Allgemein
Suchmaschinen verstehen
Suchmaschinen dienen heute selbstverständlich als Werkzeuge, um Informationen zu recherchieren. Doch wie funktionieren sie genau? Das Buch betrachtet Suchmaschinen aus vier Perspektiven: Technik, Nutzung, Recherche und gesellschaftliche Bedeutung. Es bietet eine klar strukturierte und verständliche Einführung in die Thematik. Zahlreiche Abbildungen erlauben eine schnelle Erfassung des Stoffs.Rankingverfahren und Nutzerverhalten werden dargestellt. Dazu kommen grundlegende Betrachtungen des Suchmaschinenmarkts, der Suchmaschinenoptimierung, der Suchmaschinenwerbung und der Rolle der Suchmaschinen als technische Informationsvermittler. Das Buch richtet sich an alle, die ein umfassendes Verständnis dieser Suchwerkzeuge erlangen wollen, u.a. Suchmaschinenoptimierer*innen, Entwickler*innen, Informationswissenschaftler*innen, Bibliothekarinnen und Bibliothekare sowie Verantwortliche im Online Marketing.Für die dritte Auflage wurde der Text vollständig überarbeitet, ergänzt sowie alle Statistiken und Quellen auf den neuesten Stand gebracht.DIRK LEWANDOWSKI ist Professor für Information Research und Information Retrieval an der Hochschule für Angewandte Wissenschaften Hamburg. Er ist einer der führenden Experten zum Thema Suchmaschinen und hat neben mehreren Büchern zahlreiche wissenschaftliche Aufsätze in internationalen Fachzeitschriften veröffentlicht.Einführung.- Einstieg.- Wie Suchmaschinen funktionieren.- Wie Suchmaschinen genutzt werden.- Das Ranking der Suchergebnisse.- Die Inhalte der Suchmaschinen und wie sie uns präsentiert werden.- Der Suchmaschinenmarkt.- Suchmaschinenoptimierung.- Alternativen zu Google.- Genaue Suchanfragen stellen mit der erweiterten Suche und Operatoren.- Quellen prüfen.- Das unsichtbare Web.- Recherche in sozialen Netzwerken, Frage-Antwort-Diensten und Operatoren.- Suchmaschinen und ihre Rolle als Vermittler von Informationen.- Ausblick.- Glossar.
AI for Healthcare with Keras and Tensorflow 2.0
Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, and strong QnA setup. And, lastly, after discussing how web and server technologies have come to make scaling and deploying easy, an ML app is deployed for the world to see with Docker using Flask.By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and deep learning tools and techniques to the healthcare industry.WHAT YOU WILL LEARN* Get complete, clear, and comprehensive coverage of algorithms and techniques related to case studies * Look at different problem areas within the healthcare industry and solve them in a code-first approach* Explore and understand advanced topics such as multi-task learning, transformers, and graph convolutional networks* Understand the industry and learn MLWHO THIS BOOK IS FORData scientists and software developers interested in machine learning and its application in the healthcare industryANSHIK has a deep passion for building and shipping data science solutions that create great business value. He is currently working as a senior data scientist at ZS Associates and is a key member on the team developing core unstructured data science capabilities and products. He has worked across industries such as pharma, finance, and retail, with a focus on advanced analytics. Besides his day-to-day activities, which involve researching and developing AI solutions for client impact, he works with startups as a data science strategy consultant. Anshik holds a bachelor’s degree from Birla Institute of Technology & Science, Pilani. He is a regular speaker at AI and machine learning conferences. He enjoys trekking and cycling.Chapter 1: Healthcare Market: A PrimerChapter Goal: Know how sub-markets like pharmaceutical, medicaltechnology, and hospital come together to form the healthcare ecosystem. Learn on how digital and mobile are shaping and reforming traditional health. With technology available and permissible to large masses via internet things like telehealth have become a norm. Also, what kind ofproblems are being solved at industry level and at various startups.Sub Topics:Healthcare Marketplace Overview● Map of how different stakeholder comes together to form the system● Medicare Overview● Paying Doctors● Healthcare CostsEmerging Trends● Changing role of consumer in healthcare● Future of Healthcare Payments● Quality of Healthcare DeliveryIndustry 4.0 and HealthcareChapter 2: Multi Task Deep Learning To Predict HospitalRe-admissionsChapter Goal: A real world case study showing how re-admissions whichcosts billions of dollars to the US healthcare system can be addressed. We will be using EHR data to cluster patients on their baseline characteristics and clinical factors and correlate with their readmission rates.Sub Topics:● Introduction to EHR data.● Exploring MIMIC III datasets● Establishing a baseline model to assess re-admission rates usingensemble of classification models with handling class imbalance.● Using auto-encoder to create a distributed representation of features.● Clustering patients● Analyzing readmission rate based on clusters.● Comparative analysis between baseline and deep learning basedmodel.Chapter 3: Predict Medical Billing Codes from Clinical NotesChapter Goal: Clinical notes contain information on prescribed proceduresand diagnosis from doctors and are used for accurate billings in the current medical system, but these are not readily available. One has to extract them manually for the process to be carried out seamlessly. We are attempting to solve this problem using a classification model using the MIMIC III datasets introduced above.Sub Topics:● Introduction to case study data.● Learn about transfer learning in NLP by fine-tuning the BERT modelfor your task.● Using various attention based sequence modelling architectures likeLSTM and transformers to predict medical billing codes.Chapter 4: Extracting Structured Data from Receipt ImagesChapter Goal: Just like any other sales job, the sales rep of a Pharma firm isalways on the field. While being on the field lots of receipts get generated for reimbursement on food and travel. It becomes difficult to keep track of bills which don’t follow company guidelines. In this case study we will explore how to extract information from receipt images and structure various information from it.Sub Topics:● Introduction to information extraction through Images.● Exploring receipt data● Using graph CNN to extract information○ What is a graph convolutional architecture○ How is it different from traditional convolutional layers○ Applications○ Hands on example to demonstrate training of a graph CNN● Exploring recent trends in extracting information from templatedocuments.Chapter 5: Handle Availability of Low-Training Data in HealthcareChapter Goal: Availability of training data has limited the use of advancedmodels and general interest for problems in the healthcaredomain. Get introduced to weak supervision techniques that canbe used to handle low training data. Also learn about upcominglibraries (like Snorkel and Astron) and research in this field.Sub Topics:● Explore weak supervision learning using Snorkel and Astron● Learn to create label functions● Hands on experimentation with a simple classification problem onapplication of concepts from weak supervised learningChapter 6: Federated Learning and HealthcareChapter Goal: Federated learning enables distributed machine learning inwhich machine learning models train on decentralized data.This is deemed as the future of ML models as sharing patientlevel data becomes more difficult for organizations due toprivacy and security concerns.Sub Topics:● Introduction to federated learning and what it means for healthcare● Hands on example on how to use the concepts of federated learningin one of your project○ Load and prepare an example decentralized datasets○ Design a federated learning architecture to predict diagnosisof inflammation in bladder.● Learn about TensorFlow federatedChapter 7: Medical ImagingChapter Goal: Complete end to end analysis of how to develop a deep -learning based medical diagnosis system using images. Learn about different kinds of image scans available like (cellular images, X-Ray scans etc.) . Also learn about the challenges such as accessibility of data, difference in image quality and how to address it, explainability etc. in disease detection via images.Sub Topics:● What is medical imaging● Different kinds of image analysis● Deep learning based methods for image analysis● Understanding how to deal with 2-D and 3-D images● Solve image classification and segmentation problem● Understand challenges like accessibility of data, image quality issues,explainability etc.Chapter 8: Machine has all the Answers, Except What’s the Purpose of Life.Chapter Goal: Introduction to concepts of a Question & Answering system.Comparative analysis of different Question and Answering architectures. Hands-on-Example of building your own Q&A system to ask and query questions over published medical papers on pubmed.Sub Topics:● Review and understand various Question & Answering Techniques.● Comparative analysis of different Question and Answeringarchitectures● What is BERT architecture ?● Using Bio-Bert architecture to train your own Q&A SystemChapter 9: You Need an Audience NowChapter Goal: Learned something from the book, excited to show it to theworld. In this chapter we are going to do exactly that, we are going to learn how to bring your models live and let the world interact with it. We will be building a Django app taking the Question Answering case study in point and also learning the basics of using docker for deployment.Sub Topics:● Understand technologies like Streamlit, Flask and Django that can helpyou deploy your model depending upon the use case.● What is docker and why should we dockerize our solutions.● Building a production grade docker application.● Django basics● Using services like Heroku or Github SPAs to deploy your DjangoApp and bring it live.
Entwickeln Sie Ihre eigene Blockchain
Dieses Buch bietet eine umfassende Einführung in die Blockchain- und Distributed-Ledger-Technologie. Es ist ein Leitfaden für Praktiker und enthält detaillierte Beispiele und Erklärungen, wie sich eine Blockchain von Grund auf neu aufbauen und betreiben lässt. Durch seinen konzeptionellen Hintergrund und praktische Übungen ermöglicht dieses Buch Studenten, Lehrern und Krypto-Enthusiasten, ihre erste Blockkette zu starten, wobei Vorkenntnisse der zugrunde liegenden Technologie vorausgesetzt werden. Wie baue ich eine Blockchain auf? Wie präge ich eine Kryptowährung? Wie schreibe ich einen Smart Contract? Wie starte ich ein Initial Coin Offering (ICO)? Dies sind einige der Fragen, die dieses Buch beantwortet. Ausgehend von den Anfängen und der Entwicklung früher Kryptowährungen werden die konzeptionellen Grundlagen für die Entwicklung sicherer Software beschrieben. Die Themen umfassen u. a. Konsens-Algorithmen, Mining und Dezentralisierung. „Dies ist ein einzigartiges Buch über die Blockchain-Technologie. Die Autoren haben die perfekte Balance zwischen Breite der Themen und Tiefe der technischen Diskussion gefunden. Aber das wahre Juwel ist die Sammlung sorgfältig kuratierter praktischer Übungen, die den Leser schon ab Kapitel 1 durch den Prozess des Aufbaus einer Blockchain führen.“ Volodymyr Babich, Professor für Betriebs- und Informationsmanagement, McDonough School of Business, Georgetown University „Eine ausgezeichnete Einführung in die DLT-Technologie für ein nicht-technisches Publikum. Das Buch ist vollgepackt mit Beispielen und Übungen, die das Erlernen der zugrunde liegenden Prozesse der Blockchain-Technologie für alle, vom Studenten bis zum Unternehmer, erheblich erleichtern.“ Serguei Netessine, Dhirubhai Ambani Professor für Innovation und Entrepreneurship, The Wharton School, University of Pennsylvania
Cultural Commons in the Digital Ecosystem
INTELLECTUAL TECHNOLOGIES SET COORDINATED BY JEAN-MAX NOYER AND MARYSE CARMESThe dynamics of production, circulation and dissemination of knowledge that are currently developing in the digital ecosystem testify to a profound change in capitalism. On the margins of the traditional duo of knowledge markets and exclusive property rights, the emerging notion of cultural commons is opening the door to new modes of production based on hybrid market arrangements and an inclusive understanding of property.This book studies the political economy of cultural commons in the digital ecosystem, outlining the contexts and areas of thought in which this concept has emerged and identifying the socio-economic, technical and political issues associated with it. It also analyzes the specific physical conditions that enable the implementation of the economy of cultural commons in a specific digital ecosystem, that of books, by studying the effects of digital libraries and self-publishing platforms. MAUD PÉLISSIER is an Associate Professor and Research Director. She carries out her research at the Mediterranean Institute for Information and Communication Sciences of the University of Toulon, France.Introduction ixPART 1. THE INTELLECTUAL MOVEMENT OF THE CULTURAL COMMONS 1INTRODUCTION TO PART 1 3CHAPTER 1. THE PIONEERING APPROACH OF JURISTS FROM THE BERKMAN CENTER FOR INTERNET AND SOCIETY 71.1. A critique of the maximalist doctrine of intellectual property 71.1.1. The enclosure of the intangible commons of the mind 91.1.2. The threat of disappearance of free culture in cyberspace 121.2. The political economy of information commons 171.2.1. Shared ownership and individual freedom 181.2.2. A new mode of information production 221.3. The creative commons in the field of works of the mind 281.3.1. Incarnation of free culture practices 281.3.2. Institutionalization of free culture: Creative Commons licenses 311.3.3. The modalities of cohabitation with the commercial cultural economy 341.4. Propagation in the intellectual and militant sphere in France 421.4.1. The challenge of legalizing non-market sharing 431.4.2. The challenge of legal recognition of the information commons 491.5. Recent extensions of the BCIS approach 541.5.1. The digital public domain: the perimeter of cultural commons 551.5.2. Network infrastructure as a commons 601.5.3. Remuneration of volunteer contributors 63CHAPTER 2. THE OSTROMIAN APPROACH TO THE KNOWLEDGE COMMONS 692.1. Ostrom’s original theory of the land commons 712.1.1. An institutional definition of the commons 712.1.2. A questioning of the “tragedy of the commons” 722.1.3. Communal property as a bundle of rights 752.1.4. An institutional approach to the self-organization of common resources 782.2. The knowledge commons: Hess and Ostrom’s approach 802.2.1. The singularity of information common pool resources (CPR) 802.2.2. Digital libraries as information CPRs 842.2.3. Institutional analysis and development framework (IAD) 872.3. Open access platforms as scientific commons? 902.3.1. Open access: a major transformation of the editorial ecosystem 912.3.2. Open access platforms: which bundles of user rights? 992.3.3. Enrichment and sustainability of the scientific commons 1072.4. Cooperative platforms as social commons? 1182.4.1. A rapprochement with the social and solidarity economy 1182.4.2. Conditions for exploiting the social value created 1222.4.3. Governance of cooperative platforms 1262.4.4. Commoners’ remuneration: a right to contribute 133PART 2. THE COMMONS IN THE DIGITAL BOOK ECOSYSTEM 137INTRODUCTION TO PART 2 139CHAPTER 3. DIGITAL LIBRARIES AS HERITAGE COMMONS 1413.1. A favorable context 1423.1.1. A new documentary order 1423.1.2. Cultural public data as a public good 1443.2. The production methods of heritage commons 1493.2.1. The Google challenge 1493.2.2. Public/private partnerships: threat or opportunity? 1523.2.3. On-demand digitization and citizen contribution 1563.2.4. The heritage commons: a plasticity of forms 1573.3. Governance issue: enriching our common heritage 1613.3.1. The construction of a shared heritage infrastructure 1613.3.2. Content editorialization and digital mediation 164CHAPTER 4. THE WRITTEN COMMONS IN THE PUBLISHING INDUSTRY 1694.1. The transformations of the editorial ecosystem 1704.1.1. Digital textuality and new uses 1704.1.2. The digital book immersed in an attention economy 1724.1.3. The digital book and the growth of self-publishing 1764.2. Wattpad: a common narrative of the misguided written word 1784.2.1. The use of CC licenses: a hidden reality 1794.2.2. A progressive attraction to the attention economy 1804.2.3. Strengthened cohabitation with publishers: the announced end of free culture 1824.3. Self-publishing and free culture: a multifaceted face 1844.3.1. The Lulu platform: open source for the book market? 1844.3.2. In Libro Veritas and Framabook: free book editions 187Conclusion 193References 199Index 207
Smart Healthcare System Design
SMART HEALTHCARE SYSTEM DESIGNTHIS BOOK DEEPLY DISCUSSES THE MAJOR CHALLENGES AND ISSUES FOR SECURITY AND PRIVACY ASPECTS OF SMART HEALTH-CARE SYSTEMS.The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. AUDIENCE: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable. SK HAFIZUL ISLAM received his PhD degree in Computer Science and Engineering in 2013 from the Indian Institute of Technology [IIT (ISM)] Dhanbad, Jharkhand, India. He is an assistant professor in the Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani (IIIT Kalyani), West Bengal, India. He has authored or coauthored 110 research papers in journals and conference proceedings.DEBABRATA SAMANTA is an assistant professor in the Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his PhD in Computer Science and Engg. from the National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. He is the owner of 17 Indian patents and has authored and coauthored more than 135 research papers in international journals. Preface xviiAcknowledgments xxiii1 MACHINE LEARNING TECHNOLOGIES IN IOT EEG-BASED HEALTHCARE PREDICTION 1Karthikeyan M.P., Krishnaveni K. and Muthumani N.1.1 Introduction 21.1.1 Descriptive Analytics 31.1.2 Analytical Methods 31.1.3 Predictive Analysis 41.1.4 Behavioral Analysis 41.1.5 Data Interpretation 41.1.6 Classification 41.2 Related Works 71.3 Problem Definition 91.4 Research Methodology 91.4.1 Components Used 101.4.2 Specifications and Description About Components 101.4.2.1 Arduino 101.4.2.2 EEG Sensor—Mindwave Mobile Headset 111.4.2.3 Raspberry pi 121.4.2.4 Working 131.4.3 Cloud Feature Extraction 131.4.4 Feature Optimization 141.4.5 Classification and Validation 151.5 Result and Discussion 161.5.1 Result 161.5.2 Discussion 231.6 Conclusion 271.6.1 Future Scope 27References 282 SMART HEALTH APPLICATION FOR REMOTE TRACKING OF AMBULATORY PATIENTS 33Shariq Aziz Butt, Muhammad Waqas Anjum, Syed Areeb Hassan, Arindam Garai and Edeh Michael Onyema2.1 Introduction 342.2 Literature Work 342.3 Smart Computing for Smart Health for Ambulatory Patients 352.4 Challenges With Smart Health 362.4.1 Emergency Support 362.4.2 The Issue With Chronic Disease Monitoring 382.4.3 An Issue With the Tele-Medication 382.4.4 Mobility of Doctor 402.4.5 Application User Interface Issue 402.5 Security Threats 412.5.1 Identity Privacy 412.5.2 Query Privacy 422.5.3 Location of Privacy 422.5.4 Footprint Privacy and Owner Privacy 432.6 Applications of Fuzzy Set Theory in Healthcare and Medical Problems 432.7 Conclusion 51References 513 DATA-DRIVEN DECISION MAKING IN IOT HEALTHCARE SYSTEMS—COVID-19: A CASE STUDY 57Saroja S., Haseena S. and Blessa Binolin Pepsi M.3.1 Introduction 583.1.1 Pre-Processing 593.1.2 Classification Algorithms 603.1.2.1 Dummy Classifier 603.1.2.2 Support Vector Machine (SVM) 603.1.2.3 Gradient Boosting 613.1.2.4 Random Forest 623.1.2.5 Ada Boost 633.2 Experimental Analysis 633.3 Multi-Criteria Decision Making (MCDM) Procedure 633.3.1 Simple Multi Attribute Rating Technique (SMART) 643.3.1.1 COVID-19 Disease Classification Using SMART 643.3.2 Weighted Product Model (WPM) 663.3.2.1 COVID-19 Disease Classification Using WPM 663.3.3 Method for Order Preference by Similarity to the Ideal Solution (TOPSIS) 673.3.3.1 COVID-19 Disease Classification Using TOPSIS 683.4 Conclusion 69References 694 TOUCH AND VOICE-ASSISTED MULTILINGUAL COMMUNICATION PROTOTYPE FOR ICU PATIENTS SPECIFIC TO COVID-19 71B. Rajesh Kanna and C.Vijayalakshmi4.1 Introduction and Motivation 724.1.1 Existing Interaction Approaches and Technology 734.1.2 Challenges and Gaps 744.2 Proposed Prototype of Touch and Voice-Assisted Multilingual Communication 754.3 A Sample Case Study 824.4 Conclusion 82References 845 CLOUD-ASSISTED IOT SYSTEM FOR EPIDEMIC DISEASE DETECTION AND SPREAD MONITORING 87Himadri Nath Saha, Reek Roy and Sumanta Chakraborty5.1 Introduction 885.2 Background & Related Works 925.3 Proposed Model 985.3.1 ThinkSpeak 1005.3.2 Blood Oxygen Saturation (SpO2) 1005.3.3 Blood Pressure (BP) 1015.3.4 Electrocardiogram (ECG) 1015.3.5 Body Temperature (BT) 1025.3.6 Respiration Rate (RR) 1025.3.7 Environmental Parameters 1035.4 Methodology 1035.5 Performance Analysis 1105.6 Future Research Direction 1115.7 Conclusion 112References 1136 IMPACT OF HEALTHCARE 4.0 TECHNOLOGIES FOR FUTURE CAPACITY BUILDING TO CONTROL EPIDEMIC DISEASES 115Himadri Nath Saha, Sumanta Chakraborty, Sourav Paul, Rajdeep Ghosh and Dipanwita Chakraborty Bhattacharya6.1 Introduction 1166.2 Background and Related Works 1206.3 System Design and Architecture 1286.4 Methodology 1316.5 Performance Analysis 1386.6 Future Research Direction 1386.7 Conclusion 139References 1397 SECURITY AND PRIVACY OF IOT DEVICES IN HEALTHCARE SYSTEMS 143Himadri Nath Saha and Subhradip Debnath7.1 Introduction 1447.2 Background and Related Works 1457.3 Proposed System Design and Architecture 1477.3.1 Modules 1487.3.1.1 Wireless Body Area Network 1487.3.1.2 Centralized Network Coordinator 1497.3.1.3 Local Server 1497.3.1.4 Cloud Server 1507.3.1.5 Dedicated Network Connection 1517.4 Methodology 1517.5 Performance Analysis 1607.6 Future Research Direction 1617.7 Conclusion 163References 1648 AN IOT-BASED DIET MONITORING HEALTHCARE SYSTEM FOR WOMEN 167Suganyadevi S., Shamia D. and Balasamy K.8.1 Introduction 1688.2 Background 1778.2.1 Food Consumption 1778.2.2 Food Consumption Monitoring 1788.2.3 Health Monitoring Methods Using Physical Methodology 1798.2.3.1 Traditional Form of Self-Report 1798.2.3.2 Self-Reporting Methodology Through Smart Phones 1798.2.3.3 Food Frequency Questionnaire 1798.2.4 Methods for Health Tracking Using Automated Approach 1808.2.4.1 Pressure Process 1808.2.4.2 Surveillance Video Method 1808.2.4.3 Method of Doppler Sensing 1808.3 Necessity of Wearable Approach? 1818.4 Different Approaches for Wearable Sensing 1818.4.1 Approach of Acoustics 1828.4.1.1 Detection of Chewing 1828.4.1.2 Detection of Swallowing 1838.4.1.3 Shared Chewing/Swallowing Discovery 1838.5 Description of the Methodology 1848.6 Description of Various Components Used 1858.6.1 Sensors 1858.6.1.1 Sensors for Cardio-Vascular Monitoring 1858.6.1.2 Sensors for Activity Monitoring 1868.6.1.3 Sensors for Body Temperature Monitoring 1878.6.1.4 Sensor for Galvanic Skin Response (GSR) Monitoring 1888.6.1.5 Sensor for Monitoring the Blood Oxygen Saturation (SpO2 ) 1898.7 Strategy of Communication for Wearable Systems 1898.8 Conclusion 192References 1949 A SECURE FRAMEWORK FOR PROTECTING CLINICAL DATA IN MEDICAL IOT ENVIRONMENT 203Balasamy K., Krishnaraj N., Ramprasath J. and Ramprakash P.9.1 Introduction 2039.1.1 Medical IoT Background & Perspective 2049.1.1.1 Medical IoT Communication Network 2049.2 Medical IoT Application Domains 2099.2.1 Smart Doctor 2099.2.2 Smart Medical Practitioner 2099.2.3 Smart Technology 2099.2.4 Smart Receptionist 2109.2.5 Disaster Response Systems (DRS) 2109.3 Medical IoT Concerns 2109.3.1 Security Concerns 2119.3.2 Privacy Concerns 2129.3.3 Trust Concerns 2129.4 Need for Security in Medical IoT 2129.5 Components for Enhancing Data Security in Medical IoT 2149.5.1 Confidentiality 2149.5.2 Integrity 2149.5.3 Authentication 2159.5.4 Non-Repudiation 2159.5.5 Privacy 2159.6 Vulnerabilities in Medical IoT Environment 2159.6.1 Patient Privacy Protection 2159.6.2 Patient Safety 2169.6.3 Unauthorized Access 2169.6.4 Medical IoT Security Constraints 2179.7 Solutions for IoT Healthcare Cyber-Security 2189.7.1 Architecture of the Smart Healthcare System 2189.7.1.1 Data Perception Layer 2189.7.1.2 Data Communication Layer 2199.7.1.3 Data Storage Layer 2199.7.1.4 Data Application Layer 2199.8 Execution of Trusted Environment 2209.8.1 Root of Trust Security Services 2209.8.2 Chain of Trust Security Services 2229.9 Patient Registration Using Medical IoT Devices 2239.9.1 Encryption 2249.9.2 Key Generation 2259.9.3 Security by Isolation 2259.9.4 Virtualization 2259.10 Trusted Communication Using Block Chain 2299.10.1 Record Creation Using IoT Gateways 2299.10.2 Accessibility to Patient Medical History 2309.10.3 Patient Enquiry With Hospital Authority 2309.10.4 Block Chain Based IoT System Architecture 2319.10.4.1 First Layer 2319.10.4.2 Second Layer 2319.10.4.3 Third Layer 2329.11 Conclusion 232References 23310 EFFICIENT DATA TRANSMISSION AND REMOTE MONITORING SYSTEM FOR IOT APPLICATIONS 235Laith Farhan, Firas MaanAbdulsattar, Laith Alzubaidi, Mohammed A. Fadhel, Banu ÇalışUslu and Muthana Al-Amidie10.1 Introduction 23610.2 Network Configuration 23610.2.1 Message Queuing Telemetry Transport (MQTT) Protocol 23810.2.2 Embedded Database SQLite 24210.2.3 Eclipse Paho Library 24210.2.4 Raspberry Pi Single Board Computer 24210.2.5 Custard Pi Add-On Board 24310.2.6 Pressure Transmitter (Type 663) 24410.3 Data Filtering and Predicting Processes 24510.3.1 Filtering Process 24510.3.2 Predicting Process 24610.3.3 Remote Monitoring Systems 24810.4 Experimental Setup 24910.4.1 Implementation Using Python 25110.4.1.1 Prerequisites 25110.4.2 Monitoring Data 25110.4.3 Experimental Results 25510.4.3.1 IoT Device Results 25510.4.3.2 Traditional Network Results 25710.5 Conclusion 261References 26111 IOT IN CURRENT TIMES AND ITS PROSPECTIVE ADVANCEMENTS 265T. Venkat Narayana Rao, Abhishek Duggirala, Muralidhar Kurni and Syed Tabassum Sultana11.1 Introduction 26611.1.1 Introduction to Industry 4.0 26611.1.2 Introduction to IoT 26611.1.3 Introduction to IIoT 26711.2 How IIoT Advances Industrial Engineering in Industry 4.0 Era 26711.3 IoT and its Current Applications 26811.3.1 Home Automation 26811.3.2 Wearables 26911.3.3 Connected Cars 26911.3.4 Smart Grid 26911.4 Application Areas of IIoT 27011.4.1 IIoT in Healthcare 27011.4.2 IIoT in Mining 27011.4.3 IIoT in Agriculture 27111.4.4 IIoT in Aerospace 27111.4.5 IIoT in Smart Cities 27211.4.6 IIoT in Supply Chain Management 27211.5 Challenges of Existing Systems 27211.5.1 Security 27211.5.2 Integration 27311.5.3 Connectivity Issues 27311.6 Future Advancements 27311.6.1 Data Analytics in IoT 27411.6.2 Edge Computing 27411.6.3 Secured IoT Through Blockchain 27411.6.4 A Fusion of AR and IoT 27511.6.5 Accelerating IoT Through 5G 27511.7 Case Study of DeWalt 27511.8 Conclusion 276References 27612 RELIANCE ON ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND DEEP LEARNING IN THE ERA OF INDUSTRY 4.0 281T. Venkat Narayana Rao, Akhila Gaddam, Muralidhar Kurni and K. Saritha12.1 Introduction to Artificial Intelligence 28212.1.1 History of AI 28212.1.2 Views of AI 28212.1.3 Types of AI 28312.1.4 Intelligent Agents 28412.2 AI and its Related Fields 28612.3 What is Industry 4.0? 28912.4 Industrial Revolutions 28912.4.1 First Industrial Revolution (1765) 29012.4.2 Second Industrial Revolution (1870) 29012.4.3 Third Industrial Revolution (1969) 29012.4.4 Fourth Industrial Revolution 29112.5 Reasons for Shifting Towards Industry 4.0 29112.6 Role of AI in Industry 4.0 29212.7 Role of ML in Industry 4.0 29212.8 Role of Deep Learning in Industry 4.0 29312.9 Applications of AI, ML, and DL in Industry 4.0 29412.10 Challenges 29512.11 Top Companies That Use AI to Augment Manufacturing Processes in the Era of Industry 4.0 29612.12 Conclusion 297References 29713 THE IMPLEMENTATION OF AI AND AI-EMPOWERED IMAGING SYSTEM TO FIGHT AGAINST COVID-19—A REVIEW 301Sanjay Chakraborty and Lopamudra Dey13.1 Introduction 30213.2 AI-Assisted Methods 30413.2.1 AI-Driven Tools to Diagnose COVID-19 and Drug Discovery 30413.2.2 AI-Empowered Image Processing to Diagnosis 30613.3 Optimistic Treatments and Cures 30713.4 Challenges and Future Research Issues 30813.5 Conclusion 308References 30914 IMPLEMENTATION OF MACHINE LEARNING TECHNIQUES FOR THE ANALYSIS OF TRANSMISSION DYNAMICS OF COVID-19 313C. Vijayalakshmi and S. Bangusha Devi14.1 Introduction 31414.2 Data Analysis 31514.3 Methodology 31514.3.1 Linear Regression Model 31514.3.2 Time Series Model 31814.4 Results and Discussions 32014.4.1 Model Estimation and Studying its Adequacy 32314.4.2 Regression Model for Daily New Cases and New Deaths 33014.5 Conclusions 348References 348Index 351
The Definitive Guide to Conversational AI with Dialogflow and Google Cloud
Build enterprise chatbots for web, social media, voice assistants, IoT, and telephony contact centers with Google's Dialogflow conversational AI technology. This book will explain how to get started with conversational AI using Google and how enterprise users can use Dialogflow as part of Google Cloud. It will cover the core concepts such as Dialogflow essentials, deploying chatbots on web and social media channels, and building voice agents including advanced tips and tricks such as intents, entities, and working with context.The Definitive Guide to Conversational AI with Dialogflow and Google Cloud also explains how to build multilingual chatbots, orchestrate sub chatbots into a bigger conversational platform, use virtual agent analytics with popular tools, such as BigQuery or Chatbase, and build voice bots. It concludes with coverage of more advanced use cases, such as building fulfillment functionality, building your own integrations, securing your chatbots, and building your own voice platform with the Dialogflow SDK and other Google Cloud machine learning APIs.After reading this book, you will understand how to build cross-channel enterprise bots with popular Google tools such as Dialogflow, Google Cloud AI, Cloud Run, Cloud Functions, and Chatbase.WHAT YOU WILL LEARN* Discover Dialogflow, Dialogflow Essentials, Dialogflow CX, and how machine learning is used* Create Dialogflow projects for individuals and enterprise usage* Work with Dialogflow essential concepts such as intents, entities, custom entities, system entities, composites, and how to track context* Build bots quickly using prebuilt agents, small talk modules, and FAQ knowledge bases* Use Dialogflow for an out-of-the-box agent review* Deploy text conversational UIs for web and social media channels* Build voice agents for voice assistants, phone gateways, and contact centers* Create multilingual chatbots* Orchestrate many sub-chatbots to build a bigger conversational platform* Use chatbot analytics and test the quality of your Dialogflow agent* See the new Dialogflow CX concepts, how Dialogflow CX fits in, and what’s different in Dialogflow CXWHO THIS BOOK IS FOREveryone interested in building chatbots for web, social media, voice assistants, or contact centers using Google’s conversational AI/cloud technology.Lee Boonstra is a senior developer advocate at Google working with conversational AI. In this role she focuses on Dialogflow, Contact Center AI and speech technology. Lee is based in Amsterdam, the Netherlands, where she has been working with different technologies over the past 15 years, ranging from web/mobile, Ext JS, Sencha Touch, and Node.js, to conversational AI, Dialogflow, Actions on Google and Contact Centers.Over the years she has helped many brands and enterprises to build and deploy conversational AI solutions (chatbots and voice assistants) at enterprise scale. She’s worn different hats from engineer to technical trainer to sales engineer to developer advocate. Prior to Google, Lee worked at Sencha Inc.You can find Lee on online via the Twitter handle: @ladysign.CHAPTER 1: INTRODUCTION TO CONVERSATIONAL AIWhy do some chatbots fail?Machine learning simply explainedChatbots and machine learningMachine learning and GoogleAbout DialogflowDialogflow essentials & Dialogflow CXAbout Google CloudAbout Contact Center AIOther Google conversational AI productsActions on Google / Action BuilderAdLingoChatbaseDuplexMeenaSummaryReferenceCHAPTER 2: GETTING STARTED WITH DIALOGFLOW ESSENTIALSCreating a Dialogflow agentCreating Dialogflow agents for enterprisesConfiguring your Dialogflow projectSummaryReferenceCHAPTER 3: DIALOGFLOW ESSENTIALS CONCEPTSSetting up intentsCreating custom entitiesCreating intents with entities in training phrasesKeeping contextTesting in the simulatorSummaryReferenceCHAPTER 4: BUILDING CHATBOTS WITH TEMPLATESCreating prebuilt agentsEnabling small talk modulesCreating a FAQ knowledge baseSummaryReferenceCHAPTER 5: REVIEWING YOUR AGENTValidating your Dialogflow agentSummaryReferenceCHAPTER 6: DEPLOYING YOUR CHATBOT TO WEB & SOCIAL MEDIA CHANNELSIntegrating your agent with Google ChatIntegrating your agent with a web demoIntegrating your agent with a Dialogflow MessengerSummaryReferenceCHAPTER 7: BUILDING VOICE AGENTSBuilding a voice AI for a virtual assistant like the Google AssistantBuilding a callbot with a phone gatewayBuilding bots for contact centers with Contact Center AIImproving speech qualityFine tuning voice bots with SSMLSummaryReferenceCHAPTER 8: CREATING A MULTILINGUAL CHATBOTBuilding multilingual chatbotsSummaryReferenceCHAPTER 9: ORCHESTRATE MULTIPLE SUB CHATBOTS FROM ONE CHAT INTERFACECreating a mega agentSummaryReferenceCHAPTER 10: CREATING FULFILLMENT WEBHOOKSBuilding a fulfillment with the built-in editorBuilding webhook fulfillmentsBuilding multilingual webhook fulfillmentsUsing local webhooksSecuring webhooksSummaryReferenceCHAPTER 11: CREATING A CUSTOM INTEGRATION WITH THE DIALOGFLOW SDKImplementing a custom chatbot in your website front-endCreating rich responses in your chatbot integrationUsing markdown syntax & conditional templates in in your Dialogflow responsesSummaryReferenceCHAPTER 12: IMPLEMENTING A DIALOGFLOW VOICE AGENT IN YOUR WEBSITE OR APP USING THE SDKBuilding a client-side web application which streams audio from a browser microphone to a serverBuilding a web server which receives a browser microphone stream to detect intentsRetrieving audio results from Dialogflow and play it in your browserSummaryReferenceCHAPTER 13: COLLECTING & MONITORING ADVANCED AGENT INSIGHTSCapturing conversation related metrics to store in BigQuerySession IdDate / time stampSentiment scoreLanguage & keywordPlatformIntent detectionBuilding a platform for capturing conversation related metrics and redact sensitive informationDetecting user sentimentMonitoring chat session & funnel metrics with Dialogflow , Chatbase or Actions on GoogleTotal UsageThe number of requests the intent was matched to and the percentage of all users that matched the intent.Completion Rate & Drop off Rate / Drop off PlaceUser retentionEndpoint healthDiscoveryDialogflow Built-in AnalyticsMonitoring metrics with ChatbaseAnalytics on Actions on GoogleCapturing chatbot model health metrics for testing the underlying NLU model qualityTrue positive - A correctly matched intentFalse positive - A misunderstood requestTrue negative - An unsupported requestFalse negative - A missed requestAccuracyPrecisionRecall & falloutF1 scoreConfusion matrixROC curveImprove the Dialogflow NLU model with built-in trainingSummaryReference
The Future of the Automotive Industry
Nothing defined the 20th century more than the evolution of the car industry. The 2020 decade will see the automotive industry leap forward beyond simply moving people geographically toward a new purpose: to become a services industry. This book takes readers on a journey where cars will evolve towards becoming “computers on wheels."The automotive industry is one of the sectors most profoundly changed by digitalization and the 21st century energy needs. You'll explore the shifting paradigms and how cars today represent a new interpretation of what driving should be and what cars should offer. This book presents exciting case studies on how artificial intelligence (AI) and data analytics are used to design future cars, predict car efficiency, ensure safety and simulate engineering dynamics for its design, as well as a new arena for IoT and human data. It opens a window into the origins of cars becoming software-run machines, first to run internal diagnostics, and then to become machines connected to other external machines via Bluetooth, to finally the Internet via 5G.From transportation to solving people’s problems, The Future of the Automotive Industry is less about the technology itself, but more about the outcomes of technology in the future, and the transformative power it has over a much beloved item: cars.WHAT YOU’LL LEARN* Explore smart cities and their evolution when it comes to traffic and vehicles* Gain a new perspective on the future of cars and transportation based on how digital technologies will transform vehicles * Examine how AI and IoT will create new contexts of interactions with drivers and passengers alike* Review concepts such as personalizing the driving experience and how this will take form* See how self-driving cars impact data mining of personal dataWHO THISBOOK IS FORAnyone with an interest in digital advancements in the automotive industry beyond the connected car.Inma Martinez is a digital pioneer and A.I. scientist who has worked across a variety of sectors driving forth their digital transformation. The automotive industry is one of them, where she has worked since the mid-2000s in vehicle connectivity and innovation as well as venturing out into the Formula 1 experience. Inma intimately knows how cars are conceptualized, designed, manufactured, branded, sold, and now, how their evolving into digital machines, a future that is bound to transform this industry from transportation into a services sector, solving people’s problems and addressing the green economy challenges.Chapter 1: OK Computer.- Chapter 2: Mission Control.- Chapter 3: The 5G Car.- Chapter 4: On Brand.- Chapter 5: I.AM.Car.- Chapter 6: Second Home.- Chapter 7: Automation.- Chapter 8: Together in Electric Dreams.- Chapter 9: Smart.- Chapter 10: Digital.
Embracing Risk
THIS BOOK PROVIDES AN INTRODUCTION TO THE THEORY AND PRACTICE OF CYBER INSURANCE. Insurance as an economic instrument designed for risk management through risk spreading has existed for centuries. Cyber insurance is one of the newest sub-categories of this old instrument. It emerged in the 1990s in response to an increasing impact that information security started to have on business operations. For much of its existence, the practice of cyber insurance has been on how to obtain accurate actuarial information to inform specifics of a cyber insurance contract. As the cybersecurity threat landscape continues to bring about novel forms of attacks and losses, ransomware insurance being the latest example, the insurance practice is also evolving in terms of what types of losses are covered, what are excluded, and how cyber insurance intersects with traditional casualty and property insurance. The central focus, however, has continued to be risk management through risk transfer, the key functionality of insurance.The goal of this book is to shift the focus from this conventional view of using insurance as primarily a risk management mechanism to one of risk control and reduction by looking for ways to re-align the incentives. On this front we have encouraging results that suggest the validity of using insurance as an effective economic and incentive tool to control cyber risk. This book is intended for someone interested in obtaining a quantitative understanding of cyber insurance and how innovation is possible around this centuries-old financial instrument.* Preface* Acknowledgments* Introduction: What is Insurance and What is Cyber Insurance?* A Basic Cyber Insurance Contract Model* Insuring Clients with Dependent Risks* A Practical Underwriting Process* How to Pre-Screen: Risk Assessment Using Data Analytics* Open Problems and Closing Thoughts* Bibliography* Author's Biography
Mit Arduino die elektronische Welt entdecken
Der Arduino-Mikrocontroller ist aus der Elektronikwelt nicht mehr wegzudenken, er hat sich zu einem Standard im Hobbybereich entwickelt. In unzahligen Projekten kommt das Arduino-Board zum Einsatz, Hunderttausende von ausgereiften Softwarelosungen stehen fur jeden zuganglich und unter freier Lizenz zur Verfugung. Der Arduino ist leicht zu programmieren. Preiswerte elektronische Bauteile wie LCDs, Sensoren und Motoren konnen an das Arduino-Board angeschlossen und damit gesteuert werden. Mit "e;Arduino die elektronische Welt entdecken"e; fhrt den Leser in die faszinierende Welt der Elektronik und Programmierung ein. Die Hardware wird leicht verstndlich dargestellt und die Programmierung des Mikrocontrollers Schritt fr Schritt grundstzlich erklrt. Herzstck des Buches sind 48 detailliert beschriebene Arduino-Bastelprojekte, wobei sich die Komplexitt von Projekt zu Projekt steigert. In jedem Bastelprojekt wird ein neues Grundlagenthema behandelt, neue Hardware wird eingefhrt und neue Programmierkniffeund -werkzeuge werden vorgestellt. Jedes Bastelprojekt ist mit zahlreichen Fotos und Abbildungen illustriert und kann Schritt fr Schritt nachgebaut werden. Alle verwendeten Bauteile werden genau erklrt und in ihrer prinzipiellen Funktionsweise vorgestellt. Die Bastelprojekte knnen beliebig erweitert und fr andere Zwecke angepasst werden. Generationen von Hobbybastlern haben mit Erik Bartmanns Bestsellerbuch bereits die Arduino-Programmierung gelernt. In der komplett berarbeiteten 4. Neuauflage des Arduino-Standardwerkes wurden neue Bauteile wie der ESP32 oder LoRaWAN aufgenommen und neue Entwicklerwerkzeuge wie Node-RED, KiCad und MQTT behandelt.
Stability Analysis and Controller Design of Local Model Networks
This book treats various methods for stability analysis and controller design of local model networks (LMNs). LMNs have proved to be a powerful tool in nonlinear dynamic system identification. Their system architecture is more suitable for controller design compared to alternative approximation methods. The main advantage is that linear controller design methods can be, at least locally, applied and combined with nonlinear optimization to calibrate stable state feedback as well as PID controller. The calibration of stable state-feedback controllers is based on the closed loop stability analysis methods. Here, global LMIs (Linear Matrix Inequalities) can be derived and numerically solved. For LMN based nonlinear PID controllers deriving global LMIs is not possible. Thus, two approaches are treated in this book. The first approach works iteratively to get LMIs in each iteration step. The second approach uses a genetic algorithm to determine the PID controller parameters where for each individual the stability is checked. It allows simultaneous enhancement of (competing) optimization criteria. CHRISTIAN MAYR received the M.S. degree in mechanical engineering, the Ph.D. degree in technical sciences from TU Wien, Vienna, Austria, in 2009 and 2013, respectively. Since 2013 he is with AVL List GmbH, Graz, Austria. First as Development Engineer, from 2017 as Project Manager, in 2020 as Team Leader and since 2021 Department Manager for Virtualization Application. Dynamic Local Model Networks.- Open Loop Stability Analysis.- Closed-Loop Stability Analysis and Controller Design.- PID Controller Design.
Die Oracle Datenbank 19c
Diese Einführung in die Oracle Datenbankadministration bietet einen schnellen Einstieg in die Installation, den Betrieb und das Backup einer Oracle 19c Datenbank. Dabei liegt der Fokus auf Datenbanken, die nicht in der Cloud, sondern auf eigenen Servern (on premise) betrieben werden. Es wird gezeigt, wie eine Einzelinstanz als herkömmliche Non-CDB oder als Multitenant-Containerdatenbank aufgesetzt werden kann und wie beim Aufbau eines Real Application Clusters vorgegangen werden muss. Erläutert werden die Komponenten, aus denen eine Datenbank und ihre Instanz bestehen, die Bedeutung von Speicherbereichen und Schemaobjekten. Die Besonderheiten einer Containerdatenbank gegenüber der älteren Non-CDB Architektur werden beschrieben. Hinweise werden gegeben, welche Initialisierungsparameter besser auf ihren Vorgabewerten belassen und welche unbedingt angepasst werden sollten. Besonderen Raum wurde dem Thema Backup und Recovery eingeräumt. Es wird gezeigt, welche Befehle in einem Sicherungsskript nicht fehlen sollten und wie Schäden an einer Oracle Datenbank erkannt und repariert werden können. Nach der Lektüre sollten sich Leserinnen und Leser nicht mehr orientierungslos gegenüber einer Oracle Datenbank fühlen.Thorsten Grebe berät und betreut seit über 15 Jahren Organisationen aus Wirtschaft und öffentlichem Dienst zur Oracle Datenbank. Er ist Oracle Certified Master (OCM) und hat auf der DOAG Jahreskonferenz in Nürnberg, Europas größter Oracle Anwenderkonferenz, mehrere Vorträge zu Kernthemen der Oracle Datenbank gehalten. Einführung - Installation - Oracle Datenbank Grundlagen - Backup und Recovery
Third Space, Information Sharing, and Participatory Design
SOCIETY FACES MANY CHALLENGES IN WORKPLACES, EVERYDAY LIFE SITUATIONS, AND EDUCATION CONTEXTS. Within information behavior research, there are often calls to bridge inclusiveness and for greater collaboration, with user-centered design approaches and, more specifically, participatory design practices. Collaboration and participation are essential in addressing contemporary societal challenges, designing creative information objects and processes, as well as developing spaces for learning, and information and research interventions. The intention is to improve access to information and the benefits to be gained from that. This also applies to bridging the digital divide and for embracing artificial intelligence. With regard to research and practices within information behavior, it is crucial to consider that all users should be involved. Many information activities (i.e., activities falling under the umbrella terms of information behavior and information practices) manifest through participation, and thus, methods such as participatory design may help unfold both information behavior and practices as well as the creation of information objects, new models, and theories. Information sharing is one of its core activities. For participatory design with its value set of democratic, inclusive, and open participation towards innovative practices in a diversity of contexts, it is essential to understand how information activities such as sharing manifest itself. For information behavior studies it is essential to deepen understanding of how information sharing manifests in order to improve access to information and the use of information.Third Space is a physical, virtual, cognitive, and conceptual space where participants may negotiate, reflect, and form new knowledge and worldviews working toward creative, practical and applicable solutions, finding innovative, appropriate research methods, interpreting findings, proposing new theories, recommending next steps, and even designing solutions such as new information objects or services. Information sharing in participatory design manifests in tandem with many other information interaction activities and especially information and cognitive processing. Although there are practices of individual information sharing and information encountering, information sharing mostly relates to collaborative information behavior practices, creativity, and collective decision-making.Our purpose with this book is to enable students, researchers, and practitioners within a multi-disciplinary research field, including information studies and Human–Computer Interaction approaches, to gain a deeper understanding of how the core activity of information sharing in participatory design, in which Third Space may be a platform for information interaction, is taking place when using methods utilized in participatory design to address contemporary societal challenges. This could also apply for information behavior studies using participatory design as methodology. We elaborate interpretations of core concepts such as participatory design, Third Space, information sharing, and collaborative information behavior, before discussing participatory design methods and processes in more depth. We also touch on information behavior, information practice, and other important concepts. Third Space, information sharing, and information interaction are discussed in some detail. A framework, with Third Space as a core intersecting zone, platform, and adaptive and creative space to study information sharing and other information behavior and interactions are suggested. As a tool to envision information behavior and suggest future practices, participatory design serves as a set of methods and tools in which new interpretations of the design of information behavior studies and eventually new information objects are being initiated involving multiple stakeholders in future information landscapes. For this purpose, we argue that Third Space can be used as an intersection zone to study information sharing and other information activities, but more importantly it can serve as a Third Space Information Behavior (TSIB) study framework where participatory design methodology and processes are applied to information behavior research studies and applications such as information objects, systems, and services with recognition of the importance of situated awareness.* Preface* Acknowledgments* Abbreviations* Introduction: Contemporary Challenges Faced in the Emerging Information Context* Foundation and Components* Participatory Design as an Approach for Participation* Third Space* Information Sharing and Other Information Activities* Third Space as an Intersection Zone for Information Behavior Studies* Conclusion and the Way Forward* Appendix A: General Guideline for Conducting a Participatory Design Workshop Called Future Workshop* Bibliography* Authors' Biographies
Clean C++20
Write maintainable, extensible, and durable software with modern C++. This book, updated for the recently released C++20 standard, is a must for every developer, software architect, or team leader who is interested in well-crafted C++ code, and thus also wants to save development costs. If you want to teach yourself about writing better C++ code, Clean C++20 is exactly what you need. It is written for C++ developers of all skill levels and shows by example how to write understandable, flexible, maintainable, and efficient C++ code. Even if you are a seasoned C++ developer, there are nuggets and data points in this book that you will find useful in your work.If you don't take care with your codebase, you can produce a large, messy, and unmaintainable beast in any programming language. However, C++ projects in particular are prone to get messy and tend to slip into a maintenance nightmare. There is lots of C++ code out there that looks as if it was written in the 1980s, completely ignoring principles and practices of well-written and modern C++.It seems that C++ developers have been forgotten by those who preach Software Craftsmanship and Clean Code principles. The web is full of C++ code examples that may be very fast and highly optimized, but whose developers have completely ignored elementary principles of good design and well-written code. This book will explain how to avoid this and how to get the most out of your C++ code. You'll find your coding becomes more efficient and, importantly, more fun.WHAT YOU WILL LEARN* Gain sound principles and rules for clean coding in C++* Carry out test-driven development (TDD)* Better modularize your C++ code base* Discover and apply C++ design patterns and idioms* Write C++ code in both object-oriented and functional programming stylesWHO THIS BOOK IS FORAny C++ developer or software engineer with an interest in producing better code.STEPHAN ROTH is a coach, consultant, and trainer for systems and software engineering with German consultancy company oose Innovative Informatik eG located in Hamburg. Before he joined oose, he worked for many years as a software developer, software architect, and systems engineer in the field of radio reconnaissance and communication intelligence systems. He has developed sophisticated applications, especially in a high-performance system environment, and graphical user interfaces using C++ and other programming languages. Stephan is an active supporter of the Software Craftsmanship movement and is concerned with principles and practices of Clean Code Development (CCD).CH01 - IntroductionCH02 - Build a Safety NetCH03 - Be PrincipledCH04 - Basics of Clean C++CH05 - Advanced concepts of modern C++CH06 - Object OrientationCH07 - Functional ProgrammingCH08 - Test Driven DevelopmentCH09 - Design Patterns and IdiomsAppendix A - Small UML GuideBibliography
Beginning Azure Synapse Analytics
Get started with Azure Synapse Analytics, Microsoft's modern data analytics platform. This book covers core components such as Synapse SQL, Synapse Spark, Synapse Pipelines, and many more, along with their architecture and implementation.The book begins with an introduction to core data and analytics concepts followed by an understanding of traditional/legacy data warehouse, modern data warehouse, and the most modern data lakehouse. You will go through the introduction and background of Azure Synapse Analytics along with its main features and key service capabilities. Core architecture is discussed, along with Synapse SQL. You will learn its main features and how to create a dedicated Synapse SQL pool and analyze your big data using Serverless Synapse SQL Pool. You also will learn Synapse Spark and Synapse Pipelines, with examples. And you will learn Synapse Workspace and Synapse Studio followed by Synapse Link and its features. You will go through use cases in Azure Synapse and understand the reference architecture for Synapse Analytics.After reading this book, you will be able to work with Azure Synapse Analytics and understand its architecture, main components, features, and capabilities.WHAT YOU WILL LEARN* Understand core data and analytics concepts and data lakehouse concepts* Be familiar with overall Azure Synapse architecture and its main components* Be familiar with Synapse SQL and Synapse Spark architecture components* Work with integrated Apache Spark (aka Synapse Spark) and Synapse SQL engines* Understand Synapse Workspace, Synapse Studio, and Synapse Pipeline* Study reference architecture and use casesWHO THIS BOOK IS FORAzure data analysts, data engineers, data scientists, and solutions architectsBHADRESH SHIYAL is an Azure data architect and Azure data engineer. For the past seven years, he has been working with a large multi-national IT corporation as Solutions Architect. Prior to that, he spent almost a decade in private and public sector banks in India in various IT positions working on various Microsoft technologies. He has 18 years of IT experience, including working for two years on an international assignment from London. He has much experience in application design, development, and deployment.He has worked on various technologies, including Visual Basic, SQL Server, SharePoint Technologies, .NET MVC, O365, Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen1/Gen2, Azure SQL Data Warehouse, Power BI, Spark SQL, Scala, Delta Lake, Azure Machine Learning, Azure Information Protection, Azure .NET SDK, Azure DevOps, and more.He holds multiple Azure certifications that include Microsoft Certified Azure Solutions Architect Expert, Microsoft Certified Azure Data Engineer Associate, Microsoft Certified Azure Data Scientist Associate, and Microsoft Certified Azure Data Analyst Associate.Bhadresh has worked as Solutions Architect on a large-scale Azure Data Lake implementation project as well as on a data transformation project and on large-scale customized content management systems. He has also worked as Technical Reviewer for the book Data Science using Azure, prior to authoring this book.CHAPTER 1: CORE DATA AND ANALYTICS CONCEPTSCHAPTER GOAL: Introducing readers to some of the important core data and analytics concepts as a foundationNO OF PAGES : 15SUB -TOPICS1. Introduction/Background2. Core Data Concepts1. Structured Data2. Unstructured Data3. Semi-Structured Data4. Batch Data5. Streaming Data6. Difference between Streaming Data and Batch Data7. Relational Data and its characteristics3. Core Analytics Concepts1. Data Ingestion1. ELT2. ETL2. Data Processing3. Data Exploration4. Data Visualization5. Analytics Techniques1. Descriptive2. Diagnostic3. Predictive4. Prescriptive5. Cognitive4. SummaryCHAPTER 2: MODERN DATA WAREHOUSE AND DATA LAKEHOUSECHAPTER GOAL: Providing conceptual understanding about traditional / legacy Data Warehouse, Modern Data Warehouse and finally the most modern Data Lakehouse.NO OF PAGES: 25SUB - TOPICS1. Introduction/Background2. What is Data Warehouse?3. Why do we need a Data Warehouse?4. What is Modern Data Warehouse?5. Comparison between Traditional Data Warehouse and Modern Data Warehouse?6. What is Data Lakehouse?7. Comparison between Data Warehouse and Data Lakehouse8. Benefits of Data Lakehouse9. Examples of Data Lakehouse10. SummaryCHAPTER 3: INTRODUCTION TO AZURE SYNAPSE ANALYTICSCHAPTER GOAL: Building foundational knowledge by introducing Azure Synapse Analytics, its main features and its key services capabilitiesNO OF PAGES : 20SUB - TOPICS:1. Introduction/Background2. What is Azure Synapse Analytics?3. Azure Synapse Analytics vs Azure SQL Datawarehouse4. Why should you learn Azure Synapse Analytics?5. Main Features1. Unified Experience2. Powerful Insights3. Limitless Scale4. Instant Clarity5. Security and Privacy6. Key Services Capabilities1. EDW2. Data Lake Exploration3. Multiple Language Support4. Low-Code or Code-Free Data Orchestration5. Integrated Apache Spark and SQL Engines6. Stream Analytics7. AI Integration8. BI Integration9. Management and Security7. SummaryCHAPTER 4: ARCHITECTURE AND ITS MAIN COMPONENTSCHAPTER GOAL: Explaining Azure Synapse Analytics Core Architecture and its main components as it is very different from traditional Data Warehouse Architecture and its components.NO OF PAGES: 15SUB - TOPICS:1. Introduction/Background2. High Level Architecture3. Main Components of Architecture1. Synapse SQL2. Synapse Spark3. Synapse Pipelines4. Synapse Studio5. Synapse Link4. SummaryCHAPTER 5: SYNAPSE SQLCHAPTER GOAL: Exploring Synapse SQL in detail including its architecture, its main features with some How-Tos to make the readers familiar with some important activities which can be carried out for Synapse SQLNO OF PAGES: 25SUB - TOPICS:1. Background / Introduction2. Synapse SQL Architecture Components1. Azure Storage2. Control Node3. Compute Node4. Data Movement Service5. Distributions3. Synapse SQL Pool4. Synapse SQL On-Demand5. Synapse SQL Features6. Resource Consumption Models7. Synapse SQL - Best Practices8. How-Tos1. Create an Azure Synapse SQL Pool2. Create an Azure Synapse SQL On-Demand3. Load Data using COPY Statement4. Load data from Azure Data Lake Storage for Synapse SQL5. Load data by using Azure Data Factory6. Ingest data into Azure Data Lake Storage Gen29. SummaryCHAPTER 6: SYNAPSE SPARKCHAPTER GOAL: Explaining Synapse Sparks and its main components including Delta Lake along with some How-Tos to make the readers familiar with important tasks pertaining to Synapse Spark.NO OF PAGES: 30SUB - TOPICS:1. Introduction/Background2. What is Apache Spark3. Synapse Spark Capabilities4. What is Delta Lake and its importance in Spark?5. Synapse Spark Job Optimization6. Development Libraries7. Apache Spark Machine Learning8. How-Tos1. Create Synapse Spark Cluster2. Load Data using Synapse Spark Cluster3. Export / Import Data with Apache Spark9. SummaryCHAPTER 7: SYNAPSE PIPELINESCHAPTER GOAL: Introducing Azure Synapse Pipelines and how it integrates with Azure Data Factory. Detailed explanation to various types of Pipeline activities with examples.No of pages: 20SUB - TOPICS:1. Introduction / Background2. Overview of Azure Data Factory3. Data Movement Activities4. Data Transformation Activities5. Control Flow Activities6. Copy Pipeline Example7. Transformation Pipeline Example8. Scheduling Pipelines9. SummaryCHAPTER 8: SYNAPSE WORKSPACE AND SYNAPSE STUDIOCHAPTER GOAL: To make readers familiar with Synapse Workspace and Synapse Studio including its main features and its capabilities and to give understanding about how to accomplish some important tasks using workspace and studio.NO OF PAGES: 25SUB - TOPICS:1. What is Synapse Workspace?2. Workspace Components and Features3. What is Synapse Studio?4. Main Features5. Capabilities (What it can do?)6. Linking Power BI to Synapse Studio7. How-To carry out important activities using Studio8. SummaryCHAPTER 9: SYNAPSE LINKCHAPTER GOAL: To explain differences between OLTP and OLAP, why HTAP is required and its benefits and then introducing Synapse Link along with its Cosmos DB integration, its features and use cases.NO OF PAGES: 20SUB - TOPICS:1. Introduction / Background2. OLTP vs OLAP3. What is HTAP?4. HTAP Benefits5. What is Azure Synapse Link?6. Azure Cosmos DB Analytical Store7. Synapse Link Features8. Synapse Link Use Cases9. SummaryCHAPTER 10: AZURE SYNAPSE USE CASES AND REFERENCE ARCHITECTURESChapter Goal: To make readers familiar with Synapse Workspace and Synapse Studio including its main features and its capabilities and to give understanding about how to accomplish some important tasks using workspace and studio.NO OF PAGES: 15SUB - TOPICS:1. Introduction / Background2. Where you should use Synapse Analytics?3. Where it should not be used?4. Few Examples of Use cases of Synapse Analytics5. Reference Architecture for Synapse Analytics6. Summary
(ISC)2 CISSP Certified Information Systems Security Professional Official Study Guide
Your Complete Guide to Preparing for the CISSP Certification, Updated for the CISSP 2021 Exam The (ISC)2 CISSP Official Study Guide, 9th Edition is your one-stop resource for complete coverage of the 2021 CISSP exam objectives. You’ll prepare for the exam smarter and faster with Sybex thanks to superior content including: assessment tests that check exam readiness, objective map, written labs, key topic exam essentials, and challenging chapter review questions. Reinforce what you have learned with the exclusive Sybex online learning environment and test bank, assessable across multiple devices. Get prepared for the CISSP exam with Sybex. Coverage of all exam objectives in this Study Guide means you’ll be ready for: Security and Risk ManagementAsset SecuritySecurity Architecture and EngineeringCommunication and Network SecurityIdentity and Access Management (IAM)Security Assessment and TestingSecurity OperationsSoftware Development Security Interactive learning environment Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit www.wiley.com/go/sybextestprep, register to receive your unique PIN, and instantly gain one year of FREE access to: Interactive test bank with four additional practice exams, each with 125 unique questions. Practice exams help you identify areas where further review is needed. Get more than 90% of the answers correct, and you're ready to take the certification exam.More than 700 electronic flashcards to reinforce learning and last minute prep before the exam.Comprehensive glossary in PDF format gives you instant access to the key terms so you are fully prepared. ABOUT THE CISSP CERTIFICATION The CISSP is the most globally recognized certification in the information security market. This vendor neutral certification validates an information security professional's deep technical and managerial knowledge and experience to effectively design, engineer, and manage the overall security posture of an organization. (ISC)2 is a global nonprofit organization that maintains the Common Body of Knowledge for information security professionals. Candidates must have experience, subscribe to the (ISC)2 Code of Ethics, and maintain continuing education requirements or recertify every three years. Visit www.isc2.org to learn more. The only Official CISSP Study Guide - fully updated for the 2021 CISSP Body of Knowledge (ISC)2 Certified Information Systems Security Professional (CISSP) Official Study Guide, 9th Edition has been completely updated based on the latest 2021 CISSP Exam Outline. This bestselling Sybex Study Guide covers 100% of the exam objectives. You'll prepare for the exam smarter and faster with Sybex thanks to expert content, knowledge from our real-world experience, advice on mastering this adaptive exam, access to the Sybex online interactive learning environment, and much more. Reinforce what you've learned with key topic exam essentials and chapter review questions. The three co-authors of this book bring decades of experience as cybersecurity practitioners and educators, integrating real-world expertise with the practical knowledge you'll need to successfully pass the CISSP exam. Combined, they've taught cybersecurity concepts to millions of students through their books, video courses, and live training programs. Along with the book, you also get access to Sybex's superior online interactive learning environment that includes: Over 900 new and improved practice test questions with complete answer explanations. This includes all of the questions from the book plus four additional online-only practice exams, each with 125 unique questions. You can use the online-only practice exams as full exam simulations. Our questions will help you identify where you need to study more. Get more than 90 percent of the answers correct, and you're ready to take the certification exam.More than 700 Electronic Flashcards to reinforce your learning and give you last-minute test prep before the examA searchable glossary in PDF to give you instant access to the key terms you need to know for the examNew for the 9th edition: Audio Review. Author Mike Chapple reads the Exam Essentials for each chapter providing you with 2 hours and 50 minutes of new audio review for yet another way to reinforce your knowledge as you prepare. All of the online features are supported by Wiley's support agents who are available 24x7 via email or live chat to assist with access and login questions. Coverage of all of the exam topics in the book means you'll be ready for: Security and Risk ManagementAsset SecuritySecurity Architecture and EngineeringCommunication and Network SecurityIdentity and Access Management (IAM)Security Assessment and TestingSecurity OperationsSoftware Development Security Mike Chapple, PhD, CISSP, is Teaching Professor of IT, Analytics, and Operations at the University of Notre Dame’s Mendoza College of Business. He is a cybersecurity professional and educator with over 25 years of experience. Mike provides cybersecurity certification resources at his website, CertMike.com. James Michael Stewart, CISSP, CEH, CHFI, ECSA, CND, ECIH, CySA+, PenTest+, CASP+, Security+, Network+, A+, CISM, and CFR, has been writing and training for more than 25 years, with a current focus on security. He has been writing and teaching CISSP materials since 2002. He is the author of and contributor to more than 75 books on security certifications. Darril Gibson, CISSP, Security+, CASP, is the CEO of YCDA (short for You Can Do Anything), and he has authored or coauthored more than 40 books. Darril regularly writes, consults, and teaches on a wide variety of technical and security topics and holds several certifications. Introduction xxxvii Assessment Test lix Chapter 1 Security Governance Through Principles and Policies 1 Security 101 3 Understand and Apply Security Concepts 4 Confidentiality 5 Integrity 6 Availability 7 DAD, Overprotection, Authenticity, Non-repudiation, and AAA Services 7 Protection Mechanisms 11 Security Boundaries 13 Evaluate and Apply Security Governance Principles 14 Third-Party Governance 15 Documentation Review 15 Manage the Security Function 16 Alignment of Security Function to Business Strategy, Goals, Mission, and Objectives 17 Organizational Processes 19 Organizational Roles and Responsibilities 21 Security Control Frameworks 22 Due Diligence and Due Care 23 Security Policy, Standards, Procedures, and Guidelines 23 Security Policies 24 Security Standards, Baselines, and Guidelines 24 Security Procedures 25 Threat Modeling 26 Identifying Threats 26 Determining and Diagramming Potential Attacks 28 Performing Reduction Analysis 28 Prioritization and Response 30 Supply Chain Risk Management 31 Summary 33 Exam Essentials 33 Written Lab 36 Review Questions 37 Chapter 2 Personnel Security and Risk Management Concepts 43 Personnel Security Policies and Procedures 45 Job Descriptions and Responsibilities 45 Candidate Screening and Hiring 46 Onboarding: Employment Agreements and Policies 47 Employee Oversight 48 Offboarding, Transfers, and Termination Processes 49 Vendor, Consultant, and Contractor Agreements and Controls 52 Compliance Policy Requirements 53 Privacy Policy Requirements 54 Understand and Apply Risk Management Concepts 55 Risk Terminology and Concepts 56 Asset Valuation 58 Identify Threats and Vulnerabilities 60 Risk Assessment/Analysis 60 Risk Responses 66 Cost vs. Benefit of Security Controls 69 Countermeasure Selection and Implementation 72 Applicable Types of Controls 74 Security Control Assessment 76 Monitoring and Measurement 76 Risk Reporting and Documentation 77 Continuous Improvement 77 Risk Frameworks 79 Social Engineering 81 Social Engineering Principles 83 Eliciting Information 85 Prepending 85 Phishing 85 Spear Phishing 87 Whaling 87 Smishing 88 Vishing 88 Spam 89 Shoulder Surfing 90 Invoice Scams 90 Hoax 90 Impersonation and Masquerading 91 Tailgating and Piggybacking 91 Dumpster Diving 92 Identity Fraud 93 Typo Squatting 94 Influence Campaigns 94 Establish and Maintain a Security Awareness, Education, and Training Program 96 Awareness 97 Training 97 Education 98 Improvements 98 Effectiveness Evaluation 99 Summary 100 Exam Essentials 101 Written Lab 106 Review Questions 107 Chapter 3 Business Continuity Planning 113 Planning for Business Continuity 114 Project Scope and Planning 115 Organizational Review 116 BCP Team Selection 117 Resource Requirements 119 Legal and Regulatory Requirements 120 Business Impact Analysis 121 Identifying Priorities 122 Risk Identification 123 Likelihood Assessment 125 Impact Analysis 126 Resource Prioritization 128 Continuity Planning 128 Strategy Development 129 Provisions and Processes 129 Plan Approval and Implementation 131 Plan Approval 131 Plan Implementation 132 Training and Education 132 BCP Documentation 132 Summary 136 Exam Essentials 137 Written Lab 138 Review Questions 139 Chapter 4 Laws, Regulations, and Compliance 143 Categories of Laws 144 Criminal Law 144 Civil Law 146 Administrative Law 146 Laws 147 Computer Crime 147 Intellectual Property (IP) 152 Licensing 158 Import/Export 158 Privacy 160 State Privacy Laws 168 Compliance 169 Contracting and Procurement 171 Summary 171 Exam Essentials 172 Written Lab 173 Review Questions 174 Chapter 5 Protecting Security of Assets 179 Identifying and Classifying Information and Assets 180 Defining Sensitive Data 180 Defining Data Classifications 182 Defining Asset Classifications 185 Understanding Data States 185 Determining Compliance Requirements 186 Determining Data Security Controls 186 Establishing Information and Asset Handling Requirements 188 Data Maintenance 189 Data Loss Prevention 189 Marking Sensitive Data and Assets 190 Handling Sensitive Information and Assets 192 Data Collection Limitation 192 Data Location 193 Storing Sensitive Data 193 Data Destruction 194 Ensuring Appropriate Data and Asset Retention 197 Data Protection Methods 199 Digital Rights Management 199 Cloud Access Security Broker 200 Pseudonymization 200 Tokenization 201 Anonymization 202 Understanding Data Roles 204 Data Owners 204 Asset Owners 205 Business/Mission Owners 206 Data Processors and Data Controllers 206 Data Custodians 207 Administrators 207 Users and Subjects 208 Using Security Baselines 208 Comparing Tailoring and Scoping 209 Standards Selection 210 Summary 211 Exam Essentials 211 Written Lab 213 Review Questions 214 Chapter 6 Cryptography and Symmetric Key Algorithms 219 Cryptographic Foundations 220 Goals of Cryptography 220 Cryptography Concepts 223 Cryptographic Mathematics 224 Ciphers 230 Modern Cryptography 238 Cryptographic Keys 238 Symmetric Key Algorithms 239 Asymmetric Key Algorithms 241 Hashing Algorithms 244 Symmetric Cryptography 244 Cryptographic Modes of Operation 245 Data Encryption Standard 247 Triple DES 247 International Data Encryption Algorithm 248 Blowfish 249 Skipjack 249 Rivest Ciphers 249 Advanced Encryption Standard 250 CAST 250 Comparison of Symmetric Encryption Algorithms 251 Symmetric Key Management 252 Cryptographic Lifecycle 255 Summary 255 Exam Essentials 256 Written Lab 257 Review Questions 258 Chapter 7 PKI and Cryptographic Applications 263 Asymmetric Cryptography 264 Public and Private Keys 264 RSA 265 ElGamal 267 Elliptic Curve 268 Diffie–Hellman Key Exchange 269 Quantum Cryptography 270 Hash Functions 271 SHA 272 MD5 273 RIPEMD 273 Comparison of Hash Algorithm Value Lengths 274 Digital Signatures 275 HMAC 276 Digital Signature Standard 277 Public Key Infrastructure 277 Certificates 278 Certificate Authorities 279 Certificate Lifecycle 280 Certificate Formats 283 Asymmetric Key Management 284 Hybrid Cryptography 285 Applied Cryptography 285 Portable Devices 285 Email 286 Web Applications 290 Steganography and Watermarking 292 Networking 294 Emerging Applications 295 Cryptographic Attacks 297 Summary 301 Exam Essentials 302 Written Lab 303 Review Questions 304 Chapter 8 Principles of Security Models, Design, and Capabilities 309 Secure Design Principles 310 Objects and Subjects 311 Closed and Open Systems 312 Secure Defaults 314 Fail Securely 314 Keep It Simple 316 Zero Trust 317 Privacy by Design 319 Trust but Verify 319 Techniques for Ensuring CIA 320 Confinement 320 Bounds 320 Isolation 321 Access Controls 321 Trust and Assurance 321 Understand the Fundamental Concepts of Security Models 322 Trusted Computing Base 323 State Machine Model 325 Information Flow Model 325 Noninterference Model 326 Take-Grant Model 326 Access Control Matrix 327 Bell–LaPadula Model 328 Biba Model 330 Clark–Wilson Model 333 Brewer and Nash Model 334 Goguen–Meseguer Model 335 Sutherland Model 335 Graham–Denning Model 335 Harrison–Ruzzo–Ullman Model 336 Select Controls Based on Systems Security Requirements 337 Common Criteria 337 Authorization to Operate 340 Understand Security Capabilities of Information Systems 341 Memory Protection 341 Virtualization 342 Trusted Platform Module 342 Interfaces 343 Fault Tolerance 343 Encryption/Decryption 343 Summary 343 Exam Essentials 344 Written Lab 347 Review Questions 348 Chapter 9 Security Vulnerabilities, Threats, and Countermeasures 353 Shared Responsibility 354 Assess and Mitigate the Vulnerabilities of Security Architectures, Designs, and Solution Elements 355 Hardware 356 Firmware 370 Client-Based Systems 372 Mobile Code 372 Local Caches 375 Server-Based Systems 375 Large-Scale Parallel Data Systems 376 Grid Computing 377 Peer to Peer 378 Industrial Control Systems 378 Distributed Systems 380 High-Performance Computing (HPC) Systems 382 Internet of Things 383 Edge and Fog Computing 385 Embedded Devices and Cyber-Physical Systems 386 Static Systems 387 Network-Enabled Devices 388 Cyber-Physical Systems 389 Elements Related to Embedded and Static Systems 389 Security Concerns of Embedded and Static Systems 390 Specialized Devices 393 Microservices 394 Infrastructure as Code 395 Virtualized Systems 397 Virtual Software 399 Virtualized Networking 400 Software-Defined Everything 400 Virtualization Security Management 403 Containerization 405 Serverless Architecture 406 Mobile Devices 406 Mobile Device Security Features 408 Mobile Device Deployment Policies 420 Essential Security Protection Mechanisms 426 Process Isolation 426 Hardware Segmentation 427 System Security Policy 427 Common Security Architecture Flaws and Issues 428 Covert Channels 428 Attacks Based on Design or Coding Flaws 430 Rootkits 431 Incremental Attacks 431 Summary 432 Exam Essentials 433 Written Lab 440 Review Questions 441 Chapter 10 Physical Security Requirements 447 Apply Security Principles to Site and Facility Design 448 Secure Facility Plan 448 Site Selection 449 Facility Design 450 Implement Site and Facility Security Controls 452 Equipment Failure 453 Wiring Closets 454 Server Rooms/Data Centers 455 Intrusion Detection Systems 458 Cameras 460 Access Abuses 462 Media Storage Facilities 462 Evidence Storage 463 Restricted and Work Area Security 464 Utility Considerations 465 Fire Prevention, Detection, and Suppression 470 Implement and Manage Physical Security 476 Perimeter Security Controls 477 Internal Security Controls 481 Key Performance Indicators of Physical Security 483 Summary 484 Exam Essentials 485 Written Lab 488 Review Questions 489 Chapter 11 Secure Network Architecture and Components 495 OSI Model 497 History of the OSI Model 497 OSI Functionality 498 Encapsulation/Deencapsulation 498 OSI Layers 500 TCP/IP Model 504 Analyzing Network Traffic 505 Common Application Layer Protocols 506 Transport Layer Protocols 508 Domain Name System 509 DNS Poisoning 511 Domain Hijacking 514 Internet Protocol (IP) Networking 516 IPv4 vs. IPv6 516 IP Classes 517 ICMP 519 IGMP 519 ARP Concerns 519 Secure Communication Protocols 521 Implications of Multilayer Protocols 522 Converged Protocols 523 Voice over Internet Protocol (VoIP) 524 Software-Defined Networking 525 Microsegmentation 526 Wireless Networks 527 Securing the SSID 529 Wireless Channels 529 Conducting a Site Survey 530 Wireless Security 531 Wi-Fi Protected Setup (WPS) 533 Wireless MAC Filter 534 Wireless Antenna Management 534 Using Captive Portals 535 General Wi-Fi Security Procedure 535 Wireless Communications 536 Wireless Attacks 539 Other Communication Protocols 543 Cellular Networks 544 Content Distribution Networks (CDNs) 545 Secure Network Components 545 Secure Operation of Hardware 546 Common Network Equipment 547 Network Access Control 549 Firewalls 550 Endpoint Security 556 Cabling, Topology, and Transmission Media Technology 559 Transmission Media 559 Network Topologies 563 Ethernet 565 Sub-Technologies 566 Summary 569 Exam Essentials 570 Written Lab 574 Review Questions 575 Chapter 12 Secure Communications and Network Attacks 581 Protocol Security Mechanisms 582 Authentication Protocols 582 Port Security 585 Quality of Service (QoS) 585 Secure Voice Communications 586 Public Switched Telephone Network 586 Voice over Internet Protocol (VoIP) 586 Vishing and Phreaking 588 PBX Fraud and Abuse 589 Remote Access Security Management 590 Remote Access and Telecommuting Techniques 591 Remote Connection Security 591 Plan a Remote Access Security Policy 592 Multimedia Collaboration 593 Remote Meeting 593 Instant Messaging and Chat 594 Load Balancing 595 Virtual IPs and Load Persistence 596 Active-Active vs. Active-Passive 596 Manage Email Security 596 Email Security Goals 597 Understand Email Security Issues 599 Email Security Solutions 599 Virtual Private Network 602 Tunneling 603 How VPNs Work 604 Always-On 606 Split Tunnel vs. Full Tunnel 607 Common VPN Protocols 607 Switching and Virtual LANs 610 Network Address Translation 614 Private IP Addresses 616 Stateful NAT 617 Automatic Private IP Addressing 617 Third-Party Connectivity 618 Switching Technologies 620 Circuit Switching 620 Packet Switching 620 Virtual Circuits 621 WAN Technologies 622 Fiber-Optic Links 624 Security Control Characteristics 624 Transparency 625 Transmission Management Mechanisms 625 Prevent or Mitigate Network Attacks 625 Eavesdropping 626 Modification Attacks 626 Summary 626 Exam Essentials 628 Written Lab 630 Review Questions 631 Chapter 13 Managing Identity and Authentication 637 Controlling Access to Assets 639 Controlling Physical and Logical Access 640 The CIA Triad and Access Controls 640 Managing Identification and Authentication 641 Comparing Subjects and Objects 642 Registration, Proofing, and Establishment of Identity 643 Authorization and Accountability 644 Authentication Factors Overview 645 Something You Know 647 Something You Have 650 Something You Are 651 Multifactor Authentication (MFA) 655 Two-Factor Authentication with Authenticator Apps 655 Passwordless Authentication 656 Device Authentication 657 Service Authentication 658 Mutual Authentication 659 Implementing Identity Management 659 Single Sign-On 659 SSO and Federated Identities 660 Credential Management Systems 662 Credential Manager Apps 663 Scripted Access 663 Session Management 663 Managing the Identity and Access Provisioning Lifecycle 664 Provisioning and Onboarding 665 Deprovisioning and Offboarding 666 Defining New Roles 667 Account Maintenance 667 Account Access Review 667 Summary 668 Exam Essentials 669 Written Lab 671 Review Questions 672 Chapter 14 Controlling and Monitoring Access 677 Comparing Access Control Models 678 Comparing Permissions, Rights, and Privileges 678 Understanding Authorization Mechanisms 679 Defining Requirements with a Security Policy 681 Introducing Access Control Models 681 Discretionary Access Control 682 Nondiscretionary Access Control 683 Implementing Authentication Systems 690 Implementing SSO on the Internet 691 Implementing SSO on Internal Networks 694 Understanding Access Control Attacks 699 Risk Elements 700 Common Access Control Attacks 700 Core Protection Methods 713 Summary 714 Exam Essentials 715 Written Lab 717 Review Questions 718 Chapter 15 Security Assessment and Testing 723 Building a Security Assessment and Testing Program 725 Security Testing 725 Security Assessments 726 Security Audits 727 Performing Vulnerability Assessments 731 Describing Vulnerabilities 731 Vulnerability Scans 732 Penetration Testing 742 Compliance Checks 745 Testing Your Software 746 Code Review and Testing 746 Interface Testing 751 Misuse Case Testing 751 Test Coverage Analysis 752 Website Monitoring 752 Implementing Security Management Processes 753 Log Reviews 753 Account Management 754 Disaster Recovery and Business Continuity 754 Training and Awareness 755 Key Performance and Risk Indicators 755 Summary 756 Exam Essentials 756 Written Lab 758 Review Questions 759 Chapter 16 Managing Security Operations 763 Apply Foundational Security Operations Concepts 765 Need to Know and Least Privilege 765 Separation of Duties (SoD) and Responsibilities 767 Two-Person Control 768 Job Rotation 768 Mandatory Vacations 768 Privileged Account Management 769 Service Level Agreements (SLAs) 771 Addressing Personnel Safety and Security 771 Duress 771 Travel 772 Emergency Management 773 Security Training and Awareness 773 Provision Resources Securely 773 Information and Asset Ownership 774 Asset Management 774 Apply Resource Protection 776 Media Management 776 Media Protection Techniques 776 Managed Services in the Cloud 779 Shared Responsibility with Cloud Service Models 780 Scalability and Elasticity 782 Perform Configuration Management (CM) 782 Provisioning 783 Baselining 783 Using Images for Baselining 783 Automation 784 Managing Change 785 Change Management 787 Versioning 788 Configuration Documentation 788 Managing Patches and Reducing Vulnerabilities 789 Systems to Manage 789 Patch Management 789 Vulnerability Management 791 Vulnerability Scans 792 Common Vulnerabilities and Exposures 792 Summary 793 Exam Essentials 794 Written Lab 796 Review Questions 797 Chapter 17 Preventing and Responding to Incidents 801 Conducting Incident Management 803 Defining an Incident 803 Incident Management Steps 804 Implementing Detective and Preventive Measures 810 Basic Preventive Measures 810 Understanding Attacks 811 Intrusion Detection and Prevention Systems 820 Specific Preventive Measures 828 Logging and Monitoring 834 Logging Techniques 834 The Role of Monitoring 837 Monitoring Techniques 840 Log Management 844 Egress Monitoring 844 Automating Incident Response 845 Understanding SOAR 845 Machine Learning and AI Tools 846 Threat Intelligence 847 The Intersection of SOAR, Machine Learning, AI, and Threat Feeds 850 Summary 851 Exam Essentials 852 Written Lab 855 Review Questions 856 Chapter 18 Disaster Recovery Planning 861 The Nature of Disaster 863 Natural Disasters 864 Human-Made Disasters 869 Understand System Resilience, High Availability, and Fault Tolerance 875 Protecting Hard Drives 875 Protecting Servers 877 Protecting Power Sources 878 Trusted Recovery 879 Quality of Service 880 Recovery Strategy 880 Business Unit and Functional Priorities 881 Crisis Management 882 Emergency Communications 882 Workgroup Recovery 883 Alternate Processing Sites 883 Database Recovery 888 Recovery Plan Development 890 Emergency Response 891 Personnel and Communications 891 Assessment 892 Backups and Off-site Storage 892 Software Escrow Arrangements 896 Utilities 897 Logistics and Supplies 897 Recovery vs. Restoration 897 Training, Awareness, and Documentation 898 Testing and Maintenance 899 Read-Through Test 899 Structured Walk-Through 900 Simulation Test 900 Parallel Test 900 Full-Interruption Test 900 Lessons Learned 901 Maintenance 901 Summary 902 Exam Essentials 902 Written Lab 903 Review Questions 904 Chapter 19 Investigations and Ethics 909 Investigations 910 Investigation Types 910 Evidence 913 Investigation Process 919 Major Categories of Computer Crime 923 Military and Intelligence Attacks 924 Business Attacks 925 Financial Attacks 926 Terrorist Attacks 926 Grudge Attacks 927 Thrill Attacks 928 Hacktivists 928 Ethics 929 Organizational Code of Ethics 929 (ISC)2 Code of Ethics 930 Ethics and the Internet 931 Summary 933 Exam Essentials 934 Written Lab 935 Review Questions 936 Chapter 20 Software Development Security 941 Introducing Systems Development Controls 943 Software Development 943 Systems Development Lifecycle 952 Lifecycle Models 955 Gantt Charts and PERT 964 Change and Configuration Management 964 The DevOps Approach 966 Application Programming Interfaces 967 Software Testing 969 Code Repositories 970 Service-Level Agreements 971 Third-Party Software Acquisition 972 Establishing Databases and Data Warehousing 973 Database Management System Architecture 973 Database Transactions 977 Security for Multilevel Databases 978 Open Database Connectivity 982 NoSQL 982 Storage Threats 983 Understanding Knowledge-Based Systems 984 Expert Systems 984 Machine Learning 985 Neural Networks 986 Summary 987 Exam Essentials 987 Written Lab 988 Review Questions 989 Chapter 21 Malicious Code and Application Attacks 993 Malware 994 Sources of Malicious Code 995 Viruses 995 Logic Bombs 999 Trojan Horses 1000 Worms 1001 Spyware and Adware 1004 Ransomware 1004 Malicious Scripts 1005 Zero-Day Attacks 1006 Malware Prevention 1006 Platforms Vulnerable to Malware 1007 Antimalware Software 1007 Integrity Monitoring 1008 Advanced Threat Protection 1008 Application Attacks 1009 Buffer Overflows 1009 Time of Check to Time of Use 1010 Backdoors 1011 Privilege Escalation and Rootkits 1011 Injection Vulnerabilities 1012 SQL Injection Attacks 1012 Code Injection Attacks 1016 Command Injection Attacks 1016 Exploiting Authorization Vulnerabilities 1017 Insecure Direct Object References 1018 Directory Traversal 1018 File Inclusion 1020 Exploiting Web Application Vulnerabilities 1020 Cross-Site Scripting (XSS) 1021 Request Forgery 1023 Session Hijacking 1024 Application Security Controls 1025 Input Validation 1025 Web Application Firewalls 1027 Database Security 1028 Code Security 1029 Secure Coding Practices 1031 Source Code Comments 1031 Error Handling 1032 Hard-Coded Credentials 1033 Memory Management 1034 Summary 1035 Exam Essentials 1035 Written Lab 1036 Review Questions 1037 Appendix A Answers to Review Questions 1041 Chapter 1: Security Governance Through Principles and Policies 1042 Chapter 2: Personnel Security and Risk Management Concepts 1045 Chapter 3: Business Continuity Planning 1049 Chapter 4: Laws, Regulations, and Compliance 1051 Chapter 5: Protecting Security of Assets 1053 Chapter 6: Cryptography and Symmetric Key Algorithms 1056 Chapter 7: PKI and Cryptographic Applications 1058 Chapter 8: Principles of Security Models, Design, and Capabilities 1060 Chapter 9: Security Vulnerabilities, Threats, and Countermeasures 1062 Chapter 10: Physical Security Requirements 1067 Chapter 11: Secure Network Architecture and Components 1071 Chapter 12: Secure Communications and Network Attacks 1075 Chapter 13: Managing Identity and Authentication 1078 Chapter 14: Controlling and Monitoring Access 1080 Chapter 15: Security Assessment and Testing 1082 Chapter 16: Managing Security Operations 1084 Chapter 17: Preventing and Responding to Incidents 1086 Chapter 18: Disaster Recovery Planning 1089 Chapter 19: Investigations and Ethics 1091 Chapter 20: Software Development Security 1093 Chapter 21: Malicious Code and Application Attacks 1095 Appendix B Answers to Written Labs 1099 Chapter 1: Security Governance Through Principles and Policies 1100 Chapter 2: Personnel Security and Risk Management Concepts 1100 Chapter 3: Business Continuity Planning 1101 Chapter 4: Laws, Regulations, and Compliance 1102 Chapter 5: Protecting Security of Assets 1102 Chapter 6: Cryptography and Symmetric Key Algorithms 1103 Chapter 7: PKI and Cryptographic Applications 1104 Chapter 8: Principles of Security Models, Design, and Capabilities 1104 Chapter 9: Security Vulnerabilities, Threats, and Countermeasures 1105 Chapter 10: Physical Security Requirements 1106 Chapter 11: Secure Network Architecture and Components 1108 Chapter 12: Secure Communications and Network Attacks 1109 Chapter 13: Managing Identity and Authentication 1110 Chapter 14: Controlling and Monitoring Access 1111 Chapter 15: Security Assessment and Testing 1111 Chapter 16: Managing Security Operations 1112 Chapter 17: Preventing and Responding to Incidents 1113 Chapter 18: Disaster Recovery Planning 1113 Chapter 19: Investigations and Ethics 1114 Chapter 20: Software Development Security 1114 Chapter 21: Malicious Code and Application Attacks 1115 Index 1117
Bausteine eines Managements Künstlicher Intelligenz
Algorithmen Künstlicher Intelligenz werden stetig weiterentwickelt und kommen in immer mehr Anwendungen in Wirtschaft und Gesellschaft zum Einsatz. Es werden professionelle Prozesse und Strukturen benötigt, um Anwendungen zu entwickeln, zu betreiben und in den betrieblichen Kontext zu integrieren. Dieses essential beschreibt die grundsätzlichen Prozesse eines Managements Künstlicher Intelligenz und zeigt Beispiele für konkreten unternehmerischen Nutzen. Wettbewerbsvorteile durch Künstliche Intelligenz.- Grundlagen.- Stand in Wissenschaft und Praxis.- Managementmodell.- Nächste Schritte.
(ISC)2 CISSP Certified Information Systems Security Professional Official Practice Tests
FULL-LENGTH PRACTICE TESTS COVERING ALL CISSP DOMAINS FOR THE ULTIMATE EXAM PREPThe (ISC)2 CISSP Official Practice Tests is a major resource for (ISC)2 Certified Information Systems Security Professional (CISSP) candidates, providing 1300 unique practice questions. The first part of the book provides 100 questions per domain. You also have access to four unique 125-question practice exams to help you master the material. As the only official practice tests endorsed by (ISC)2, this book gives you the advantage of full and complete preparation. These practice tests align with the 2021 version of the exam to ensure up-to-date preparation, and are designed to cover what you will see on exam day. Coverage includes: Security and Risk Management, Asset Security, Security Architecture and Engineering, Communication and Network Security, Identity and Access Management (IAM), Security Assessment and Testing, Security Operations, and Software Development Security.The CISSP credential signifies a body of knowledge and a set of guaranteed skills that put you in demand in the marketplace. This book is your ticket to achieving this prestigious certification, by helping you test what you know against what you need to know.* Test your knowledge of the 2021 exam domains* Identify areas in need of further study* Gauge your progress throughout your exam preparation* Practice test taking with Sybex’s online test environment containing the questions from the bookThe CISSP exam is refreshed every few years to ensure that candidates are up-to-date on the latest security topics and trends. Currently-aligned preparation resources are critical, and periodic practice tests are one of the best ways to truly measure your level of understanding.ABOUT THE AUTHORSMIKE CHAPPLE, PhD, CISSP, is Teaching Professor of Information Technology, Analytics, and Operations at Notre Dame’s Mendoza College of Business and serves as the Academic Director of the University’s Master of Science in Business Analytics program. He holds multiple additional certifications, including the CIPP/US, CySA+, CISM, PenTest+, and Security+. He is a bestselling author of more than 25 books including (ISC)2 CISSP Certified Information Systems Security Professional Official Study Guide,7th, 8th, and 9th Editions.DAVID SEIDL, CISSP, is Vice President for Information Technology and CIO at Miami University. During his IT career, he has served in a variety of technical and information security roles including serving at the Senior Director for Campus Technology Services at the University of Notre Dame where he co-led Notre Dame’s move to the cloud. He holds multiple additional technical certifications including CySA+, Pentest+, GPEN, and GCIH. David has written books on security certification and cyberwarfare, including co-authoring the previous editions of CISSP (ISC)2 Official Practice Tests as well as multiple cybersecurity Sybex Study Guides and Practice Tests for other certifications.Introduction xvCHAPTER 1 SECURITY AND RISK MANAGEMENT (DOMAIN 1) 1CHAPTER 2 ASSET SECURITY (DOMAIN 2) 25CHAPTER 3 SECURITY ARCHITECTURE AND ENGINEERING (DOMAIN 3) 49CHAPTER 4 COMMUNICATION AND NETWORK SECURITY (DOMAIN 4) 73CHAPTER 5 IDENTITY AND ACCESS MANAGEMENT (DOMAIN 5) 97CHAPTER 6 SECURITY ASSESSMENT AND TESTING (DOMAIN 6) 121CHAPTER 7 SECURITY OPERATIONS (DOMAIN 7) 145CHAPTER 8 SOFTWARE DEVELOPMENT SECURITY (DOMAIN 8) 169CHAPTER 9 PRACTICE TEST 1 195CHAPTER 10 PRACTICE TEST 2 225CHAPTER 11 PRACTICE TEST 3 253CHAPTER 12 PRACTICE TEST 4 283APPENDIX ANSWERS 311Chapter 1: Security and Risk Management (Domain 1) 312Chapter 2: Asset Security (Domain 2) 321Chapter 3: Security Architecture and Engineering (Domain 3) 333Chapter 4: Communication and Network Security (Domain 4) 342Chapter 5: Identity and Access Management (Domain 5) 353Chapter 6: Security Assessment and Testing (Domain 6) 365Chapter 7: Security Operations (Domain 7) 377Chapter 8: Software Development Security (Domain 8) 389Chapter 9: Practice Test 1 400Chapter 10: Practice Test 2 414Chapter 11: Practice Test 3 428Chapter 12: Practice Test 4 441Index 457
Modellierung
Die Grundlagen der Modellierung beherrschen!Die Modellierung ist eine typische Arbeitsmethode in der Informatik: Aufgaben, Probleme oder Strukturen werden untersucht und formal beschrieben. Erst danach werden sie durch den Entwurf von Software, Algorithmen, Daten oder Hardware gelöst bzw. implementiert. Zur Anwendung der Modellierung steht ein breites Spektrum von Kalkülen und Notationen zur Verfügung.Dieses Buch soll eine Übersicht über die wichtigsten Kalküle der Informatik und ein grundlegendes Verständnis für diese vermitteln. Anhand von vielen praktischen Beispielen lernen Sie die grundlegenden Modellierungstechniken kennen und werden in deren Anwendung eingeführt.Dieses Buch vermittelt systematisch und praxisnah den Lehrstoff für Einführungsvorlesungen zur Modellierung und eignet sich für Bachelor-Studiengänge der Informatik und verwandter Fächer. Es werden behandelt:- Modellierung mit Wertebereichen- Terme und Algebren- Logik- Modellierung mit Graphen- Modellierung von Strukturen- Modellierung von Abläufen- FallstudienAuf plus.hanser-fachbuch.de finden Sie zu diesem Titel kostenloses digitales Zusatzmaterial in Form von umfassenden Vorlesungsmaterialien und Übungen mitsamt Lösungen. Prof. Dr. Uwe Kastens und Prof. Dr. Hans Kleine Büning lehrten Informatik an der Universität Paderborn und hielten dort im Wechsel die Modellierungsvorlesung.
Machine Learning for Oracle Database Professionals
Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle’s Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines.Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions.WHAT YOU WILL LEARN* Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation* Understand Oracle offerings for machine learning* Develop machine learning with Oracle database using the built-in machine learning packages* Develop and deploy machine learning models using OML4SQL and OML4R* Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning* Develop and deploy machine learning projects in Oracle Autonomous Database* Build an automated pipeline that can detect and handle changes in data/model performanceWHO THIS BOOK IS FORDatabase developers and administrators who want to learn about machine learning, developers who want to build models and applications using Oracle Database’s built-in machine learning feature set, and administrators tasked with supporting applications on Oracle Database that make use of the Oracle Machine Learning feature setHELI HELSKYAHO is CEO for Miracle Finland Oy. She holds a master’s degree in computer science from the University of Helsinki and specializes in databases. At the moment she is working on her doctoral studies, researching and teaching at the University of Helsinki. Her research areas cover big data, multi-model databases, schema discovery, and methods and tools for utilizing semi-structured data for decision making.Heli has been working in IT since 1990. She has held several positions, but every role has included databases and database designing. She believes that understanding your data makes using the data much easier. She is an Oracle ACE Director, an Oracle Groundbreaker Ambassador, and a frequent speaker at many conferences. She is the author of several books and has been listed as one of the TOP 100 influencers in the IT sector in Finland for each year from 2015 to 2020.JEAN YU is a Senior Staff MLOps Engineer at Habana Labs, an Intel company. Prior to that, she was a Senior Data Engineer on the IBM Hybrid Cloud Management Data Science Team. Her current interests include deep learning, model productization, and distributed training of massive transformer-based language models. She holds a master's degree in computer science from the University of Texas at San Antonio. She has more than 25 years of experience in developing, deploying, and managing software applications, as well as in leading development teams. Her recent awards include an Outstanding Technical Achievement Award for significant innovation in Cloud Brokerage Cost and Asset Management products in 2019 as well as an Outstanding Technical Achievement Award for Innovation in the Delivery of Remote Maintenance Upgrade for Tivoli Storage Manager in 2011.Jean is a master inventor with 14 patents granted. She has been a voting member of the IBM Invention Review Board from 2006 to 2020. She has been a speaker at conferences such as North Central Oracle Apps User Group Training Day 2019 and Collaborate 2020.KAI YU is a Distinguished Engineer of the Dell Technical Leadership Community. He is responsible for providing technical leadership to Dell Oracle Solutions Engineering. He has over 27 years of experience in architecting and implementing various IT solutions, specializing in Oracle database, IT infrastructure, and cloud as well as business analytics and machine learning.Kai has been a frequent speaker at various IT/Oracle conferences with over 200 presentations in more than 20 countries. He also authored 36 articles in technical journals such as IEEE Transactions on Big Data, and has co-authored the Apress book Expert Oracle RAC12c. He has been an Oracle ACE Director since 2010, and has served on the IOUG/Quest Conference committee and served as IOUG RAC SIG president and IOUG CLOUG SIG co-founder and vice president. He received the 2011 OAUG Innovator of Year award and the 2012 Oracle Excellence Award: Technologist of the Year: Cloud Architect by Oracle Magazine. He holds two master’s degrees in computer science and engineering from the Huazhong University of Science and Technology and the University of Wyoming.1. Introduction to Machine Learning2. Oracle and Machine Learning3: Oracle Machine Learning for SQL4. Oracle Autonomous Database for Machine Learning5. Running Oracle Machine Learning with Autonomous Database6: Building Machine Learning Models with OML Notebooks7. Oracle Analytics Cloud8. Delivery and Automation Pipeline in Machine Learning9. ML Deployment Pipeline Using Oracle Machine Learning10. Building Reproducible ML Pipelines Using Oracle Machine Learning
Introduction to Video Game Engine Development
Start your video game development journey by learning how to build a 2D game engine from scratch. Using Java (with NetBeans as your IDE and using Java’s graphics framework) or by following along in C# (with Visual Studio as your IDE and using the MonoGame framework), you’ll cover the design and implementation of a 2D game engine in detail. Each class will be reviewed with demonstration code. You’ll gain experience using the engine by building a game from the ground up.Introduction to Video Game Engine Development reviews the design and implementation of a 2D game engine in three parts. Part 1 covers the low-level API class by class. You’ll see how to abstract lower-level functionality and design a set of classes that interact seamlessly with each other. You’ll learn how to draw objects, play sounds, render text, and more. In Part 2, you’ll review the mid-level API that is responsible for drawing the game, loading resources, and managing user input. Lastly, in Part 3, you’ll build a game from the ground up following a step-by-step process using the 2D game engine you just reviewed.On completing this book, you’ll have a solid foundation in video game engine design and implementation. You’ll also get exposure to building games from scratch, creating the solid foundation you’ll need to work with more advanced game engines, and industry tools, that require learning complex software, APIs, and IDEs.WHAT YOU WILL LEARN* Gain experience with lower-level game engine APIs and abstracting framework functionality* Write application-level APIs: launching the game, loading resources, settings, processing input, and more * Discover cross-platform APIs in the game engine projects written in both Java and C#/MonoGame * Develop games with an SDK-based game engine and simplified tool chain focused on direct control of the game through code* Master creating games by using the game engine to build a game from the ground up with only code and an IDEWHO THIS BOOK IS FORThose of you out there with some programming experience, moderate to advanced, who want to learn how to write video games using modern game engine designs.Victor Brusca is an experienced software developer specializing in building cross-platform applications and APIs. He regards himself as a self-starter with a keen eye for detail, an obsessive protection of systems/data, and a desire to write well-documented, well-encapsulated code. With over 14 years' software development experience, he has been involved in game and game engine projects on J2ME, T-Mobile SideKick, WebOS, Windows Phone, Xbox 360, Android, iOS, and web platforms.Chapter 1: MmgBase API IntroductionChapter 2: Base ClassesChapter 3: Helper ClassesChapter 4: Other ClassesChapter 5: Advanced ClassesChapter 6: Widget ClassesChapter 7: Animation ClassesChapter 8: Game Screen ClassesChapter 9: MmgCore API IntroductionChapter 10: Static Main Entry PointChapter 11: Dynamic SettingsChapter 12: Event HandlersChapter 13: Resource LoadingChapter 14: Game ScreensChapter 15: Game Build IntroductionChapter 16: PongClone Project SetupChapter 17: PongClone Main Menu ScreenChapter 18: PongClone Game ScreenChapter 19: Conclusion
PowerShell for Beginners
Learn the basic tools and commands to write scripts in PowerShell 7. This hands-on guide is designed to get you up and running on PowerShell quickly - introducing interactive menus, reading and writing files, and creating code that talks over the network to other scripts, with mini games to facilitate learning.PowerShell for Beginners starts with an introduction to PowerShell and its components. It further discusses the various tools and commands required for writing scripts in PowerShell 7, with learning reinforced by writing mini games. You will learn how to use variables and conditional statements for writing scripts followed by loops and arrays. You will then work with functions and classes in PowerShell. Moving forward, you will go through the PowerShell Console, customizing the title and text colors. Along the way you will see how to read a key press and make sound in PowerShell. The final sections cover game engine layout, how to build a title screen, and implementing the game design using code flow, title screens, levels, and much more.After reading the book you will be able to begin working with PowerShell 7 scripts and understand how to use its tools and commands effectively.WHAT YOU WILL LEARN* Use Microsoft Visual Studio Code to develop scripts* Understand variables, loops and conditional statements in PowerShell* Work with scripts to develop a game* Discover and use ASCII art generators* Comprehend game objects and code* Create client-server scripts that communicate over a network* Read and write to files* Capture input from the keyboard* Make PowerShell speak words to help the visually impaired* Create text-based adventure gamesWHO THIS BOOK IS FORSoftware developers who want to start working with PowerShell scripts.IAN WATERS works for Southern IT Networks Ltd as the technical director. He works with Managed Service Providers (MSPs) striving to provide the best possible IT support services to businesses in the south east of England. Ian has an overall experience of 15 years in IT where he has been working on Windows Server, Exchange, Active Directory, Microsoft 365, PowerShell, and many more. He is a frequent blogger and posts articles related to Microsoft’s new technologies on Slash Admin.Chapter 1: Introduction.Chapter 2: Beginners Guide to PowerShell and Visual Studio CodeChapter 3: Variables.Chapter 4: Conditional Statements.Chapter 5: Loops.Chapter 6: Arrays.Chapter 7: Functions.Chapter 8: Classes.Chapter 9: Customising The Console.Chapter 10: User Input.Chapter 11: Dragon Slayer.Chapter 12: Getting Colourful.Chapter 13: ASCII Table.Chapter 14: Cursor Control.Chapter 15: Background Processing.Chapter 16: Networking.Chapter 18: Working with Files.Chapter 19: Game EngineChapter 20: Creating ASCII ArtChapter 21: Power Bomber
Essential Computer Science
Understand essential computer science concepts and skills. This book focuses on the foundational and fundamental concepts upon which expertise in specific areas can be developed, including computer architecture, programming language, algorithm and data structure, operating systems, computer networks, distributed systems, security, and more.According to code.org, there are 500,000 open programming positions available in the US— compared to an annual crop of just 50,000 graduating computer science majors. The US Department of Labor predicted that there will be almost a million and a half computer science jobs in the very near future, but only enough programmers to fill roughly one third of these jobs.To bridge the gap, many people not formally trained in computer science are employed in programming jobs. Although they are able to start programming and coding quickly, it often takes them time to acquire the necessary understanding to gain the requisite skills to become an efficient computer engineer or advanced developer.WHAT YOU WILL LEARN* The fundamentals of how a computer works* The basics of computer programming and programming paradigms* How to write efficient programs* How the hardware and software work together to provide a good user experience and enhance the usability of the system* How computers can talk to each other* How to ensure the security of the system* The fundamentals of cloud offerings, implications/trade-offs, and deployment/adoption configurations* The fundamentals of machine learningWHO THIS BOOK IS FORComputer programmers lacking a formal education in computer science, and anyone with a formal education in computer science, looking to develop a general understanding of computer science fundamentalsPAUL D. CRUTCHER is Senior Principal Engineer at Intel Corporation and manages the Platform Software Architecture team in the Client Computing Group. He has worked at Intel for more than 25 years and has also worked at two smaller software companies. Paul has a degree in computer science, with expertise spanning software development, architecture, integration, and validation based on systems engineering best practices in multiple areas. He holds several patents and has written multiple papers and presentations.NEERAJ KUMAR SINGH is a Principal Engineer at Intel with more than 15 years of system software and platform design experience. His areas of expertise are hardware software co-design, system/platform architecture, and system software design & development. Neeraj is the lead author of two other books: System on Chip Interfaces for Low Power Design and Industrial System Engineering for Drones: A Guide with Best Practices for Designing, in addition to many other papers and presentations.PETER TIEGS is Principle Engineer at Intel with 20 years of software experience. Inside Intel he often consults on DevOps topics such as build automation and source code branching. Over the last decade Peter evangelized continuous integration and delivery as well as agile practices at Intel. He has written software at all levels of the stack from embedded C code to VUE.js. His programming language of choice is Python.Chapter 1: Concept and Fundamentals of Computer SystemIn this chapter we discuss a brief history and evolution of a computer System, and fundamentals of how it operates.1. Evolution of Computer System2. Von Neumann Model/Architecture: I/O, CPU and memory1. Fetch:2. Decode,3. Execute3. Fetch: Address and Data4. Decode: Instructions and Instruction Set Architecture:1. Encode/Decode1. Number Representation2. Negative Numbers3. Little Endian/Big Endian.2. Instruction Format, Opcode, Operand3. Addressing modes4. ISA:1. Categories: RISC, CISC etc.2. Examples: x86, ARM etc.5. Execute:1. Fundamentals of Digital Logic2. Examples: ADD, SUB.6. Computer Hardware Advancements/Extensions:1. Compute Block: Pipelining, and Predictive Execution and Data Hazards2. Memory Hierarchy: Cache (inclusive, exclusive), Memory3. Interrupt Based vs. Polling1. Interrupt Service Routine4. DMA5. Multiprocessor: SIMD, MIMD, VLIW etc.7. Basic Architecture of x86 based computer1. Stack, PC, General Purpose Registers (GPRs) etc.8. IO Devices- Interface and Controller Advancements, Example: PCIe, USB1. Controller, Bus, and Device9. Internal and External View of an Example Computer System Design10. References and further reading:1. Digital Logic and Computer Design: Morris Mano2. Computer Organization and Design: The Hardware/Software Interface: Hennessy and PattersonChapter 2: Programming the Computer HardwareIn the preceding chapter we discussed the fundamentals about the computer hardware and architecture. Now having understood that, let’s discuss how to program/instruct the hardware to do what we want/need.1. What’s programming?2. Assembly and Machine language3. Programming in High Level Language- why?4. Programming Language Fundamentals:1. Language Definition:· Syntax· High Level Constructs to Machine Level Mapping, example:1. Variable definition to memory allocation2. Assignment to mov3. Operators to respective: ADD, SUB, MUL etc.4. Conditional to cmp and jmp5. Loops to cmp and jmp etc.6. Functions to call and return, and stack· Other Key Concepts:1. Variable Scope and Lifetime,2. Data Type and Type Casting3. Formal, and Actual Parameter(arguments),4. Function Call by Value and Reference5. Lambda functions2. Translation from High Level to Machine Level Language:· Lexical: picking up tokens· Parser: Syntax and Semantic Analysis· Code Generation1. Intermediate code- why?2. Optimization- why?3. Symbol Table4. Libraries and Runtime?· Why?· Linking Process· Static, and Dynamic libraries· Benefits and tradeoffs- DLL Hell?5. IDE: The one that puts it all together5. Programming Paradigms:1. Procedural, Object Oriented,2. Interpreted vs Compiled etc.3. Why different Languages?6. Good Code1. Architecture and2. Design Patterns7. References and further reading:1. Compilers: Principles, Techniques, and Tools: Aho Ullman Sethi2. The art of computer Programming: Knuth3. Linkers and Loaders: LevineChapter 3: Algorithm and Data StructureWe’ve discussed computer hardware and how to program it to achieve desired purpose. In this chapter we will discuss how to make programs more efficient.1. What is an Algorithm2. Good and *not so good* Algorithm:1. Time/Space Complexity2. Asymptotic Notation3. Fundamental Data Structure and Algorithm:1. Store (Data Structure): Stack, Queue, Tree, Graph, Linked List, Array, Hash2. Making use of the Data: Searching, Sorting4. Problem Solving Techniques:1. Recursion,2. Divide and Conquer3. Dynamic programming,4. Brute force,5. Greedy Algorithms,5. Class of problems:1. NP Complete and NP Hard problems2. Tractable and Intractable problems.6. Databases:1. Why: Persistence and Volume2. Fundamental Requirements: ACID3. Brief History of Database System Evolution4. Most Prominent Current Database Systems:· Structured Data/ Unstructured Data· Relational Data: Oracle, MySQL etc.· NoSQL1. Why2. Brief History and Examples: Graph database Neo4j, BigTable, CouchDB, Cassandra, MongoDB7. References and further reading:1. Introduction to Algorithms: Thomas Cormen2. Database System Concepts: Avi SilberschatzChapter 4: Operating SystemHaving discussed the computer hardware and software fundamentals, now we will discuss how they work together to provide a good user experience and enhance the usability of the system.1. Purpose of Operating System:1. Bridge between User and the Hardware2. What Systems need OS2. Key Drivers:1. General Purpose: Multifunction2. Multi-processor,3. Multi-tasking4. Multiuser3. Key Function:1. User Authentication:· Virtualize CPU: Scheduling: Affinity, Preemption2. Virtualize Memory:· Segmentation, Paging, Demand Paging, Swapping3. Access and Protection:· Serialization: Deadlocks, Locks, and Semaphores· Separation:1. User Mode and Kernel/*Super User* Mode2. Separation Implementation1. Protection Ring/Layers3. Switching between Kernel and User Mode4. Access to Hardware:1. Device Driver, DDI, and Driver Models4. User Shell: UI/Command Based· Launching an Application· Application/Program vs Process/Thread· Application/Executable Format.· Application Loading Process5. Persistence of Configuration and Settings· Registry for Windows· Configuration Files for Linux4. OS Categories:1. Real time, and General Purpose2. Design Considerations for Real time OS5. Reference:1. Operating System Concepts: Silberschatz, Galvin2. Operating Systems: Three Easy Pieces: Andrea CChapter 5: Computer Networks and Distributed Systems So far, we discussed the computer systems in isolation. There is a need for computers to talk to each other to enable communication and create distributed systems. In this chapter we will discuss how computers can talk to each other.1. History/Evolution of Networks/Internet2. Protocol-Stateful and Stateless Protocol3. Internet protocol (IP), TCP and UDP1. Host, IP Address, MAC, Port, Socket2. DNS, DHCP3. Proxy, Firewall, Router, Firewall4. Distributed Systems: Prominent Architectures1. Client-Server2. Peer-to-Peer3. N-Tier5. Distributed System Example:1. World Wide Web- How it Works?2. FTP- How it Works6. Case Study: Developing Web Application1. System Architecture2. Frontend- Technologies3. Backend - Technologies7. Reference and further reading:1. Computer Networking: A Top-Down Approach: Kurose RossChapter 6: Computer SecurityNow, that we discussed about the computer systems and how they can and do work together in computer networks. It becomes of pertinent importance to ensure the security of the system. In this chapter we’ll talk about the same.1. Security- What and Why?2. Security of Standalone System:1. Physical Security2. Access Control- Authentication· Authentication: Purpose· Active Directory/Kerberos· Integrated Windows Authentication· Biometric3. Malware(viruses) and Antiviruses- How they Work?3. Communication Security1. Cryptography· Symmetric, Asymmetric: Public and Private· Various Algorithms:(AES-512, DES, …)2. Hashing, Signing, Salting4. Putting it in Practice1. Algorithms to Exchange the Keys2. Certificate3. Digital signatures4. Chain and Root of Trust5. Certification Authorities, and Trust Chain6. Certificate Stores5. Applications of the Security Concepts/Mechanisms:1. Secure Boot2. Network Security: TLS, SSL, HTTPS, IPsec, VPNChapter 7: Cloud Computing Traditionally, the businesses have managed their backend servers on their own at their premise. However, there is a trend to consolidate these resources and services somewhere (cloud) on network. And, these services can be used by businesses as needed. The resources can thus be shared and optimized. The services are provided and managed by “cloud service providers.” In this chapter we’ll discuss about the cloud offerings, implications/trade-off and deployment/adoption configurations.1. Cloud and its Offerings (Types)1. IaaS2. SaaS3. PaaS2. Benefits of Cloud Computing3. Cloud Deployment/Adoption Configurations1. Private,2. Public3. Hybrid,4. Cloud Resource Types: VM/Compute, Database, File Share, Lambda etc.5. Cloud Interface/Mechanism6. Developing and Deploying on Cloud1. Cloud Orchestration and Deployment7. Top Cloud Providers: AWS, Azure, Google Cloud, Oracle etc.8. Considerations for Developing Portable and Interoperable SolutionsChapter 8: Machine LearningSo far, we, the human beings, have been developing algorithms and programs which computers just carry out. The algorithms and logic are developed and coded by human beings. The evolution in processing power and data storage has allowed computers to be able to learn and develop logic/intelligence form the data inputs- aka machine learning. In this chapter we discuss the fundamentals of machine learning.What it is? Algorithmic Programming vs. Machine Learning1. Fundamental Concepts in Machine Learning:· Model· Training· Inference2. Four Different Categories of Machine Learning:· Supervised· Unsupervised· Semi-supervised· Reinforcement3. Real and Practical Applications of Machine Learning· Ex: Web Search, E-Comm/Social Media Suggestions etc.2. Evolution of Machine Learning:1. Data Science to AI and ML3. Practical Machine Learning:1. Top leading machine learning frameworks· TensorFlow, PyTorch, ONNX, CAFFE, Keras, Firebase ML kit etc.4. Machine Learning and Cloud- Relationship and Dependency?Appendix: A: SDLCPlanning, Analysis, Design, Implementation, Test, Deploy and MaintenanceAppendix B: Software Engineering Practices:1. Planning and Management Practices: Agile2. Documentation3. Testing:1. Phases and Categories of Testing and Goals· Algorithm Testing, Unit Testing, Integration etc.2. Test Driven Development4. Developing for Debug5. Continuous Integration and Continuous Deployment1. Purpose and Mechanism?2. Tools: Jenkins, TeamCity etc.6. Build Optimization and Tools:1. Purpose and Mechanism2. Tools: Make, Maven, Gradle7. SCM1. Goal and Mechanism2. Tools: P4, SVN, GitAppendix: C: ACPI System States Appendix: C: Complete Flow of Boot to OS1. Computer BIOS and Boot process2. Co-ordination b/w Firmware and OS3. ACPI and Power Management?
Bewegung!
Das Wichtigste an Präsentationen ist ihr Inhalt - ganz klar! Aber es kommt auch darauf an, diesen Inhalt so zu präsentieren, dass die Zuschauer ihn optimal aufnehmen können und jederzeit gedanklich bei dem Punkt sind, den der Präsentator gerade erläutert. Deshalb sollten Inhalte Stück für Stück auf Mausklick eingeblendet werden - so wird niemand abgelenkt. Was sich bewegt, wirkt immer anregender und interessanter als statische Inhalte. Es kommt nur darauf an, diese Bewegung sinnvoll und passend zum Kontext zu gestalten: Ein Diagramm kann schrittweise aufgebaut werden, eine Tabelle nach und nach aufgedeckt, ein Prozess mit einem Video leicht erläutert werden. Excel-Tabellen können innerhalb der Präsentation lesbar präsentiert werden. Alle Inhalte richten sich an Anwender im beruflichen Umfeld. Die gezeigten Möglichkeiten eignen sich natürlich auch für die Arbeit mit Kindern und alle anderen Anwendungen von PowerPoint!Ina Koys ist langjährige Trainerin für MS-Office-Produkte. Viele Fragen werden in den Kursen immer wieder gestellt, aber selten in Fachbüchern behandelt. Einige davon beantwortet sie jetzt in der Reihe "kurz & knackig".
Visual Analysis of Multilayer Networks
THIS IS AN OVERVIEW AND STRUCTURED ANALYSIS OF CONTEMPORARY MULTILAYER NETWORK VISUALIZATION. IT SURVEYS TECHNIQUES AS WELL AS TOOLS, TASKS, AND ANALYTICS FROM WITHIN APPLICATION DOMAINS. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them.Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains.The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization.* Preface* Figure Credits* Introduction and Overview* Multilayer Networks Across Domains* The Layer as an Entity* Task Taxonomy for Multilayer Networks* Visualization of Nodes and Relationships Across Layers* Interacting with and Analyzing Multilayer Networks* Attribute Visualization and Multilayer Networks* Evaluation of Multilayer Network Visualization Systems and Techniques* Conclusions* Bibliography* Authors' Biographies* List of Figures