Allgemein
Advances in Data Science and Analytics
ADVANCES IN DATA SCIENCE AND ANALYTICSPRESENTING THE CONCEPTS AND ADVANCES OF DATA SCIENCE AND ANALYTICS, THIS VOLUME, WRITTEN AND EDITED BY A GLOBAL TEAM OF EXPERTS, ALSO GOES INTO THE PRACTICAL APPLICATIONS THAT CAN BE UTILIZED ACROSS MULTIPLE DISCIPLINES AND INDUSTRIES, FOR BOTH THE ENGINEER AND THE STUDENT, FOCUSING ON MACHINING LEARNING, BIG DATA, BUSINESS INTELLIGENCE, AND ANALYTICS.Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries. For the purposes of this volume, data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. While a data scientist is expected to forecast the future based on past patterns, data analysts extract meaningful insights from various data sources. Although data mining and other related areas have been around for a few decades, data science and analytics are still quickly evolving, and the processes and technologies change, almost on a day-to-day basis. This volume provides an overview of some of the most important advances in these areas today, including practical coverage of the daily applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library. M. NIRANJANAMURTHY, PHD, is an assistant professor in the Department of Computer Applications, M. S. Ramaiah Institute of Technology, Bangalore, Karnataka, India. He earned his PhD in computer science at JJTU. He has over 13 years of teaching experience and two years of industry experience as a software engineer. He has published four books and 85 papers in technical journals and conferences. He has six patents to his credit and has won numerous awards. HEMANT KUMAR GIANEY, PHD, is a senior assistant professor in the Computer Science Department at Vellore Institute of Technology, AP, India. He also worked at Thapar Institute of Engineering and Technology, Patiala, Punjab, India and worked as a post-doctoral researcher in the Computer Science and Engineering Department at National Cheng Kung University in Taiwan. He has over 15 years of teaching and industry experience. He has conducted many workshops and has been a guest speaker in various universities. He has also published many research papers on in scientific and technical journals. AMIR H. GANDOMI, PHD, is a professor of data science in the Department of Engineering and Information Technology, University of Technology Sydney. Before joining UTS, he was an assistant professor at the School of Business, Stevens Institute of Technology, NJ, and a distinguished research fellow at BEACON Center, Michigan State University. He has published over 150 journal papers and four books and collectively has been cited more than 14,000 times. He has been named as one of the world’s most influential scientific minds and a Highly Cited Researcher (top 1%) for three consecutive years, from 2017 to 2019. He has also served as associate editor, editor, and guest editor in several prestigious journals and has delivered several keynote talks. He is also part of a NASA technology cluster on Big Data, Artificial Intelligence, and Machine Learning. Preface xv1 IMPLEMENTATION TOOLS FOR GENERATING STATISTICAL CONSEQUENCE USING DATA VISUALIZATION TECHNIQUES 1Dr. Ajay B. Gadicha, Dr. Vijay B. Gadicha, Prof. Sneha Bohra and Dr. Niranjanamurthy M.1.1 Introduction 21.2 Literature Review 41.3 Tools in Data Visualization 41.4 Methodology 141.4.1 Plotting the Data 141.4.2 Plotting the Model on Data 151.4.3 Quantifying Linear Relationships 161.4.4 Covariance vs. Correlation 171.5 Conclusion 18References 182 DECISION MAKING AND PREDICTIVE ANALYSIS FOR REAL TIME DATA 21Umesh Pratap Singh2.1 Introduction 222.2 Data Analytics 232.2.1 Descriptive Analytics 232.2.2 Diagnostic Analytics 232.2.3 Predictive Analytics 232.2.4 Prescriptive Analytics 242.3 Predictive Modeling 242.4 Categories of Predictive Models 242.5 Process of Predictive Modeling 252.5.1 Requirement Gathering 262.5.2 Data Gathering 262.5.3 Data Analysis and Massaging 262.5.4 Machine Learning Statistics 262.5.5 Predictive Modeling 262.5.6 Prediction and Decision Making 272.6 Predictive Analytics Opportunities 272.6.1 Detecting Fraud 272.6.2 Reduction of Risk 272.6.3 Marketing Campaign Optimization 282.6.4 Operation Improvement 282.6.5 Clinical Decision Support System 282.7 Classification of Predictive Analytics Models 282.7.1 Predictive Models 282.7.2 Descriptive Models 292.7.3 Decision Models 292.8 Predictive Analytics Techniques 292.8.1 Predictive Analytics Software 292.8.2 The Importance of Good Data 302.8.3 Predictive Analytics vs. Business Intelligence 302.8.4 Pricing Information 302.9 Data Analysis Tools 302.9.1 Excel 302.9.2 Tableau 312.9.3 Power BI 312.9.4 Fine Report 312.9.5 R & Python 312.10 Advantages & Disadvantages of Predictive Modeling 312.10.1 Advantages 312.10.2 Disadvantages 322.10.2.1 Data Labeling 322.10.2.2 Obtaining Massive Training Datasets 322.10.2.3 The Explainability Problem 322.10.2.4 Generalizability of Learning 332.10.2.5 Bias in Algorithms and Data 332.11 Predictive Analytics Biggest Impact 332.11.1 Predicting Demand 332.11.2 Transformation Using Technology and Process 342.11.3 Improved Pricing 342.11.4 Predictive Maintenance 352.12 Application of Predictive Analytics 352.12.1 Financial and Banking Services 352.12.2 Retail 352.12.3 Health and Insurance 362.12.4 Oil and Gas Utilities 362.12.5 Public Sector 362.13 Future Scope of Predictive Modeling 362.13.1 Technological Advancements 372.13.2 Changes in Work 372.13.3 Risk Mitigation 372.14 Conclusion 37References 383 OPTIMIZING WATER QUALITY WITH DATA ANALYTICS AND MACHINE LEARNING 39Bin Liang, Zhidong Li, Hongda Tian, Shuming Liang, Yang Wang and Fang Chen3.1 Introduction 393.2 Related Work 413.3 Data Sources and Collection 423.4 Water Demand Forecasting 433.4.1 Network Flow and Zone Demand Estimation 433.4.2 Demand Forecasting 443.4.2.1 Feature Importance 453.4.2.2 Forecast Horizon 463.4.3 Performance Characterization 463.5 Re-Chlorination Optimization 493.5.1 Data 513.5.2 Water Age Estimation 523.5.2.1 Travel Time Estimation 533.5.2.2 Residential Time Estimation 543.5.3 Ammonia Prediction 543.5.4 Optimization Model Definition 573.5.5 Improvements in Customer Water Quality 593.5.6 Plant Dosing Optimization 623.6 Conclusion 63Acknowledgements 63References 634 LIP READING FRAMEWORK USING DEEP LEARNING AND MACHINE LEARNING 67Hemant Kumar Gianey, Parth Khandelwal, Prakhar Goel, Rishav Maheshwari, Bhannu Galhotra and Divyanshu Pratap Singh4.1 Introduction 684.1.1 Overview 684.1.2 Motivation 684.1.3 Lip Reading System Outcomes and Deliverables 694.2 The Emergence and Definition of the Lip-Reading System 704.2.1 Background of Domain 704.2.2 Identified Problems 784.2.3 Tools and Technologies Used 784.2.4 Implementation Aspects 784.2.4.1 Data Preparation 794.3 Design and Components of Lip-Reading System 824.4 Lip Reading System Architecture 824.5 Testing 844.6 Problems Encountered During Implementation 844.6.1 Assumptions and Constraints 854.7 Conclusion 854.8 Future Work 85References 865 NEW PERSPECTIVE TO MANAGEMENT, ECONOMIC GROWTH AND DEBT NEXUS ANALYSIS: EVIDENCE FROM INDIAN ECONOMY 89Edmund Ntom Udemba, Festus Victor Bekun, Dervis Kirikkaleli and Esra Sipahi Döngül5.1 Introduction 905.2 Literature Review 925.2.1 External Debt and Economic Growth 925.2.2 Trade Openness, FDI, and Economic Growth 945.2.3 FDI and Economic Growth 945.3 Data 955.3.1 Analytical Framework and Data Description 965.3.2 Theoretical Background and Specifications 965.3.2.1 Model Specification 985.4 Methodology and Findings 995.4.1 Unit Root Testing 995.4.2 Cointegration 995.4.3 Vector Error Correction Model 1035.4.4 Long-Run Relationship Estimation 1055.4.5 Causality Test 1075.5 Conclusion and Policy Implications 108Declarations 109Availability of Data and Materials 109Competing Interests 110Funding 110Authors’ Contributions 110Acknowledgments 110References 1106 DATA-DRIVEN DELAY ANALYSIS WITH APPLICATIONS TO RAILWAY NETWORKS 115Boyu Li, Ting Guo, Yang Wang and Fang Chen6.1 Introduction 1166.2 Related Works 1186.3 Background Knowledge 1196.3.1 Background and Problem Formulation 1206.3.1.1 Train Delay 1206.3.1.2 Delay Propagation 1216.3.2 Preliminaries 1226.3.2.1 Bayesian Inference 1236.3.2.2 Markov Property 1236.4 Delay Propagation Model 1236.4.1 Conditional Bayesian Delay Propagation 1236.4.1.1 Delay Self-Propagation 1246.4.1.2 Incremental Run-Time Delay 1256.4.1.3 Incremental Dwell Time Delay 1256.4.1.4 Accumulative Departure Delay 1266.4.2 Cross-Line Propagation, Backward Propagation and Train Connection Propagation 1276.5 Primary Delay Tracing Back 1306.5.1 Delay Candidates Selection 1306.5.2 Relation Construction 1316.5.2.1 Preceding and Following Trains 1316.5.2.2 Preceding and Connecting Trains 1316.6 Evaluation on Dwell Time Improvement Strategy 1326.7 Experiments 1356.7.1 Experiment Setting 1356.7.2 Temporal Prediction of Delay Propagation 1376.7.3 Spatial Prediction of Delay Propagation 1386.7.4 Case Study of Primary Delay Tracing Down 1396.7.5 Evaluation of Dwell Time Improvement Strategy 1406.8 Conclusion 142References 1427 PROPOSING A FRAMEWORK TO ANALYZE BREAST CANCER IN MAMMOGRAM IMAGES USING GLOBAL THRESHOLDING, GRAY LEVEL CO-OCCURRENCE MATRIX, AND CONVOLUTIONAL NEURAL NETWORK (CNN) 145Ms. Tanishka Dixit and Ms. Namrata Singh7.1 Introduction & Purpose of Study 1467.1.1 Segmentation 1467.1.1.1 Types of Segmentation 1477.1.2 Compression 1507.2 Literature Review & Motivation 1537.3 Proposed Work 1617.3.1 Algorithm 1617.3.2 Explanation 1627.3.3 Flowchart 1627.4 Observation Tables and Figures 1637.5 Conclusion 1767.6 Future Work 176References 1768 IOT TECHNOLOGIES FOR SMART HEALTHCARE 181Rehab A. Rayan, Imran Zafar and Christos Tsagkaris8.1 Introduction 1828.2 Literature Review 1838.2.1 IoT-Based Smart Health 1838.2.2 Advantages of Applying IoT in Health 1868.3 Findings 1878.3.1 Significant Features and Applications of IoT in Health 1878.3.1.1 Simultaneous Monitoring and Reporting 1898.3.1.2 End-to-End Connectivity and Affordability 1908.3.1.3 Data Analysis 1908.3.1.4 Tracking, Alerts, and Remote Medical Care 1908.3.1.5 Research 1918.3.1.6 Patient-Generated Health Data (PGHD) 1918.3.1.7 Management of Chronic Diseases and Preventative Care 1918.3.1.8 Home-Based and Short-Term Care 1928.4 Case Study: CyberMed as an IoT-Based Smart Health Model 1928.5 Discussions 1938.5.1 Limitations of Adopting IoT in Health 1938.5.1.1 Data Security and Privacy 1938.5.1.2 Connectivity 1948.5.1.3 Compatibility and Data Integration 1958.5.1.4 Implementation Cost 1958.5.1.5 Complexity and Risk of Errors 1958.6 Future Insights 1968.7 Conclusions 197References 1979 ENHANCEMENT OF SCALABILITY OF SVM CLASSIFIERS FOR BIG DATA 203Vijaykumar Bhajantri, Shashikumar G. Totad and Geeta R. Bharamagoudar9.1 Introduction 2049.2 Support Vector Machine 2059.2.1 Challenges 2089.3 Parallel and Distributed Mechanism 2099.3.1 Shared-Memory Parallelism 2099.4 Distributed Big Data Architecture 2109.4.1 Hadoop MapReduce 2109.4.2 Spark 2109.4.3 Akka 2119.5 Distributed High Performance Computing 2129.5.1 GASNet 2129.5.2 Charm++ 2139.6 GPU Based Parallelism 2149.6.1 Cuda 2159.6.2 OpenCL 2159.7 Parallel and Distributed SVM Algorithms 2179.7.1 Ls-svm 2189.7.2 Cascade SVM 2199.7.3 dc Svm 2209.7.4 Parallel Distributed Multiclass SVM Algorithms 2229.8 Conclusion and Future Research Directions 222References 22510 ELECTRICAL NETWORK-RELATED INCIDENT PREDICTION BASED ON WEATHER FACTORS 233Hongda Tian, Jessie Nghiem and Fang Chen10.1 Introduction 23310.2 Related Work 23510.3 Methodology 23510.3.1 Binary Classification of Incident and Normality 23510.3.2 Incident Categorization Using Natural Language Processing 23610.3.3 Classification of Multiple Types of Incidents 23610.4 Experiments 23710.4.1 Data Sets 23710.4.2 Evaluation Metrics 23910.4.3 Binary Classification 23910.4.4 Incident Categorization 24110.4.5 Multi-Class Classification 24210.5 Conclusion and Future Work 244Acknowledgements 244References 24511 GREEN IOT: ENVIRONMENT-FRIENDLY APPROACH TO IOT 247Abhishek Goel and Siddharth Gautam11.1 Introduction 24711.2 G-IoT (Green Internet of Things) 24911.3 Layered Architecture of G-IoT 25111.3.1 Data Center/Cloud 25211.3.2 Data Analytics and Control Applications It 25211.3.3 Data Aggregation and Storage 25311.3.4 Edge Computing 25311.3.5 Communication and Processing Unit 25411.4 Techniques for Implementation of G-IoT 25711.5 Power Saving Methods Based on Components 26611.6 Applications of G-IoT 26611.7 Challenges and Future Scope 26911.8 Case Study 26911.9 Conclusion 270References 27112 BIG-DATA ANALYTICS: A NEW PARADIGM SHIFT IN MICRO FINANCE INDUSTRY 275Vinay Pal Singh, Rohit Bansal and Ram Singh12.1 Introduction 27612.2 Reality of Area and Transcendent Difficulties 27612.2.1 Probable Overlending 27812.2.2 Information Imbalance 27812.2.3 Retreating Not-for-Profit Sector 27812.2.4 Neighbourhood Pressure 27912.3 Data Analytics in Microfinance 28012.3.1 Types of Data Analytics Used in Microfinance 28012.3.2 Use of Big Data in Microfinance Industry 28112.3.3 Risk and Data Based Credit Decisions 28212.3.4 Product Development and Selection 28312.3.5 Product or Service Positioning 28312.3.6 M-Commerce and E-Payments 28312.3.7 Making Reliable Credit Decisions 28412.3.8 Big Data-Driven Model Promises Psychometric Evaluations 28412.3.9 Product Build-Up, Service Positioning, and Offering 28412.4 Opportunities and Risks in Using Data Analytics 28412.5 Risk in Utilizing Big Data 28712.6 Conclusion 290References 29013 BIG DATA STORAGE AND ANALYSIS 293Namrata Dhanda13.1 Introduction 29313.1.1 6 V’s of Big Data 29413.1.2 Types of Data 29513.1.3 Issues in Handling Big Data 29713.2 Hadoop as a Solution to Challenges of Big Data 29713.2.1 The Hadoop Ecosystem 29813.2.2 Rack Awareness Policy in HDFS 30713.3 In-Memory Storage and NoSQL 30813.3.1 Key-Value Data Stores 30913.3.2 Document Stores 30913.3.3 Wide Column Stores 31013.3.4 Graph Stores 31013.3.5 Multi-Modal Databases 31013.4 Advantages of NoSQL Database 31013.5 Conclusion 311References 31114 A FRAMEWORK FOR ANALYSING SOCIAL MEDIA AND DIGITAL DATA BY APPLYING MACHINE LEARNING TECHNIQUES FOR PANDEMIC MANAGEMENT 313Mutyala Sridevi14.1 Introduction 31414.2 Literature Review 31414.3 Understanding Pandemic Analogous to a Disaster 31714.4 Application of Machine Learning Techniques at Various Phases of Pandemic Management 31814.4.1 Mitigation Phase 31914.4.2 Preparedness Phase 32014.4.3 Response Phase 32114.4.4 Recovery Phase 32114.5 Generalized Framework to Apply Machine Learning Techniques for Pandemic Management 32214.6 Conclusion 324References 324About the Editors 327Index 329
A Pocket Guide to Hci and Ux Design
Currently, the Human Computer Interaction (HCI) and User Experience (UX) design is a hot topic to nurture and practice in various industry as related knowledge is very relevant to create best quality consumer experiences and thus increases the chance of product/service/software acceptance in the market. This book provides concise information on HCI and UX Design. A practice-oriented contents are presented inside this book in these fields of study. This book covers principles of interaction design, Information Design, System design, user interface (UI) design, human factors engineering, essential UX process & methods, usability engineering etc. and fundamentals of UI prototyping is also covered in this book. Strategies to design interfaces for augmented reality (AR), virtual reality (VR), extended reality (ER), AI based Virtual Agents and Chatbots are also elaborated in this book. This book is also serving as a guide for design ethics and intellectual property rights (IPR). It is worth to have this book by the UX & UI design Practionars, and Aspirants of HCI and UX Design, to gain the knowledge in these domains very quickly. The UX design students and the students of Computer Science & Engineering can also refer this book as a tutorial for their curriculum.
Technical Building Blocks
This book offers comprehensive coverage of the various technologies and techniques used to build technical products. You will learn how technical product development is collaboratively done across multiple technical teams, primarily those in software engineering, data engineering, and AI/ML engineering. You will also be introduced to the technologies these teams use to develop features and products.Many roles in the organization work alongside these technical product development teams and act as liaisons between them, the stakeholders, the customers, and the leadership team. The people in these roles must understand technical aspects ranging from system design to artificial intelligence, and be able to engage in technical discussions with the engineering teams to determine the pros, cons, and risks associated with the development of a technology product or feature.Technical Building Blocks will help you master these technical skills. The book has just the right level of technical details to neither overwhelm with unnecessary technical depth, nor be superficial.From concepts to code snippets, authors Gaurav Sagar and Vitalii Syrovatskyi cover it all to give you an understanding of the engineer's mind and their work. Special emphasis on figures and charts will help you grasp complex ideas more quickly. After reading this book, you’ll be able to effectively communicate with engineering teams, provide valuable inputs in the system design review meetings of upcoming features and products, synthesize and simplify technical updates for cross-functional teams and stakeholders, and pass those dreaded technical interviews at your dream companies.WHAT YOU WILL LEARN* Intrinsic details of the teams and techniques used for product development * Concepts of cloud computing and its deployment models* System design fundamentals required to architect features and products * Evolution of data pipelines and data storage solutions to support big data* ML and deep learning algorithms to build intelligence into products* Securing products through identity and access management using cryptography* Role and working of blockchains, smart contracts, NFTs, and dApps in Web3 WHO THIS BOOK IS FORProfessionals in roles who work with software engineering teams and want to build their technical muscle, such as product managers, program managers, business analysts, project managers and product owners. Also useful for those preparing to crack the technical interview for these roles.GAURAV SAGAR is a director of product management at Salesforce, Inc. and has done product management at Indeed, Amazon Web Services, and Amazon payments. He has over 11 years of experience in building both consumer and enterprise products and has deep industry knowledge of cloud computing, online advertising, ecommerce, and fintech. He has multiple patents and speaks at conferences. He is also an avid programmer and was a data scientist prior to his transition in product management. He holds a M.S. in Business Analytics and a B.S. in Computer Science. In his off hours, he loves to hike and go on short road trips, besides programming for his hobby projects.VITALII SYROVATSKYI is an engineering manager at Google. Previously, he was the software development manager at Amazon where he led the development of products and features for Amazon Web Services (AWS) and Amazon payment products. He has over 15 years of experience in developing technical products, managing, and building engineering teams in multiple industries, namely, search advertising, cloud computing, capital management, online payments, and computer networking. He is founder of a tech company and has firsthand experience in leading cross-functional teams and managing all end-to-end aspects of the business. He has a M.S. and a B.S. in Mathematics, and a M.S. and a B.S. in Economics. Outside of work, he enjoys exploring the beautiful Pacific Northwest. Chapter 1: PRODUCT DEVELOPMENT - A SYNERGY OFTEAM, TECHNIQUES, AND TECHNOLOGIESComposition of a product team* The Product managerThe UX researcher and the UX Designer * The Product marketing managerThe Product scientist / Data Scientist* Popular software development methodologiesWaterfall vs Agile * Scrum vs KanbanVersion control* Need for version control Understanding Git * Gitfarm and Github Feature development using Git* Overview of core software development technologies OSI model and the Internet * Client side vs server sideCloud * MicroservicesData management * Artificial intelligenceCryptography * Federated Identity managementDevops and CI/CD* Rise of DevopsUnderstanding CI / CD* Metrics monitoring Tracking health - System metrics * Tracking success - Product metrics (A/B tests, multivariate tests, multiarmed bandit models)CHAPTER 2: CLOUD - ON DEMAND COMPUTING RESOURCES FOR SCALE AND SPEED* History of cloud * Motivations for cloud adoption Cloud delivery models* IaaS vs PaaS vs SaaSCloud deployment models* Public / Private / HybridVirtualization* OS based vs Hardware basedVirtualization management* ContainerizationContainer architecture * Containers vs VMsInfrastructure as code * Serverless compute Cloud storage * Cloud security and NetworkingThreats and need for security * Data centers and the ISPsVirtual private networks and Access control lists * Firewalls and Load balancersIdentity and access management* Service quality metrics (SLAs)Use cases* Configuring a virtual machine in public cloud (EC2)Static website using object storage in public cloud (S3)CHAPTER 3: SYSTEM DESIGN: ARCHITECTING ROBUST, SCALABLE AND MODULAR APPLICATIONS* Need for distributed system design* Monolithics and some issues* Vertical and horizontal scalingKey characteristics of distributed systems * Considerations and trade-offsPerformance and scalability * Latency and throughputAvailability and consistency* MicroservicesCommunication style* RESTful, RPC, Webhook and GraphQLAPI gateway and service discovery * API documentation API measures (Latency, Availability, Robustness) * Use case: Building a RESTful APIContent delivery networks (CDNs) * Load balancer and Reverse proxyDatabase* Relational database management system Replication * FederationDenormalization and Sharding * NoSQL systems* Key-value storeDocument store * Columnar databases Graph databases* CacheMotivation * Types of caching (Client, CDN, server, application)CDN* AsynchronismTesting and Security * Use casesBuilding a ticketing system (like ticketmaster) * Building a video streaming service (like Netflix)CHAPTER 4: DATA ENGINEERING AND ANALYTICS - MANAGING DATA AND DERIVING INSIGHTS* Data engineering and analytics* Evolution of data needs * Supply chain of data (from raw to actionable insights)* Data storage * Streaming data sources* NoSQL databasesRDBMS * Data warehouseData lake* Data pipelinesData cleaning and transformation * ETLWorkflow orchestration (Airflow)* Big dataData vs Big data * Big data formats (Parquet, ORC, Avro)Data Analytics* Streaming vs batch analyticsPopular analysis tools* Hadoop and HivePresto and Spark* Popular data analytics platformPowerBI, Tableau, Looker * Offerings from public cloud providersCHAPTER 5: ARTIFICIAL INTELLIGENCE - BUILDING INTELLIGENCE THROUGHAUTOMATIC LEARNING* Relationship of Machine learning and Deep learning Learning approaches of machine learning * Steps to solve a machine learning problemOverview of ML algorithms * Popular (shallow) ML algorithmsUses cases - Shallow ML in action * Overview of deep learning algorithmsPopular deep learning algorithms * Use cases - Deep learning in actionWhen not to use deep learning * Rise of AI EthicsCHAPTER 6: INFORMATION SECURITY - SAFEGUARDING RESOURCES AND BUILDING TRUST* Need for securing digital assetsEncryption and hashing * Digital signaturesPublic key infrastructure * Certificate management (TLS)Identity Management* Single sign-on SAML * Openid / OauthAccess Management* RBACABAC* Use CasesUse of digital signatures in Docusign * Use of JWT for financial transactions through StripeCHAPTER 7: Specialty technologies - Special purpose technologies gaining traction* Blockchain * History * StructurePopular applications (Cryptocurrencies and NFTs) * Use case: Building a simple block chainInternet of things (IoT)* HistoryIoT architecture * IoT ApplicationsChallenges and criticism * IoT, Edge computing and 5GConcept and applications* Virtual realityDevelopments over time * Mixed realityApplications * ConcernsSearch Engines* Information retrievalImportance of relevance * Semantic search enginesUse case: Building a search engine using elastic searchAppendix* INSTALLING VIRTUALBOX * Windows * MacOS * Linux (Ubuntu)* LINUX 101* Linux vs Mac OS vs WindowsDirectory structure of linux * Basic linux management through command line* INSTALLING DOCKER * Windows MacOS * Linux (Ubuntu)* INTRODUCTION TO PYTHON * Variables Data structures (Lists, Tuples, Dictionaries and Sets) * Flow control: Conditional statements and loopsFunctions * Classes* Modules and Packages
Certified OpenStack Administrator Study Guide
Gain a better understanding of how to work with the modern OpenStack IaaS Cloud platform. This updated book is designed to help you pass the latest “Yoga” version of the Certified OpenStack Administrator (COA) exam from the Open Infrastructure Foundation. OpenStack is a cloud operating system that controls large pools of computer storage and networking resources throughout a datacenter.All exercises have been updated and re-written for the current version of the exam using the modern CLI tool. This book covers 100% of the exam requirements and each topic is taught using practical exercises and instructions for the command line and for the Horizon dashboard. All chapters are followed by review questions and answers.Even after you have taken and passed the COA exam, this book will remain a useful reference to come back to time after time.WHAT YOU WILL LEARN* Understand the components that make up the Cloud* Install OpenStack distribution from Red Hat, Canonical or community versions* Run OpenStack in a virtual test environment* Understand where to find information for to further work with OpenStackWHO THIS BOOK IS FOR__Cloud and Linux engineers who want to pass the Certified OpenStack Administrator Exam.ANDREY MARKELOV is an experienced Linux and Cloud architect who has worked for large Russian and International companies (LANIT, Red Hat and Ericsson, currently). He has written and published more than fifty articles about Linux and Unix systems services, virtual systems and open source (Linux Format RE, Сomputerra, PCWeek/RE and others). Andrey is the author of the only Russian OpenStack book. He has been teaching Microsoft and Red Hat authorized courses for over 10 years. Andrey is a Red Hat Certified Architect since 2009, and is also a Microsoft Certified System Engineer, Sun Certified System Administrator, Novell Certified Linux Professional, Mirantis Certified OpenStack Administrator, and VMware Certified Professional.CHAPTER 1: GETTING STARTED with Certified OpenStackWhat is Certified OpenStack Administrator Exam?Tips for COA Exam PreparationOther OpenStack CertificationsUnderstanding the Components That Make Up the CloudHistory of OpenStack ProjectOpenStack Distribution and VendorsCHAPTER 2: HOW TO BUILD YOUR OWN VIRTUAL TEST ENVIRONMENTInstalling Vanilla OpenStack with the DevStack ToolInstalling RDO OpenStack Distribution with PackStackInstalling Ubuntu OpenStack with MicrostackCHAPTER 3: OPENSTACK APISUsing the OpenStack CLICreate and manage RC files to authenticate with Keystone for command line useArchitecture of HorizonVerify Operation of the DashboardReview QuestionAnswer to Review QuestionCHAPTER 4: IDENTITY MANAGEMENTArchitecture and Main Components of KeystoneManaging Keystone Catalog Services and EndpointsManaging/Creating Domains, Projects, Users, and RolesCreate and manage policy files and user access rulesManaging and Verifying Operation of the Identity ServiceReview QuestionsAnswers to Review QuestionsCHAPTER 5: IMAGE MANAGEMENTArchitecture and Main Components of GlanceDeploying a New Image to an OpenStack InstanceManaging ImagesManaging Image Back EndsVerifying Operation of the Image ServiceReview QuestionsAnswers to Review QuestionsCHAPTER 6: OPENSTACK NETWORKINGArchitecture and Components of NeutronArchitecture of Open vSwitchManage Network ResourcesManage Project Security Group RulesManage QuotasManage network interfaces on compute instancesVerify Operation of Network ServiceReview QuestionsAnswers to Review QuestionsCHAPTER 7: OPENSTACK COMPUTEArchitecture and Components of NovaManaging FlavorsManaging and Accessing an Instance Using a KeypairLaunching, Shutting Down, and Terminating the InstanceConfigure an instance with a floating IPManaging Instance SnapshotsManaging QuotasGetting Nova StatsManage Nova host consoles (VNC, NOVNC, spice)Verifying Operation and Managing Nova Compute ServersReview QuestionsAnswers to Review QuestionsCHAPTER 8: OPENSTACK OBJECT STORAGEOverview of Swift Object StorageManaging Permissions on a Container in Object StorageUsing the cURL Tool for Working with SwiftManaging Expiring ObjectsMonitoring Swift ClusterReview QuestionsAnswers to Review QuestionsCHAPTER 9: BLOCK STORAGEArchitecture and Components of CinderManage Volume and Mount It to a Nova InstanceCreate Volume Group for Block StorageManage QuotasBack Up and Restore Volumes and SnapshotsManage Volume SnapshotsManage Volumes EncryptionSet Up Storage PoolsReview QuestionsAnswers to Review QuestionsCHAPTER 10: TROUBLESHOOTINGThe Main Principles of TroubleshootingHow to Check the OpenStack VersionWhere to Find and How to Analyze Log FilesBack Up the Database Used by an OpenStack InstanceAnalyze Host/Guest OS and Instance StatusAnalyze Messaging ServersAnalyze Network StatusDigest the OpenStack EnvironmentReview QuestionsAnswers to Review QuestionsCHAPTER 11: CONCLUSIONANNEX: ORCHESTRATION OF OPENSTACK WITH HEAT
Introduction to Transformers for NLP
Get a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing.This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation.After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library.WHAT YOU WILL LEARN* Understand language models and their importance in NLP and NLU (Natural Language Understanding)* Master Transformer architecture through practical examples* Use the Hugging Face library in Transformer-based language models* Create a simple code generator in Python based on Transformer architectureWHO THIS BOOK IS FORData Scientists and software developers interested in developing their skills in NLP and NLU (Natural Language Understanding)Shashank Mohan Jain has been working in the IT industry for around 20 years mainly in the areas of cloud computing, machine learning and distributed systems. He has keen interests in virtualization techniques, security, and complex systems. Shashank has software patents 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 LANGUAGE MODELSChapter Goal: History and introduction to language modelsSub-topics:• What is a language model• Evolution of language models from n-grams to now Transformer based models• High-level intro to Google BERTCHAPTER 2: TRANSFORMERSChapter Goal: Introduction to Transformers and their architectureSub-topics:Introduction to Transformers• Deep dive into Transformer architecture and how attention plays a key role in Transformers• How Transformer realizes tasks like sentiment analysis, Q&A, sentence masking, etc.CHAPTER 3: INTRO TO HUGGING FACE LIBRARYChapter Goal: Gives an introduction to Hugging Face libraries and how they are used in achieving NLP tasksSub-topics:• What is Hugging Face, and how its emerge as a relevant library for various data sets and models related to NLP• Creating simple Hugging Face applications for NLP tasks like sentiment analysis, sentence masking, etc.• Play around with different models available in the IT space.CHAPTER 4: CODE GENERATORChapter Goal: Cover an example of a code generator using Transformer architecture.Sub-topics:• Creating a simple code generator wherein user input is text in NLP like sorting a given array of numbers.• The generator will take the user text and generate Python code or YAML (yet another markup language)file as an example for Kubernetes• Deploying the model on the cloud as a service in KubernetesCHAPTER 5: TRANSFORMER BASED APPLICATIONSChapter Goal: Summary of the topics around Transformers, Hugging Face libraries, and their usage.Subtopics:• Summary of Transformer based applications and language models.• Summarize Hugging Face libraries and why how they are relevant in NLP.
Target C#
So, you want to learn C# and Visual Studio 2022, but are a bit intimidated? Don’t be. Programming is within your grasp! Programmers at any level have to fully understand, and more importantly, be able to code the core constructs. It is impossible to use complex programming concepts such as classes before understanding what methods and variables and their data types are. Once there is a foundation built on the basics, then all other topics can fall in line.While it is a forgone conclusion that languages change with the introduction of new features, the core concepts do not. Even large enterprises do not always update to the latest versions of languages and frameworks; their "backbone" applications have been developed to work, regardless. More than ever, enterprises need developers who can master and apply the core programming concepts and then be "up-skilled" with newer language levels and features as they integrate into the company.This book builds from the ground up. You will begin with an introduction to programming, learning the foundational concepts needed to become a C# programmer. You will then put to practice a wide range of programming concepts, including data types, selection, iteration, arrays, methods, classes and objects, serialization, file handling, and string handling. You will learn enough to develop applications that emulate commercial application code. Once you’ve got the foundational concepts, get ready to dive into common programming routines, including linear search, binary search, bubble sort and insertion sort, and use C# to code them. Code example annotations supplement the learning and are designed to enhance learning while also explaining why the code does what it does. This book:* Teaches core programming through well-explained and simple-to-follow instructions* Reinforces programming skills through the use of coding examples that extend user learnings* Explains theoretical programming concepts; applies them practically with code examples * Introduces the latest Microsoft C# Integrated Development Environment (Visual Studio 2022)* Enlists clear, precise, and easy-to-understand language to assist readers of all levels and experience* Uses a mix of "theory" and practical information that is designed to be friendly and engagingWHO THIS BOOK IS FORBeginners, those refreshing their C# skills, or those moving from another programming language. No skills or previous knowledge is required. Readers will need to download Visual Studio 2022 Community Edition as this is what the book code has been based on, but they could use other Integrated Development Environments.GERARD BYRNE is Senior Technical Trainer for a US-based Forbes 100 company. He works to up-skill and re-skill software engineers who develop business-critical software applications. He also helps refine the programming skills of "returners" to the workforce, and introduces new graduates to the application of software development within the commercial environment.Gerard's subject expertise has been developed over a multi-decade career as a teacher, lecturer, and technical trainer in a corporate technology environment. He has delivered a range of courses across computer languages and frameworks, and understands how to teach skills and impart knowledge to a range of learners. He has taught people in the use of legacy technologies such as COBOL and JCL and more "modern" technologies and frameworks such as C#, Java, Spring, Android, JavaScript, Node, HTML, CSS, Bootstrap, React, Python, and Test-Driven Development.Gerard has mastered how to teach difficult concepts in a simple way that makes learning accessible and enjoyable. The content of his notes, labs, and other materials follow the simple philosophy of keeping it simple, while making the instructions detailed. He is passionate about software development and believes we can all learn to write code if we are patient and understand the basic coding concepts.Chapter 1. .NETChapter 2. Software InstallationChapter 3. IntroductionChapter 4. Input and OutputChapter 5. Commenting CodeChapter 6. Data TypesChapter 7. Casting and ParsingChapter 8. ArithmeticChapter 9. SelectionChapter 10. IterationChapter 11. ArraysChapter 12. MethodsChapter 13. ClassesChapter 14. InterfacesChapter 15. String HandlingChapter 16. File HandlingChapter 17. Exception HandlingChapter 18. SerializationChapter 19. StructsChapter 20. EnumerationsChapter 21. DelegatesChapter 22. EventsChapter 23. GenericsChapter 24. Common RoutinesChapter 25. Programming LabsChapter 26. C# 11
MCA Microsoft Certified Associate Azure Security Engineer Study Guide
PREPARE FOR THE MCA AZURE SECURITY ENGINEER CERTIFICATION EXAM FASTER AND SMARTER WITH HELP FROM SYBEXIn the MCA Microsoft Certified Associate Azure Security Engineer Study Guide: Exam AZ-500, cybersecurity veteran Shimon Brathwaite walks you through every step you need to take to prepare for the MCA Azure Security Engineer certification exam and a career in Azure cybersecurity. You’ll find coverage of every domain competency tested by the exam, including identity management and access, platform protection implementation, security operations management, and data and application security. You’ll learn to maintain the security posture of an Azure environment, implement threat protection, and respond to security incident escalations. Readers will also find:* Efficient and accurate coverage of every topic necessary to succeed on the MCA Azure Security Engineer exam* Robust discussions of all the skills you need to hit the ground running at your first—or next—Azure cybersecurity job* Complementary access to online study tools, including hundreds of bonus practice exam questions, electronic flashcards, and a searchable glossaryThe MCA Azure Security Engineer AZ-500 exam is a challenging barrier to certification. But you can prepare confidently and quickly with this latest expert resource from Sybex. It’s ideal for anyone preparing for the AZ-500 exam or seeking to step into their next role as an Azure security engineer. ABOUT THE AUTHORSHIMON BRATHWAITE is Editor-in-Chief of securitymadesimple.org, a website dedicated to teaching business owners how to secure their companies and helping cybersecurity professionals start and advance their careers. He is the author of three cybersecurity books and holds CEH, Security+, and AWS Security specialist certifications. Introduction xixAssessment Test xxvCHAPTER 1 INTRODUCTION TO MICROSOFT AZURE 1What Is Microsoft Azure? 3Cloud Environment Security Objectives 4Confidentiality 4Integrity 4Availability 5Nonrepudiation 5Common Security Issues 5Principle of Least Privilege 5Zero-Trust Model 6Defense in Depth 6Avoid Security through Obscurity 9The AAAs of Access Management 9Encryption 10End-to-End Encryption 11Symmetric Key Encryption 11Asymmetric Key Encryption 11Network Segmentation 13Basic Network Configuration 13Unsegmented Network Example 14Internal and External Compliance 15Cybersecurity Considerations for the Cloud Environment 16Configuration Management 17Unauthorized Access 17Insecure Interfaces/APIs 17Hijacking of Accounts 17Compliance 18Lack of Visibility 18Accurate Logging 18Cloud Storage 18Vendor Contracts 19Link Sharing 19Major Cybersecurity Threats 19DDoS 19Social Engineering 20assword Attacks 21Malware 21Summary 24Exam Essentials 24Review Questions 26CHAPTER 2 MANAGING IDENTITY AND ACCESS IN MICROSOFT AZURE 29Identity and Access Management 31Identifying Individuals in a System 31Identifying and Assigning Roles in a System and to an Individual 32Assigning Access Levels to Individuals or Groups 33Adding, Removing, and Updating Individuals and Their Roles in a System 33Protecting a System’s Sensitive Data and Securing the System 33Enforcing Accountability 34IAM in the Microsoft Azure Platform 34Creating and Managing Azure AD Identities 34Managing Azure AD Groups 37Managing Azure Users 39Adding Users to Your Azure AD 39Managing External Identities Using Azure AD 40Managing Secure Access Using Azure Active Directory 42Implementing Conditional Access Policies, Including MFA 44Implementing Azure AD Identity Protection 45Enabling the Policies 47Implement Passwordless Authentication 50Configuring an Access Review 52Managing Application Access 57Integrating Single Sign-On and Identity Providers for Authentication 57Creating an App Registration 58Configuring App Registration Permission Scopes 58Managing App Registration Permission Consent 59Managing API Permission to Azure Subscriptions 60Configuring an Authentication Method for a Service Principal 61Managing Access Control 62Interpret Role and Resource Permissions 62Configuring Azure Role Permissions for Management Groups, Subscriptions, Resource Groups, and Resources 63Assigning Built-In Azure AD Roles 64Creating and Assigning Custom Roles, Including Azure Roles and Azure AD Roles 65Summary 66Exam Essentials 67Review Questions 70CHAPTER 3 IMPLEMENTING PLATFORM PROTECTIONS 73Implementing Advanced Network Security 75Securing Connectivity of Hybrid Networks 75Securing Connectivity of Virtual Networks 77Creating and Configuring Azure Firewalls 78Azure Firewall Premium 79Creating and Configuring Azure Firewall Manager 82Creating and Configuring Azure Application Gateway 82Creating and Configuring Azure Front Door 87Creating and Configuring a Web Application Firewall 91Configuring Network Isolation for Web Apps and Azure Functions 93Implementing Azure Service Endpoints 94Implementing Azure Private Endpoints, Including Integrating with Other Services 97Implementing Azure Private Link 98Implementing Azure DDoS Protection 101Configuring Enhanced Security for Compute 102Configuring Azure Endpoint Protection for VMs 102Enabling Update Management in Azure Portal 104Configuring Security for Container Services 108Managing Access to the Azure Container Registry 109Configuring Security for Serverless Compute 109Microsoft Recommendations 111Configuring Security for an Azure App Service 112Exam Essentials 118Review Questions 122CHAPTER 4 MANAGING SECURITY OPERATIONS 125Configure Centralized Policy Management 126Configure a Custom Security Policy 126Create Custom Security Policies 127Creating a Policy Initiative 128Configuring Security Settings and Auditing by Using Azure Policy 129Configuring and Managing Threat Protection 130Configuring Microsoft Defender for Cloud for Servers (Not Including Microsoft Defender for Endpoint) 131Configuring Microsoft Defender for SQL 134Using the Microsoft Threat Modeling Tool 139Azure Monitor 147Visualizations in Azure Monitor 148Configuring and Managing Security Monitoring Solutions 149Creating and Customizing Alert Rules by Using Azure Monitor 149Configuring Diagnostic Logging and Retention Using Azure Monitor 157Monitoring Security Logs Using Azure Monitor 159Microsoft Sentinel 167Configuring Connectors in Microsoft Sentinel 170Evaluating Alerts and Incidents in Microsoft Sentinel 175Summary 176Exam Essentials 177Review Questions 179CHAPTER 5 SECURING DATA AND APPLICATIONS 183Configuring Security for Storage in Azure 184Storage Account Access Keys 185Configuring Access Control for Storage Accounts 185Configuring Storage Account Access Keys 189Configuring Azure AD Authentication for Azure Storage and Azure Files 191Configuring Delegated Access for Storage Accounts 202Configuring Security for Databases 220Summary 254Exam Essentials 255Review Questions 257APPENDIX A AN AZURE SECURITY TOOLS OVERVIEW 261Chapter 2, “Managing Identity and Access on Microsoft Azure” 262Azure Active Directory (AD) 262Microsoft Authenticator App 265Azure API Management 265Chapter 3, “Implementing Platform Protections” 266Azure Firewall 266Azure Firewall Manager 267Azure Application Gateway 269Azure Front Door 273Web Application Firewall 273Azure Service Endpoints 274Azure Private Links 274Azure DDoS Protection 275Microsoft Defender for Cloud 276Azure Container Registry 277Azure App Service 278Chapter 4, “Managing Security Operations” 279Azure Policy 279Microsoft Threat Modeling Tool 281Microsoft Sentinel 287How Does Microsoft Sentinel Work? 289Automation 290Chapter 5, “Securing Data and Applications” 290Azure Key Vault 299APPENDIX B ANSWERS TO REVIEW QUESTIONS 301Chapter 1: Introduction to Microsoft Azure 302Chapter 2: Managing Identity and Access in Microsoft Azure 303Chapter 3: Implementing Platform Protections 304Chapter 4: Managing Security Operations 305Chapter 5: Securing Data and Applications 306Index 309
CompTIA Project+ Practice Tests
AN INDISPENSABLE STUDY AID FOR AN IN-DEMAND PROJECT MANAGEMENT CERTIFICATIONIn the newly updated second edition of CompTIA Project+ Practice Tests: Exam PK0-005, veteran tech educator and project manager Brett J. Feddersen delivers an indispensable study aid for anyone preparing for the CompTIA Project+ certification exam or a new career in project management. This new edition is fully revised to reflect recent changes to the Project+ PK0-005 exam, and offers new questions that emphasize the importance of agile and other iterative project management methodologies commonly used in IT environments. You’ll explore every objective covered by the Project+ exam, including project management concepts, project life cycle phases, project tools and documentation, and the basics of information technology and governance. You’ll also find:* Hands-on and practical information you can use immediately to prepare for a new career in project management, or for expanding your existing skillset* Hundreds of domain-by-domain questions that pinpoint exactly where you excel and where you need more training* A true-to-life testing format that prepares you for the real-world exam and reduces test anxiety so you can focus on succeeding your first time taking the testA can’t-miss resource for aspiring and veteran project managers, CompTIA Project+ Practice Tests: Exam PK0-005, Second Edition, belongs in the hands of anyone hoping to master the latest version of the Project+ exam or distinguish themselves on their first day of a new project management job. ABOUT THE AUTHORBRETT J. FEDDERSEN, Project+, MPS, PMP, is a career public servant with 25 years of experience in government including the United States Marine Corps, the state of Colorado, the city of Boulder (Colorado), and with the Regional Transportation District (RTD) in the Denver/Metro area. Brett has been a certified project manager since 2007, and has contributed to several books on both CompTIA Project+ and the PMP exams. In additional to his commitment to the project management community, Brett is passionate about leadership and organizational excellence, and has contributed to several cultural revolutions helping government agencies transform into high performing organizations. Introduction xvChapter 1 Project Management Concepts (Domain 1.0) 1Chapter 2 Project Life Cycle Phases (Domain 2.0) 39Chapter 3 Tools and Documentation (Domain 3.0) 79Chapter 4 Basics of IT and Governance (Domain 4.0) 123Chapter 5 Practice Test 1 163Chapter 6 Practice Test 2 183APPENDIX ANSWERS TO REVIEW QUESTIONS 203Chapter 1: Project Management Concepts (Domain 1.0) 204Chapter 2: Project Life Cycle Phases (Domain 2.0) 218Chapter 3: Tools and Documentation (Domain 3.0) 232Chapter 4: Basics of IT and Governance (Domain 4.0) 246Chapter 5: Practice Test 1 261Chapter 6: Practice Test 2 268Index 275
Building Quality Shaders for Unity®
Understand what shaders are and what they’re used for: Shaders are often seen as mystical and difficult to develop, even by skilled programmers, artists, and developers from other game design disciplines. This book dispels that idea by building up your shader knowledge in stages, starting with fundamental shader mathematics and how shader development mindset differs from other types of art and programming, and slowly delves into topics such as vertex and fragment shaders, lighting, depth-based effects, texture mapping, and Shader Graph.This book presents each of these topics with a comprehensive breakdown, the required theory, and some practical applications for the techniques learned during each chapter. The HLSL (High Level Shading Language) code and Shader Graphs will be provided for each relevant section, as well as plenty of screenshots.By the end of this book, you will have a good understanding of the shader development pipeline and you will be fully equipped to start making your own aesthetic and performant shader effects for your own games!YOU WILL LEARN TO• Use shaders across Unity’s rendering pipelines• Write shaders and modify their behavior with C# scripting• Use Shader Graph for codeless development• Understand the important math behind shaders, particularly space transformations• Profile the performance of shaders to identify optimization targetsWHO IS THIS BOOK FORThis book is intended for beginners to shader development, or readers who may want to make the jump from shader code to Shader Graph. It will also include a section on shader examples for those who already know the fundamentals of shaders and are looking for specific use cases. Daniel Ilett is an ambitious and motivated PhD student at the University of Warwick. He is a passionate game developer, specialising in shaders and technical art. He publishes a range of educational and tutorial content, including videos and written work, aimed at beginners and intermediate developers. He also does freelance work on shaders and visual effects for games. Chapter 1: Introduction to Shaders in UnitySub-topics:• Brief overview of shader fundamentals• Unity’s built-in pipeline• URP (Universal Render Pipeline)• HDRP (High Definition Render Pipeline)Chapter 2: Maths for Shader DevelopmentSub-topics:• Vectors in 2D and 3D• Dot product, cross product, and other vector operations• Matrices• Multiplication, transpose, inverse, and common matrix operations• Important spaces in computer graphics• Homogeneous coordinate systems• Transformation between spacesChapter 3: Your Very First ShaderSub-topics:• The shader pipeline, and data flow• ShaderLab, SubShaders and Fallbacks• Shader Tags• The appdata struct: Input to the vertex shader• The vertex shader• The v2f struct: Data passed between the vertex and fragment shader• The fragment shaderChapter 4: Shader GraphSub-topics:• The argument for node-based editors• The vertex and fragment stages• Shader nodes & properties• Your first Shader GraphChapter 5: Textures, UV Coordinates & Normal MappingSub-topics:• What is texture mapping?• What are UV coordinates?• Scaling, rotating and offsetting UVs• Sampler states• Normal mapping & tangent spaceChapter 6: TransparencySub-topics:• Transparency vs opacity• Alpha-blended transparency• Sorting• Screen-door (“dithered”) transparencyChapter 7: The Depth Buffer• What is the depth buffer?• Depth-testing and culling• Depth-based shader effectsChapter 8: More Shader FundamentalsSub-topics:• Shader keywords and variants• Single- and multi-pass shaders• GrabPass and UsePass• Unity’s standard shader librariesChapter 9: Lighting & ShadowsSub-topics:• Lighting theory: Diffuse, specular, ambient, and Fresnel light• Phong shading• Physically based rendering• Shadow castingChapter 10: Image Effects & Post ProcessingSub-topics:• Post Processing in the Built-in pipeline, URP and HDRP• Convolution kernels, Gaussian blur and multi-pass effects.• Edge detection with a Sobel kernel• Better edge detection using the depth texture and normal textureChapter 11: Advanced ShadersSub-topics:• Geometry shaders: adding or modifying vertices• Tessellation shaders: subdividing a mesh• Building an LOD system with tessellation shaders• Compute shaders: arbitrary computation on the GPUChapter 12: Profiling & OptimizationSub-topics:• The Unity Profiler and Frame Debugger• Branching in shaders• Avoiding overdraw• Multi-material objects• BatchingChapter 13: Shader Recipes For Your GamesSub-topics:• World-space reconstruction in post processing shaders• Custom lighting: cel-shading (toon shading)• Vertex displacement – realistic water (Gerstner waves)• Refraction by modifying the framebuffer• Interactive snow layers (modifying the height of a mesh based on gameplay actions)• Holograms using emissive colour• Using Voronoi noise to make marble
Hyperrealität und Transhumanismus
Digitale Technologien sind heute ein fester Bestandteil des Alltags. Der Mensch wird zunehmend selbst zu einem Teil dieses Netzwerks aus Maschinen. Der französische Soziologe Jean Baudrillard beschreibt bereits vor mehreren Jahrzehnten eine solche Welt, in der sich Realität und Fiktion nicht länger unterscheiden lassen. Sie verschmelzen untrennbar zu einer neuen Realität, einer Hyperrealität, in der jeglicher Bezug zu den eigentlichen Phänomenen verloren gegangen ist. Der Transhumanismus hat die Verbesserung des Menschen durch Technologien im Fokus. Durch die Verbindung des biologischen Körpers mit Maschinen sollen die natürlichen Grenzen seiner physischen und mentalen Leistungsfähigkeit überwunden werden. Der Mensch soll seine Evolution aktiv gestalten, um sich letztendlich zu einem posthumanen Wesen zu entwickeln. Dieser Fortschritt erscheint nötig, um nicht durch Maschinen ersetzt zu werden. Auf den ersten Blick wirken viele Ideen zu Cyborgs und Künstlicher Intelligenz wie Science-Fiction Vorstellungen. Jean Baudrillard greift Bilder dieser Art auf und illustriert an ihnen, wie die Welt bereits ist. Eine fiktive Welt, die zur Wirklichkeit wird – Mirco Spiegel untersucht in diesem Buch, ob Visionen des Transhumanismus ein Teil davon sind.
Weighted Automata, Formal Power Series and Weighted Logic
The main objective of this work is to represent the behaviors of weighted automata by expressively equivalent formalisms: rational operations on formal power series, linear representations by means of matrices, and weighted monadic second-order logic. First, we exhibit the classical results of Kleene, Büchi, Elgot and Trakhtenbrot, which concentrate on the expressive power of finite automata. We further derive a generalization of the Büchi–Elgot–Trakhtenbrot Theorem addressing formulas, whereas the original statement concerns only sentences. Then we use the language-theoretic methods as starting point for our investigations regarding power series. We establish Schützenberger’s extension of Kleene’s Theorem, referred to as Kleene–Schützenberger Theorem. Moreover, we introduce a weighted version of monadic second-order logic, which is due to Droste and Gastin. By means of this weighted logic, we derive an extension of the Büchi–Elgot–Trakhtenbrot Theorem. Thus, we point out relations among the different specification approaches for formal power series. Further, we relate the notions and results concerning power series to their counterparts in Language Theory. Overall, our investigations shed light on the interplay between languages, formal power series, automata and monadic second-order logic. Introduction.- Languages, Automata and Monadic Second-Order Logic.- Weighted Automata.- The Kleene–Schützenberger Theorem.- Weighted Monadic Second-Order Logic and Weighted Automata.- Summary and Further Research.
Beginning Eleventy
Leverage the power of Eleventy to quickly produce static sites that are efficient and fast. This project-oriented book simplifies the process of setting up Eleventy and manipulating content, using little more than a text editor or free software.It will equip you with a starting tool set that you can use to develop future projects or incorporate into your existing workflow. More importantly, you'll take websites to the next level, reducing the reliance on tools that are bloated, prone to being hacked and not the most efficient. Beginning Eleventy is an excellent resource for getting acquainted with creating and manipulating blogs using a static site generator approach. It takes the view that you don’t have to create something complex and unwieldy; you can build something quickly, then extend it using the power of the API and plugins over time, without sacrificing speed or features.WHAT YOU’LL LEARN:* Implement the Eleventy framework in a project* Explore some of the options for customizing content using the framework* Gain an appreciation of pointers around maintenance requirements, and how this might compare to other blog systems* Work through some example projects, to help build up a working blog from standalone demos to implementing with other tools or librariesTHIS BOOK IS FOR?* Website developers who are already familiar with JavaScript, who are looking for a fast and simple framework to deliver high quality results fast* Developers who are looking to leverage the Eleventy framework to quickly create an online blog using little more than a text editor, producing optimized content in modern browsers using tools they will already have* Those in agile development teams, where time is of the essence and need to deliver high quality results quicklyALEX LIBBY is a frontend engineer and seasoned computer book author who hails from England. His passion for all things Open Source dates back to the days of his degree studies, where he first came across web development and has been hooked ever since. His daily work involves extensive use of React, NodeJS, JavaScript, HTML, and CSS; Alex enjoys tinkering with different open source libraries to see how they work. He has spent a stint maintaining the jQuery Tools library and enjoys writing about Open Source technologies, principally for front end UI development.INTRODUCTIONChapter 1: Introducing EleventyChapter 2: Creating StructureChapter 3: Sourcing DataChapter 4: Creating TemplatesChapter 5: Configuring OptionsChapter 6: Styling the Site and ContentChapter 7: Creating PluginsChapter 8: Internationalizing the SiteChapter 9: Localizing ContentChapter 10: Polishing the SiteChapter 11: Deployment and Publishing
Cognitive Computing Models in Communication Systems
COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMSA CONCISE BOOK ON THE LATEST RESEARCH FOCUSING ON PROBLEMS AND CHALLENGES IN THE AREAS OF DATA TRANSMISSION TECHNOLOGY, COMPUTER ALGORITHMS, AI-BASED DEVICES, COMPUTER TECHNOLOGY, AND THEIR SOLUTIONS.The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area. The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques. Readers will find in this succinctly written and unique book:* Topics covering the applications of advanced cognitive devices, models, architecture, and techniques.* A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms.* In-depth information about new cognitive computing models and conceptual frameworks and their implementation.AUDIENCEThe book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system. BUDATI ANIL KUMAR, PHD, is an associate professor in the ECE Department, Gokaraju Rangaraju Institute of Engineering & Technology (Autonomous), Hyderabad, India. He has more than 12 years of experience in teaching and six years of experience in research and has published more than 50 research articles in journals and conferences. His current research interests include cognitive radio networks, software-defined radio networks, artificial intelligence, 6G emerging technologies, mulsemedia computing, and UAVs in 5G and 6G. S. B. GOYAL, PHD, is Director, Faculty of Information Technology, City University, Malaysia. He has more than 20 experience and has published 100+ papers in journals and conferences. SARDAR M.N. ISLAM, PHD, is Director of Decision Sciences and Modelling Program at Victoria University, Australia. He has authored 31scholarly academic books in different disciplines, as well as more than 250 journal articles in his specialized research areas. Preface xiAcknowledgement xiii1 DESIGN OF A LOW-VOLTAGE LDO OF CMOS VOLTAGE REGULATOR FOR WIRELESS COMMUNICATIONS 1S. Pothalaiah, Dayadi Lakshmaiah, B. Prabakar Rao, D. Nageshwar Rao, Mohammad Illiyas and G. Chandra Sekhar1.1 Introduction 21.2 LDO Controller Arrangement and Diagram Drawing 21.2.1 Design of the LDO Regulator 41.2.1.1 Design of the Fault Amplifier 41.2.1.2 Design of the MPT Phase 81.3 Conclusion 14References 142 PERFORMANCE ANALYSIS OF MACHINE LEARNING AND DEEP LEARNING ALGORITHMS FOR SMART CITIES: THE PRESENT STATE AND FUTURE DIRECTIONS 15Pradeep Bedi, S. B. Goyal, Sardar MN Islam, Jia Liu and Anil Kumar Budati2.1 Introduction 162.2 Smart City: The Concept 162.3 Application Layer 182.3.1 Smart Homes and Buildings 182.3.1.1 Smart Surveillance 182.3.2 Smart Transportation and Driving 192.3.3 Smart Healthcare 192.3.4 Smart Parking 192.3.5 Smart Grid 192.3.6 Smart Farming 192.3.7 Sensing Layer 202.3.8 Communication Layer 202.3.9 Data Layer 202.3.10 Security Layer 212.4 Issues and Challenges in Smart Cities: An Overview 212.5 Machine Learning: An Overview 222.5.1 Supervised Learning 222.5.2 Support Vector Machines (SVMs) 222.5.3 Artificial Neural Networks 232.5.4 Random Forest 242.5.5 Naïve Bayes 252.6 Unsupervised Learning 262.7 Deep Learning: An Overview 262.7.1 Autoencoder 272.7.2 Convolution Neural Networks (CNNs) 272.7.3 Recurrent Neural Networks (RNNs) 282.8 Deep Learning vs Machine Learning 292.9 Smart Healthcare 302.9.1 Evolution Toward a Smart Healthcare Framework 302.9.2 Application of ML/DL in Smart Healthcare 312.10 Smart Transport System 332.10.1 Evolution Toward a Smart Transport System 332.10.2 Application of ML/DL in a Smart Transportation System 342.11 Smart Grids 362.11.1 Evolution Toward Smart Grids 362.11.2 Application of ML/DL in Smart Grids 382.12 Challenges and Future Directions 402.13 Conclusion 41References 413 APPLICATION OF MACHINE LEARNING ALGORITHMS AND MODELS IN 3D PRINTING 47Chetanpal Singh3.1 Introduction 483.2 Literature Review 503.3 Methods and Materials 653.4 Results and Discussion 693.5 Conclusion 70References 724 A NOVEL MODEL FOR OPTIMAL RELIABLE ROUTING PATH PREDICTION IN MANET 75S.R.M. Krishna, S. Pothalaiah and R. Santosh4.1 Introduction 764.2 Analytical Hierarchical Process Technique 774.3 Mathematical Models and Protocols 784.3.1 Rough Sets 784.3.1.1 Pawlak Rough Set Theory Definitions 784.3.2 Fuzzy TOPSIS 794.4 Routing Protocols 804.4.1 Classification of Routing Paths 804.5 RTF-AHP Model 814.5.1 Rough TOPSIS Fuzzy Set Analytical Hierarchical Process Algorithm 814.6 Models for Optimal Routing Performance 834.6.1 Genetic Algorithm Technique 844.6.2 Ant Colony Optimization Technique 844.6.3 RTF-AHP Model Architecture Flow 844.7 Results and Discussion 854.8 Conclusion 88References 885 IOT-BASED SMART TRAFFIC LIGHT CONTROL 91Sreenivasa Rao Ijjada and K. Shashidhar5.1 Introduction 925.2 Scope of the Proposed Work 935.3 Proposed System Implementation 945.4 Testing and Results 995.5 Test Results 1005.6 Conclusion 104References 1056 DIFFERENTIAL QUERY EXECUTION ON PRIVACY PRESERVING DATA DISTRIBUTED OVER HYBRID CLOUD 107Sridhar Reddy Vulapula, P. V. S. Srinivas and Jyothi Mandala6.1 Introduction 1076.2 Related Work 1086.3 Proposed Solution 1106.3.1 Data Transformation 1106.3.2 Data Distribution 1136.3.3 Query Execution 1146.4 Novelty in the Proposed Solution 1156.5 Results 1156.6 Conclusion 119References 1207 DESIGN OF CMOS BASE BAND ANALOG 123S. Pothalaiah, Dayadi Lakshmaiah, Bandi Doss, Nookala Sairam and K. Srikanth7.1 Introduction 1247.2 Proposed Technique of the BBA Chain for Reducing Energy Consumption 1257.3 Channel Preference Filter 1307.4 Programmable Amplifier Gain 1327.5 Executed Outcomes 1337.6 Conclusion 135References 1358 REVIEW ON DETECTION OF NEUROMUSCULAR DISORDERS USING ELECTROMYOGRAPHY 137G. L. N. Murthy, Rajesh Babu Nemani, M. Sambasiva Reddy and M. K. Linga Murthy8.1 Introduction 1388.2 Materials 1398.3 Methods 1408.4 Conclusion 142References 1429 DESIGN OF COMPLEMENTARY METAL–OXIDE SEMICONDUCTOR RING MODULATOR BY BUILT-IN THERMAL TUNING 145P. Bala Murali Krishna, Satish A., R. Yadgiri Rao, Mohammad Illiyas and I. Satya Narayana9.1 Introduction 1469.2 Device Structure 1479.3 dc Performance 1499.4 Small-Signal Radiofrequency Assessments 1499.5 Data Modulation Operation (High Speed) 1509.6 Conclusions and Acknowledgments 152References 15310 LOW-POWER CMOS VCO USED IN RF TRANSMITTER 155D. Subbarao, Dayadi Lakshmaiah, Farha Anjum, G. Madhu Sudhan Rao and G. Chandra Sekhar10.1 Introduction 15610.2 Transmitter Architecture 15710.3 Voltage-Controlled Ring Oscillator Design 15810.4 CMOS Combiner 16110.5 Conclusion 163References 16311 A NOVEL LOW-POWER FREQUENCY-MODULATED CONTINUOUS WAVE RADAR BASED ON LOW-NOISE MIXER 165Dayadi Lakshmaiah, Bandi Doss, J.V.B. Subrmanyam, M.K. Chaitanya, Suresh Ballala, R. Yadagirir Rao and I. Satya Narayana11.1 Introduction 16611.2 FMCW Principle 16811.3 Results 17411.4 Conclusion 178References 17912 A HIGHLY INTEGRATED CMOS RF T XUsed for IEEE 802.15.4 181Dayadi Lakshmaiah, Subbarao, C.H. Sunitha, Nookala Sairam and S. Naresh12.1 Introduction 18212.2 Related Work 18212.3 Simulation Results and Discussion 18512.4 Conclusion 186References 18713 A NOVEL FEEDFORWARD OFFSET CANCELLATION LIMITING AMPLIFIER IN RADIO FREQUENCIES 189Dayadi Lakshmaiah, L. Koteswara Rao, I. Satya Narayana, B. Rajeshwari and I. Venu13.1 Introduction 19013.2 Hardware Design 19013.2.1 Limiting Amplifier 19013.2.2 Offset Extractor 19213.2.3 Architecture and Gain 19213.2.4 Quadrature Detector 19213.2.5 Sensitivity 19413.3 Experimental Results 19513.4 Conclusion 195References 19614 A SECURED NODE AUTHENTICATION AND ACCESS CONTROL MODEL FOR IOT SMART HOME USING DOUBLE-HASHED UNIQUE LABELED KEY-BASED VALIDATION 199Sulaima Lebbe Abdul Haleem14.1 Introduction 20014.2 Challenges in IoT Security and Privacy 20314.2.1 Heterogeneous Communication and Devices 20314.2.2 Physical Equipment Integration 20414.2.3 Resource Handling Limitations 20414.2.4 Wide Scale 20414.2.5 Database 20414.3 Background 20914.4 Proposed Model 21014.4.1 Communication Flow 21414.4.1.1 IoT Node and Registration Authority 21414.4.1.2 User and Local Authorization Authority 21514.5 Results 21514.6 Conclusion 21814.7 Claims 218References 219Index 221
Battery-less NFC Sensors for the Internet of Things
The implementation of near-field communication (NFC) technology in smartphones has grown rapidly, especially due to the use of this technology as a payment system. In addition, the ability to use the energy transmitted not only for communication, but also for feeding other devices, which together with the low cost of NFC chips and the internet connectivity of the smartphones, allows the design of battery-less RF tags with sensing capabilities, whose information can be sent to the cloud. This is of great interest in the increasing amount of IoT (Internet of Things) scenarios.This book studies the feasibility of these sensors, analyzing the different parameters that have an influence on performance and in the range of operation. It also presents techniques to increase the range and analyzes the effects of certain materials when they are close to the antenna. The design and analysis of several sensors that can be powered and read by any NFC enabled device are presented in this work.MARTÍ BOADA is a postdoctoral researcher in the Department of Electronic, Electric and Automatic Engineering (URV), Tarragona, Spain, and has a PhD in telecommunication engineering.ANTONIO LAZARO is a full-time professor in the Department of Electronic, Electric and Automatic Engineering (URV), Tarragona, Spain, and has a PhD in telecommunication engineering.DAVID GIRBAU is a full-time professor in the Department of Electronic, Electric and Automatic Engineering (URV), Tarragona, Spain, and has a PhD in telecommunication engineering.RAMÓN VILLARINO is an assistant professor in the Department of Electronic, Electric and Automatic Engineering (URV), Tarragona, Spain, and has a PhD in telecommunication engineering.1. Wireless Power Transfer Applied to NFC2. Case Study 1: Soil Moisture Sensor3. Case Study 2: Smart Diaper4. Case Study 3: NFC Sensor for pH Monitoring5. Case Study 4: Fruit Ripeness Sensor
Data Science Handbook
DATA SCIENCE HANDBOOKTHIS DESK REFERENCE HANDBOOK GIVES A HANDS-ON EXPERIENCE ON VARIOUS ALGORITHMS AND POPULAR TECHNIQUES USED IN REAL-TIME IN DATA SCIENCE TO ALL RESEARCHERS WORKING IN VARIOUS DOMAINS.Data Science is one of the leading research-driven areas in the modern era. It is having a critical role in healthcare, engineering, education, mechatronics, and medical robotics. Building models and working with data is not value-neutral. We choose the problems with which we work, make assumptions in these models, and decide on metrics and algorithms for the problems. The data scientist identifies the problem which can be solved with data and expert tools of modeling and coding.The book starts with introductory concepts in data science like data munging, data preparation, and transforming data. Chapter 2 discusses data visualization, drawing various plots and histograms. Chapter 3 covers mathematics and statistics for data science. Chapter 4 mainly focuses on machine learning algorithms in data science. Chapter 5 comprises of outlier analysis and DBSCAN algorithm. Chapter 6 focuses on clustering. Chapter 7 discusses network analysis. Chapter 8 mainly focuses on regression and naive-bayes classifier. Chapter 9 covers web-based data visualizations with Plotly. Chapter 10 discusses web scraping.The book concludes with a section discussing 19 projects on various subjects in data science.AUDIENCEThe handbook will be used by graduate students up to research scholars in computer science and electrical engineering as well as industry professionals in a range of industries such as healthcare.KOLLA BHANU PRAKASH, PHD, is a Professor and Research Group Head for A.I. & Data Science Research group at K L University, India. He has published more than 80 research papers in international and national journals and conferences, as well as authored/edited 12 books and seven patents. His research interests include deep learning, data science, and quantum computing.Acknowledgment xiPreface xiii1 DATA MUNGING BASICS1 Introduction 11.1 Filtering and Selecting Data 61.2 Treating Missing Values 111.3 Removing Duplicates 141.4 Concatenating and Transforming Data 161.5 Grouping and Data Aggregation 20References 202 DATA VISUALIZATION 232.1 Creating Standard Plots (Line, Bar, Pie) 262.2 Defining Elements of a Plot 302.3 Plot Formatting 332.4 Creating Labels and Annotations 382.5 Creating Visualizations from Time Series Data 422.6 Constructing Histograms, Box Plots, and Scatter Plots 44References 543 BASIC MATH AND STATISTICS 573.1 Linear Algebra 573.2 Calculus 583.2.1 Differential Calculus 583.2.2 Integral Calculus 583.3 Inferential Statistics 603.3.1 Central Limit Theorem 603.3.2 Hypothesis Testing 603.3.3 ANOVA 603.3.4 Qualitative Data Analysis 603.4 Using NumPy to Perform Arithmetic Operations on Data 613.5 Generating Summary Statistics Using Pandas and Scipy 643.6 Summarizing Categorical Data Using Pandas 683.7 Starting with Parametric Methods in Pandas and Scipy 843.8 Delving Into Non-Parametric Methods Using Pandas and Scipy 873.9 Transforming Dataset Distributions 91References 944 INTRODUCTION TO MACHINE LEARNING 974.1 Introduction to Machine Learning 974.2 Types of Machine Learning Algorithms 1014.3 Explanatory Factor Analysis 1144.4 Principal Component Analysis (PCA) 115References 1215 OUTLIER ANALYSIS 1235.1 Extreme Value Analysis Using Univariate Methods 1235.2 Multivariate Analysis for Outlier Detection 1255.3 DBSCan Clustering to Identify Outliers 127References 1336 CLUSTER ANALYSIS 1356.1 K-Means Algorithm 1356.2 Hierarchial Methods 1416.3 Instance-Based Learning w/ k-Nearest Neighbor 149References 1567 NETWORK ANALYSIS WITH NETWORKX 1577.1 Working with Graph Objects 1597.2 Simulating a Social Network (ie; Directed Network Analysis) 1637.3 Analyzing a Social Network 169References 1718 BASIC ALGORITHMIC LEARNING 1738.1 Linear Regression 1738.2 Logistic Regression 1838.3 Naive Bayes Classifiers 189References 1959 WEB-BASED DATA VISUALIZATIONS WITH PLOTLY 1979.1 Collaborative Aanalytics 1979.2 Basic Charts 2089.3 Statistical Charts 2129.4 Plotly Maps 216References 21910 WEB SCRAPING WITH BEAUTIFUL SOUP 22110.1 The BeautifulSoup Object 22410.2 Exploring NavigableString Objects 22810.3 Data Parsing 23010.4 Web Scraping 23310.5 Ensemble Models with Random Forests 235References 254DATA SCIENCE PROJECTS 25711 COVID19 DETECTION AND PREDICTION 259Bibliography 27512 LEAF DISEASE DETECTION 277Bibliography 28313 BRAIN TUMOR DETECTION WITH DATA SCIENCE 285Bibliography 29514 COLOR DETECTION WITH PYTHON 297Bibliography 30015 DETECTING PARKINSON’S DISEASE 301Bibliography 30216 SENTIMENT ANALYSIS 303Bibliography 30617 ROAD LANE LINE DETECTION 307Bibliography 31518 FAKE NEWS DETECTION 317Bibliography 31819 SPEECH EMOTION RECOGNITION 319Bibliography 32220 GENDER AND AGE DETECTION WITH DATA SCIENCE 323Bibliography 33921 DIABETIC RETINOPATHY 341Bibliography 35022 DRIVER DROWSINESS DETECTION IN PYTHON 351Bibliography 35623 CHATBOT USING PYTHON 357Bibliography 36324 HANDWRITTEN DIGIT RECOGNITION PROJECT 365Bibliography 36825 IMAGE CAPTION GENERATOR PROJECT IN PYTHON 369Bibliography 37926 CREDIT CARD FRAUD DETECTION PROJECT 381Bibliography 39127 MOVIE RECOMMENDATION SYSTEM 393Bibliography 41128 CUSTOMER SEGMENTATION 413Bibliography 43129 BREAST CANCER CLASSIFICATION 433Bibliography 44330 TRAFFIC SIGNS RECOGNITION 445Bibliography 453
Modern C Up and Running
Learn how to program in modern C, from the basics through the advanced topics required for proficiency. This book is the fastest path to C fluency for anyone experienced in a general-purpose programming language. From start to finish, code examples highlight the idioms and best practices behind efficient, robust programs in a variety of areas.The book opens with a thorough coverage of syntax, built-in data types and operations, and program structure. C has quirks and presents challenges, which are covered in detail. The coverage of advanced features is what sets this book apart from others. Among the advanced topics covered are floating-point representation in the IEEE 754 standard; embedded assembly language in C code for overflow detection; regular expressions, assertions, and internationalization; WebAssembly through C; and software libraries for C and other clients.Memory efficiency and safety are the two major challenges in C programming, and you’ll explore these challenges through a series of C examples. Arrays and structures, which are the means to high-level data representation, are covered in connection with pointers, which provide efficiency. The book again uses code examples in covering networking and wire-level security; concurrency (multiprocessing and multithreading); instruction-level parallelism; and interprocess communication through shared memory and files, pipes, message queues, and signals.Many books introduce C, but few also explain how to use it properly and optimally. Essential C does just that.WHAT YOU'LL LEARN* Accelerate your path to C mastery with this book for experienced programmers* Refresh your approach to program structure and data types* Dive into aggregates and pointers using modern C language* Revisit storage classes and scope* Dive into concurrency (multiprocessing and multithreading) and instruction-level parallelism* Finish with regular expressions, assertions, signals, locales and moreWHO THIS BOOK IS FORProfessional programmers or software developers who has prior experience with C or in general wanting an accelerated learning guide to modern C programming language.Martin Kalin has a Ph.D. from Northwestern University and is a professor in the College of Computing and Digital Media at DePaul University. He has co-written a series of books on C and C++ and written a book on Java for programmers. He enjoys commercial programming and has co-developed large distributed systems in process scheduling and product configuration.1. Program Structure2. Basic Data Types3. Aggregates and Pointers4. Storage Classes5. Input and Output6. Networking7. Concurrency and Parallelism8. Miscellaneous Topics
Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling
The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime. This work focuses on developing a reactive job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore investigated for the concept of multiple agents that control products including transportation and resource allocation.ABOUT THE AUTHORSCHIRIN BÄR researched at the RWTH-Aachen University at the Institute for Information Management in Mechanical Engineering (IMA) on the optimization of production control of flexible manufacturing systems using reinforcement learning. As operations manager and previously as an engineer, she developed and evaluated the research results based on real systems. Introduction.- Requirements for Production Scheduling in Flexible Manufacturing.- Reinforcement Learning as an Approach for Flexible Scheduling.- Concept for Multi-Resources Flexible Job-Shop Scheduling.- Multi-Agent Approach for Reactive Scheduling in Flexible Manufacturing.- Empirical Evaluation of the Requirements.- Integration into a Flexible Manufacturing System.- Bibliography.
Big Data - Big Accountability
Mit dem Phänomen „Big Data“ als Teil einer datengetriebenen Zukunft verbinden sich seit Jahren enorme Hoffnungen und große Ängste. Immer mehr Akteure aus dem privaten und öffentlichen Sektor sammeln und nutzen solche Datenmassen zu vielfältigen Zwecken. Dabei stellt sich aus datenschutzrechtlicher Perspektive die Frage: Ist es möglich, Big-Data-Verfahren im Einklang mit der Datenschutz-Grundverordnung durchzuführen oder bedeutet Big Data zwangsläufig „Small Privacy“? Am Beispiel der Betrugsbekämpfung mit Big Data in der Kraftfahrzeughaftpflichtversicherung analysiert Constantin Herfurth die datenschutzrechtlichen Rahmenbedingungen und entwickelt neue Modelle, um bewährte Datenschutzgrundsätze innovativ anwenden zu können und eine "Big Accountability" zu schaffen. Dabei zeichnet er nicht nur ein differenzierteres Bild von Big Data, sondern zeigt auch Wege für eine datenschutzkonforme Gestaltung auf und regt die Weiterentwicklung bestehender Mechanismen und Instrumente der Datenschutz-Grundverordnung an.CONSTANTIN HERFURTH war als wissenschaftlicher Mitarbeiter mit dem Forschungsschwerpunkt Big Data und Datenschutz von 2016 bis 2018 am Fachgebiet Öffentliches Recht, IT-Recht und Umweltrecht von Prof. Dr. Gerrit Hornung, LL.M. an der Universität Kassel tätig. Seit 2018 arbeitet er als Rechtsanwalt für eine internationale Kanzlei in München und berät zu Datenschutz und Cybersecurity.Einführung.- Versicherungsbetrug in der Kraftfahrzeug-Haftpflichtversicherung.- Bekämpfung von Versicherungsbetrug mittels Big Data.- Rechtsrahmen des europäischen und nationalen Datenschutzrechts.- Anwendungsbereich der Datenschutz-Grundverordnung.- Anforderungen der Datenschutz-Grundverordnung.- Zusammenfassung.
System Firmware
Find the right bootloader solution or combination of firmware required to boot a platform considering its security, product features, and optimized boot solutions. This book covers system boot firmware, focusing on real-world firmware migration from closed source to open source adaptation.The book provides an architectural overview of popular boot firmware. This includes both closed sourced and/or open source in nature, such as Unified Extensible Firmware Interface (UEFI), coreboot, and Slim Bootloader and their applicable market segments based on product development and deployment requirements.Traditional system firmware is often complex and closed sourced whereas modern firmware is still a kind of hybrid between closed and open source. But what might a future firmware model look like? The most simplistic boot firmware solution uses open source firmware development. This bookhelps you decide how to choose the right boot firmware for your products and develop your own boot firmware using open source. Coverage includes:* Why open source firmware is used over closed source* The pros and cons of closed and open source firmware* A hybrid work model: for faster bring-up activity using closed source, binary integrated with open source firmwareWHAT YOU WILL LEARN* Understand the architecture of standard and popular boot firmware* Pick the correct bootloader for your required target hardware* Design a hybrid workflow model for the latest chipset platform* Understand popular payload architectures and offerings for embedded systems* Select the right payload for your bootloader solution to boot to the operating system* Optimize the system firmware boot time based on your target hardware requirement* Know the product development cycle using open source firmware developmentWho This Book Is ForEmbedded firmware and software engineers migrating the product development from closed source firmware to open source firmware for product adaptation needs as well as engineers working for open source firmware development. A secondary audience includes engineers working on various bootloaders such as open source firmware, UEFI, and Slim Bootloader development, as well as undergraduate and graduate students working on developing firmware skill sets.SUBRATA BANIK is a Firmware Engineer with more than a decade being spent in the computer industry and acquired experiences in system firmware design, development and debugging across various firmware architectures like UEFI, coreboot, Slim bootloader etc. for x86 and ARM platforms. Subrata has profound experience on platform enablement that leads into working for all the leading PC-makers’ products. Subrata is an active member of open-source firmware (OSF) development across different projects like coreboot, oreboot, flashrom, EDKII etc., where he is one of the leading contributors in the open firmware (coreboot) development. Subrata has received multiple US Patents and is very passionate about learning new technology and sharing knowledge among enthusiast engineers. Subrata has presented his technical talks at industry events such as Open Source Firmware conference, Institute for Security and Technology, Intel Developer Forum etc.When not writing or working, he can be found enjoying watching sports (especially football) or spending time with his daughter. A fun fact about Subrata is, he is a strong believer of Time travel existence.VINCENT ZIMMER has been working on embedded firmware for the last 30 years. Vincent has contributed to or created firmware spanning various firmware initiatives, including the Extensible Firmware Interface, where Vincent presently leads the Security subteam in the UEFI Forum. Vincent has also co-authored various papers and books, along with being a named co-inventor on over 450 US patents.PREFACE: This section to capture the author's personal experience about the current available bootloader solutions for target hardware and why authors think this book might be helpful for the target audience.ACKNOWLEDGEMENT: This section acknowledges the contribution of domain expert(s) who has contributed into this book apart from the authors.CHAPTER 1: INTRODUCTION ABOUT THE BOOK: SYSTEM FIRMWARE: AN ESSENTIAL GUIDE TO OPEN SOURCE AND EMBEDDED SOLUTIONS book is a handbook for target audience to learn about the basics of system boot firmware, understand various different types of solutions available while designing system firmware for target embedded system. This book will help its reader to understand the minimal knowledge required to start the firmware journey, understanding the different system firmware architecture and find the right bootloader solution or combinations of firmware’s required to boot the platform.This section would cover:* Motivation for this book* Who is the Reader?* Top reasons to migrate to open source firmware solution from close sourceWhat are the contents?CHAPTER 2: STARTER: To provide the historical introduction about the boot firmware, its origin, what all different solutions available like closed soured boot firmware and open source boot firmware. Define the goals for readers to create their own open source boot firmware for target hardware, create hybrid work model if case SoC vendors still has some proprietary close source firmware to work with open source firmware to develop the target hardware along with non-goals like understanding the architecture of all possible bootloaders, payloads and firmware offerings, understand the bootloader security aspect while developing the product, scope of improving the quality of service for boot firmware using multi core environment, learn from the case study about optimizing boot firmware boot prints and boot time by introducing various concepts.CHAPTER 3: KNOWING YOUR HARDWARE: This section provides detailed understanding of hardware interfaces that firmware needs to manage prior to boot to an operating system. This is a very basic understanding section of system boot firmware without which one really can’t make progress further into their bootloader journey. A good understanding of hardware interfaces and how to program those interfaces is a minimum expectation from any BIOS engineer while working on any hardware project. Idea here is to provide ample details on any sample motherboard design and required programmable hardware interface at boot time, for example: UART, SPI, USB, SATA, Display etc.CHAPTER 4: UNDERSTANDINGBOOTLOADER AND ITS MINIMUM REQUIREMENTS: There are many different types of firmware that exist based on underlying hardware requirements like system boot firmware, device firmware, platform security firmware, manageability firmware. Each firmware has its minimum requirements to complete its assigned task to initialize the underlying hardware and/or abstract the hardware to higher level applications. This section is to focus on system boot firmware and provide details about what is a bootloader, what are the basic characteristics a firmware must call it bootloader, finally understanding the minimum requirement to design a bootloader. This book would be like a handbook for the reader where the reader would be in a comfortable position to design its own bootloader at the end of this session. It won’t be possible to do so unless the reader has understood the basic expectation from the bootloader and upcoming chapters would guide readers to choose the appropriate bootloader for the target hardware.CHAPTER 5: DIFFERENT TYPES OF BOOTLOADERS: BIOS as acronym suggest is responsible for BASIC INPUT/ OUTPUT SYSTEM. The BIOS in modern PCs initializes and tests the system hardware components and loads an operating system from a mass memory device. If a developer wants to write their own bootloader on any architecture, (ARM, IA, RISC etc.) then they must gather the appropriate documents (which aren’t always known), hence Chapter 3 is to provide those specific details about designing their own bootloader. And this section is to provide the architectural details about the popular or market leading bootloaders along with its applicable market segments because of its characteristics: idea here is to understand the Pros and Cons of each offering.* EFI came during early development of the first Intel–HP Itanium systems in the mid-1990s. Then transform into UEFI and become widely used bootloaders for consumer electronic products in the modern era. UEFI has several implementations, with the EFI Developer Kit II (EDKII) being the most prominent.* COREBOOT, formerly known as LINUXBIOS, is an open software project aimed at replacing proprietary firmware (BIOS or UEFI). So far widely used over specific areas like Chrome platforms like Chromebook, Chromebox, Chrome tablets/ slates, Govt. projects etc. Interestingly in the last few years coreboot has seen a major adaptation by several industry leaders for their product lines.* SLIM BOOTLOADER is an open-source boot firmware, built from the ground up to be small, secure and optimized running on Intel x86 architecture.CHAPTER 6: HYBRID WORK MODEL: Open source bootloader development has enormous dependency over SoC vendors for providing the documentation and reference code for CPU, memory and chipset initialization. A real desire to have an entire product developed with an open source concept, be it like SoC, hardware schematics, firmware and software. But the majority of silicon vendors are yet to adopt the open source development model for their products, resulting in sharing SoC reference code as part of license agreement among a small group typically known as Independent BIOS Vendors (IBVs). This section defines the possible hybrid work model where users can still build their open source bootloader solution while working with closed or restricted SoC, hardware platform.* FIRMWARE SUPPORT PACKAGE (FSP) - A new industry specification to work with all sorts of possible closed source SoC, CPU and/or hardware design using standard APIs to communicate with any bootloader. Over the last few years, industry has shown great adaptation towards FSP and this eventually helped many SoC vendors to migrate their reference code solutions from closed source code sharing among specific groups to API based open source binary blobs for interoperability with any bootloader.CHAPTER 7: PICKING THE CORRECT PAYLOAD: As salt is a very important ingredient for preparing good food, the same is also applicable for bootloaders as well, for any bootloader the payload is like salt. There are few bootloaders where payload is already integrated into it by default and one can’t likely replace it with other payload offerings. There is some boot firmware to allow selection of payload as per product need. The payload is a very essential entity in boot firmware due to various reasons like, an efficient payload can eventually reduce the boot firmware boot print and allow smooth transitions towards operating system, also provide early interactive interface or test framework to execute various utilities to measure hardware health. This section provides architecture details of all popular payloads and its current offerings to help users to choose the correct payload for their product.* TIANOCORE – Mostly integrated with UEFI bootloader by default and widely used payload solution.* LINUXBOOT – Perfect payload for simple bootloader like coreboot and allowing more runway for Linux like payload to load compatible operating system,* DEPTHCHARGE – Payload with specific product requirements like Chromebooks.An idea to share the design principle for future proof concepts like Universal Payload where these payloads are getting mutual benefit from each other and define unified APIs expectations from boot firmware.CHAPTER 8: CASE STUDIES: This section to capture the case study done on real hardware on below topics. This real-life example will help users to think through more innovation while designing their own open source boot firmware· REDUCE FIRMWARE BOOT TIME: To demonstrate the boot optimization done on a real hardware platform using open source firmware development model.· Supporting new CPU architecture migration with UEFI: DEMONSTRATE AN EFFICIENT EVALUATION BOARD HARDWARE DESIGN BASED ON ARM SOC IN A VISION TO REDUCE THE FIRMWARE BOUNDARY. · Reducing the system firmware boundary with LinuxBoot: HIGHLIGHTING THE VALUE OF LINUXBOOT IN THE FUTURE SYSTEM FIRMWARE DESIGN, NOT ONLY HELPS TO SHRINK THE FIRMWARE SPACE BUT ALSO BRINGS THE VALUE OF THE BOOT KERNEL INTO FIRMWARE TO DO MORE POWERFUL OPERATION WITH EASE.· ADOPTING HYBRID FIRMWARE DEVELOPMENT MODEL: Real life example from product development journey based on latest IA chipset platform to demonstrate hybrid firmware development model combining open source bootloader, payload solutions and closed source binary blobs.Apart from this APPENDIX sections for source code references based on Chapter 8 Case Study.GLOSSARY and INDEX as applicable for connecting back the main topics.
Getting Started with the Uno Platform and WinUI 3
Get ready to build applications that can run anywhere using the Uno Platform and WinUI.Modern application development can be an intimidating and complex topic, especially when you are building cross-platform applications that need to support multiple operating systems and form factors. There are so many options when it comes to frameworks and selecting the right one for your enterprise is critical in delivering a successful product to market. For the developer who has zero experience building apps with Xamarin, UWP, WinUI, or the Uno Platform, this book deconstructs those complex concepts into tangible building blocks so that productivity gains are immediately recognized.You will start off learning basic concepts and get a bird's-eye view of the enabling technologies to ensure that you feel comfortable with the tools and terminology. From there, you will learn about some of the more popular options in the .NET ecosystem, understand their attributes and shortcomings, and learn why the Uno Platform is ideal for building a cross-platform application that targets Android, iOS, Windows, WASM (Web Assembly), Linux, and MacOS.Then, you will follow a product release timeline that takes you through building an application, introducing key concepts at every step of the way. Each section of the book is chock full of tips and edge case documentations for the different platforms.WHAT YOU WILL LEARN* Manage multi-targeting solutions: specifically, how to handle the different project heads* Effectively write cross-platform software and handle the edge cases of the different platforms* Understand the fundamentals of working with Uno Platform WinUI apps* Explore enterprise-grade application architecture using MVVM* Understand Dependency Injection and how it applies to application architectureWHO THIS BOOK IS FORDevelopers who understand some basics of C# and object-oriented programmingSKYE HOEFLING is a Lead Software Engineer and works on cross-platform apps for desktop, mobile, and web using Xamarin and .NET technologies. She has been using .NET and Microsoft technologies since 2006 and has a Bachelor of Science degree from Rochester Institute of Technology in Game Design and Development. Skye has a background in enterprise software, building custom web portals for large corporations as well as small projects used by general consumers. She is an active Open Source contributor, a Microsoft MVP in Developer Technologies, and a .NET Foundation Member. You can find her on twitter @SkyeTheDev as well at her software development blog, SkyeTheDev, where you will find a wide range of blogs.Chapter 1: Introduction to Uno PlatformChapter 2: File New ProjectChapter 3: Your First PageChapter 4: Application StylesChapter 5: Platform Specific Code and XAMLChapter 6: Master-Detail Menu and DashboardChapter 7: Custom FontsChapter 8: Model-View-ViewModel (MVVM)Chapter 9: Dependency Injection and LoggingChapter 10: Application NavigationChapter 11: Authentication with Azure Active DirectoryChapter 12: ConvertersChapter 13: Microsoft Graph, Web APIs, and MyFilesPageChapter 14: Microsoft Graph and Dashboard MenuChapter 15: Images and GridViewChapter 16: SelectorsChapter 17: OneDrive NavigationChapter 18: Offline Data AccessChapter 19: Complete App
Enterprise Systems Architecture
Enhance your technical and business skills to better manage your organization’s technology ecosystem. This book aims to explain how to align the technology landscape to service your company’s business operating model.The book begins by exploring different architectural approaches before taking a deep dive into multiple layers of the architectural stack and the methodology of each component. You’ll also learn about the many products delivered by enterprise architecture. To complete the book, author Daljit Banger delves into the various roles and responsibilities of an enterprise architect.After completing Enterprise Systems Architecture, you will understand how to develop an ICT (Information Communication Technology) strategy to meet the needs of your organization.WHAT WILL YOU LEARN* Gain a complete understanding of enterprise architecture* Conceptualize the enterprise ecosystem using the EsA canvas* Master the products and services of an enterprise architecture functionWHO THIS BOOK IS FORArchitects (Enterprise, Solution, or Technical), CTOs, Business Analysts, or any stakeholder in delivering technology services to their organization.DALJIT BANGER has 40 years of solid IT Industry experience, having undertaken assignments in locations across the globe, including the UK, USA, Sweden, Switzerland, Finland, Hong Kong, and Brazil on behalf of large multinational companies.Daljit has successfully managed several large professional teams of Architects, written in several publications and is the author of several freeware software products for Enterprise Architecture.Daljit holds a Master of Science (MSc) Degree and is a Chartered IT Fellow of the British Computer Society and Chairs the British Computer Society Enterprise Architecture Specialist Group.Chapter 1: Architectural Approaches* MODAF (Ministry of Defense Architecture Framework)* DODAF (Department of Defense Architecture Framework)* TOGAF (The Open Group Architecture Framework)* Zachman Framework* Federal Enterprise Architecture* Meta ModelsChapter 2: Layers Expanded and Explores* Layer 0 (Business Operating Model)* Layer 1 (Business Process Later)* Layer 2 (Capabilities and Services)* Layer 3 (Applications)* Layer 4 (Data/Information Services)* Layer 5 (Technological Services)Chapter 3: Products for Delivering the EA.* Background* Contributing Factors* IT Governance * Technical Debt Management Chapter 4: Roles and Responsibilities* Enterprise Architect * Solutions Architect* Technical Architect* Aligning Architect Chapter 5: Developing the ICT Strategy* Simple Strategy Plan * Strategy CycleChapter 6: Final Note
Hybrid Intelligent Approaches for Smart Energy
HYBRID INTELLIGENT APPROACHES FOR SMART ENERGYGREEN TECHNOLOGIES AND CLEANER ENERGY ARE TWO OF THE MOST IMPORTANT TOPICS FACING OUR WORLD TODAY, AND THE MARCH TOWARD EFFICIENT ENERGY SYSTEMS, SMART CITIES, AND OTHER GREEN TECHNOLOGIES, HAS BEEN, AND CONTINUES TO BE, A LONG AND INTRICATE ONE. BOOKS LIKE THIS ONE KEEP THE VETERAN ENGINEER AND STUDENT, ALIKE, UP TO DATE ON CURRENT TRENDS IN THE TECHNOLOGY AND OFFER A REFERENCE FOR THE INDUSTRY FOR ITS PRACTICAL APPLICATIONS.Energy optimization and consumption prediction are necessary to prevent energy waste, schedule energy usage, and reduce the cost. Today, smart computing technologies are slowly replacing the traditional computational methods in energy optimization, consumption, scheduling, and usage. Smart computing is an important core technology in today’s scientific and engineering environment. Smart computation techniques such as artificial intelligence, machine learning, deep learning and Internet of Things (IoT) are the key role players in emerging technologies across different applications, industries, and other areas. These newer, smart computation techniques are incorporated with traditional computation and scheduling methods to reduce power usage in areas such as distributed environment, healthcare, smart cities, agriculture and various functional areas. The scope of this book is to bridge the gap between traditional power consumption methods and modern consumptions methods using smart computation methods. This book addresses the various limitations, issues and challenges of traditional energy consumption methods and provides solutions for various issues using modern smart computation technologies. These smart technologies play a significant role in power consumption, and they are cheaper compared to traditional technologies. The significant limitations of energy usage and optimizations are rectified using smart computations techniques, and the computation techniques are applied across a wide variety of industries and engineering areas. Valuable as reference for engineers, scientists, students, and other professionals across many areas, this is a must-have for any library. JOHN A, PHD, is an assistant professor at Galgotias University, Greater Noida, India, and he received his PhD in computer science and engineering from Manonmaniam Sundaranar University, Tirunelveli, India. He has presented papers in various national and international conferences and has published papers in scientific journals. SENTHIL KUMAR MOHAN, PHD, is an associate professor in the Department of Software and System Engineering at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He received his PhD in engineering and technology from Vellore Institute of Technology, and he has contributed to many research articles in various technical journals and conferences. SANJEEVIKUMAR PADMANABAN, PHD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has almost ten years of teaching, research and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching. YASIR HAMID, PHD, is an assistant professor in the Department of Information Security Engineering Technology at Abu Dhabi Polytechnic. He earned his PhD in 2019 from Pondicherry University in Computer Science and Engineering. Before joining ADPOLY, he was an assistant professor in the Department of Computer Science, Islamic University of Science and Technology, India. He is an editorial board member on many scientific and technical journals. List of Contributors xiiiPreface xvAcknowledgements xix1 REVIEW AND ANALYSIS OF MACHINE LEARNING BASED TECHNIQUES FOR LOAD FORECASTING IN SMART GRID SYSTEM 1Shihabudheen KV and Sheik Mohammed S1.1 Introduction 21.2 Forecasting Methodology 41.3 AI-Based Prediction Methods 51.3.1 Single Prediction Methods 51.3.1.1 Linear Regression 51.3.1.2 Artificial Neural Networks (ANN) 71.3.1.3 Support Vector Regression (SVR) 81.3.1.4 Extreme Learning Machine 91.3.1.5 Neuro-Fuzzy Techniques 101.3.1.6 Deep Learning Techniques 111.3.2 Hybrid Prediction Methods 121.3.2.1 Combined AI-Based Prediction Techniques 121.3.2.2 Signal Decomposition Based Prediction Techniques 131.3.2.3 EMD Based Decomposition 141.3.2.4 Wavelet Based Decomposition 141.4 Results and Discussions 151.4.1 Description of Dataset 151.4.2 Performance Analysis of Single Prediction Methods for Load Forecasting 161.4.2.1 Feature Selection 161.4.2.2 Optimal Parameter Selection 171.4.2.3 Prediction Results of Single Prediction Methods 171.4.3 Performance Analysis of Hybrid Prediction Methods for Load Forecasting 171.4.4 Comparative Analysis 211.5 Conclusion 22References 232 ENERGY OPTIMIZED TECHNIQUES IN CLOUD AND FOG COMPUTING 27N.M. Balamurugan, TKS Rathish babu, K Maithili and M. Adimoolam2.1 Introduction 282.2 Fog Computing and Its Applications 332.3 Energy Optimization Techniques in Cloud Computing 382.4 Energy Optimization Techniques in Fog Computing 422.5 Summary and Conclusions 44References 453 ENERGY-EFFICIENT CLOUD COMPUTING TECHNIQUES FOR NEXT GENERATION: WAYS OF ESTABLISHING AND STRATEGIES FOR FUTURE DEVELOPMENTS 49Praveen Mishra, M. Sivaram, M. Arvindhan, A. Daniel and Raju Ranjan3.1 Introduction 503.2 A Layered Model of Cloud Computing 523.2.1 System of Architecture 533.3 Energy and Cloud Computing 543.3.1 Performance of Network 553.3.2 Reliability of Servers 553.3.3 Forward Challenges 553.3.4 Quality of Machinery 563.4 Saving Electricity Prices 563.4.1 Renewable Energy 573.4.2 Cloud Freedom 573.5 Energy-Efficient Cloud Usage 583.6 Energy-Aware Edge OS 583.7 Energy Efficient Edge Computing Based on Machine Learning 593.8 Energy Aware Computing Offloading 613.8.1 Energy Usage Calculation and Simulation 633.9 Comments and Directions for the Future 63References 644 ENERGY OPTIMIZATION USING SILICON DIOXIDE COMPOSITE AND ANALYSIS OF WIRE ELECTRICAL DISCHARGE MACHINING CHARACTERISTICS 67M.S. Kumaravel, N. Alagumurthi and P. Mathiyalagan4.1 Introduction 674.2 Materials and Methods 694.3 Results and Discussion 724.3.1 XRD Analysis 724.3.2 SEM Analysis 734.3.3 Grey Relational Analysis (GRA) 734.3.4 Main Effects Graph 764.3.5 Analysis of Variance (ANOVA) 774.3.6 Confirmatory Test 784.4 Conclusion 80Acknowledgement 80References 805 OPTIMAL PLANNING OF RENEWABLE DG AND RECONFIGURATION OF DISTRIBUTION NETWORK CONSIDERING MULTIPLE OBJECTIVES USING PSO TECHNIQUE FOR DIFFERENT SCENARIOS 83Balmukund Kumar and Aashish Kumar Bohre5.1 Introduction 845.2 Literature Review for Recent Development in DG Planning and Network Reconfiguration 845.3 System Performance Parameters and Index 875.4 Proposed Method 885.4.1 Formulation of Multi-Objective Fitness Function 885.4.2 Backward-Forward-Sweep Load Flow Based on BIBC-BCBV Method 895.5 PSO Based Optimization 905.6 Test Systems 925.7 Results and Discussions 925.8 Conclusions 101References 1026 INVESTIGATION OF ENERGY OPTIMIZATION FOR SPECTRUM SENSING IN DISTRIBUTED COOPERATIVE IOT NETWORK USING DEEP LEARNING TECHNIQUES 107M. Pavithra, R. Rajmohan, T. Ananth Kumar, S. Usharani and P. Manju Bala6.1 Introduction 1086.2 IoT Architecture 1116.3 Cognitive Spectrum Sensing for Distributed Shared Network 1136.4 Intelligent Distributed Sensing 1156.5 Heuristic Search Based Solutions 1176.6 Selecting IoT Nodes Using Framework 1186.7 Training With Reinforcement Learning 1196.8 Model Validation 1206.9 Performance Evaluations 1236.10 Conclusion and Future Work 125References 1267 ROAD NETWORK ENERGY OPTIMIZATION USING IOT AND DEEP LEARNING 129N. M. Balamurugan, N. Revathi and R. Gayathri7.1 Introduction 1297.2 Road Network 1327.2.1 Types of Road 1327.2.2 Road Structure Representation 1347.2.3 Intelligent Road Lighting System 1357.3 Road Anomaly Detection 1397.4 Role of IoT in Road Network Energy Optimization 1417.5 Deep Learning of Road Network Traffic 1427.6 Road Safety and Security 1427.7 Conclusion 144References 1448 ENERGY OPTIMIZATION IN SMART HOMES AND BUILDINGS 147S. Sathya, G. Karthi, A. Suresh Kumar and S. Prakash8.1 Introduction 1488.2 Study of Energy Management 1508.3 Energy Optimization in Smart Home 1508.3.1 Power Spent in Smart-Building 1538.3.2 Hurdles of Execution in Energy Optimization 1568.3.3 Barriers to Assure SH Technologies 1568.4 Scope and Study Methodology 1578.4.1 Power Cost of SH 1588.5 Conclusion 159References 1599 MACHINE LEARNING BASED APPROACH FOR ENERGY MANAGEMENT IN THE SMART CITY REVOLUTION 161Deepica S., S. Kalavathi, Angelin Blessy J. and D. Maria Manuel Vianny9.1 Introduction 1629.1.1 Smart City: What is the Need? 1629.1.2 Development of Smart City 1639.2 Need for Energy Optimization 1669.3 Methods for Energy Effectiveness in Smart City 1669.3.1 Smart Electricity Grids 1669.3.2 Smart Transportation and Smart Traffic Management 1699.3.3 Natural Ventilation Effect 1729.4 Role of Machine Learning in Smart City Energy Optimization 1739.4.1 Machine Learning: An Overview 1739.5 Machine Learning Applications in Smart City 1759.6 Conclusion 177References 17810 DESIGN OF AN ENERGY EFFICIENT IOT SYSTEM FOR POULTRY FARM MANAGEMENT 181G. Rajakumar, G. Gnana Jenifer, T. Ananth Kumar and T. S. Arun Samuel10.1 Introduction 18210.2 Literature Survey 18310.3 Proposed Methodology 18710.3.1 Monitoring and Control Module 18810.3.2 Monitoring Temperature 18810.3.3 Monitoring Humidity 18910.3.4 Monitoring Air Pollutants 18910.3.5 Artificial Lightning 19010.3.6 Monitoring Water Level 19010.4 Hardware Components 19010.4.1 Arduino UNO 19010.4.2 Temperature Sensor 19010.4.3 Humidity Sensor 19110.4.4 Gas Sensor 19210.4.5 Water Level Sensor 19210.4.6 LDR Sensor 19310.4.7 GSM (Global System for Mobile Communication) Modem 19410.5 Results and Discussion 19510.5.1 Hardware Module 19510.5.2 Monitoring Temperature 19610.5.3 Monitoring Gas Content 19810.5.4 Monitoring Humidity 19810.5.5 Artificial Lighting 19810.5.6 Monitoring Water Level 19810.5.7 Poultry Energy-Efficiency Tips 19910.6 Conclusion 201References 20311 IOT BASED ENERGY OPTIMIZATION IN SMART FARMING USING AI 205N. Padmapriya, T. Ananth Kumar, R. Aswini, R. Rajmohan, P. Kanimozhi and M. Pavithra11.1 Introduction 20611.2 IoT in Smart Farming 20811.2.1 Benefits of Using IoT in Agriculture 20811.2.2 The IoT-Based Smart Farming Cycle 20911.3 AI in Smart Farming 21011.3.1 Artificial Intelligence Revolutionises Agriculture 21011.4 Energy Optimization in Smart Farming 21111.4.1 Energy Optimization in Smart Farming Using IoT and AI 21211.5 Experimental Results 21511.5.1 Analysis of Network Throughput 21611.5.2 Analysis of Network Latency 21711.5.3 Analysis of Energy Consumption 21811.5.4 Applications of IoT and AI in Smart Farming 21911.6 Conclusion 220References 22112 SMART ENERGY MANAGEMENT TECHNIQUES IN INDUSTRIES 5.0 225S. Usharani, P. Manju Bala, T. Ananth Kumar, R. Rajmohan and M. Pavithra12.1 Introduction 22612.2 Related Work 22712.3 General Smart Grid Architecture 22912.3.1 Energy Sub-Sectors 23012.3.1.1 Smart Grid: State-of-the-Art Inside Energy Sector 23012.3.2 EV and Power-to-Gas: State-of-the-Art within Biomass and Transport 23112.3.3 Constructing Zero Net Energy (CZNE): State-of-the-Art Inside Field of Buildings 23312.3.4 Manufacturing Industry: State-of-the-Art 23412.3.5 Smart Energy Systems 23512.4 Smart Control of Power 23612.4.1 Smart Control Thermal System 23612.4.2 Smart Control Cross-Sector 23712.5 Subsector Solutions 23812.6 Smart Energy Management Challenges in Smart Factories 23912.7 Smart Energy Management Importance 24012.8 System Design 24112.9 Smart Energy Management for Smart Grids 24112.10 Experimental Results 24712.11 Conclusions 250References 25113 ENERGY OPTIMIZATION TECHNIQUES IN TELEMEDICINE USING SOFT COMPUTING 253R. Indrakumari13.1 Introduction 25313.2 Essential Features of Telemedicine 25513.3 Issues Related to Telemedicine Networks 25613.4 Telemedicine Contracts 25713.5 Energy Efficiency: Policy and Technology Issue 25813.5.1 Soft Computing 25813.5.2 Fuzzy Logic 26013.5.3 Artificial Intelligence 26013.5.4 Genetic Algorithms 26313.5.5 Expert System 26313.5.6 Expert System Based on Fuzzy Logic Rules 26413.6 Patient Condition Monitoring 26613.7 Analysis of Physiological Signals and Data Processing 27113.8 M-Health Monitoring System Architecture 27213.9 Conclusions 275References 27614 HEALTHCARE: ENERGY OPTIMIZATION TECHNIQUES USING IOT AND MACHINE LEARNING 279G. Vallathan, Senthilkumar Meyyappan and T. Rajani14.1 Introduction 28014.2 Energy Optimization Process 28114.3 Energy Optimization Techniques in Healthcare 28314.3.1 Energy Optimization in Building 28314.3.2 Machine Learning for Energy Optimization 28414.3.3 Reinforcement Learning for Energy Optimization 28614.3.4 Energy Optimization of Sustainable Internet of Things (IoT) 28714.4 Future Direction of Energy Optimizations 28814.5 Conclusion 289References 28915 CASE STUDY OF ENERGY OPTIMIZATION: ELECTRIC VEHICLE ENERGY CONSUMPTION MINIMIZATION USING GENETIC ALGORITHM 291Pedram Asef15.1 Introduction 29215.2 Vehicle Modelling to Optimisation 29515.2.1 Vehicle Mathematical Modelling 29515.2.2 Vehicle Model Optimisation Process: Applied Genetic Algorithm 29815.2.3 GA Optimisation Results and Discussion 30115.3 Conclusion 305References 305About the Editors 307Index 309
Scrum in der Praxis (3. Auflg.)
Erfahrungen, Problemfelder und ErfolgsfaktorenScrum ist die in Unternehmen am häufigsten verwendete agile Methode. Allerdings bietet Scrum zunächst lediglich ein Rahmenwerk, das durch eigene Ideen und Kreativität ausgefüllt und gestaltet werden muss. Um Scrum effizient anzuwenden, sind umfassende praktische Erfahrungen und ein grundlegendes Verständnis des agilen Wertesystems unabdingbar.Hier hilft dieses Buch: Anhand zahlreicher Praxisbeispiele wird dargestellt, wie Scrum aufgesetzt und durchgeführt werden kann, welche typischen Herausforderungen dabei auftreten und wie diesen entgegnet werden kann. Vorgestellt werden Handlungsalternativen, die dabei helfen, ein Projekt zielgerichtet und schnell auf die Erfolgsspur zu bringen. Auf Basis eines beispielhaften Projekts werden die Schlüsselstellen und konkrete anwendbare Empfehlungen zur Ausgestaltung gegeben.Die 3. Auflage enthält viele weitere Praxistipps und ein neues Kapitel zur Remote-Arbeit mit Scrum. Weiter werden die neuesten Anpassungen des Scrum Guide berücksichtigt.Autoren:Robert Wiechmann unterstützt seit 2008 mit Herzblut Organisationen bei ihrer agilen Transition. Seine Motivation als selbstständiger Berater und Coach ist es seit jeher, die Menschen von einer wert-, menschen- und kundenzentrierten Zusammenarbeit zu begeistern. Wertschätzung und Vertrauen bilden die Basis seiner Arbeit. Neben seiner beratenden und coachenden Tätigkeit ist er unter anderem als Trainer und Moderator tätig. Als Autor und Mitbegründer der agilen Community „Agile by Nature“ leistet er zudem seinen Beitrag, die Idee eines neuen Miteinanders in der Arbeitswelt zu verbreiten.Sven Röpstorff ist Gesellschafter der kommitment GmbH & Co. KG in Hamburg, wo er als Agile Coach, Trainer und Interim Manager tätig ist. Sein Ziel ist die nachhaltige Entwicklung von Organisationen, wobei für ihn immer der Mensch im Mittelpunkt steht. Sven ist stets auf der Suche nach Verbesserungen und neuen Wegen, um Agilität einem immer größer werdenden Publikum auf interessante und spielerische Weise nahezubringen. Seiner Meinung nach kann man agile Vorgehensweisen am besten dadurch veranschaulichen, dass man sie für die Menschen sichtbar, fühlbar, und erlebbar macht. Seine Erfahrungen aus vielen Jahren in unterschiedlichen Rollen und Projekten teilt er als Autor, Konferenzsprecher und Blogger und ist Mitbegründer der „Agile by Nature“ Community.Zielgruppen:Scrum Master, Agile CoachesProjektleiter*innenProduktmanager*innenEntwickler*innenIT-Management
Handbook for SAP PP in S/4HANA
If you're looking to increase your knowledge of one of the core modules of SAP S/4HANA, this is the book for you. Settle in and let a long-time SAP professional guide you through the SAP Production Planning and Execution module.Author Himanshu Goel begins by explaining the nuts and bolts of production planning in SAP S/4HANA, before delving into various manufacturing methodologies such as discrete manufacturing, repetitive manufacturing, and process industry. He'll then walk you through setting up master data such as the material master, bill of material, work center, routing, and production version. You'll then learn, step-by-step, how SAP PP processes are established from production order-based manufacturing to process order-based manufacturing.This book explains the complex concepts of production planning and execution in a straightforward manner and makes for an invaluable guide for SAP PP users from production planners to shop floor managers and even junior/mid-level SAP PP consultants. After reading this book, you'll fully understand the concepts of SAP PP, and have insight into the latest developments in S/4HANA.WHAT YOU WILL LEARN* Understand master data in SAP PP* Study production planning; i.e., SOP and demand management* Explore discrete and repetitive manufacturing* Acquire knowledge on Process IndustryWHO IS THIS BOOK FORProduction planners, shop floor managers, and junior or mid-level SAP PP consultants who are looking to understand the concepts of SAP PP in SAP S/4HANA.HIMANSHU GOEL is an SAP-certified Solution Architect. He has more than 15 years of experience in designing and deploying SAP solutions primarily in production planning and execution, quality management, and plant maintenance. He’s a supply chain professional focused on solving business problems and delivering customer-centric solutions. He has worked on several large-scale, end-to-end SAP implementation and rollout projects. He authored the e-bite Introducing the Material Master in SAP S/4HANA, published by SAP Press, and has also contributed several entries on blogs.sap.com. He is quite passionate about SAP and loves all things SAP.Chapter 1: IntroductionCHAPTER GOAL: This section introduces the three production execution methodologies made possible in SAP software, and at a high level describes what developments have happened related to discrete manufacturing in SAP S/4HANANo of pages: 10SUB -TOPICS :1.1 Manufacturing Types1.1.1 Discrete Manufacturing1.1.2 Repetitive Manufacturing1.1.3 Process ManufacturingChapter 2: Master DataCHAPTER GOAL: This section explains the master data needed for discrete manufacturing process.NO OF PAGES: 50SUB - TOPICS1. Material Master2. BOM3. Work Center4. Routing5. Production VersionCHAPTER 3: PRODUCTION PLANNINGCHAPTER GOAL: Production PlanningNO OF PAGES: 40SUB - TOPICS:1. Sales & Operation Planning2. Demand ManagementChapter 4: Material Requirement PlanningCHAPTER GOAL: This chapter explains the concepts of Material Requirement Planning in SAP.NO OF PAGES: 30SUB - TOPICS:1. Material Requirement Planning2. Master Production Scheduling3. Consumption Based PlanningChapter 5: Production Order ManagementCHAPTER GOAL: This chapter explains the production execution with Production order based manufacturing.No of pages: 40SUB - TOPICS:1. Production Order2. Goods Issue3. Confirmation4. Goods ReceiptChapter 6: Repetitive ManufacturingCHAPTER GOAL: This chapter explains the production execution with Repetitive manufacturing.No of pages: 20SUB - TOPICS:1. Master data for REM2. Production execution with REMChapter 7: Process Order ManagementChapter Goal: This chapter explains the production execution with Process order based manufacturing.NO OF PAGES: 40SUB - TOPICS:1. Process Order2. Goods Issue3. Confirmation4. Goods ReceiptCHAPTER 8: CAPACITY REQUIREMENT PLANNINGCHAPTER GOAL: This chapter explains the capacity requirement planning.No of pages: 20SUB - TOPICS:1. Capacity Evaluation2. Capacity LevellingCHAPTER 9: REPORTSCHAPTER GOAL: This chapter explains the important reports and tools that can be used in SAP PPNO OF PAGES: 20SUB - TOPICS:1. Stock Requirement List2. Production Order List3. Stock List4. Where used listCHAPTER 10: INNOVATIONS IN S/4HANACHAPTER GOAL: This chapter explains the latest innovations in S/4HANANO OF PAGES: 40SUB - TOPICS:1. Demand Driven MRP2. MRP Live3. Predictive MRP