Note: Intro -- Contents -- Editors and Contributors -- Cloud Computing -- An Efficient Honey Bee Approach for Load Adjusting in Cloud Environment -- 1 Introduction -- 2 Related Work -- 3 Proposed HBI-LA -- 3.1 Overview of Honey Bee Method -- 3.2 Description of Proposed HBI-LA Scheme with Concept of Aging -- 4 Performance Analysis -- 5 Conclusion -- 6 Future Work -- References -- A Novel Approach of Task Scheduling in Cloud Computing Environment -- 1 Introduction -- 2 Scheduling Model -- 2.1 Application Model -- 2.2 System Resource Model -- 2.3 Preliminaries of Task Scheduling -- 2.4 Task Scheduling Objective -- 3 Proposed Algorithm -- 3.1 Illustrative Examples -- 4 Conclusion -- References -- Development and Design Strategies of Evidence Collection Framework in Cloud Environment -- 1 Introduction -- 2 Comparative Research of Existing Data and Evidence Collection Tools, Techniques, Frameworks, Algorithm, and Approaches in Cloud Forensics -- 3 Noteworthy Contributions in the Field of Proposed Work -- 4 Expected Outcome of the Proposed Work -- 5 Conclusion -- References -- A Systematic Analysis of Task Scheduling Algorithms in Cloud Computing -- 1 Introduction -- 2 Task Scheduling Models Classification -- 3 Basic Task Scheduling Problem Definition -- 4 Scheduling Attributes -- 5 Study of Task Scheduling Algorithms: Review and Analysis -- 6 Conclusion -- References -- A Survey on Cloud Federation Architecture and Challenges -- 1 Introduction -- 2 Literature Review -- 3 The Basic Architecture -- 3.1 Frontend Module -- 3.2 Resource Broker Module -- 3.3 Cloud Interface Module -- 4 A Broker Based Framework -- 4.1 Resource Discovery -- 4.2 Resource Provisioning -- 4.3 Resource Scheduling -- 4.4 Monitoring -- 4.5 Cost Estimation and Billing -- 4.6 Resource Information Service -- 5 Federation of Hybrid Clouds -- 5.1 Hybrid Clouds. , 5.2 Hierarchical Structure of Cloud -- 5.3 Architecture -- 6 Challenges -- 6.1 Energy and Resource Utilization -- 6.2 Distributed Resource Finding and Allocation -- 6.3 Resource Provisioning -- 6.4 Network Monitoring in Federated Clouds -- 6.5 Security and Privacy in Federated Clouds -- 6.6 Inter-domain Communication -- 7 Conclusion -- References -- Multi-tier Authentication for Cloud Security -- 1 Introduction -- 2 Characteristics of Cloud Computing -- 2.1 On Demand Self Service -- 2.2 Broad Network Access -- 2.3 Resource Pooling -- 2.4 Rapid Elasticity -- 2.5 Measured Service -- 3 Cloud Delivery Models -- 3.1 SPI Model -- 3.2 Cloud Deployment Models -- 4 Security for Cloud Systems -- 4.1 Security Parameters -- 4.2 Security Threats -- 5 Security Measures -- 6 Literature Review -- 7 Proposed Algorithm -- 7.1 Modules of the Proposed System -- 8 Conclusion -- References -- Investigations of Microservices Architecture in Edge Computing Environment -- 1 Introduction -- 2 Review of Literature -- 2.1 Programming Model for Edge Computing Environment -- 2.2 Microservices Architecture -- 3 Objectives -- 4 Conclusion -- References -- Improving Reliability of Mobile Social Cloud Computing using Machine Learning in Content Addressable Network -- 1 Introduction -- 2 Related Work -- 2.1 Fault Tolerance in Computing Environment -- 2.2 Quality of Service in Computing Environment -- 2.3 Content Addressable Network -- 3 Mobile Social Cloud Computing (MSCC) -- 3.1 MSCC Architecture -- 3.2 Preamble -- 4 Proposed Work -- 4.1 Proposed Framework -- 4.2 Proposed Algorithm -- 5 Simulation Scenario, Experimental Setup, and Result Analysis -- 5.1 Simulation Configuration -- 5.2 Experiment Scenarios -- 5.3 Results and Analysis -- 6 Comparative Study -- 7 Conclusion and Prospects -- References -- Data De-duplication Scheme for File Checksum in Cloud -- 1 Introduction. , 2 Related Work -- 3 System Architecture -- 4 Results and Discussion -- 4.1 Snapshots -- 5 Conclusion -- References -- A Survey on Cloud Computing Security Issues and Cryptographic Techniques -- 1 Introduction -- 2 Security Issues of Deployment Models in Cloud -- 2.1 Security Concerns in Public Cloud -- 2.2 Security Concerns in Private Cloud -- 2.3 Security Concerns in Hybrid Cloud -- 3 Security Issues in Cloud Service Models -- 3.1 Security Concerns in Software as a Service (SaaS) -- 3.2 Security Concern in Platform as a Service (PaaS) -- 3.3 Security Concerns in Infrastructure as a Service (IaaS) -- 4 Cryptographic Techniques for Cloud -- 4.1 Asymmetric Key Algorithms -- 4.2 Symmetric Key Algorithms -- 4.3 Hash Function Algorithms -- 4.4 Authentication Schemes -- 5 Recent Trends and Algorithms for Cloud Security -- 5.1 Securing Cloud Computing Environment Based on DNA Cryptography -- 5.2 Quantum Cryptography for Secure Cloud Computing -- 5.3 Hybrid Cryptographic Algorithms -- 6 Conclusion -- References -- Machine Learning -- Features Identification for Filtering Credible Content on Twitter Using Machine Learning Techniques -- 1 Introduction -- 2 Background Study -- 2.1 User Specified Features for Finding the Credibility of Tweets -- 3 Explaining Credibility -- 3.1 Evaluating Credibility -- 4 Data Crawling and Labeling Credibility -- 5 Feature Analysis and Classification -- 6 Best Features Analysis -- 7 Conclusion and Future Work -- References -- Perspectives of Healthcare Sector with Artificial Intelligence -- 1 Introduction -- 1.1 What Is Artificial Intelligence? -- 1.2 The Need for Artificial Intelligence -- 1.3 How Is Artificial Intelligence Helping the Patients? -- 1.4 Using AI to Help Medical Professionals -- 1.5 Administrators Leverage AI to Plan Efficiently -- 1.6 Limitations of Artificial Intelligence. , 2 Applications of AI in the Healthcare Sector -- 3 Artificial Intelligence for Medical Professionals -- 4 Artificial Intelligence in the Healthcare Administrative Perspective -- 5 Conclusion -- References -- A Novel Approach for Stock Market Price Prediction Based on Polynomial Linear Regression -- 1 Introduction -- 2 Literature Review -- 3 Simple Linear Regression -- 4 Polynomial Linear Regression -- 5 Implementation Details -- 6 Performance Evaluation -- 7 Result Analysis -- 8 Conclusion -- References -- Real-Time Classification of Twitter Data Using Decision Tree Technique -- 1 Introduction -- 2 Literature Review -- 3 Problem Definition -- 4 Proposed Work -- 5 Experimental and Result Analysis -- 6 Conclusion -- References -- Dynamic Web Service Composition Using AI Planning Technique: Case Study on Blackbox Planner -- 1 Introduction -- 2 Related Work -- 3 AI Planning for Dynamic WSC -- 4 Experiments and Results -- 4.1 Travel Domain -- 4.2 Case I -- 4.3 Case II -- 5 Conclusion -- References -- A Study of Deep Learning in Text Analytics -- 1 Introduction -- 2 Text Preprocessing -- 3 Feature Extraction Using Deep Architectures -- 4 Applications of Deep Learning in Text Processing -- 4.1 Text Classification -- 4.2 Document Summarization -- 4.3 Question Answering -- 4.4 Machine Translation -- 4.5 Caption Generation -- 4.6 Speech Recognition -- 5 Conclusion -- References -- Image Segmentation of Breast Cancer Histopathology Images Using PSO-Based Clustering Technique -- 1 Introduction -- 2 Literature Survey -- 3 K-means Clustering -- 4 Genetic Algorithm (GA) -- 5 Particle Swarm Optimization (PSO) -- 6 Experimental Results -- 7 Conclusion -- References -- Survey of Methods Applying Deep Learning to Distinguish Between Computer Generated and Natural Images -- 1 Introduction -- 2 Problem Statement -- 3 Previous Work. , 4 Methods Implementing Deep Learning to Distinguish Between CG and NI -- 4.1 Method I: Rahmouni et al. [15] -- 4.2 Method II: Quan et al. [16] -- 4.3 Method III: Rezende et al. [17] -- 5 Theoretical Findings -- 5.1 Building of Standard Dataset -- 5.2 Increased Focus on Classifying Compressed Images -- 5.3 Testing of Combination of Features Generated from Various CNNs -- 6 Conclusion -- References -- SVM Hyper-Parameters Optimization using Multi-PSO for Intrusion Detection -- 1 Introduction -- 2 Support Vector Machine (SVM) -- 3 Particle Swarm Optimization (PSO) -- 4 Proposed Model -- 5 Result Analysis -- 5.1 Range of the Parameters C and γ -- 5.2 Results -- 6 Conclusion -- References -- A Survey on SVM Hyper-Parameters Optimization Techniques -- 1 Introduction -- 2 Various Selection Criterion -- 2.1 Leave-One-Out Bound -- 2.2 Support Vector Count -- 2.3 Radius-Margin Bound -- 3 Various Searching Techniques -- 3.1 Gradient Descent -- 3.2 Grid Search -- 3.3 Genetic Algorithms -- 3.4 Covariance Matrix Adaptation Evolution Strategies (CMA-ES) -- 3.5 Particle Swarm Optimization -- 3.6 Hybrid-Optimization Techniques -- 4 Conclusion -- References -- Review of F0 Estimation in the Context of Indian Classical Music Expression Detection -- 1 Motivation and Context -- 2 Different Types of Music Expressions -- 2.1 Glissando and Legato -- 2.2 Vibrato -- 2.3 Tremolo -- 2.4 Kobushi -- 3 Pitch Extraction Methods Used -- 3.1 Discrete Fourier Transform -- 3.2 Constant Q Transforms -- 3.3 YIN Algorithm -- 4 Dataset for Experimentation -- 4.1 Simulated Notes -- 4.2 Recorded Notes -- 5 Results and Discussion -- 6 Conclusion and Future Scope -- References -- Classification and Detection of Breast Cancer Using Machine Learning -- 1 Introduction -- 2 Related Work Heading -- 3 Methodology Used -- 3.1 Soft Computing Models -- 3.2 Model Diagram -- 3.3 Evaluation Measures. , 3.4 Dataset Details.