEMENTATION USING GENETIC ALGORITHM
STRATEGIES OF EVALUATION OF QUERY PLANS RELATED TO LARGE SCALE DATA
ALGORITHM
EXPERIMENTAL ANALYSIS
DISCUSSION AND FUTURE DIRECTION
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
Secure Communication Over In-Vehicle Network Using Message Authentication
Abstract
INTRODUCTION
Background for Vehicle Security
Hacking Incidents on Vehicles
Economic Value at Risk Due to Poor Security Investments
Security Goals
Security Attacks
Techniques to Implement Security Mechanisms
Network Security Model
Security by Design
Cybersecurity Concept for Connected Car
Designing Secure Automotive Systems
Security by Design across CAR Development Lifecycle
Vehicle Communication Buses
Format of Request and Response Messages
Internal Key used for Decryption and Encryption
AES Algorithm
Sequence of Key Update Procedure
Routine Control (31 hex) Service
Steps Involved in Key Update
Step 1:
Step 2:
Step 3:
Step 4:
STEP 5:
Step 6:
Step 7:
Step 8:
DESIGN AND IMPLEMENTATION
Overview of the AUTOSAR Standard
AUTOSAR Architecture Overview
AUTOSAR Software Architecture and Features for Security
Design Flow within AUTOSAR Security Software Modules
Implementation of in-vehicle Message Authentication
Sequence Diagram Authentication during Direct Transmission
Sequence Diagram Verification during Direct Reception
Introduction to DaVinci Developer tool
Introduction to DaVinci Configurator Pro Tool
Introduction to CANoe Tool Environment
Test Setup and CAN message Data Base for Verification
Software Flashing Method
Secret Key Storage into the Target Hardware Memory
Verification Result for Message Authentication
MAC Messages
Additional Test Methods for Cyber Security Verification and Validation
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
A Decision Model for Reliability Analysis of Agricultural Sensor Data for Smart Irrigation 4.0
Abstract
INTRODUCTION
LITERATURE SURVEY
PROPOSED METHODOLOGY
Dataset Acquisition
Dataset Pre-Processing
Framework
Algorithm
Parameter Estimation
Modeling/Training Stage
Hyper-Parameter Tuning
EXPERIMENTAL RESULT & ANALYSIS
Precision
Recall
F1. Score
Comparative Analysis
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
Machine Learning based Smart Electricity Monitoring & Fault Detection for Smart City 4.0 Ecosystem
Abstract
INTRODUCTION
RELATED WORKS
PROPOSED FRAMEWORK
Electricity Prediction Module
Threshold Calculation Module
Fault Detection Module
EXPERIMENTAL RESULT & ANALYSIS
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
Investigating the Effectiveness of Mobile Learning in Higher Education
Abstract
INTRODUCTION
MODEL CONSTRUCTION AND DEVELOPMENT OF HYPOTHESIS
Technology Acceptance and Learner Satisfaction
System Success and Learner satisfaction
Environmental Factors and Learner satisfaction
Technology Acceptance and Learner Intention
System Success and Learner Intention
Environmental Factors and Learner Intention
Learner Satisfaction and M-learning effectiveness
Learner Intention and M-learning effectiveness
METHODOLOGY
Operational Design
Data Collection
Instrument Development
RESULT
Data Analysis and Results – Qualitative Study
Technology Acceptance
System Success
Environmental Factors
Learner Satisfaction
Learner Intention
M-Learning Effectiveness
Data Analysis and Results – Quantitative
SEM in VPLS
Results of Hypothesis Testing
DISCUSSION AND CONCLUSION
ABBREVIATIONS
REFERENCES
Socio-Economy of Coastal Fishing Community of Southern Coast of Odisha: A Case Study
Abstract
INTRODUCTION
Information and Methodology
Result and Discussion
Overall population, geography, and literacy of Odisha
Origin, present status, geography, and administrative classification of Ganjam
Census (Govt. of India) 2011
Ganjam District Population
Ganjam District Population Growth Rate
Ganjam District Density
Ganjam Literacy Rate
Ganjam Sex Ratio
Ganjam Child Population
Ganjam District Urban Population
Ganjam District Rural Population
Education Facilities
Socio-economic status of the coastal total fishing community of Ganjam
Fishing Activities
Assets of the Fishermen
Fishing Fleets
Fishing craft
Fishing gear and method
Fish Harvest
Fish Marketing and Preservation
Problems Encountered in Fish Marketing
Socio-economics
Welfare Schemes
Role of Different Banks in Financing Fishermen
Fisheries Co-operatives
Geomorphology
Potential Fishing Zone (PFZ) Advisories using Remote Sensing Technology for Reduction of Fuel Consumption and Search Time and Improvement of Catch
Socio-economic Situation of Fisherwomen in Ganjam District: A Case Study
Significant Problems Associated with the Fisherwomen Community
Lack of Empowerment among Women
Inadequate Systems and Techniques to Support Fisher Women Micro-enterprises
Lack of Capacity Building, Skills, and Institution
Coastal Fishing Community at Gopalpur-on-sea (the Most Important Coastal Site for Fshing and Tourism of Ganjam District): A Particular Case Study
Ongoing Problems and Subsequent Demands of the Coastal Fishing Community of Gopalpur-on-sea
Conclusion
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
References
Filtering Techniques for Removing Noise From ECG Signals
Abstract
INTRODUCTION
Artifacts
Types of Artifact in ECG Signal
Power Line Interference
Muscle Contractions
Electrode Motion Artifacts
Baseline Wandering
Reversed Lead
ECG RECORDING CONDITIONS
Calibration of the Equipment
Recording Procedure
ECG Signal Filtering
Decomposition
Discrete Wavelet Transform based Decomposition
ALGORITHM: DWT Decomposition
Denoising of ECG Signal
Hard and Soft Thresholding
Wavelet Thresholding
EMD-Thresholding
Wavelet-based Thresholding
Wavelet Frequency Thresholding
ECG Signal Filtering Techniques
Low-Pass Filters
High-Pass Filter
Derivative Base Filters
EVALUATION CRITERIA FOR DENOISING
Signal to Noise Ratio
Mean Square Error
EXPERIMENTAL RESULTS
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
REFERENCES
Deep Learning Techniques for Biomedical Research and Significant Gene Identification using Next Generation Sequencing (NGS) Data: - A Review
Abstract
INTRODUCTION
BACKGROUND
DNA SEQUENCING
Sanger Sequencing
Next Generation Sequencing (The Rising Trend)
NGS GENE EXPRESSION DATA (STRUCTURE, CHARACTER, AND CHALLENGES)
QC TOOLS FOR NGS DATA PRE-PROCESSING
MACHINE LEARNING TECHNIQUES FOR NGS DATA ANALYSIS
Various Datamining Methods for Sequence data
Taxonomy of Datamining, ML, and DL Techniques used for NGS data Analysis
MACHINE LEARNING TECHNIQUES FOR NGS FEATURE SELECTION
Filter Method
Wrapper Method
Embedded Method
Hybrid Method
Ensemble Method
FEATURE EXTRACTION TECHNIQUES FOR NGS DATA
Correlation-based Feature Selection (CFS)
Fast Correlation-Based Filter (FCBF)
INTERACT
Information Gain
ReliefF
Minimum Redundancy Maximum Relevance (mRMR)
LASSO (Least Absolute Shrinkage and Selection Operator)
Elastic Net (E-Net)
Random Forest (RF)
ISSUES AND OPPORTUNITIES WITH TRADITIONAL MACHINE LEARNING
DEEP LEARNING (THE EMERGING TREND)
The Revolution of Deep Learning
DEEP LEARNING APPROACH FOR NGS DATA ANALYSIS
Artificial Neural Network (ANN)
Convolutional Neural Network (CNN)
Deep Neural Network (DNN)
Feedforward Neural Network (FNN)
Recurrent Neural Network (RNN)
SIGNIFICANT GENE IDENTIFICATION AND ANNOTATION
SUMMARY OF DL METHODS USED FOR NGS DATA ANALYSIS
CRITICAL OBSERVATION
Data Volume
Data Quality
The Curse of Dimensionality
Interpretability
Domain Complexity
Biological Annotation
CONCLUSION AND FUTURE SCOPE
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
References
Breast Cancer Detection Using Machine Learning Concepts
Abstract
INTRODUCTION
Background
Undertaking Thorough Medical History
Imaging Tests
Advanced Test
Classification Using the Techniques
Dataset
PROPOSED SYSTEM
Problem Statement
Objectives
Why WDBC?
LITERATURE SURVEY
Technological Development
Dataset used in the Research
Related Work
METHODOLOGIES
Learning Algorithms
Measuring the Effectiveness of the Models
Processing of Patterns
Results and Discussion
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENT
References
Advances in Computing
Communications and
Informatics
(Volume 5)
Data Science and
Interdisciplinary Research:
Recent Trends and Applications
Edited by
Brojo Kishore Mishra
Department of Computer Science & Engineering
NIST Institute of Science and Technology (Autonomous)
Institute Park, Pallur Hills, Golanthara
Berhampur-761008, Odisha, India
BENTHAM SCIENCE PUBLISHERS LTD.
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PREFACE
Data science has recently gained much attention for a number of reasons, Big Data is the most significant among them. Scientists (from almost all disciplines including physics, chemistry, biology, and sociology, among others) and engineers (from all fields including civil, environmental, chemical, and mechanical, among others) are faced with challenges posed by data volume, variety, and velocity, or Big Data.
The book contains quantitative research, case studies, conceptual papers, and model papers, review papers, theoretical backing, etc. This book will cover data science and its application to interdisciplinary science.
This book will prove valuable for graduate students, researchers, academicians, and professionals in information science, business, health, planning, manufacturing, and other areas who are interested in exploring the ever-expanding research on Data Science.
Chapter-01 provides a detailed survey and comparative analysis of various methodologies in the prediction of rainfall over multiple countries.
Chapter -02 focuses on applying clustering for gaining the benefits of evolutionary computation to process large-scale data and based on optimality, the performance of the datasets can be measured.
Chapter-05 presents an investigation of the data obtained from IoT sensors and observed that a huge amount of work can be done in the reliability analysis of the data from the sensors deployed in the agricultural fields.
Chapter-06 says that - Smart devices have rapidly started intruding our lifestyles with the technological promotion of the Internet of Things. One of the most used smart devices is the electric meter. Urban areas witness power theft as well as un-proportionate billing, both incurring tremendous losses to the respective exchequers. We thought that if a system may be designed which can predict power utilization and also classify the current usage, it would be beneficial to both the service providers as well as the consumers. Equipped with such thoughts, thorough research was conducted to monitor electric consumption and fault detection in the devices.
Chapter-08 focused on undertaking a quick analysis of socio-economic conditions. Information on the aforementioned parameters was gathered in order to get insight into the research area's socio-economic profile.
In the end, we thank the contributory authors, reviewers and my family members for their support. Special thanks to Prof. (Dr.) Pradeep Kumar Singh for his best support as a Book Series Editor. The editors are also thankful to all members of Bentham Science Publication house.
Brojo Kishore Mishra
Department of Computer Science & Engineering
NIST Institute of Science and Technology (Autonomous)
Institute Park, Pallur Hills, Golanthara
Berhampur-761008, Odisha, India
List of Contributors
Adrija DasguptaDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaA. KavithaDepartment of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IndiaC. Kishor Kumar ReddyStanley College of Engineering and Technology for Women, Hyderabad, IndiaDiganta SenguptaDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaD. AlameluKGiSL Institute of Technology, Coimbatore, Tamil Nadu, IndiaDebasish Swapnesh Kumar NayakDepartment of Computer Science & Engineering, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, IndiaDas JayashankarAvior Genomics, Mumbai, IndiaFahmina TaranumComputer Science and Engineering Department, Muffakham Jah College of Engineering and Technology, Hyderabad, IndiaGouri C. KhadabadiDepartment of CSE, KLS Gogte Institute of Technolgy, Belagavi, IndiaJyoti Prakash MishraGandhi Institute for Education and Technology, Baniatangi, hubaneswar, Affiliated to BijuPatnaik University of Technology, Rourkela, Odisha, IndiaJayashankar DasAvior Genomics, Mumbai, IndiaK. ManimekalaiDepartment of Computer Applications, Sri GVG Visalakshi College for Women, Udumalpet, Tamil Nadu, IndiaK. SrideviComputer Science and Engineering Department, Muffakham Jah College of Engineering and Technology, Hyderabad, IndiaManjunath ManaguliDepartment of ECE, KLS Gogte Institute of Technology, Belagavi, IndiaNguyen Gia NhuDean, Graduate School, Duy Tan University, Da Nang, VietnamN. VenugopalSri Krishna College of Technology, Coimbatore, Tamil Nadu, IndiaP.R. AnishaStanley College of Engineering and Technology for Women, Hyderabad, IndiaPankaja S. KadalgiDepartment of CSE, KLS Gogte Institute of Technolgy, Belagavi, IndiaSambit Kumar MishraGandhi Institute for Education and Technology, Baniatangi, hubaneswar, Affiliated to BijuPatnaik University of Technology, Rourkela, Odisha, IndiaSudha SlakeDepartment of CSE, KLS Gogte Institute of Technolgy, Belagavi, IndiaSubhash MondalDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaSamrat PodderDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaSuharta BanerjeeDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaSugata GhoshDepartment of Computer Science and Engineering, Meghnad Saha Institute of Technology, Kolkata, IndiaT. PadmavatiDepartment of Marine Sciences, Berhampur University, Odisha, IndiaTripti SwarnkarDepartment of Computer Application, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, IndiaV. KalaiarasiPSG College of Arts and Science, Coimbatore, Tamil Nadu, IndiaZdzislaw PolkowskiDepartment of Humanities and Social Sciences, The Karkonosze University of Applied Sciences in Jelenia Góra, Jelenia Góra, Poland
A Comprehensive Study and Analysis on Prediction of Rainfall Across Multiple Countries using Machine Learning
C. Kishor Kumar Reddy1,*,P.R. Anisha1,Nguyen Gia Nhu2
1 Stanley College of Engineering and Technology for Women, Hyderabad, India
2 Dean, Graduate School, Duy Tan University, Da Nang, Vietnam
Abstract
Rainfall is one of the most considerable natural occurrences, which is important for both human beings and living beings. Since the environment is changing and there is a huge change in weather, it is noted that the rainfall cycles are also varying and the earth’s temperature is increasing day-by-day. The changes in weather conditions like humidity, pressure, wind speed, dew point and temperature affect the agriculture, industry, production, and construction and also lead to floods and land-slides. Hence it is one of the important factors to be noted for human beings to keep track of the natural occurrences in order to survive. In order to overcome these issues, a system is required which is able to forecast and predict the rainfall using statistical techniques which is the most popular tool in modern technology. This paper provides a detailed survey and comparative analysis of various methodologies used in the prediction of rainfall over multiple countries. Comparison is made in terms of various performance measures: accuracy, precision, recall, RMSE, specificity, sensitivity, MAE, F-Measure, ROC and RAE. Further, the drawbacks with existing approaches applied so far in the prediction are discussed.
Keywords: Artificial Neural Networks, Classification Techniques, Decision Trees, Naïve Bayes, Rainfall, Random Forest, SVM.
*Corresponding author C. Kishor Kumar Reddy: Stanley College of Engineering and Technology for Women, Hyderabad, India; E-mail:
[email protected].