Computer und IT
Machine Learning Techniques and Analytics for Cloud Security
MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITYTHIS BOOK COVERS NEW METHODS, SURVEYS, CASE STUDIES, AND POLICY WITH ALMOST ALL MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY SOLUTIONSThe aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. AUDIENCEResearch scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography. RAJDEEP CHAKRABORTY obtained his PhD in CSE from the University of Kalyani. He is currently an assistant professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Garia, Kolkata, India. He has several publications in reputed international journals and conferences and has authored a book on hardware cryptography. His field of interest is mainly in cryptography and computer security.ANUPAM GHOSH obtained his PhD in Engineering from Jadavpur University. He is currently a professor in the Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata. He has published more than 80 papers in reputed international journals and conferences. His field of interest is mainly in AI, machine learning, deep learning, image processing, soft computing, bioinformatics, IoT, data mining. JYOTSNA KUMAR MANDAL obtained his PhD in CSE from Jadavpur University He has more than 450 publications in reputed international journals and conferences. His field of interest is mainly in coding theory, data and network security, remote sensing & GIS-based applications, data compression error corrections, information security, watermarking, steganography and document authentication, image processing, visual cryptography, MANET, wireless and mobile computing/security, unify computing, chaos theory, and applications. ContentsPrefacePART I: CONCEPTUAL ASPECTS ON CLOUD AND APPLICATIONS OF MACHINE LEARNING 11 HYBRID CLOUD: A NEW PARADIGM IN CLOUD COMPUTING 3Moumita Deb and Abantika Choudhury1.1 Introduction 31.2 Hybrid Cloud 51.2.1 Architecture 61.2.2 Why Hybrid Cloud is Required? 61.2.3 Business and Hybrid Cloud 71.2.4 Things to Remember When Deploying Hybrid Cloud 81.3 Comparison Among Different Hybrid Cloud Providers 91.3.1 Cloud Storage and Backup Benefits 111.3.2 Pros and Cons of Different Service Providers 111.3.2.1 AWS Outpost 121.3.2.2 Microsoft Azure Stack 121.3.2.3 Google Cloud Anthos 121.3.3 Review on Storage of the Providers 131.3.3.1 AWS Outpost Storage 131.3.3.2 Google Cloud Anthos Storage 131.3.4 Pricing 151.4 Hybrid Cloud in Education 151.5 Significance of Hybrid Cloud Post-Pandemic 151.6 Security in Hybrid Cloud 161.6.1 Role of Human Error in Cloud Security 181.6.2 Handling Security Challenges 181.7 Use of AI in Hybrid Cloud 191.8 Future Research Direction 211.9 Conclusion 22References 22xixv2 RECOGNITION OF DIFFERENTIALLY EXPRESSED GLYCAN STRUCTURE OF H1N1 VIRUS USING UNSUPERVISED LEARNING FRAMEWORK 25Shillpi Mishrra2.1 Introduction 252.2 Proposed Methodology 272.3 Result 282.3.1 Description of Datasets 292.3.2 Analysis of Result 292.3.3 Validation of Results 312.3.3.1 T-Test (Statistical Validation) 312.3.3.2 Statistical Validation 332.3.4 Glycan Cloud 372.4 Conclusions and Future Work 38References 393 SELECTION OF CERTAIN CANCER MEDIATING GENES USING A HYBRID MODEL LOGISTIC REGRESSION SUPPORTED BY PRINCIPAL COMPONENT ANALYSIS (PC-LR) 41Subir Hazra, Alia Nikhat Khurshid and Akriti3.1 Introduction 413.2 Related Methods 443.3 Methodology 463.3.1 Description 473.3.2 Flowchart 493.3.3 Algorithm 493.3.4 Interpretation of the Algorithm 503.3.5 Illustration 503.4 Result 513.4.1 Description of the Dataset 513.4.2 Result Analysis 513.4.3 Result Set Validation 523.5 Application in Cloud Domain 563.6 Conclusion 58References 59PART II: CLOUD SECURITY SYSTEMS USING MACHINE LEARNING TECHNIQUES 614 COST-EFFECTIVE VOICE-CONTROLLED REAL-TIME SMART INFORMATIVE INTERFACE DESIGN WITH GOOGLE ASSISTANCE TECHNOLOGY 63Soumen Santra, Partha Mukherjee and Arpan Deyasi4.1 Introduction 644.2 Home Automation System 654.2.1 Sensors 654.2.2 Protocols 664.2.3 Technologies 664.2.4 Advantages 674.2.5 Disadvantages 674.3 Literature Review 674.4 Role of Sensors and Microcontrollers in Smart Home Design 684.5 Motivation of the Project 704.6 Smart Informative and Command Accepting Interface 704.7 Data Flow Diagram 714.8 Components of Informative Interface 724.9 Results 734.9.1 Circuit Design 734.9.2 LDR Data 764.9.3 API Data 764.10 Conclusion 784.11 Future Scope 78References 785 SYMMETRIC KEY AND ARTIFICIAL NEURAL NETWORK WITH MEALY MACHINE: A NEOTERIC MODEL OF CRYPTOSYSTEM FOR CLOUD SECURITY 81Anirban Bhowmik, Sunil Karforma and Joydeep Dey5.1 Introduction 815.2 Literature Review 855.3 The Problem 865.4 Objectives and Contributions 865.5 Methodology 875.6 Results and Discussions 915.6.1 Statistical Analysis 935.6.2 Randomness Test of Key 945.6.3 Key Sensitivity Analysis 955.6.4 Security Analysis 965.6.5 Dataset Used on ANN 965.6.6 Comparisons 985.7 Conclusions 99References 996 AN EFFICIENT INTRUSION DETECTION SYSTEM ON VARIOUS DATASETS USING MACHINE LEARNING TECHNIQUES 103Debraj Chatterjee6.1 Introduction 1036.2 Motivation and Justification of the Proposed Work 1046.3 Terminology Related to IDS 1056.3.1 Network 1056.3.2 Network Traffic 1056.3.3 Intrusion 1066.3.4 Intrusion Detection System 1066.3.4.1 Various Types of IDS 1086.3.4.2 Working Methodology of IDS 1086.3.4.3 Characteristics of IDS 1096.3.4.4 Advantages of IDS 1106.3.4.5 Disadvantages of IDS 1116.3.5 Intrusion Prevention System (IPS) 1116.3.5.1 Network-Based Intrusion Prevention System (NIPS) 1116.3.5.2 Wireless Intrusion Prevention System (WIPS) 1126.3.5.3 Network Behavior Analysis (NBA) 1126.3.5.4 Host-Based Intrusion Prevention System (HIPS) 1126.3.6 Comparison of IPS With IDS/Relation Between IDS and IPS 1126.3.7 Different Methods of Evasion in Networks 1136.4 Intrusion Attacks on Cloud Environment 1146.5 Comparative Studies 1166.6 Proposed Methodology 1216.7 Result 1226.8 Conclusion and Future Scope 125References 1267 YOU ARE KNOWN BY YOUR MOOD: A TEXT-BASED SENTIMENT ANALYSIS FOR CLOUD SECURITY 129Abhijit Roy and Parthajit Roy7.1 Introduction 1297.2 Literature Review 1317.3 Essential Prerequisites 1337.3.1 Security Aspects 1337.3.2 Machine Learning Tools 1357.3.2.1 Naïve Bayes Classifier 1357.3.2.2 Artificial Neural Network 1367.4 Proposed Model 1367.5 Experimental Setup 1387.6 Results and Discussions 1397.7 Application in Cloud Security 1427.7.1 Ask an Intelligent Security Question 1427.7.2 Homomorphic Data Storage 1427.7.3 Information Diffusion 1447.8 Conclusion and Future Scope 144References 1458 THE STATE-OF-THE-ART IN ZERO-KNOWLEDGE AUTHENTICATION PROOF FOR CLOUD 149Priyanka Ghosh8.1 Introduction 1498.2 Attacks and Countermeasures 1538.2.1 Malware and Ransomware Breaches 1548.2.2 Prevention of Distributing Denial of Service 1548.2.3 Threat Detection 1548.3 Zero-Knowledge Proof 1548.4 Machine Learning for Cloud Computing 1568.4.1 Types of Learning Algorithms 1568.4.1.1 Supervised Learning 1568.4.1.2 Supervised Learning Approach 1568.4.1.3 Unsupervised Learning 1578.4.2 Application on Machine Learning for Cloud Computing 1578.4.2.1 Image Recognition 1578.4.2.2 Speech Recognition 1578.4.2.3 Medical Diagnosis 1588.4.2.4 Learning Associations 1588.4.2.5 Classification 1588.4.2.6 Prediction 1588.4.2.7 Extraction 1588.4.2.8 Regression 1588.4.2.9 Financial Services 1598.5 Zero-Knowledge Proof: Details 1598.5.1 Comparative Study 1598.5.1.1 Fiat-Shamir ZKP Protocol 1598.5.2 Diffie-Hellman Key Exchange Algorithm 1618.5.2.1 Discrete Logarithm Attack 1618.5.2.2 Man-in-the-Middle Attack 1628.5.3 ZKP Version 1 1628.5.4 ZKP Version 2 1628.5.5 Analysis 1648.5.6 Cloud Security Architecture 1668.5.7 Existing Cloud Computing Architectures 1678.5.8 Issues With Current Clouds 1678.6 Conclusion 168References 1699 A ROBUST APPROACH FOR EFFECTIVE SPAM DETECTION USING SUPERVISED LEARNING TECHNIQUES 171Amartya Chakraborty, Suvendu Chattaraj, Sangita Karmakar and Shillpi Mishrra9.1 Introduction 1719.2 Literature Review 1739.3 Motivation 1749.4 System Overview 1759.5 Data Description 1769.6 Data Processing 1769.7 Feature Extraction 1789.8 Learning Techniques Used 1799.8.1 Support Vector Machine 1799.8.2 k-Nearest Neighbors 1809.8.3 Decision Tree 1809.8.4 Convolutional Neural Network 1809.9 Experimental Setup 1829.10 Evaluation Metrics 1839.11 Experimental Results 1859.11.1 Observations in Comparison With State-of-the-Art 1879.12 Application in Cloud Architecture 1889.13 Conclusion 189References 19010 AN INTELLIGENT SYSTEM FOR SECURING NETWORK FROM INTRUSION DETECTION AND PREVENTION OF PHISHING ATTACK USING MACHINE LEARNING APPROACHES 193Sumit Banik, Sagar Banik and Anupam Mukherjee10.1 Introduction 19310.1.1 Types of Phishing 19510.1.1.1 Spear Phishing 19510.1.1.2 Whaling 19510.1.1.3 Catphishing and Catfishing 19510.1.1.4 Clone Phishing 19610.1.1.5 Voice Phishing 19610.1.2 Techniques of Phishing 19610.1.2.1 Link Manipulation 19610.1.2.2 Filter Evasion 19610.1.2.3 Website Forgery 19610.1.2.4 Covert Redirect 19710.2 Literature Review 19710.3 Materials and Methods 19910.3.1 Dataset and Attributes 19910.3.2 Proposed Methodology 19910.3.2.1 Logistic Regression 20210.3.2.2 Naïve Bayes 20210.3.2.3 Support Vector Machine 20310.3.2.4 Voting Classification 20310.4 Result Analysis 20410.4.1 Analysis of Different Parameters for ML Models 20410.4.2 Predictive Outcome Analysis in Phishing URLs Dataset 20510.4.3 Analysis of Performance Metrics 20610.4.4 Statistical Analysis of Results 2100.4.4. 1 ANOVA: Two-Factor Without Replication 21010.4.4.2 ANOVA: Single Factor 21010.5 Conclusion 210References 211PART III: CLOUD SECURITY ANALYSIS USING MACHINE LEARNING TECHNIQUES 21311 CLOUD SECURITY USING HONEYPOT NETWORK AND BLOCKCHAIN: A REVIEW 215Smarta Sangui * and Swarup Kr Ghosh11.1 Introduction 21511.2 Cloud Computing Overview 21611.2.1 Types of Cloud Computing Services 21611.2.1.1 Software as a Service 21611.2.1.2 Infrastructure as a Service 21811.2.1.3 Platform as a Service 21811.2.2 Deployment Models of Cloud Computing 21811.2.2.1 Public Cloud 21811.2.2.2 Private Cloud 21811.2.2.3 Community Cloud 21911.2.2.4 Hybrid Cloud 21911.2.3 Security Concerns in Cloud Computing 21911.2.3.1 Data Breaches 21911.2.3.2 Insufficient Change Control and Misconfiguration 21911.2.3.3 Lack of Strategy and Security Architecture 22011.2.3.4 Insufficient Identity, Credential, Access, and Key Management 22011.2.3.5 Account Hijacking 22011.2.3.6 Insider Threat 22011.2.3.7 Insecure Interfaces and APIs 22011.2.3.8 Weak Control Plane 22111.3 Honeypot System 22111.3.1 VM (Virtual Machine) as Honeypot in the Cloud 22111.3.2 Attack Sensing and Analyzing Framework 22211.3.3 A Fuzzy Technique Against Fingerprinting Attacks 22311.3.4 Detecting and Classifying Malicious Access 22411.3.5 A Bayesian Defense Model for Deceptive Attack 22411.3.6 Strategic Game Model for DDoS Attacks in Smart Grid 22611.4 Blockchain 22711.4.1 Blockchain-Based Encrypted Cloud Storage 22811.4.2 Cloud-Assisted EHR Sharing via Consortium Blockchain 22911.4.3 Blockchain-Secured Cloud Storage 23011.4.4 Blockchain and Edge Computing–Based Security Architecture 23011.4.5 Data Provenance Architecture in Cloud Ecosystem Using Blockchain 23111.6 Comparative Analysis 23311.7 Conclusion 233References 23412 MACHINE LEARNING–BASED SECURITY IN CLOUD DATABASE—A SURVEY 239Utsav Vora, Jayleena Mahato, Hrishav Dasgupta, Anand Kumar and Swarup Kr Ghosh12.1 Introduction 23912.2 Security Threats and Attacks 24112.3 Dataset Description 24412.3.1 NSL-KDD Dataset 24412.3.2 UNSW-NB15 Dataset 24412.4 Machine Learning for Cloud Security 24512.4.1 Supervised Learning Techniques 24512.4.1.1 Support Vector Machine 24512.4.1.2 Artificial Neural Network 24712.4.1.3 Deep Learning 24912.4.1.4 Random Forest 25012.4.2 Unsupervised Learning Techniques 25112.4.2.1 K-Means Clustering 25212.4.2.2 Fuzzy C-Means Clustering 25312.4.2.3 Expectation-Maximization Clustering 25312.4.2.4 Cuckoo Search With Particle Swarm Optimization (PSO) 25412.4.3 Hybrid Learning Techniques 25612.4.3.1 HIDCC: Hybrid Intrusion Detection Approach in Cloud Computing 25612.4.3.2 Clustering-Based Hybrid Model in Deep Learning Framework 25712.4.3.3 K-Nearest Neighbor–Based Fuzzy C-Means Mechanism 25812.4.3.4 K-Means Clustering Using Support Vector Machine 26012.4.3.5 K-Nearest Neighbor–Based Artificial Neural Network Mechanism 26012.4.3.6 Artificial Neural Network Fused With Support Vector Machine 26112.4.3.7 Particle Swarm Optimization–Based Probabilistic Neural Network 26112.5 Comparative Analysis 26212.6 Conclusion 264References 26713 MACHINE LEARNING ADVERSARIAL ATTACKS: A SURVEY BEYOND 271Chandni Magoo and Puneet Garg13.1 Introduction 27113.2 Adversarial Learning 27213.2.1 Concept 27213.3 Taxonomy of Adversarial Attacks 27313.3.1 Attacks Based on Knowledge 27313.3.1.1 Black Box Attack (Transferable Attack) 27313.3.1.2 White Box Attack 27413.3.2 Attacks Based on Goals 27513.3.2.1 Target Attacks 27513.3.2.2 Non-Target Attacks 27513.3.3 Attacks Based on Strategies 27513.3.3.1 Poisoning Attacks 27513.3.3.2 Evasion Attacks 27613.3.4 Textual-Based Attacks (NLP) 27613.3.4.1 Character Level Attacks 27613.3.4.2 Word-Level Attacks 27613.3.4.3 Sentence-Level Attacks 27613.4 Review of Adversarial Attack Methods 27613.4.1 L-bfgs 27713.4.2 Feedforward Derivation Attack (Jacobian Attack) 27713.4.3 Fast Gradient Sign Method 27813.4.4 Methods of Different Text-Based Adversarial Attacks 27813.4.5 Adversarial Attacks Methods Based on Language Models 28413.4.6 Adversarial Attacks on Recommender Systems 28413.4.6.1 Random Attack 28413.4.6.2 Average Attack 28613.4.6.3 Bandwagon Attack 28613.4.6.4 Reverse Bandwagon Attack 28613.5 Adversarial Attacks on Cloud-Based Platforms 28713.6 Conclusion 288References 28814 PROTOCOLS FOR CLOUD SECURITY 293Weijing You and Bo Chen14.1 Introduction 29314.2 System and Adversarial Model 29514.2.1 System Model 29514.2.2 Adversarial Model 29514.3 Protocols for Data Protection in Secure Cloud Computing 29614.3.1 Homomorphic Encryption 29714.3.2 Searchable Encryption 29814.3.3 Attribute-Based Encryption 29914.3.4 Secure Multi-Party Computation 30014.4 Protocols for Data Protection in Secure Cloud Storage 30114.4.1 Proofs of Encryption 30114.4.2 Secure Message-Locked Encryption 30314.4.3 Proofs of Storage 30314.4.4 Proofs of Ownership 30514.4.5 Proofs of Reliability 30614.5 Protocols for Secure Cloud Systems 30914.6 Protocols for Cloud Security in the Future 30914.7 Conclusion 310References 311PART IV: CASE STUDIES FOCUSED ON CLOUD SECURITY 31315 A STUDY ON GOOGLE CLOUD PLATFORM (GCP) AND ITS SECURITY 315Agniswar Roy, Abhik Banerjee and Navneet Bhardwaj15.1 Introduction 31515.1.1 Google Cloud Platform Current Market Holding 31615.1.1.1 The Forrester Wave 31715.1.1.2 Gartner Magic Quadrant 31715.1.2 Google Cloud Platform Work Distribution 31715.1.2.1 SaaS 31815.1.2.2 PaaS 31815.1.2.3 IaaS 31815.1.2.4 On-Premise 31815.2 Google Cloud Platform’s Security Features Basic Overview 31815.2.1 Physical Premises Security 31915.2.2 Hardware Security 31915.2.3 Inter-Service Security 31915.2.4 Data Security 32015.2.5 Internet Security 32015.2.6 In-Software Security 32015.2.7 End User Access Security 32115.3 Google Cloud Platform’s Architecture 32115.3.1 Geographic Zone 32115.3.2 Resource Management 32215.3.2.1 Iam 32215.3.2.2 Roles 32315.3.2.3 Billing 32315.4 Key Security Features 32415.4.1 Iap 32415.4.2 Compliance 32515.4.3 Policy Analyzer 32615.4.4 Security Command Center 32615.4.4.1 Standard Tier 32615.4.4.2 Premium Tier 32615.4.5 Data Loss Protection 32915.4.6 Key Management 32915.4.7 Secret Manager 33015.4.8 Monitoring 33015.5 Key Application Features 33015.5.1 Stackdriver (Currently Operations) 33015.5.1.1 Profiler 33015.5.1.2 Cloud Debugger 33015.5.1.3 Trace 33115.5.2 Network 33115.5.3 Virtual Machine Specifications 33215.5.4 Preemptible VMs 33215.6 Computation in Google Cloud Platform 33215.6.1 Compute Engine 33215.6.2 App Engine 33315.6.3 Container Engine 33315.6.4 Cloud Functions 33315.7 Storage in Google Cloud Platform 33315.8 Network in Google Cloud Platform 33415.9 Data in Google Cloud Platform 33415.10 Machine Learning in Google Cloud Platform 33515.11 Conclusion 335References 33716 CASE STUDY OF AZURE AND AZURE SECURITY PRACTICES 339Navneet Bhardwaj, Abhik Banerjee and Agniswar Roy16.1 Introduction 33916.1.1 Azure Current Market Holding 34016.1.2 The Forrester Wave 34016.1.3 Gartner Magic Quadrant 34016.2 Microsoft Azure—The Security Infrastructure 34116.2.1 Azure Security Features and Tools 34116.2.2 Network Security 34216.3 Data Encryption 34216.3.1 Data Encryption at Rest 34216.3.2 Data Encryption at Transit 34216.3.3 Asset and Inventory Management 34316.3.4 Azure Marketplace 34316.4 Azure Cloud Security Architecture 34416.4.1 Working 34416.4.2 Design Principles 34416.4.2.1 Alignment of Security Policies 34416.4.2.2 Building a Comprehensive Strategy 34516.4.2.3 Simplicity Driven 34516.4.2.4 Leveraging Native Controls 34516.4.2.5 Identification-Based Authentication 34516.4.2.6 Accountability 34516.4.2.7 Embracing Automation 34516.4.2.8 Stress on Information Protection 34516.4.2.9 Continuous Evaluation 34616.4.2.10 Skilled Workforce 34616.5 Azure Architecture 34616.5.1 Components 34616.5.1.1 Azure Api Gateway 34616.5.1.2 Azure Functions 34616.5.2 Services 34716.5.2.1 Azure Virtual Machine 34716.5.2.2 Blob Storage 34716.5.2.3 Azure Virtual Network 34816.5.2.4 Content Delivery Network 34816.5.2.5 Azure SQL Database 34916.6 Features of Azure 35016.6.1 Key Features 35016.6.1.1 Data Resiliency 35016.6.1.2 Data Security 35016.6.1.3 BCDR Integration 35016.6.1.4 Storage Management 35116.6.1.5 Single Pane View 35116.7 Common Azure Security Features 35116.7.1 Security Center 35116.7.2 Key Vault 35116.7.3 Azure Active Directory 35216.7.3.1 Application Management 35216.7.3.2 Conditional Access 35216.7.3.3 Device Identity Management 35216.7.3. 4 Identity Protection 35316.7.3.5 Azure Sentinel 35316.7.3.6 Privileged Identity Management 35416.7.3.7 Multifactor Authentication 35416.7.3.8 Single Sign On 35416.8 Conclusion 355References 35517 NUTANIX HYBRID CLOUD FROM SECURITY PERSPECTIVE 357Abhik Banerjee, Agniswar Roy, Amar Kalvikatte and Navneet Bhardwaj17.1 Introduction 35717.2 Growth of Nutanix 35817.2.1 Gartner Magic Quadrant 35817.2.2 The Forrester Wave 35817.2.3 Consumer Acquisition 35917.2.4 Revenue 35917.3 Introductory Concepts 36117.3.1 Plane Concepts 36117.3.1.1 Control Plane 36117.3.1.2 Data Plane 36117.3.2 Security Technical Implementation Guides 36217.3.3 SaltStack and SCMA 36217.4 Nutanix Hybrid Cloud 36217.4.1 Prism 36217.4.1.1 Prism Element 36317.4.1.2 Prism Central 36417.4.2 Acropolis 36517.4.2.1 Distributed Storage Fabric 36517.4.2.2 Ahv 36717.5 Reinforcing AHV and Controller VM 36717.6 Disaster Management and Recovery 36817.6.1 Protection Domains and Consistent Groups 36817.6.2 Nutanix DSF Replication of OpLog 36917.6.3 DSF Snapshots and VmQueisced Snapshot Service 37017.6.4 Nutanix Cerebro 37017.7 Security and Policy Management on Nutanix Hybrid Cloud 37117.7.1 Authentication on Nutanix 37217.7.2 Nutanix Data Encryption 37217.7.3 Security Policy Management 37317.7.3.1 Enforcing a Policy 37417.7.3.2 Priority of a Policy 37417.7.3.3 Automated Enforcement 37417.8 Network Security and Log Management 37417.8.1 Segmented and Unsegmented Network 37517.9 Conclusion 376References 376PART V: POLICY ASPECTS 37918 A DATA SCIENCE APPROACH BASED ON USER INTERACTIONS TO GENERATE ACCESS CONTROL POLICIES FOR LARGE COLLECTIONS OF DOCUMENTS 381Jedidiah Yanez-Sierra, Arturo Diaz-Perez and Victor Sosa-Sosa18.1 Introduction 38118.2 Related Work 38318.3 Network Science Theory 38418.4 Approach to Spread Policies Using Networks Science 38718.4.1 Finding the Most Relevant Spreaders 38818.4.1.1 Weighting Users 38918.4.1.2 Selecting the Top � Spreaders 39018.4.2 Assign and Spread the Access Control Policies 39018.4.2.1 Access Control Policies 39118.4.2.2 Horizontal Spreading 39118.4.2.3 Vertical Spreading (Bottom-Up) 39218.4.2.4 Policies Refinement 39518.4.3 Structural Complexity Analysis of CP-ABE Policies 39518.4.3.1 Assessing the WSC for ABE Policies 39618.4.3.2 Assessing the Policies Generated in the Spreading Process 39718.4.4 Effectiveness Analysis 39818.4.4.1 Evaluation Metrics 39918.4.4.2 Adjusting the Interaction Graph to Assess Policy Effectiveness 40018.4.4.3 Method to Complement the User Interactions (Synthetic Edges Generation) 40018.4.5 Measuring Policy Effectiveness in the User Interaction Graph 40318.4.5.1 Simple Node-Based Strategy 40318.4.5.2 Weighted Node-Based Strategy 40418.5 Evaluation 40518.5.1 Dataset Description 40518.5.2 Results of the Complexity Evaluation 40618.5.3 Effectiveness Results From the Real Edges 40718.5.4 Effectiveness Results Using Real and Synthetic Edges 40818.5.4.1 Results of the Effectiveness Metrics for the Enhanced G + Graph 41018.6 Conclusions 413References 41419 AI, ML, & ROBOTICS IN ISCHOOLS: AN ACADEMIC ANALYSIS FOR AN INTELLIGENT SOCIETAL SYSTEMS 417P. K. Paul19.1 Introduction 41719.2 Objective 41919.3 Methodology 42019.3.1 iSchools, Technologies, and Artificial Intelligence, ML, and Robotics 42019.4 Artificial Intelligence, ML, and Robotics: An Overview 42719.5 Artificial Intelligence, ML, and Robotics as an Academic Program: A Case on iSchools—North American Region 42819.6 Suggestions 43119.7 Motivation and Future Works 43519.8 Conclusion 435References 436Index 439
Handbuch Infrastructure as Code
CLOUD-INFRASTRUKTUREN ERFOLGREICH AUTOMATISIEREN: STRATEGIEN FÜR DIE PRAXIS * Mithilfe von Patterns und Antipatterns Automatisierung verstehen und erfolgreich umsetzen * Pseudocode-Beispiele veranschaulichen die konkrete Umsetzung * Diese Auflage beschreibt neben dem Managen von Servern jetzt auch komplexe Container-Plattformen Kief Morris von ThoughtWorks zeigt in diesem Praxisbuch, wie Sie die von DevOps-Teams entwickelte Prinzipien, Praktiken und Patterns effektiv verwenden, um in der Cloud sicher und flexibel Infrastruktur zu managen. Es vermittelt, wie nicht nur Server, sondern auch komplexe Container-Plattformen (Stacks) aufgesetzt werden. Sie erfahren, wie sie mithilfe von Cloud- und Automatisierungstechnologien Änderungen einfach, sicher und schnell vornehmen. Sie lernen, wie Sie nahezu alles als Code definieren und setzen Praktiken aus dem Softwaredesign ein, um ein System aus kleinen, lose gekoppelten Elementen aufzubauen. Zielgruppen sind Mitarbeiterinnen und Mitarbeiter in der Systemadministration, Infrastruktur-Entwicklung, Softwareentwicklung und Architektur.
Beginning Java 17 Fundamentals
Learn the fundamentals of the Java 17 LTS or Java Standard Edition version 17 Long Term Support release, including basic programming concepts and the object-oriented fundamentals necessary at all levels of Java development. Authors Kishori Sharan and Adam L. Davis walk you through writing your first Java program step-by-step. Armed with that practical experience, you'll be ready to learn the core of the Java language. Beginning Java 17 Fundamentals provides over 90 diagrams and 240 complete programs to help you learn the topics faster.While this book teaches you the basics, it also has been revised to include the latest from Java 17 including the following: value types (records), immutable objects with an efficient memory layout; local variable type inference (var); pattern matching, a mechanism for testing and deconstructing values; sealed types, a mechanism for declaring all possible subclasses of a class; multiline text values; and switch expressions.The book continues with a series of foundation topics, including using data types, working with operators, and writing statements in Java. These basics lead onto the heart of the Java language: object-oriented programming. By learning topics such as classes, objects, interfaces, and inheritance you'll have a good understanding of Java's object-oriented model. The final collection of topics takes what you've learned and turns you into a real Java programmer.You'll see how to take the power of object-oriented programming and write programs that can handle errors and exceptions, process strings and dates, format data, and work with arrays to manipulate data.WHAT YOU WILL LEARN* Write your first Java programs with emphasis on learning object-oriented programming* How to work with switch expressions, value types (records), local variable type inference, pattern matching switch and more from Java 17* Handle exceptions, assertions, strings and dates, and object formatting* Learn about how to define and use modules* Dive in depth into classes, interfaces, and inheritance in Java* Use regular expressions* Take advantage of the JShell REPL toolWHO THIS BOOK IS FORThose who are new to Java programming, who may have some or even no prior programming experience.KISHORI SHARAN has earned a Master of Science in Computer Information Systems degree from Troy State University, Alabama. He is a Sun Certified Java 2 programmer. He has vast experience in providing training to professional developers in Java, JSP, EJB, and Web technology. He possesses over ten years of experience in implementing enterprise level Java application.ADAM L. DAVIS makes software. He’s spent many years developing in Java (since Java 1.2) and has enjoyed using Spring and Hibernate for more than a decade. Since 2006 he’s been using Groovy, Grails, HTML, CSS, and JavaScript, in addition to Java, to create SaaS web applications that help track finances for large institutions (among other things). Adam has a master’s and a bachelor’s degree in Computer Science from Georgia Tech. He is also the author of Reactive Streams in Java (Apress, 2019), Learning Groovy 3, Second Edition (Apress, 2019) and Modern Programming Made Easy, Second Edition (Apress, 2020).1. Programming Concepts2. Setting Up the Environment3. Writing Java Programs4. Data Types5. Operators6. Statements7. Classes and Objects8. Methods9. Constructors10. Modules11. Object and Objects Classes12. Wrapper Classes13. Execution Handling14. Assertions15. Strings16. Dates and Times17. Formatting Data18. Regular Expressions19. Arrays20. Inheritance21. Interfaces22. Enum Types23. Java ShellAppendix A: Character EncodingsAppendix B: Documentation Comments
Spring REST
Design and develop Java-based RESTful APIs using the latest versions of the Spring MVC and Spring Boot frameworks. This book walks you through the process of designing and building a REST application while delving into design principles and best practices for versioning, security, documentation, error handling, paging, and sorting.Spring REST provides a brief introduction to REST, HTTP, and web infrastructure. You will learn about several Spring projects such as Spring Boot, Spring MVC, Spring Data JPA, and Spring Security, and the role they play in simplifying REST application development. You will learn how to build clients that consume REST services. Finally, you will learn how to use the Spring MVC test framework to unit test and integration test your REST API.After reading this book, you will come away with all the skills to build sophisticated REST applications using Spring technologies.WHAT YOU WILL LEARN* Build Java-based microservices, native cloud, or any applications using Spring REST* Employ Spring MVC and RESTful Spring* Build a QuickPoll application example* Document REST services, as well as versioning, paging, and sorting* Test, handle errors and secure your applicationWHO THIS BOOK IS FORIntermediate Java programmers with at least some prior experience with Spring and web/cloud application development.BALAJI VARANASI is a software development manager and technology entrepreneur. He has over 13 years of experience architecting and developing Java/.Net applications and, more recently, iPhone apps. During this period he has worked in the areas of security, web accessibility, search, and enterprise portals. He has a Master s Degree in Computer Science and serves as adjunct faculty, teaching programming and information system courses. When not programming, he enjoys spending time with his lovely wife in Salt Lake City, Utah.MAXIM BARTKOV is a staff engineer with more than seven years of commercial experience in Java. Maxim specializes in building architecture for high-load systems. He is skilled in the development of Distributed High-Load Systems, Microservice architecture, Spring Framework, System Architecture, and In-Memory Data Grid (IMDG). In his spare time, he writes articles for the Java community.1. Introduction to REST2. Spring MVC & Spring Boot Primer3. RESTful Spring4. Beginning the QuickPoll Application5. Error Handling6. Documenting REST Services7. Versioning, Paging, and Sorting8. Security9. Clients and Testing10. HATEOASA. Installing cURL on Windows
Mastering Excel Through Projects
Master Excel in less than two weeks with this unique project-based book! Let’s face it, we all master skills in our own way, but building a soup-to-nuts project is one of the best ways to make learning stick and get up to speed quickly. Whether you are just getting started with Excel or are an experienced user, this book will elevate your knowledge and skills. For a beginner, the micro examples in each chapter will warm you up before you dive into the projects. For experienced users, the projects, especially those with table setup considerations, will help you become more creative in your interactions with Excel.Readers will benefit from building eight unique projects, each covering a different topic, including a word game, a food nutrition ranking, a payroll (tax withholding) calculation, an encryption, a two-way table, a Kaplan-Meier analysis, a data analysis via a pivot table and the K-means Clustering data mining method. Through these projects, you will experience firsthand how Excel skills are organized together to accomplish tasks that sound complex and daunting when first described.Get started with a word game which asks users to find English words that amount to exactly 100 points, with each letter of the alphabet assigned a point 1, 2, 3, … 26, respectively. You will disassemble a word into letters and then sum up their points, and then take it one step further, contemplating how to make the completed Excel worksheet more user friendly and completely automated. Increasingly challenging tasks like this example build on what you have learned and increase your confidence along the way, ensuring your mastery of Excel.WHAT YOU WILL LEARN* Gain confidence to tackle a challenging Excel-related mission, even those that seem impossible* Become skilled in the creative uses of Excel formulas and functions and other built-in features* Appreciate the art of refining worksheets to maximize automation* Understand the value of treating each worksheet as a unique productWHO THIS BOOK IS FORPeople who are interested in learning Excel as quickly and efficiently as possible. While Excel beginners and intermediate users are the primary audience, experienced Excel users might also discover new skills and ways of working with Excel.HONG ZHOU is a professor of computer science and mathematics at the University of Saint Joseph in Connecticut. Before returning to school for his doctoral degree, Dr. Zhou worked as a Java developer in Silicon Valley. Since 2004, Dr. Zhou has been teaching various courses in computer science, data science, mathematics, statistics, and informatics. His major research interests include data mining, bioinformatics, software agents, and blockchain. Dr. Zhou became interested in Excel through teaching computer skills and using them for research purposes; for example, applying Excel in teaching data mining, encryption, and health informatics. He also enjoys applying his Excel skills to help colleagues in their research projects.Chapter 1: Master Excel through ProjectsChapter 2: Food Nutrition RankingChapter 3: Payroll CalculationChapter 4: Public and Private Key CryptographyChapter 5: Two-Way Table and Chi-Square TestChapter 6: Kaplan-Meier AnalysisChapter 7: PivotTable Data AnalysisChapter 8: K-means Clustering and Iterative Calculation
Tableau for Business Users
Learn Tableau by working through concrete examples and issues that you are likely to face in your day-to-day work.Author Shankar Arul starts by teaching you the fundamentals of data analytics before moving on to the core concepts of Tableau. You will learn how to create calculated fields, and about the currently available calculation functionalities in Tableau, including Basic Expressions, Level of Detail (LOD) Expressions, and Table Calculations. As the book progresses, you’ll be walked through comparisons and trend calculations using tables. A concluding chapter on dashboarding will show you how to build actionable dashboards to communicate analysis and visualizations. You’ll also see how Tableau can complement and communicate with Excel.After completing this book, you will be ready to tackle the challenges of data analytics using Tableau without getting bogged down by the technicalities of the tool.WHAT WILL YOU LEARNMaster the core concepts of Tableau * Automate and simplify dashboards to help business users* Understand the basics of data visualization techniques* Leverage powerful features such as parameters, table calculations, level of detail expressions, and more WHO IS THIS BOOK FORBusiness analysts, data analysts, as well as financial analysts.Shankar Arul holds a Masters in industrial engineering from Virginia Tech, USA and an MBA in Finance from ESSEC, France. He has more than 15 years of hands-on experience in the field of Data Visualization and data science. Having faced the frustrations of Business users in data-driven decision making, in companies such as BNP, Apple, Groupon and Kering, he decided to enable the Business users with the power of data visualization and Tableau through this book. Chapter 1: IntroductionCHAPTER GOAL: THE NEED FOR DATA VISUALIZATION TOOLS SUCH AS TABLEAU FOR BUSINESS USERSNO OF PAGES 4SUB -TOPICS1. Why visualize data2. Who is this book for3. How is this book differentChapter 2: Installation and SetupChapter Goal: Onboard readers with the setup of tableau.NO OF PAGES: 3SUB - TOPICS1. Installation of tableau2. Data sources required for the exercisesChapter 3: Fundamentals of DataCHAPTER GOAL: GENTLE INTRODUCTION TO THE FUNDAMENTALS OF DATANo of pages : 6SUB - TOPICS:1. Data types2. Data sources3. Data preparation4. Converting business questions to the language of dataChapter 4: The Crux of TableauCHAPTER GOAL: DISTILLATION OF THE CORE CONCEPTS OF TABLEAUNO OF PAGES: 17SUB - TOPICS:1. 4 Building pillars2. Putting it all together3. Show me3. Sheets & DashboardsChapter 5: CalculationsCHAPTER GOAL: ENRICH THE DATA BY CREATING CALCULATED FIELDSNo of pages: 16SUB - TOPICS:1. Grouping Values2. Calculated Fields3. Row level, Aggreation & Dis-Aggregation4. Bringin more data5. Importance of Cardinality6. Data ModelingChapter 6: Tables & Table CalculationsChapter Goal: Comparisons and trend calculations through tablesNO OF PAGES: 15SUB - TOPICS:1. Show me or start from scratch ?2. Table totals3. Table calculations4. SortingChapter 7: Advanced TipsCHAPTER GOAL: ADVANCED FUNCTIONALITIES OF TABLEAUNo of pages: 15SUB - TOPICS:1. Dynamic Inputs - Parameters2. Top 10/20/50 filters3. Dual Axis4. Shapes & Icons5. Level of detail calculations6. Reference lines & forecast7. Order of operationsChapter 8: DashboardsCHAPTER GOAL: BRING IT ALL TOGETHER BY ENABLING USERS TO BUILD INTERACTIVE DASHBOARDSNO OF PAGES: 9SUB - TOPICS:1. Less I more2. Dashboards: A view from 10000ft3. Fit & Layout4. Filters & Interaction
Beginning React and Firebase
Use React with Firebase to build four beginner-friendly apps. A lot of React tutorials out there today only cover basic web apps, but with additional features the web apps included in this book can be converted into fully scaled startups.You will start with the basics: learn to deploy a React app with Firebase hosting. Next, you will learn to create a fully functional "ToDo" app that will use Firebase database to store a list action items. You will also learn to create a "Stories" app, in which you can show short vertical videos, and a document storage app. Here, we will be able to log in using Google Authentication, and will learn to store files in the app using Firebase storage. Lastly, you will create a career social media app. Your users will be able to log in using email and password authentication. You will learn to use Redux in this project.While creating these web apps, you will employ multiple concepts, including React hooks, React components, and how to use Material UI. You will learn to use Firebase to host your database, as well as hosting your app. With these projects in your portfolio you'll be ready to take your developer skills to the next level.WHAT YOU'LL LEARN* Use Firebase’s powerful services, and how to connect Firebase with React* Explore the React ecosystem, including Redux and React hooks* Work with MaterialUI, the popular React UI framework* Understand how to use Google Authentication techniques in your sites* Deploy all sites using simple Firebase hostingWHO THIS BOOK IS FORDevelopers at the beginning of their career, or anyone who wants to take their React skills to the next level.Nabendu Biswas is a full stack JavaScript developer who has been working in the IT industry for the past 16 years and has worked for some of the world’s top development firms and investment banks. He is a passionate tech blogger who publishes on dev.to and medium.com and on thewebdev.tech. He is an all-round nerd, passionate about everything JavaScript, React and Gatsby. You can find him on Twitter @nabendu82.Chapter One: Getting Started with React and Firebase· Introduction to firebase· Creating an account in firebase· Setting up hosting from firebase console· Deploying a simple ReactJS project from terminalChapter Two: TODO App· Firebase initial setup· React basic setup· Code to show local Todo list· Using Material UI in project· Setting up firebase database· Integrating firebase database with React· Implementing Edit and Delete feature· Deploying and hosting through firebaseChapter Three: Stories App· Firebase initial setup· React basic setup· Adding Short videos to site· Adding snap feature to video· Setting up firebase database· Integrating firebase database with React· Deploying and hosting through firebaseChapter Four: Storage App· Firebase initial setup· React basic setup· Creating Header and Sidebar component· Setting up firebase database· Integrating firebase database with React· Using firebase storage to upload files· Adding Google Authentication· Deploying and hosting through firebaseChapter Five: Social Media App· Firebase initial setup· React basic setup· Create the Header· Create the Sidebar· Create the Feed component· Setting up firebase database· Integrating firebase database with React· Adding Redux to project· Adding email/password authentication· Deploying and hosting through firebase
Implementing Always On VPN
Implement and support Windows 10 Always On VPN, the successor to Microsoft's popular DirectAccess. This book teaches you everything you need to know to test and adopt the technology at your organization that is widely deployed around the world.The book starts with an introduction to Always On VPN and discusses fundamental concepts and use cases to compare and contrast it with DirectAccess. You will learn the prerequisites required for implementation and deployment scenarios. The book presents the details of recommended VPN protocols, client IP address assignment, and firewall requirements. Also covered is how to configure Routing and Remote Access Service (RRAS) along with security and performance optimizations. The Configuration Service Provider (CSP) is discussed, and you will go through provisioning Always On VPN to Windows 10 clients using PowerShell and XML as well as Microsoft Intune. Details about advanced client configuration and integration with Azure security services are included. You will know how to implement Always On VPN infrastructure in a redundant and highly available (HA) configuration, and guidance for ongoing system maintenance and operational support for the VPN and NPS infrastructure is provided. And you will know how to diagnose and troubleshoot common issues with Always On VPN.After reading this book, you will be able to plan, design, and implement a Windows 10 Always On VPN solution to meet your specific requirements.WHAT WILL YOU LEARN* Prepare your infrastructure to support Windows 10 Always On VPN on premises or in the cloud* Provision and manage Always On VPN clients using modern management methods such as Intune* Understand advanced integration concepts for extending functionality with Microsoft Azure* Troubleshoot and resolve common configuration and operational errors for your VPNWHO THIS BOOK IS FORIT professionals and technology administrators for organizations of all sizesRICHARD HICKS is the founder and principal consultant at Richard M. Hicks Consulting, Inc. He is a widely recognized enterprise mobility and security infrastructure expert with more than 25 years of experience implementing secure remote access and Public Key Infrastructure (PKI) solutions for organizations around the world. Richard is a former Microsoft Most Valuable Professional (MVP 2009-2019) and is active in the online community, sharing his knowledge and experience with IT professionals on his blog and through various social media channels. Visit his web site https://www.richardhicks.com/ or connect with him on Twitter @richardhicks. CHAPTER 1 – ALWAYS ON VPN OVERVIEWo This chapter will introduce Always On VPN as a technology and cover the concepts and underlying technologies used by the solution. We will discuss the high-level use cases and compare with its predecessor, DirectAccess.CHAPTER 2 – PLAN AN ALWAYS ON VPN DEPLOYMENTo In this chapter we will dive more deeply into the implementation prerequisites. We will identify infrastructure requirements, discuss networking and authentication requirements, and learn about various deployment scenarios. Guidance will be provided for certificate services configuration and networking models will be covered. Details about VPN protocols, client IP address assignment, and firewall requirements will also be covered.CHAPTER 3 – CONFIGURE WINDOWS SERVER FOR ALWAYS ON VPNIn this chapter, configuring Windows Server Routing and Remote Access Service (RRAS) will be covered in detail. In addition, we will cover Remote Access Service (RRAS) configuration and perform server security and performance optimizations.CHAPTER 4 – PROVISION ALWAYS ON VPN CLIENTSThis chapter will provide guidance for provisioning Always On VPN to Windows 10 clients. The Configuration Service Provider (CSP) mode will be discussed, and readers will learn to create a configuration XML file and provision it locally using PowerShell. In addition, Intune deployment using custom XML and native VPN profiles will be covered.CHAPTER 5 – CLOUD DEPLOYMENTSo For those organizations deploying infrastructure in a public cloud, this chapter will outline how to deploy an Always On VPN infrastructure in Microsoft Azure. Deploying RRAS in Azure and leveraging native cloud VPN infrastructure such as Azure Virtual Network Gateway and Azure Virtual WAN will be discussed.CHAPTER 6 – AZURE INTEGRATIONo This chapter will provide guidance for advanced client configuration and integration with Azure security services. Azure MFA integration with on-premises NPS will be covered in detail. Also, Azure Conditional Access will be covered.CHAPTER 7 – HIGH AVAILABILITYo This chapter will describe in detail how to implement an Always On VPN infrastructure in a redundant and highly available configuration. Locally redundancy NPS and VPN servers will be covered. Guidance for multisite deployment with geographic redundancy for VPN servers will be included.CHAPTER 8 – MONITOR AND REPORTo This chapter will cover ongoing system maintenance and operational support for the VPN and NPS infrastructure. It will include guidance for ensuring automatic certificate management, how to renew certificates that cannot be managed automatically, how to find logging details, and which monitoring tools can be effective for daily operation.CHAPTER 9 – TROUBLESHOOTINGo This chapter will provide detailed guidance for troubleshooting and resolving common configuration and operational errors for the VPN and authentication infrastructure, from both the client and server perspective. Common failure scenarios will be covered, and detailed resolution steps will be provided.CHAPTER 10 – MIGRATE FROM DIRECTACCESS TO ALWAYS ON VPNo Always On VPN is most commonly deployed to replace existing DirectAccess infrastructure. In this chapter I’ll provide guidance and share experience for migrating from DirectAccess to Always On VPN seamlessly and without disruption.
PowerShell Fast Track
Create complex scripts in PowerShell and learn how to connect them to cloud services like Azure and Azure AD. This book will help you learn PowerShell by providing small “cheat” snippets that you can combine to write efficient and effective scripts.PowerShell Fast Track starts with the basics of PowerShell before moving on to discuss functions like date and logs, along with concepts such as inputs for your scripts. Author Vikas Sukhija then walks you through interactive input and Snapins modules, where you will learn GUI button prompts and how to import sessions. He’ll then show you how to report errors through email and log errors to a text file. Reporting CSV (Comma Separate Value) is discussed next, followed by a demonstration of miscellaneous functions, including how to connect your PowerShell scripts with Azure, SharePoint, Teams and other services. As you progress further, you’ll see how PowerShell provides powerful features for automation that can be leveraged for managing your Teams workload. Finally, using practical examples, you will learn how to implement and create scripts for day-to-day usage.After reading this book, you will be able to hit the ground running and use PowerShell’s powerful features in your own work.WHAT WILL YOU LEARN:* Utilize code Snippets to perform practical tasks* Combine the code to create more complex scripts.* Logging and reporting* Connect to various products such as Exchange, SharePoint, Teams, and AzureADWHO IS THIS BOOK FOR:System administratorsVikas Sukhija has over a decade of IT infrastructure experience with expertise in Messaging, Collaboration & IT automations utilizing PowerShell, PowerApps , Power Automate and other tools. He is currently working as a Global Director at Golden Five Consulting in Canada. He is also a Blogger, Architect, Microsoft MVP and is known by the name TechWizard. As an experienced professional he is assisting small to large enterprises in architecting, implementing, and automating Microsoft 365 and Azure. CHAPTER 1. POWERSHELL BASICSVariables & Printing If Else/ switch Conditional / Logical Operators Loops For –Loop While –Loop FunctionsCHAPTER 2. DATE & LOGSDefine LogsFirst day & Last day of MonthMidnight Create Folders based on Date Recycle Logs Progress barCHAPTER 3. INPUT TO YOUR SCRIPTSImport CSV Import from text file Input from ArrayCHAPTER 4. INTERACTIVE INPUTRead-host Parameters GUI Button PromptCHAPTER 5. ADDING SNAP INS/ MODULESPowerShell Snapins Modules Import Session Example:CHAPTER 6. SENDING EMAILCHAPTER 7. ERROR REPORTINGReporting Error thru EmailLogging Everything including Error Logging error to Text fileCHAPTER 8. REPORTING CSVReport HTML ReportingCHAPTER 9. MISCELLANEOUS KEYWORDSSplit ReplaceSelect-StringCompare-ObjectCHAPTER 10. PRODUCT EXAMPLES (DAILY USE)Microsoft Exchange Clean Database so that mailboxes appear in disconnected stateFind Disconnected Mailboxes Clustered Mailbox Status (2007)Extract Message accept from Active Sync Stats Message Tracking Search mailbox / Delete Messages Exchange Quota Report Set Quota Active Directory Export Group members Set values for Ad attributes Export Active Directory attributes Add members to the group from text file Remove members to the group from text file Office 365 Exchange Online Mailbox Report Exchange Online Message Tracking Searching Unified Log11. Appendix
Computers For Seniors For Dummies
A SIMPLE GUIDE TO COMPUTERS THAT'LL SHOW YOU WHAT ALL THE FUSS IS ABOUTMost people new to computers find them a little intimidating at first. But with the right guidance, even a total novice can be sending email and banking online in no time at all. Computers For Seniors For Dummies is your must-have computing companion, full of crystal clear, step-by-step instructions for accessing websites, opening and using programs, and keeping yourself safe from viruses and hackers. And unlike the confusing "tips" from your son-in-law, you can rely on the For Dummies brand to deliver advice that actually works! Whether you've set up your computer and are ready to start using it or it's still sitting in the box, this book walks you through each and every step you need to take to connect with your family or share your photos with your friends on Facebook. It'll also show you how to:* Research topics you're interested in on the web while steering clear of malicious websites and emails that can harm your computer* Shop online in a way that keeps your credit card info secure* Find recipes, diet tips, the latest news, or your favorite TV showComputers For Seniors For Dummies is your one-stop resource for taking control of your computer, transforming it from an expensive paperweight into the most useful gadget in your home. Filled with easy-on-the-eyes type and tons of explanatory images, this is the book that will finally get you up to speed on personal computing. FAITHE WEMPEN is a computer and information technology instructor at Indiana University Purdue University at Indianapolis. She designs online technology courses for corporate clients and is the author of over 150 books on computer hardware and software.Introduction 1PART 1: GET GOING! 5Chapter 1: Buying a Computer 7Chapter 2: Setting Up Your Computer 33Chapter 3: Buying and Setting Up a Printer 61PART 2: GETTING UP TO SPEED WITH WINDOWS 75Chapter 4: Working with Apps in Windows 77Chapter 5: Six Great Apps that Come with Windows 107Chapter 6: Managing Your Personal Files 127Chapter 7: Making Windows Your Own 153PART 3: GOING ONLINE 175Chapter 8: Getting Connected to the Internet 177Chapter 9: Browsing the Web 191Chapter 10: Staying Safe While Online 213Chapter 11: Keeping in Touch with Mail 233Chapter 12: Working in the Cloud 253Chapter 13: Connecting with People Online 269PART 4: HAVING FUN 289Chapter 14: Let’s Play a Game! 291Chapter 15: Creating and Viewing Digital Photos and Videos 305Chapter 16: Listening to Music on Your PC 325PART 5: WINDOWS TOOLKIT 341Chapter 17: Working with Networks 343Chapter 18: Protecting Windows 361Chapter 19: Maintaining Windows 373Index 389
Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms
COGNITIVE BEHAVIOR AND HUMAN COMPUTER INTERACTION BASED ON MACHINE LEARNING ALGORITHMSTHE OBJECTIVE OF THIS BOOK IS TO PROVIDE THE MOST RELEVANT INFORMATION ON HUMAN-COMPUTER INTERACTION TO ACADEMICS, RESEARCHERS, AND STUDENTS AND FOR THOSE FROM INDUSTRY WHO WISH TO KNOW MORE ABOUT THE REAL-TIME APPLICATION OF USER INTERFACE DESIGN.Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas. This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come. AUDIENCE: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics. SANDEEP KUMAR, PHD is a Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published more than 100 research papers in various international/national journals and 6 patents. He has been awarded the “Best Excellence Award” in New Delhi, 2019.ROHIT RAJA, PHD is an associate professor in the IT Department at the Guru Ghasidas, Vishwavidyalaya, Bilaspur (Central University-CG). He gained his PhD in Computer Science and Engineering in 2016 from C. V. Raman University India. He has filed successfully 10 (9 national + 1 international) patents and published more than 80 research papers in various international/national journals. SHRIKANT TIWARI, PHD is an assistant professor in the Department of Computer Science & Engineering (CSE) at Shri Shankaracharya Technical Campus, Junwani, Bhilai, Distt. Chattisgarh, India. He received his PhD from the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012. SHILPA RANI, PHD is an assistant professor in the Department of Computer Science & Engineering, Neil Gogte Institute of Technology, Hyderabad, India. Preface xv1 COGNITIVE BEHAVIOR: DIFFERENT HUMAN-COMPUTER INTERACTION TYPES 1S. Venkata Achyuth Rao, Sandeep Kumar and GVRK Acharyulu1.1 Introduction: Cognitive Models and Human-Computer User Interface Management Systems 21.1.1 Interactive User Behavior Predicting Systems 21.1.2 Adaptive Interaction Observatory Changing Systems 31.1.3 Group Interaction Model Building Systems 41.1.4 Human-Computer User Interface Management Systems 51.1.5 Different Types of Human-Computer User Interfaces 51.1.6 The Role of User Interface Management Systems 61.1.7 Basic Cognitive Behavioral Elements of Human- Computer User Interface Management Systems 71.2 Cognitive Modeling: Decision Processing User Interacting Device System (DPUIDS) 91.2.1 Cognitive Modeling Automation of Decision Process Interactive Device Example 91.2.2 Cognitive Modeling Process in the Visualization Decision Processing User Interactive Device System 111.3 Cognitive Modeling: Decision Support User Interactive Device Systems (DSUIDS) 121.3.1 The Core Artifacts of the Cognitive Modeling of User Interaction 131.3.2 Supporting Cognitive Model for Interaction Decision Supportive Mechanism 131.3.3 Representational Uses of Cognitive Modeling for Decision Support User Interactive Device Systems 141.4 Cognitive Modeling: Management Information User Interactive Device System (MIUIDS) 171.5 Cognitive Modeling: Environment Role With User Interactive Device Systems 191.6 Conclusion and Scope 20References 202 CLASSIFICATION OF HCI AND ISSUES AND CHALLENGES IN SMART HOME HCI IMPLEMENTATION 23Pramod Vishwakarma, Vijay Kumar Soni, Gaurav Srivastav and Abhishek Jain2.1 Introduction 232.2 Literature Review of Human-Computer Interfaces 262.2.1 Overview of Communication Styles and Interfaces 332.2.2 Input/Output 372.2.3 Older Grown-Ups 372.2.4 Cognitive Incapacities 382.3 Programming: Convenience and Gadget Explicit Substance 402.4 Equipment: BCI and Proxemic Associations 412.4.1 Brain-Computer Interfaces 412.4.2 Ubiquitous Figuring—Proxemic Cooperations 432.4.3 Other Gadget-Related Angles 442.5 CHI for Current Smart Homes 452.5.1 Smart Home for Healthcare 452.5.2 Savvy Home for Energy Efficiency 462.5.3 Interface Design and Human-Computer Interaction 462.5.4 A Summary of Status 482.6 Four Approaches to Improve HCI and UX 482.6.1 Productive General Control Panel 492.6.2 Compelling User Interface 502.6.3 Variable Accessibility 522.6.4 Secure Privacy 542.7 Conclusion and Discussion 55References 563 TEACHING-LEARNING PROCESS AND BRAIN-COMPUTER INTERACTION USING ICT TOOLS 63Rohit Raja, Neelam Sahu and Sumati Pathak3.1 The Concept of Teaching 643.2 The Concept of Learning 653.2.1 Deficient Visual Perception in a Student 673.2.2 Proper Eye Care (Vision Management) 683.2.3 Proper Ear Care (Hearing Management) 683.2.4 Proper Mind Care (Psychological Management) 693.3 The Concept of Teaching-Learning Process 703.4 Use of ICT Tools in Teaching-Learning Process 763.4.1 Digital Resources as ICT Tools 773.4.2 Special ICT Tools for Capacity Building of Students and Teachers 773.4.2.1 CogniFit 773.4.2.2 Brain-Computer Interface 783.5 Conclusion 80References 814 DENOISING OF DIGITAL IMAGES USING WAVELET-BASED THRESHOLDING TECHNIQUES: A COMPARISON 85Devanand Bhonsle4.1 Introduction 854.2 Literature Survey 874.3 Theoretical Analysis 894.3.1 Wavelet Transform 904.3.1.1 Continuous Wavelet Transform 904.3.1.2 Discrete Wavelet Transform 914.3.1.3 Dual-Tree Complex Wavelet Transform 944.3.2 Types of Thresholding 954.3.2.1 Hard Thresholding 964.3.2.2 Soft Thresholding 964.3.2.3 Thresholding Techniques 974.3.3 Performance Evaluation Parameters 1024.3.3.1 Mean Squared Error 1024.3.3.2 Peak Signal–to-Noise Ratio 1034.3.3.3 Structural Similarity Index Matrix 1034.4 Methodology 1034.5 Results and Discussion 1054.6 Conclusions 112References 1125 SMART VIRTUAL REALITY–BASED GAZE-PERCEPTIVE COMMON COMMUNICATION SYSTEM FOR CHILDREN WITH AUTISM SPECTRUM DISORDER 117Karunanithi Praveen Kumar and Perumal Sivanesan5.1 Need for Focus on Advancement of ASD Intervention Systems 1185.2 Computer and Virtual Reality–Based Intervention Systems 1185.3 Why Eye Physiology and Viewing Pattern Pose Advantage for Affect Recognition of Children With ASD 1205.4 Potential Advantages of Applying the Proposed Adaptive Response Technology to Autism Intervention 1215.5 Issue 1225.6 Global Status 1235.7 VR and Adaptive Skills 1245.8 VR for Empowering Play Skills 1255.9 VR for Encouraging Social Skills 1255.10 Public Status 1265.11 Importance 1275.12 Achievability of VR-Based Social Interaction to Cause Variation in Viewing Pattern of Youngsters With ASD 1285.13 Achievability of VR-Based Social Interaction to Cause Variety in Eye Physiological Indices for Kids With ASD 1295.14 Possibility of VR-Based Social Interaction to Cause Variations in the Anxiety Level for Youngsters With ASD 132References 1336 CONSTRUCTION AND RECONSTRUCTION OF 3D FACIAL AND WIREFRAME MODEL USING SYNTACTIC PATTERN RECOGNITION 137Shilpa Rani, Deepika Ghai and Sandeep Kumar6.1 Introduction 1386.1.1 Contribution 1396.2 Literature Survey 1406.3 Proposed Methodology 1436.3.1 Face Detection 1436.3.2 Feature Extraction 1436.3.2.1 Facial Feature Extraction 1436.3.2.2 Syntactic Pattern Recognition 1436.3.2.3 Dense Feature Extraction 1476.3.3 Enhanced Features 1486.3.4 Creation of 3D Model 1486.4 Datasets and Experiment Setup 1486.5 Results 1496.6 Conclusion 152References 1547 ATTACK DETECTION USING DEEP LEARNING–BASED MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM 157Nishant Kaushal, Sukhwinder Singh and Jagdish Kumar7.1 Introduction 1587.2 Proposed Methodology 1607.2.1 Expert One 1607.2.2 Expert Two 1607.2.3 Decision Level Fusion 1617.3 Experimental Analysis 1627.3.1 Datasets 1627.3.2 Setup 1627.3.3 Results 1637.4 Conclusion and Future Scope 163References 1648 FEATURE OPTIMIZED MACHINE LEARNING FRAMEWORK FOR UNBALANCED BIOASSAYS 167Dinesh Kumar, Anuj Kumar Sharma, Rohit Bajaj and Lokesh Pawar8.1 Introduction 1688.2 Related Work 1698.3 Proposed Work 1708.3.1 Class Balancing Using Class Balancer 1718.3.2 Feature Selection 1718.3.3 Ensemble Classification 1718.4 Experimental 1728.4.1 Dataset Description 1728.4.2 Experimental Setting 1738.5 Result and Discussion 1738.5.1 Performance Evaluation 1738.6 Conclusion 176References 1769 PREDICTIVE MODEL AND THEORY OF INTERACTION 179Raj Kumar Patra, Srinivas Konda, M. Varaprasad Rao, Kavitarani Balmuri and G. Madhukar9.1 Introduction 1809.2 Related Work 1819.3 Predictive Analytics Process 1829.3.1 Requirement Collection 1829.3.2 Data Collection 1849.3.3 Data Analysis and Massaging 1849.3.4 Statistics and Machine Learning 1849.3.5 Predictive Modeling 1859.3.6 Prediction and Monitoring 1859.4 Predictive Analytics Opportunities 1859.5 Classes of Predictive Analytics Models 1879.6 Predictive Analytics Techniques 1889.6.1 Decision Tree 1889.6.2 Regression Model 1899.6.3 Artificial Neural Network 1909.6.4 Bayesian Statistics 1919.6.5 Ensemble Learning 1929.6.6 Gradient Boost Model 1929.6.7 Support Vector Machine 1939.6.8 Time Series Analysis 1949.6.9 k-Nearest Neighbors (k-NN) 1949.6.10 Principle Component Analysis 1959.7 Dataset Used in Our Research 1969.8 Methodology 1989.8.1 Comparing Link-Level Features 1999.8.2 Comparing Feature Models 2009.9 Results 2019.10 Discussion 2029.11 Use of Predictive Analytics 2049.11.1 Banking and Financial Services 2059.11.2 Retail 2059.11.3 Well-Being and Insurance 2059.11.4 Oil Gas and Utilities 2069.11.5 Government and Public Sector 2069.12 Conclusion and Future Work 206References 20810 ADVANCEMENT IN AUGMENTED AND VIRTUAL REALITY 211Omprakash Dewangan, Latika Pinjarkar, Padma Bonde and Jaspal Bagga10.1 Introduction 21210.2 Proposed Methodology 21410.2.1 Classification of Data/Information Extracted 21510.2.2 The Phase of Searching of Data/Information 21610.3 Results 21810.3.1 Original Copy Publication Evolution 21810.3.2 General Information/Data Analysis 22410.3.2.1 Nations 22410.3.2.2 Themes 22710.3.2.3 R&D Innovative Work 22710.3.2.4 Medical Services 22910.3.2.5 Training and Education 23010.3.2.6 Industries 23210.4 Conclusion 233References 23511 COMPUTER VISION AND IMAGE PROCESSING FOR PRECISION AGRICULTURE 241Narendra Khatri and Gopal U Shinde11.1 Introduction 24211.2 Computer Vision 24311.3 Machine Learning 24411.3.1 Support Vector Machine 24511.3.2 Neural Networks 24511.3.3 Deep Learning 24511.4 Computer Vision and Image Processing in Agriculture 24611.4.1 Plant/Fruit Detection 24911.4.2 Harvesting Support 25211.4.3 Plant Health Monitoring Along With Disease Detection 25211.4.4 Vision-Based Vehicle Navigation System for Precision Agriculture 25211.4.5 Vision-Based Mobile Robots for Agriculture Applications 25711.5 Conclusion 259References 25912 A NOVEL APPROACH FOR LOW-QUALITY FINGERPRINT IMAGE ENHANCEMENT USING SPATIAL AND FREQUENCY DOMAIN FILTERING TECHNIQUES 265Mehak Sood and Akshay Girdhar12.1 Introduction 26612.2 Existing Works for the Fingerprint Ehancement 26912.2.1 Spatial Domain 26912.2.2 Frequency Domain 27012.2.3 Hybrid Approach 27112.3 Design and Implementation of the Proposed Algorithm 27212.3.1 Enhancement in the Spatial Domain 27312.3.2 Enhancement in the Frequency Domain 27912.4 Results and Discussion 28212.4.1 Visual Analysis 28312.4.2 Texture Descriptor Analysis 28512.4.3 Minutiae Ratio Analysis 28512.4.4 Analysis Based on Various Input Modalities 29312.5 Conclusion and Future Scope 293References 29613 ELEVATE PRIMARY TUMOR DETECTION USING MACHINE LEARNING 301Lokesh Pawar, Pranshul Agrawal, Gurjot Kaur and Rohit Bajaj13.1 Introduction 30113.2 Related Works 30213.3 Proposed Work 30313.3.1 Class Balancing 30413.3.2 Classification 30413.3.3 Eliminating Using Ranker Algorithm 30513.4 Experimental Investigation 30513.4.1 Dataset Description 30513.4.2 Experimental Settings 30613.5 Result and Discussion 30613.5.1 Performance Evaluation 30613.5.2 Analytical Estimation of Selected Attributes 31113.6 Conclusion 31113.7 Future Work 312References 31214 COMPARATIVE SENTIMENT ANALYSIS THROUGH TRADITIONAL AND MACHINE LEARNING-BASED APPROACH 315Sandeep Singh and Harjot Kaur14.1 Introduction to Sentiment Analysis 31614.1.1 Sentiment Definition 31614.1.2 Challenges of Sentiment Analysis Tasks 31814.2 Four Types of Sentiment Analyses 31914.3 Working of SA System 32114.4 Challenges Associated With SA System 32314.5 Real-Life Applications of SA 32414.6 Machine Learning Methods Used for SA 32414.7 A Proposed Method 32614.8 Results and Discussions 32814.9 Conclusion 333References 33415 APPLICATION OF ARTIFICIAL INTELLIGENCE AND COMPUTER VISION TO IDENTIFY EDIBLE BIRD’S NEST 339Weng Kin Lai, Mei Yuan Koay, Selina Xin Ci Loh, Xiu Kai Lim and Kam Meng Goh15.1 Introduction 34015.2 Prior Work 34215.2.1 Low-Dimensional Color Features 34215.2.2 Image Pocessing for Automated Grading 34315.2.3 Automated Classification 34315.3 Auto Grading of Edible Birds Nest 34315.3.1 Feature Extraction 34415.3.2 Curvature as a Feature 34415.3.3 Amount of Impurities 34415.3.4 Color of EBNs 34515.3.5 Size—Total Area 34615.4 Experimental Results 34715.4.1 Data Pre-Processing 34715.4.2 Auto Grading 34915.4.3 Auto Grading of EBNs 35315.5 Conclusion 355Acknowledgments 356References 35616 ENHANCEMENT OF SATELLITE AND UNDERWATER IMAGE UTILIZING LUMINANCE MODEL BY COLOR CORRECTION METHOD 361Sandeep Kumar, E. G. Rajan and Shilpa Rani16.1 Introduction 36216.2 Related Work 36216.3 Proposed Methodology 36416.3.1 Color Correction 36416.3.2 Contrast Enhancement 36516.3.3 Multi-Fusion Method 36616.4 Investigational Findings and Evaluation 36716.4.1 Mean Square Error 36716.4.2 Peak Signal–to-Noise Ratio 36816.4.3 Entropy 36816.5 Conclusion 375References 376Index 381
iMac For Dummies
SAY HELLO TO YOUR IMAC WITH THIS BESTSELLING GUIDEExcited to put your cool iMac through its paces? Go ahead! Say “Hey Siri” to look up information, use the large monitor to play a game or watch a movie, share documents with your iPhone or iPad, or video chat with friends or family. With its optimized system speed, your iMac can keep up with anything you want to do. How cool is that?Your iMac comes stuffed with features, and iMac For Dummies is your tour guide to explore all of them! This updated handbook has you covered, no matter if you need to work or want to play. You can:* Scroll, tap, and swipe your way through the Mac operating system * Set up Bluetooth, Wi-Fi, and other settings in Control Center * Say “Hey Siri” to have the Apple assistant search for information or launch apps * Play video games, music, movies, or TV * Stay in touch with people through Messages and Facetime * Use productivity apps, including Numbers, Pages, and Keynote * Sync to iCloud and across all your Apple devices The all-in-one design of the iMac with its monitor, processor, graphics card, and internal drive makes it ideal for work and entertainment. Pick up your copy of this comprehensive guide to the iMac, filled with screenshots and how-to steps, and ensure you use your iMac to its full potential.MARK L. CHAMBERS is a technical author, computer consultant, programmer, and hardware technician with over 30 years of experience. He has written over 30 computer books, including MacBook For Dummies, 9th Edition and Macs For Seniors For Dummies, 4th Edition.Introduction 1PART 1: GETTING STARTED WITH YOUR IMAC 5Chapter 1: Okay, This Machine Looks Really, Really Weird 7Chapter 2: Life! Give My iMac Life! 25Chapter 3: The Basics Behind macOS Monterey 33PART 2: SHAKING HANDS WITH MACOS 77Chapter 4: What’s New in Monterey? 79Chapter 5: A Nerd’s Guide to System Preferences 85Chapter 6: Searching Amidst iMac Chaos 107Chapter 7: Putting Common Apps to Work 117PART 3: CONNECTING AND COMMUNICATING 135Chapter 8: Let’s Go on Safari! 137Chapter 9: Expanding Your Horizons with iCloud 159Chapter 10: Creating a Multiuser iMac 167Chapter 11: Working Well with Networks 187Chapter 12: Hooking Up with Handy Helpers 207PART 4: LIVING THE DIGITAL LIFE 219Chapter 13: The Multimedia Joys of Music and TV 221Chapter 14: Focusing on Photos 245Chapter 15: Making Film History with iMovie 265Chapter 16: Recording Your Hits with GarageBand 285PART 5: GETTING PRODUCTIVE WITH YOUR IMAC 303Chapter 17: Desktop Publishing with Pages. 305Chapter 18: Creating Spreadsheets with Numbers 319Chapter 19: Building Presentations with Keynote 335PART 6: THE NECESSARY EVILS: TROUBLESHOOTING, UPGRADING, AND MAINTAINING 349Chapter 20: It Just Sits There 351Chapter 21: I Want to Add Stuff 365Chapter 22: Tackling the Housekeeping 377PART 7: THE PART OF TENS 393Chapter 23: Ten Ways to Speed Up Your iMac 395Chapter 24: Ten Things to Avoid Like the Plague 401Index 409
Modern Deep Learning Design and Application Development
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking.You’ll begin with a structured guide to using Keras, with helpful tips and best practices for making the most of the framework. Next, you’ll learn how to train models effectively with transfer learning and self-supervised pre-training. You will then learn how to use a variety of model compressions for practical usage. Lastly, you will learn how to design successful neural network architectures and creatively reframe difficult problems into solvable ones. You’ll learn not only to understand and apply methods successfully but to think critically about it.Modern Deep Learning Design and Methods is ideal for readers looking to utilize modern, flexible, and creative deep-learning design and methods. Get ready to design and implement innovative deep-learning solutions to today’s difficult problems.WHAT YOU’LL LEARN* Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization.* Compress deep learning models while maintaining performance.* Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. * Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.WHO THIS BOOK IS FORData scientists with some familiarity with deep learning to deep learning engineers seeking structured inspiration and direction on their next project. Developers interested in harnessing modern deep learning methods to solve a variety of difficult problems.Andre Ye is a data science writer and editor; he has written over 300 data science articles for various top data science publications with over ten million views. He is also a cofounder at Critiq, a peer revision platform that uses machine learning to match users’ essays. In his spare time, Andre enjoys keeping up with current deep learning research, playing the piano, and swimming.Chapter 1: “A Deep Dive Into Keras”Chapter Goal: To give a structured yet deep overview of Keras and to lay the groundwork for implementations in future chapters.Number of Pages: ~30Subtopics1. Why Keras? Versatility and simplicity.2. Steps needed to create a Keras model: define architecture, compile, fit.a. Compile: discuss TensorFlow optimizers, losses, and metrics.b. Fit: discuss callbacks.3. Sequential model + example.4. Functional model + example.5. Visualizing Keras models.6. Data: using NumPy arrays, Keras Image Data Generator, and TensorFlow datasets.7. Hardware: using and accessing CPU, GPU, and TPU.Chapter 2: Pre-training Strategies and Transfer LearningChapter Goal: To understand the importance of transfer learning and to use a variety of transfer learning methods to solve deep learning problems efficiently.Number of Pages: ~30Subtopics1. Transfer learning theory, practical tips and tricks.2. Accessing and using Keras and TensorFlow pretrained models.a. Bonus: converting PyTorch models (PyTorch has a wider variety) into Keras models for greater access to pretrained networks.3. Manipulating pretrained models with other network elements.4. Layer freezing.5. Self-supervised learning methods.Chapter 3: “The Versatility of Autoencoders”Chapter Goal: To understand the versatility of autoencoders and to be able to use them in a wide variety of problem scenarios.Number of Pages: ~30Subtopics1. Autoencoder theory.2. One-dimensional data autoencoder implementation, tips and tricks.3. Convolutional autoencoder implementation, tips and tricks, special concerns.4. Using autoencoders for pretraining.a. Example case study: TabNet.5. Using autoencoders for feature reduction.6. Variational autoencoders for data generation.Chapter 4: “Model Compression for Practical Deployment”Chapter Goal: To understand pruning theory, implement pruning for effective model compression, and to recognize the important role of pruning in modern deep learning research.Number of Pages: ~20Subtopics1. Pruning theory.2. Pruning Keras models with TensorFlow.3. Exciting implications of pruning – the Lottery Ticket Hypothesis.a. Example case-study: no-training neural networks.b. Example case-study: extreme learning machines.Chapter 5: “Automating Model Design with Meta-Optimization”Chapter Goal: To understand what meta-optimization is and to be able to use it to effectively automate the design of neural networks.Number of Pages: ~20Subtopics1. Meta-optimization theory.2. Demonstration of meta-optimization using HyperOpt on Keras.3. Demonstration of Auto-ML and Neural Architecture Search.Chapter 6: “Successful Neural Network Architecture Design”Chapter Goal: To gain an understanding of principles in successful neural network architecture design through three case studies.Number of Pages: ~25Subtopics1. Diversity of neural network designs and the need to design specific architectures for particular problems.2. Theory and implementation of block/cell/module design and considerations.a. Example case study: Inception model.3. Theory and implementation of “Normal” and “extreme” usages of skip connections.a. Parallel towers and cardinalityb. Example case study: UMAP model.4. Neural network scaling.a. Example case study: EfficientNet.Chapter 7: “Reframing Difficult Deep Learning Problems”Chapter Goal: To explore how hard problems can be reframed to be solved by deep learning with three case studies.Number of Pages: ~30Subtopics1. The diversity of problems deep learning is being used to solve.2. Example case study: Siamese networks – experimenting with architecture.3. Example case study: DeepInsight – experimenting with data representation.4. Example case study: Semi-supervised generative adversarial networks – experimenting with data availability.
Introducing Robotic Process Automation to Your Organization
For your robotic process automation (RPA) program to be successful, you need to follow a general framework and governance model. This book covers, in detail, what they should look like and how to adapt them to your organization.INTRODUCING ROBOTIC PROCESS AUTOMATION TO YOUR ORGANIZATION is structured to enable you, a novice to RPA, to successfully implement an RPA program at your company. RPA is rapidly growing in use, but is only starting to be taught at a university level. Many mid-level managers will be tasked with introducing an RPA program at their organizations as senior management learns of its efficacy, but will be unfamiliar with how to do so. This book provides you with the skills and information you need to make an informed decision.For decades, there has been much discussion about the fast pace of technology, the rapidly changing technology environment, and the need for companies to be on the cutting edge to remain competitive or even relevant. In this ever-changing environment, there is a need to know what can be done in terms of current processes, here and now, that will increase efficiency, benefit customers, and improve profitability. One option is RPA.This book includes information to assist you in getting the required buy-in and identifying the first few processes for automation. A structure for identifying opportunities on an ongoing basis is detailed, along with concepts that must be considered for solution design and deployment. Throughout the book there are several "pause and consider" statements to help you think about how principles pertain to your organization. Additionally, there are tips included that offer short, concrete suggestions on how to help implement the particular step being discussed.WHAT YOU WILL LEARN* Know the benefits of robotic process automation (RPA)* Understand the limitations of RPA* Ask the right questions to determine whether a process is a good candidate for automation* Obtain buy-in from skeptics at the senior and middle manager levels, and from line workers* Be familiar with the structure required for successWHO THIS BOOK IS FORMiddle managers who have either identified the need for robotic process automation (RPA) in their organization or have been directed by senior management to explore the possibility of introducing RPA to their organization; managers at all levels who hear about RPA, either through conferences, professional associations, or industry publications, and want to know more; students of business and technology who wish to broaden their understanding of important current trends.ANDRIY STOROZHUK has extensive expertise in all aspects of Lean Six Sigma, and he has utilized those skills in a variety of environments and methodologies. He has incorporated that knowledge, along with knowledge received in his university studies and constant ongoing training, in all of his work. Most recently, he brought that knowledge and experience to bear in creating an RPA program at his current place of employment.KAMAL GOYAL has been working exclusively in the field of RPA for the last six years. He has been instrumental in establishing the required infrastructure at several companies, including where he currently works. He, too, is constantly learning to keep abreast of current trends within IT.ROBERT FANTINA is an acknowledged process improvement expert, and has worked closely with Andriy and Kamal in establishing an effective and successful RPA program at his most recent place of employment. He is the author of eight books, including Practical Software Process Improvement and Your Customers’ Perception of Quality: What It Means to Your Bottom Line and How to Control It (co-author Baboo Kureemun). His paper, "Successful Software Process Implementation", was published in the journal, Software Quality Professional. He has given presentations on process improvement and quality at conferences in Atlanta, Georgia and Los Angeles, California and Orlando, Florida, among other places.Andriy, Kamal, and Robert have, combined, over 70 years of experience in various aspects of information technology.INTRODUCTIONCHAPTER 1. Initial PreparationChapter Goal: To inform the reader of different ways RPA is brought into an organization, and how to get buy-in depending on the method of introduction.- Need for RPA- Senior Management Decision- Mid-Level Management Idea- A Technology Leader Recognizes the Importance of RPACHAPTER 2. Operating Model - Governance, Sponsorship and FrameworkChapter Goal: To educate the reader on the overall structure required for an effective RPA program.- Governance: this section will assist the reader in knowing how best to structure governance within the context of his/her organization.- Sponsorship: the roles that generally provide sponsorship, and their attendant duties, are described.- Framework: a basic overview of the structure is discussed, with information on how to apply it within different types of organizations.CHAPTER 3. Opportunity IdentificationChapter Goal: To ensure that the reader has a clear idea of the kinds of processes that might be suitable for automation.- Discussion with department managers.CHAPTER 4. Opportunity AssessmentChapter Goal: To enable the reader to fully and efficiently make an assessment on whether or not a process proposed for automation is a suitable candidate.- Basic request form- Mapping the process.- Determining suitability (it is pointless to automate an inefficient process)- Meeting with governance groupCHAPTER 5. Solution DesignChapter Goal: To ensure that the reader knows how best to build a solution that will effectively automate the process.- Understanding risks- Understanding upstream and downstream changes required, and their potential impacts.CHAPTER 6. Solution Deployment, Maintenance and RetirementChapter Goal: To explain how to actually deploy the solution.- Piloting- Warranty period- Maintenance- Reuse- Phase out when the process is no longer required (if this is an eventuality)CHAPTER 7. Organizational StructureChapter Goal: RPA in your organization- Maximizing usage- Hub and Spoke- Etc.CHAPTER 8. Product Development MethodologiesChapter Goal: To explain how RPA is compatible with various development methodologies- Agile- Waterfall- Lean- DevOps- Etc.CHAPTER 9. Designing for FutureChapter Goal: Looking ahead within your organization- Designing processes digitally- Full stack automation- Simulation testing- ComplianceCHAPTER 10. SummaryChapter Goal: To concisely state the vital points of RPA- Conclusion- Wrapping it all together- High points (must haves) for successful RPA- FrameworkAPPENDIXChapter Goal: To provide tools for the RPA manager.- Templateso Request formo Business caseo Risk assessmento Map/flowchart (Visio)o Map/flowchart documentation (Word)- FAQs
Data-Driven Alexa Skills
Design and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. You will learn to use data to give your Alexa skills dynamic intelligence, in-depth knowledge, and the ability to remember.DATA-DRIVEN ALEXA SKILLS takes a step-by-step approach to skill development. You will begin by configuring simple skills in the Alexa Skill Builder Console. Then you will develop advanced custom skills that use several Alexa Skill Development Kit features to integrate with lambda functions, Amazon Web Services (AWS), and Internet data feeds. These advanced skills enable you to link user accounts, query and store data using a NoSQL database, and access real estate listings and stock prices via web APIs.WHAT YOU WILL LEARN* Set up and configure your development environment properly the first time* Build Alexa skills quickly and efficiently using Agile tools and techniques* Create a variety of data-driven Alexa skills for home and business* Access data from web applications and Internet data sources via their APIs* Test with unit-testing frameworks throughout the development life cycle* Manage and query your data using the DynamoDb NoSQL database enginesWHO THIS BOOK IS FORDevelopers who wish to go beyond Hello World and build complex, data-driven applications on Amazon's Alexa platform; developers who want to learn how to use Lambda functions, the Alexa Skills SDK, Alexa Presentation Language, and Alexa Conversations; developers interested in integrating with public APIs such as real estate listings and stock market prices. Readers will need to have basic Python skills.SIMON KINGABY is a software developer, programming professor, and public speaker residing in middle Tennessee. He believes that voice user interfaces will change the world and that tools like Alexa are just the tip of the iceberg. He spends his days moving data for Deloitte Global and teaching DataViz and FinTech at Vanderbilt University. In 2016, he published his first Alexa skill and has been enthralled by voice development ever since. In 2017, his uncle suddenly went blind and Simon began exploring ways Alexa could be used to help the blind by developing skills from “What’s the time?” and home navigation skills to smart home skills like “Turn on the coffee pot." In 2019 that same uncle committed suicide, and Simon turned his attention to mental health issues and using Alexa to help identify and prevent suicidal behavior. Now he is focused on enabling developers to use their programming abilities to build data-driven Alexa skills that will make a real difference in the world.PART I: GETTING STARTEDChapter 1: Voice User InterfacesChapter 2: Routines and BlueprintsChapter 3: The Developer AccountsChapter 4: Creating the VUI for a Custom Data-driven SkillChapter 5: Writing the Back-end CodeChapter 6: Publishing an Alexa SkillPART II: CUSTOM SKILL DEVELOPMENTChapter 7: Custom Alexa SkillsChapter 8: Beyond Hello WorldChapter 9: Configuring the VUIChapter 10: Using APL to Present on ScreensChapter 11: Coding the Lambda FunctionChapter 12: Unit Testing an Alexa SkillChapter 13: Storing the DataPART III: USING APIS IN ADVANCED SKILLSChapter 14: A Personal Net Worth SkillChapter 15: The Real Estate APIChapter 16: The Stock Market APIChapter 17: What’s Next?
Digineering
Als Folge der zunehmenden Verfügbarkeit neuer Informationstechnologien entstehen völlig neue Kundenerwartungen, Geschäftsmodelle und Prozesse. Die umfassende Neugestaltung digitaler Prozesse ist mit Konzepten der Vergangenheit nicht zu bewältigen. Business Process Management benötigt angepasste Methoden, Fähigkeiten, Technologien und Strukturen.„Digineering“ steht für die Kombination der Aspekte einer zunehmenden Digitalisierung mit den Methoden und Vorgehensweisen des Re-Engineering und überträgt damit Ansätze aus dem Business Process Management, dem Management der digitalen Transformation und dem Software-Engineering auf die aktuellen Herausforderungen der Prozessdigitalisierung.„Digineering“ liefert einen agilen Lösungsansatz, der alle Phasen der Prozessdigitalisierung von der Analyse der Kundenanforderungen über die Prozessgestaltung bis zur Implementierung neuer IT-Anwendungen umfasst. In allen Phasen werden die Potenziale innovativer IT einbezogen, um so ganzheitliche Prozesse mit einzigartigem Kundenerlebnis und hoher Effizienz zu schaffen.PROF. DR. ARNO MÜLLER lehrt an der NORDAKADEMIE Hochschule der Wirtschaft Prozessmanagement, strategisches IT-Management und Logistik und ist Geschäftsführer der bps business process solutions GmbH.PROF. DR. HINRICH SCHRÖDER ist Professor und Studiengangsleiter für Wirtschaftsinformatik an der NORDAKADEMIE Hochschule der Wirtschaft.LARS VON THIENEN ist Geschäftsführer der bps business process solutions GmbH und berät Unternehmen bei der Transformation der IT-Organisation und dem Aufbau von innovativen IT-Management-Methoden.Bausteine des Digineering.- Fitness-Check zur Entwicklung der Technology- und Capability-Roadmap.- Methoden und Rollenmodell für die Prozessdigitalisierung: (Ro)-Bots: Orchestrierung von digitalen Services und Mensch-Maschine-Kommunikation.- Roadmap zur Aufdeckung und Realisierung der KI-Potenziale in der Prozessdigitalisierung.- Dataism: Wertschöpfung mit datengetriebenen Geschäftsmodellen.- Steuerung der unternehmensweiten Prozessdigitalisierung.- Operating-Model für digitalisierte Prozesse.
Beginning IntelliJ IDEA
Get started quickly with IntelliJ, from installation to configuration to working with the source code and more. This tutorial will show you how to leverage IntelliJ’s tools to develop clean, efficient Java applications.Author TED HAGOS will first walk you through buidling your first Java applications using IntelliJ. Then, he’ll show you how to analyze your application, top to bottom; using version control and tools that allow you expand your application for big data or data science applications and more. You'll also learn some of the IDE’s advanced features to fully maximize your application's capabilities.The last portion of the book focuses on application testing and deployment, and language- and framework- specific guidelines. After reading this book and working through its freely available source code, you'll be up to speed with this powerful IDE for today's Java development.WHAT YOU WILL LEARN* Use IntelliJ IDEA to build Java applications* Set up your IDE and project* Work with source code* Extend your Java application to data science and other kinds of applications* Test and deploy your application and much moreWHO THIS BOOK IS FORProgrammers new to IntelliJ IDEA who may have some prior exposure to Java programming.Ted Hagos is a software developer by trade; at the moment, he’s Chief Technology Officer and Data Protection Officer of RenditionDigital International, a software development company based out of Dublin. He wore many hats in his 20+ years in software development e.g. team lead, project manager, architect and director for development. He also spent time as a trainer for IBM Advanced Career Education, Ateneo ITI and Asia Pacific College. He wrote a couple of books for Apress.1. Install IntelliJ2. Getting Started3. Configuring the IDE4. Configuring Projects5. Working with Source Code6. Building Applications7. Analyzing Applications8. Version Control9. Big Data / Data Science Tools10. Other Tools11. Advanced IDE Features12. Migration Guides13. Language and Framework Specific Guidelines14. Testing15. Deployment
Four Laws for the Artificially Intelligent
ASK NOT WHAT AI CAN DO FOR A COMPANY, RATHER WHAT ARTIFICIAL INTELLIGENCE MAY DO TO A COMPANY.* How does a company successfully integrate artificial intelligence into its operations?* What are the problems in doing so?* And how does the introduction of AI into society change the answer to the first question?As companies delay or even cancel initiatives in artificial intelligence, Four Laws for the Artificially Intelligent redefines possibilities and offers leverage to turn AI visions into reality. It is a story of transformation: of people, of companies, and of artificial intelligence itself.The Four Laws is unique in its combination of stories and science illustrating how a technology competing with human consciousness is introduced and assimilated within a company. A work of creative nonfiction stretched on a frame of research, it is an essential trail guide for navigating the Industry Version 4.0 jungle in a search of the fruits of innovation.
Unity Networking Fundamentals
Learn the fundamentals of networking with Unity and C#. This book covers a variety of topics, including accessing data using RESTful APIs, local networked games, and creating multiplayer online games using client-server architecture.The book provides the basics of networking, sockets, TCP vs. UDP, client-server architecture, serialization, RESTful APIs, network latency, and client-side prediction. Projects are presented to illustrate the concepts, including a chat client/server overlay for your game, and a 3D maze game that allows up to four players to connect over the network.By the end of the book, you will be familiar with low-level networking concepts such as protocols and architecture as well as high-level knowledge on how to create applications that use a client/server architecture for multiplayer games.WHAT YOU WILL LEARN* Know the difference between TCP and UDP, and the pros and cons of these protocols* Create client-server multiplayer games in Unity using C#* Receive and process data from a remote server using RESTful APIs* Understand latency and how to mitigate its impact WHO THIS BOOK IS FORReaders familiar with Unity and C# development who want to create multiplayer games SLOAN KELLY has worked in the games industry for more than 13 years. He has worked on a number of AAA and indie titles and currently works for an educational game company. He lives in Ontario, Canada with his wife and children. Sloan is on Twitter @codehoose and makes YouTube videos in his spare time.KHAGENDRA KUMAR has worked with a number of educational institutions and game studios for training and solutions. He lives in Bihar, India and spends most of his time working with game AI. He can be reached via Linkedin at /itskhagendra and Instagram @Khagendra_Developer.Chapter 1: Networking ConceptsChapter 2: SerializationChapter 3: Restful APIsChapter 4: TCP connectionsChapter 5: Networking IssuesChapter 6: Develop Maze ShooterChapter 7: LAN NetworkingChapter 8: Servers
WebAssembly for Cloud
Journey into the amazing world of WebAssembly (Wasm) and learn about how it can be applied on the cloud. This book is an introduction to Wasm aimed at professionals accustomed to working with cloud-related technologies such as Kubernetes and Istio service mesh.Author SHASHANK JAIN begins with an introduction to Wasm and its related tooling such as wasm-bindgen and wapc. He then walks you through code examples using Rust, Golang, and JavaScript to demonstrate how they can be compiled to Wasm and consumed from Wasm runtimes deployed standalone, as well as on the cloud. You will see how a wasm module can be run through an http interface, and how Wasm fits into CNCF projects such as Kubernetes and Istio service mesh. After that, you’ll learn how the polyglot nature of WebAssembly can be leveraged through examples written in languages like Rust and consumed via Golang and JavaScript, with a focus on how WebAssembly allows interoperability between them. You’ll gain an understanding of how Wasm-based modules can be deployed inside Linux containers and orchestrated via Kubernetes, and how Wasm can be used within the Istio proxy to apply rules and filters.After reading this book, you’ll have the knowledge necessary to apply WebAssembly to create multi tenanted workloads which can be polyglot in nature and can be deployed on cloud environments like Kubernetes.WHAT YOU WILL LEARN* Understand how Wasm can be used for server-side applications* Learn about Wasm memory model and Wasm module layout* How communication between host and Wasm module is facilitated* The basics of Wasm sandboxing and security* The fundamentals of tooling around Wasm, such as WAT and Wasm-pack* Create a Wasm module in Rust and consume it from JavaScript, Rust and Golang.* Grasp how Kubernetes can be used to orchestrate Wasm-based workloads* How Wasm fits into service meshWHO IS THIS BOOK FORSoftware developers/architects who are looking to hone their skills in virtualization and explore alternatives to Docker and container-based technologies for their workload deployments. Readers should have a basic programming background in languages such as Rust and Golang to get the most out of this book.Shashank Mohan Jain has been working in the IT industry for around 20 years mainly in the areas of cloud computing and distributed systems. He has keen interests in virtualization techniques, security, and complex systems. Shashank has 32 software patents (many yet to be published) to his name in the area of cloud computing, IoT, and machine learning. He is a speaker at multiple reputed cloud conferences. Shashank holds Sun, Microsoft, and Linux kernel certifications.CHAPTER 1: INTRODUCTION TO WEBASSEMBLY (WASM)Chapter Goal :History and Introduction to Wasm• What is WebAssembly and why is it important for Cloud native• Wasm architecture and how we realize virtualization via Wasm• Kind of workloads supported by Wasm (Cloud, Browser, and Edge)CHAPTER 2: WEBASSEMBLY MEMORY MODEL AND RUNTIMESChapter Goal: Memory model internals and layout of Wasm modules in memory• Introduction to Wasm file format• Deep dive into the sections of the Wasm file (function table, types, etc.) and their relevance• Memory layout for tenant isolation within a linux process using WasmCHAPTER 3: WEBASSEMBLY TEXT TOOLKITChapter Goal: Covers the WebAssembly text format by showing examples of how to write Wasm. Usage of tools like wasm2wat will also be covered with examples• Introduction to WebAssembly text format (wat)• Creating simple wat programs and compiling to Wasm using wat2wasm toolCHAPTER 4: RUST AND WEBASSEMBLY Chapter Goal: Covers examples of how to create a Wasm module in Rust and invoke it via JS and other runtimes• Creating a Rust program and compiling it as a Wasm module• Explain wasm-bindgen tool for compiling Rust to Wasm• Consuming the Rust program from a JavaScript-based runtime like Node.jsCHAPTER 5: GOLANG AND WEBASSEMBLY Chapter Goal: Covers examples of how to create a Wasm module in Golang and invoke it via JS and other runtimes• Create a Golang program and expose it as a Wasm module• Use WaPC (web assembly procedure call) to consume this program fromo Rusto Node.js• Show how complex types can be created in Wasm using WaPC and how these types can be passed between guest and host boundariesCHAPTER 6: WRITING A SIMPLE WEB APPLICATION IN WEBASSEMBLYChapter Goal: How to create a simple web app in WebAssembly• Expose the Wasm module using a web application• Web application will be written ino Rusto Node.jso Golang• All three runtimes will embed a Wasm engine and load a Wasm module on an http request. Invoke the exposed function within Wasm module and return back the http responseCHAPTER 7: DEPLOYING WASM WORKLOADS TO KUBERNETES AND SERVICE MESHChapter Goal: Showcase how Wasm modules can be deployed using the kubernetes control plane and can be represented as pods instead of Docker containers. Also covers some of the serverless aspects around and detail out a service mesh scenario where we can use Wasm-based filters for massaging the data on the Istio data plane• Intro to Kubernetes• Dockerize the embedded Wasm engine in the runtimes created in Chapter 6• Host these docker images into dockerhub• Create a Kubernetes pod using these docker images• Deploy the pod into kubernetes• Expose the web servers (hosting the Wasm runtime) as a service in k8s• Show invocation of the Wasm modules via the service• Intro to Istio and Service Mesh in context of API gateways• Create a simple Wasm filter for Istio/Envoy• Show invocation of the Wasm filter as part of the data pathCHAPTER 8: SUMMARYChapter Goal : Summary of the topics around Wasm and its usage• Summary of Wasm and various runtimes for Wasm• Summarize enablement of Wasm-based workloads on k8s
Language Server Protocol and Implementation
Understand the important aspects of implementing a production-grade language server in support of language-smart tools such as code editors and other programming utilities. This book shows you how to create a single implementation of a language server that can be used by multiple tools, enabling you to do the job once in a way that can be shared and reused.This book covers the language server protocol used for communication between programming tools and your language server. The book also provides an in-depth understanding of the design, implementation, and user experience aspects which should be considered when implementing a language server. The book walks you through an example language server implementation to illustrate the basic concepts, then goes on to cover advanced aspects of language server use such as progress reporting, launchers, and extension points.User experience is an important aspect of language server implementation and different tooling vendors strive to provide their own unique user experiences. This book explains how the protocol features can be leveraged to address the unique developer experience provided by different tooling vendors. The book also shows how to enhance the smoothness of the editing experience by orchestrating multiple features together.WHAT YOU WILL LEARN* Implement a language server from scratch* Understand language server protocol and its data models* Leverage the protocol while preserving the unique user experience of different editors* Extend the protocol to support more than its standard capabilities* Run a language server on top of launchers such as standard I/O and TCP socket* Seamlessly incorporate language semantics into your protocol featuresWHO THIS BOOK IS FORDevelopers focused on and passionate about implementing language development tools such as plug-ins and extensions for interactive development environments (IDEs) or other tools that rely upon parsing of language statements and commands, and developers who need an in-depth understanding of the language server protocol as well as how to use the language server protocol to develop extensible language servicesNADEESHAAN GUNASINGHE is Technical Lead at WSO2 and has more than five years of experience in enterprise integration, programming languages, and developer tooling. He leads the Ballerina Language Server team and is a key contributor to Ballerina, which is an open-source programming language and platform for the cloud, and he is an active contributor to the WSO2 Enterprise Service Bus.NIPUNA MARCUS is Technical Lead at WSO2 and has more than five years of experience in front end development, programming languages, and developer tooling. He was a member of the Ballerina Language Server team and a key contributor to the Ballerina programming language. 1. Developer Tools and Language Services2. Understanding the Language Server Protocol3. Implementing a Language Server4. General Messages5. Text Synchronization6. Diagnostics, Smart Editing, and Documentation7. Refactoring and Code Fixes8. Code Navigation and Navigation Helpers9. Presentation and Folding10. Workspace Operations11. Advanced ConceptsA. Data Models and Resources
Expert Oracle Database Architecture
Now in its fourth edition and covering Oracle Database 21c, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications that perform well and deliver correct results. Tom Kyte and Darl Kuhn share a simple philosophy: "you can treat Oracle as a black box and just stick data into it, or you can understand how it works and exploit it as a powerful computing environment." If you choose the latter, then you’ll find that there are few information management problems that you cannot solve quickly and elegantly.This fully revised fourth edition covers the developments and new features up to Oracle Database 21c. Up-to-date features are covered for tables, indexes, data types, sequences, partitioning, data loading, temporary tables, and more. All the examples are demonstrated using modern techniques and are executed in container and pluggable databases. The book’s proof-by-example approach encourages you to let evidence be your guide. Try something. See the result. Understand why the result is what it is. Apply your newfound knowledge with confidence. The book covers features by explaining how each one works, how to implement software using it, and the common pitfalls associated with it.Don’t treat Oracle Database as a black box. Get this book. Dive deeply into Oracle Database’s most powerful features that many do not invest the time to learn about. Set yourself apart from your competition and turbo-charge your career.WHAT YOU WILL LEARN* Identify and effectively resolve application performance issues and bottlenecks* Architect systems to leverage the full power and feature set of Oracle’s database engine* Configure a database to maximize the use of memory structures and background processes* Understand internal locking and latching technology and how it impacts your system* Proactively recommend best practices around performance for table and index structures* Take advantage of advanced features such as table partitioning and parallel executionWHO THIS BOOK IS FOROracle developers and Oracle DBAs. If you’re a developer and want a stronger understanding of Oracle features and architecture that will enable your applications to scale regardless of the workload, this book is for you. If you’re a DBA and want to intelligently work with developers to design applications that effectively leverage Oracle technology, then look no further.DARL KUHN is a DBA/developer working for Oracle. He also teaches Oracle classes at Regis University in Denver, Colorado, and is an active member of the Rocky Mountain Oracle Users Group. Darl enjoys sharing knowledge and has authored several books.THOMAS KYTE is a former vice president of the Core Technologies Group at Oracle Corporation. He is the same Tom who created the "Ask Tom" website and the Oracle Magazine column of the same name. He has a long history of answering questions about the Oracle database and tools that developers and database administrators struggle with every day.1. Developing Successful Oracle Applications2. Architecture Overview3. Files4. Memory Structures5. Oracle Processes6. Locking and Latching7. Concurrency and Multi-versioning8. Transactions9. Redo and Undo10. Database Tables11. Indexes12. Datatypes13. Partitioning14. Parallel Execution15. Data Loading and Unloading
Automated Essay Scoring
THIS BOOK DISCUSSES THE STATE OF THE ART OF AUTOMATED ESSAY SCORING, ITS CHALLENGES AND ITS POTENTIAL. One of the earliest applications of artificial intelligence to language data (along with machine translation and speech recognition), automated essay scoring has evolved to become both a revenue-generating industry and a vast field of research, with many subfields and connections to other NLP tasks. In this book, we review the developments in this field against the backdrop of Elias Page's seminal 1966 paper titled "The Imminence of Grading Essays by Computer."Part 1 establishes what automated essay scoring is about, why it exists, where the technology stands, and what are some of the main issues.In Part 2, the book presents guided exercises to illustrate how one would go about building and evaluating a simple automated scoring system, while Part 3 offers readers a survey of the literature on different types of scoring models, the aspects of essay quality studied in prior research, and the implementation and evaluation of a scoring engine. Part 4 offers a broader view of the field inclusive of some neighboring areas, and Part \ref{part5} closes with summary and discussion.This book grew out of a week-long course on automated evaluation of language production at the North American Summer School for Logic, Language, and Information (NASSLLI), attended by advanced undergraduates and early-stage graduate students from a variety of disciplines. Teachers of natural language processing, in particular, will find that the book offers a useful foundation for a supplemental module on automated scoring. Professionals and students in linguistics, applied linguistics, educational technology, and other related disciplines will also find the material here useful.* Preface* Building an Automated Essay Scoring System* From Lessons to Guidelines* Models* Generic Features* Genre- and Task-Specific Features* Automated Scoring Systems: From Prototype to Production* Evaluating for Real-World Use* Automated Feedback* Automated Scoring of Content* Automated Scoring of Speech* Fooling the System: Gaming Strategies* Looking Back, Looking Ahead* Definitions-in-Context* Index* References* Authors' Biographies
AI and Ed
The United States has undergone several major transformations economically, politically, and socially. Today, the impact of artificial intelligence will bring another transformation affecting citizens’ private lives as well as employment, communication, politics, and almost every other aspect of life.The question artificial intelligence raises is: what kind of education will students need in confronting the obvious and projected impact of technology? Transformations affect obvious aspects of life, but also raise significant issues that challenge values, ethics and standards.The purpose of this book is to define the role of education and its goals, content, and approaches that will assist citizens in addressing the challenges the artificial intelligence movement brings to the life of citizens. Positive aspects of the transformation include communication, productivity, and other issues. However, there are hazards and downsides to artificial intelligence that must be addressed through an educated society.Education’s role encompasses assisting individuals to address the positive and negative aspects of any creative intervention. Thinking coupled with insight into principles, ethics, and the meaning of life are critical. Education prepares individuals for changing times in order to protect their freedoms and democracy and find a life of purpose and meaning.George A. Goens, PhD, has written seven books and co-authored four on leadership, school reform, education, and social issues. He served an executive in teaching positions, as well as leadership consultant to public boards and individuals.Chapter 1: TransformationChapter 2: Personal TransformationChapter 3: Innovation: The Big and Small PictureChapter 4: TechnologyChapter 5: Artificial IntelligenceChapter 6: From Butterflies to Black SwansChapter 7: Artificial Intelligence and Real World IssuesChapter 8: Gains and LossesChapter 9: Implications: EducationChapter 10: Humans BeingsEpilogue: Intelligence, Mind, and HeartBibliographyIndexAbout the Author