Democratizing Application Development with Betty Blocks
Build powerful applications that impact business immediately with no-code app developmentKey Features: Understand the different capabilities, features, and low-code functionalities of Betty Blocks with real-world use casesExplore applications that impact your business right away with rapid application developmentDevelop dynamic web applications with easy drag-and-drop functionalities from Betty BlocksBook Description: This practical guide on no-code development with Betty Blocks will take you through the different features, no-code functionalities, and capabilities of the Betty Blocks platform using real-world use cases. The book will equip you with the tools to develop business apps based on various data models, business processes, and more.You'll begin with an introduction to the basic concepts of the Betty Blocks no-code platform, such as developing IT solutions on various use cases including reporting apps, data tracking apps, workflows, and business processes. After getting to grips with the basics, you'll explore advanced concepts such as building powerful applications that impact the business straight away with no-code application development and quickly creating prototypes. The concluding chapters will help you get a solid understanding of rapid application development, building customer portals, building dynamic web apps, drag-and-drop front ends, visual modelling capabilities, and complex data models.By the end of this book, you'll have gained a comprehensive understanding of building your own applications as a citizen developer using the Betty Blocks no-code platform.What You Will Learn: Understand what you can achieve with citizen developmentFind out how to build your first application with no-code developmentGet to grips with the basics of the Betty Blocks platform as a citizen developerDiscover how to build your own application or prototypeBuild business applications based on data models and business processesEnable developers to include additional functionality for citizen developersWho this book is for: This book is for citizen developers and business users who want to build applications to fulfill their business needs without depending on developers. Prior knowledge of coding and application development is not necessary, but it will speed up your learning.
Smart Until It’s Dumb
Artificial intelligence is everywhere-powering news feeds, curating search results and invisibly steering our lives. We talk to it and, increasingly, it talks back. And sometimes its answers seem eerily smart.... Until they don't.Billions of dollars have been poured into AI yet it keeps surprising us with its epic fails-confidently wrong chatbots, inadvertently racist photo apps, well-meaning autonomous cars that fail to recognize traffic cones.Industry insider Emmanuel Maggiori cuts through the hype, revealing the deceptively simple mechanisms behind AI's impressive results-and its spectacular blunders.Learn the dark secret of the AI industry-how unreasonable expectations, shady practices and outright lying have inflated a bubble of monumental proportions.Read Smart Until It's Dumb to discover how AI really works, why it's not always so smart, and why the AI bubble is about to burst.***Emmanuel Maggiori, PhD, is a 10-year AI industry insider, specialized in machine learning and scientific computing. He helps companies build complex software. He has developed AI for a wide variety of applications, from extracting objects from satellite images to packaging holiday deals for millions of travelers every day.
Machine Learning and Data Mining for Sports Analytics
This book constitutes the refereed proceedings of the 9th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2022, held in Grenoble, France, during September 19, 2022. The 10 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections as follows: Football, Racket sports, Cycling.
Machine Learning and Internet of Things for Societal Issues
Emerging Ict Technologies and Cybersecurity
This book introduces some fundamentals of information and communication technology (ICT) and other current and future technologies that are relevant to the field of cybersecurity. In a digitally connected world, cybersecurity is one of the most important issues today. We have witnessed tremendous advancements over the last two decades in various fields of networking, connectivity, electronics, and the technologies that make use of those platforms and devices. Many emerging technologies are also showing promise for future use in the cybersecurity area. Hence, it is important to understand some basics of the technologies and concepts that are making their impacts today and those which may show stronger influence in the near future. The book begins with an introduction to ICT and its advancements, then talks about Artificial Intelligence (AI), Machine Learning (ML), and Blockchain Technologies. It then goes on to cover wireless technology, Internet of Things (IoT), Distributed Cloud Computing, Quantum Computing, Virtual Reality, and other futuristic technologies that would be directly related to Cyberspace and Cybersecurity.This textbook is written in a step-by-step manner, with easily accessible information for both general readers and experts in the field. It is suitable to be used as a textbook for undergraduate and graduate courses like Computer Networks and Security, Information Security, etc.
Machine Learning for Cyber Agents
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area - the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.
Engineering Document Control, Correspondence and Information Management (Includes Software Selection Guide) for All
The book is the Who, What, When, Where, How and, very importantly, Why of Engineering Document Control with related "metadata" management and includes a comprehensive software guide, and free Access based DC software tool (time limited) with examples and drills etc.
Sustainable Design
Foreword- Introduction.- HCI and Usability.- User Participation in the System Development Process.- Physical, Cognitive and Affective Engineering.- Color, Prototyping and Navigation, Guidelines and Principles Design, Evaluation and Testing; Task Analysis.- Models and Methodologies and Integration of Methodologies; and the New Participative Methodology for Marketing Websites (NPMMW).- New Participative Methodology for Sustainable Design.- Innovative Technologies: Applications in the Present and Considerations for the Future
Intelligent Human Computer Interaction
This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Human Computer Interaction, IHCI 2022, held in Tashkent, Uzbekistan, during October 20-22, 2022. The 47 full papers and 13 short papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: Bio-inspired Computing; Cognitive computing; Human Centered AI; Intelligent Technology for Post-Covid and Web Frameworks.
What is Artificial Intelligence and CHATGPT?
Artificial Intelligence (AI) is the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction. AI is broadly classified into two main categories: rule-based systems and machine learning systems. Rule-based systems follow a set of pre-defined rules to make decisions, while machine learning systems use algorithms to learn from data and improve over time. AI has the potential to revolutionize many industries such as Natural Language Processing (NLP), Robotics, Computer Vision, Healthcare, Finance, Autonomous vehicles, Gaming and Virtual assistants. However, it also raises ethical and societal concerns, such as job displacement and privacy issues. The World Economic Forum estimates that 75 million jobs may be displaced by 2022, but that 133 million new jobs may be created in their place. People should not be scared of AI taking over jobs.
Head and Neck Tumor Segmentation and Outcome Prediction
This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022.The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 883 delineated PET/CT images was made available for training.
Cism Certified Information Security Manager Practice Exams, Second Edition
Up-to-date practice questions that cover every topic on the 2022 version of the CISM exam Take the current version of the challenging CISM exam with complete confidence using the detailed information contained in this fully updated self-study guide. Written by an expert in the field, the book features hundreds of practice exam questions that match those on the live test in content, format, tone, and feel. In-depth answer explanations are provided for both the correct and incorrect answer choices. CISM Certified Information Security Manager Practice Exams, Second Edition supplements the CISM All-in-One Exam Guide and completely covers every objective of the 2022 exam release. In total, the book contains more than 300 realistic practice questions. - Offers 100% coverage of all four CISM exam domains- Online content includes access to an additional 150 practice questions in the TotalTester Online customizable test engine - Written by a computer security expert, author, and lecturer
Machine Learning
Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering. To make optimal use of ML, it is essential to understand its underlying principles. This book approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. The book trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.The book's three-component approach to ML provides uniform coverage of a wide range of concepts and techniques. As a case in point, techniques for regularization, privacy-preservation as well as explainability amount to specific design choices for the model, data, and loss of a ML method.
Data Science, Analytics and Machine Learning with R
Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.
Blockchain Technology Solutions for the Security of IoT-Based Healthcare Systems
Blockchain Technology Solutions for the Security of IoT-Based Healthcare Systems explores the various benefits and challenges associated with the integration of blockchain with IoT healthcare systems, focusing on designing cognitive-embedded data technologies to aid better decision-making, processing and analysis of large amounts of data collected through IoT. This book series targets the adaptation of decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures, as well as big data and Internet of Things (IoT) problems can be handled in practice. Current Internet of Things (IoT) based healthcare systems are incapable of sharing data between platforms in an efficient manner and holding them securely at the logical and physical level. To this end, blockchain technology guarantees a fully autonomous and secure ecosystem by exploiting the combined advantages of smart contracts and global consensus. However, incorporating blockchain technology in IoT healthcare systems is not easy. Centralized networks in their current capacity will be incapable to meet the data storage demands of the incoming surge of IoT based healthcare wearables.
Cloud Finops
FinOps brings financial accountability to the variable spend model of cloud. Used by the majority of global enterprises, this management practice has grown from a fringe activity to the de facto discipline managing cloud spend. In this book, authors J.R. Storment and Mike Fuller outline the process of building a culture of cloud FinOps by drawing on real-world successes and failures of large-scale cloud spenders. Engineering and finance teams, executives, and FinOps practitioners alike will learn how to build an efficient and effective FinOps machine for data-driven cloud value decision-making. Complete with a road map to get you started, this revised second edition includes new chapters that cover forecasting, sustainability, and connectivity to other frameworks. You'll learn: The DNA of a highly functional cloud FinOps culture A road map to build executive support for FinOps adoption How to understand and forecast your cloud spending How to empower engineering and finance to work together Cost allocation strategies to create accountability for cloud and container spend Strategies for rate discounts from cloud commitments When and how to implement automation of repetitive cost tasks How to empower engineering team action on cost efficiency
Secure Cloud Data Transaction using Deduplication and Encryption
Data deduplication and encryption are two important techniques that can be used together to enhance the security of cloud data transactions. Data deduplication is a process that eliminates duplicate copies of data, reducing the amount of storage space required. This is done by identifying and removing redundant copies of data, leaving only one unique instance. In the context of cloud data transactions, this can reduce the amount of data that needs to be transmitted, which can improve the performance and security of the transaction. Encryption is a technique that is used to secure data by converting it into a code that can only be deciphered by someone who has the correct key. In the context of cloud data transactions, encryption can be used to protect data while it is in transit and while it is at rest. This ensures that even if the data is intercepted, it will be unreadable without the correct key. Together, data deduplication and encryption can provide a strong level of security for cloud data transactions. By reducing the amount of data that needs to be transmitted and encrypting it, these techniques can make it much more difficult for unauthorized individuals to access or modify the data.Advanced technologies offer new opportunities to Cloud computing technologies. It provides computing power and storage resources in distributed environment, while abstracting underlying infrastructure, depending on a given service. Therefore, the usage and importance of cloud-based solutions will increase significantly in time to come. However, in some cases of collaborative research and data sharing process and storage of sensitive data, which is considered as private information and should not be shared without consent (for example patient's regarding his heath consent in healthcare).Lack of standardization, with regard to access to cloud services, decreases then interoperability and flexibility of switching among CSPs. Hence, organizations may experience vendor lock-in, if unwilling to put in significant effort to accommodate their existing solutions to the new CSP. Access control systems should be reviewed and tailored for the suitability with dynamic and distributed nature of the cloud environment. Wide variety of user cases and imperfections in developing cloud technologies and standards make the aforementioned tasks even more complex and hard to realize in a unified way.
Modelling and Development of Intelligent Systems
This book constitutes the refereed proceedings of the 8th International Conference on Modelling and Development of Intelligent Systems, MDIS 2022, held in Sibiu, Romania, during October 28-30, 2022.The 21 papers included in this book were carefully reviewed and selected from 48 submissions. They were organized in the following topical sections as follows: intelligent systems for decision support; machine learning; mathematical models for development of intelligent systems; and modelling and optimization of dynamic systems.
Becoming KCNA Certified
Kick-start your learning journey and implement both Kubernetes and cloud-native technologies in real-life scenarios with this essential, practical guide to the KCNA examPurchase of the print or Kindle book includes a free PDF eBookKey Features: Gain an in-depth understanding of cloud-native computing and Kubernetes conceptsPrepare for the KCNA exam with the help of practical examples and mock examsManage your applications better with Kubernetes container orchestrationBook Description: The job market related to the cloud and cloud-native technologies is both growing and becoming increasingly competitive, making certifications like KCNA a great way to stand out from the crowd and learn about the latest advancements in cloud technologies.Becoming KCNA Certified doesn't just give you the practical skills needed to deploy and connect applications in Kubernetes, but it also prepares you to pass the Kubernetes and Cloud Native Associate (KCNA) exam on your first attempt.The book starts by introducing you to cloud-native computing, containers, and Kubernetes through practical examples, allowing you to test the theory out for yourself. You'll learn how to configure and provide storage for your Kubernetes-managed applications and explore the principles of modern cloud-native architecture and application delivery, giving you a well-rounded view of the subject. Once you've been through the theoretical and practical aspects of the book, you'll get the chance to test what you've learnt with two mock exams, with explanations of the answers, so you'll be well-prepared to appear for the KCNA exam.By the end of this Kubernetes book, you'll have everything you need to pass the KCNA exam and forge a career in Kubernetes and cloud-native computing.What You Will Learn: Get to grips with Cloud Native Computing Foundation (CNCF) and its projectsBuild, configure, and run containers with DockerBootstrap minimal Kubernetes clusters for learningManage and encrypt container traffic with Service MeshDeploy, configure, and update applications on KubernetesControl and connect the applications that run on KubernetesManage storage and provide observability on KubernetesAutomate software development with CI/CD and GitOpsWho this book is for: This book is for DevOps engineers, system administrators, developers, fresh IT graduates, or anyone interested in cloud native architecture, applications, and technologies. Those with relevant work experience looking to upskill themselves in order to manage their applications with Kubernetes in a better way will also find this book helpful. Familiarity with IT fundamentals, networks, and command line interface (CLI) is required, but no prior knowledge of Kubernetes, docker, or cloud services is needed to get started with this book.
Learning-Based Visual Compression
In recent years, the demand for visual media has been growing exponentially. Among the large amount of visual traffic over the Internet, high-resolution visual content constitutes an increasingly large percentage. With such a rapid growth of digital visual media traffic, there is a growing need for image/video compression approaches that can achieve much higher compression ratios than the ones obtained using existing conventional image/video compression methods, while maintaining a high visual quality. Visual compression is an application of data compression to lower the storage and/or transmission requirements for digital images and videos. Due to the rapid growth in visual data transmission demand, more efficient compression algorithms are needed. Considering that deep learning techniques have successfully revolutionized many visual tasks, learning-based compression algorithms have been explored over the years and have been shown to be able to outperform many conventional compression methods. This monograph provides a review of various visual compression algorithms, both end-to-end learning-based image compression approaches and hybrid image compression approaches. Some learning-based video compression methods are also discussed. In addition to describing a wide range of learning-based image compression approaches that have been developed in recent years, the survey describes widely used datasets, and discusses potential research directions.
Advancements in Smart Computing and Information Security
This two-volume constitutes the refereed proceedings of the First International Conference on Advancements in Smart Computing and Information Security, ASCIS 2022, held in Rajkot, India, in November 2022. The 37 full papers and 18 short papers presented were thoroughly reviewed and selected from the 206 submissions. The papers are organized in topical sections on artificial intelligence; smart computing; cyber security; industry.
Innovative Smart Healthcare and Bio-Medical Systems
This book presents models for the deployment of intelligent computing, information, and networking technologies to aid in preventing disease, improving the quality of care and lowering overall cost.
Security and Organization within IoT and Smart Cities
This book aims to provide the latest research developments and results in the domain of AI techniques for smart cyber ecosystems. It presents a holistic insight into AI-enabled theoretic approaches and methodology in IoT networking, security analytics using AI tools and network automation, which ultimately enable intelligent cyber space. This book will be a valuable resource for students, researchers, engineers and policy makers working in various areas related to cybersecurity and privacy for Smart Cities. This book includes chapters titled "An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security", "Smart City: Evolution and Fundamental Concepts", "Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment", "A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving Path to Eco-friendly Smart Cities", "A Novel Framework for a Cyber Secure Smart City", "Contemplating Security Challenges and Threats for Smart Cities", "Self-Monitoring Obfuscated IoT Network", "Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques", "Collaborative Digital Forensic Investigations Model for Law Enforcement: Oman as a Case Study", "Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review", "5G Security and the Internet of Things", "The Problem of Deepfake Videos and How to Counteract Them in Smart Cities", "The Rise of Ransomware Aided by Vulnerable IoT Devices", "Security Issues in Self-Driving Cars within Smart Cities", and "Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities". This book provides state-of-the-art research results and discusses current issues, challenges, solutions and recent trends related to　security and organization within IoT and Smart Cities. We expect this book to be of significant importance not only to researchers and practitioners in academia, government agencies and industries, but also for policy makers and system managers. We anticipate this book to be a valuable resource for all those working in this new and exciting area, and a "must have" for all university libraries.
Handbook of Legal AI
The Handbook of Legal Artificial Intelligence presents a comprehensive overview of the state-of-the-art and trends in the research field of legal AI. The handbook provides a solid introduction to the essentials of the field for newcomers and a selection of advanced issues as a base for future research directions.As the law gets more complex, conflicting, and ever-changing, more advanced methods, most of them come from the Artificial Intelligence (AI) field, are required for analyzing, representing and reasoning on legal knowledge. The discipline that tackles these challenges is now known as "Legal Artificial Intelligence". Legal AI is experiencing, in particular, in the latest years growth in activity, also at the industrial level, touching a variety of issues which go from the analysis of the textual content of the law, to reasoning about legal interpretation to ethical issues of AI applications in the legal domain (e.g., the artificial judge).This Handbook presents a collection of chapters which evolves around three main topics, namely norm mining (i.e., how to automatically identify, extract, classify and interlink norms from text), reasoning about norms and regulations (i.e., how to derive new legal knowledge from the existing legal knowledge bases in such a way to address automatic legal decision making), andnorm enforcement and compliance (i.e., how to check and ensure the compliance of the systems' requirements with the regulation).
Role of Social Media in Predictive Analytics
In the last decade, social media has emerged as a front-runner as a communication medium that allows people to connect at a global level by breaking the geographical barrier and enabling e-participation of people through these social media platforms which act as a virtual world. Due to the above reasons, social media has become an integral part of our lives and we use these for almost everything, ranging from news, entertainment, recommendation on products, and connecting with friends and family. This obsession is so high that out of all Internet users, 75% use social media in one way or the other. People are so much attached to this virtual world that almost every day on average, one spends at least two hours on social media. Currently, there are around 2.9 billion active social media users worldwide. These active users are continuously posting messages, images, videos, etc on various social media platforms and generating tons of user-generated content (UGC).
Comptia A＋ Certification All-In-One Exam Guide, Eleventh Edition (Exams 220-1101 & 220-1102)
This bestselling on-the-job reference and test preparation guide has been fully revised for new 2022 exam objectivesThis fully revised and updated resource offers complete coverage of the latest release of CompTIA A+ exams 220-1101 & 220-1102. You'll find learning objectives at the beginning of each chapter, exam tips, practice exam questions, and in-depth explanations. Designed to help you pass the CompTIA A+ exams with ease, this definitive guide also serves as an essential on-the-job IT reference.Covers all exam topics, including how to: Work with CPUs, RAM, BIOS, motherboards, power supplies, and other personal computer componentsInstall, configure, and maintain hard drivesManage input devices and removable mediaSet up, upgrade, and maintain Microsoft WindowsTroubleshoot and fix computer problemsInstall printers and other peripheralsConfigure and secure mobile devicesConnect to the InternetSet up wired and wireless networksProtect your personal computer and your networkImplement virtualization and cloud-based technologiesOnline content includes: Practice exams for 1101 & 1102 with hundreds of questionsOne hour of video training from Mike MeyersTotalSim simulations of performance-based questionsA collection of Mike Meyers' favorite shareware and freeware PC tools and utilities
AI and Blockchain in Healthcare
This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).
Machine Learning and Knowledge Discovery in Databases
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Hci International 2022 Posters
Learning Technologies.- HCI, Cultural Heritage and Art.- eGovernment and eBusiness.- Digital Commerce and the Customer Experience.- Social Media and the Metaverse.
Exam Ref Sc-300 Microsoft Identity and Access Administrator
Prepare for Microsoft Exam SC-300 and demonstrate your real-world ability to design, implement, and operate identity and access management systems with Microsoft Azure Active Directory (AD). Designed for professionals involved in secure authentication, access, or identity management, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Identity and Access Administrator Associate level. Focus on the expertise measured by these objectives: Implement identities in Azure AD Implement authentication and access management Implement access management for applications Plan and implement identity governance in Azure AD This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes that you are an administrator, security engineer, or other IT professional who provides, or plans to provide, secure identity and access services for an enterprise About the Exam Exam SC-300 focuses on the knowledge needed to configure and manage Azure AD tenants; create, configure, and manage Azure AD identities; implement and manage external identities and hybrid identity; plan, implement, and manage Azure Multifactor Authentication (MFA), self-service password reset, Azure AD user authentication, and Azure AD conditional access; manage Azure AD Identity Protection; implement access management for Azure resources; manage and monitor app access with Microsoft Defender for Cloud Apps; plan, implement, and monitor enterprise app integration; enable app registration; plan and implement entitlement management and privileged access; plan, implement, and manage access reviews; and monitor Azure AD. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Identity and Access Administrator Associate certification, demonstrating your abilities to design, implement, and operate identity and access management systems with Azure AD; configure and manage identity authentication and authorization for users, devices, resources, and applications; provide seamless experiences and self-service; verify identities for Zero Trust; automate Azure AD management; troubleshoot and monitor identity and access environments; and collaborate to drive strategic identity projects, modernize identity solutions, and implement hybrid identity and/or identity governance. See full details at: microsoft.com/learn
.NET MAUI Cross-Platform Application Development
Build apps for Android, iOS, macOS, and Windows using Microsoft's .NET Multi-platform App UI and BlazorKey Features: Get familiar with Microsoft's UI toolkit to build amazing interfaces for iOS, Android, Windows, and macOSBuild a cross-platform password manager based on the famous Windows app, KeePassExplore .NET MAUI development and Hybrid app development using BlazorBook Description: An evolution of Xamarin.Forms, .NET Multi-platform App UI (.NET MAUI) is a cross-platform framework for creating native mobile and desktop apps with C# and XAML. Using .NET MAUI, you can develop apps that'll run on Android, iOS, macOS, and Windows from a single shared code-base. This step-by-step guide provides a comprehensive introduction to those who are new to .NET MAUI that will have you up to speed with app development using .NET MAUI in no time.The book begins by showing you how to develop a cross-platform application using .NET MAUI and then helps you build an app throughout the chapters. You'll gain all the knowledge needed to create a cross-platform application for Android, iOS, the mac OS, and Windows from a single shared code-base using .NET MAUI. As you advance, you'll get to grips with the entire application development lifecycle, from design and implementation through to deployment to the app store through the development of a password manager app using KeePassLib. The concluding chapters will teach you how to integrate the latest frontend technology into your app through .NET MAUI Blazor.By the end of this book, you'll have learned how to develop your own cross-platform applications using .NET MAUI.What You Will Learn: Discover the latest features of .NET 6 that can be used in mobile and desktop app developmentFind out how to build cross-platform apps with .NET MAUI and BlazorImplement device-specific features using .NET MAUI EssentialsIntegrate third-party libraries and add your own device-specific featuresDiscover .NET class unit test using xUnit.net and Razor components unit test using bUnitDeploy apps in different app stores on mobile as well as desktopWho this book is for: This book is an entry-level .NET MAUI book for mobile developers interested in cross-platform application development with working experience of the .NET Core framework, as well as fresh or junior engineers who've just begun their career in mobile app development. Native application developers (desktop) or Xamarin developers who want to migrate to .NET MAUI will also benefit from this book. Basic knowledge of modern object-oriented programming language, such as C#, Java or Kotlin, is assumed.
Readability Research
From the moment we wake up to the moment we end our day, we use interfaces built out of the written word. Textual information remains now, as it has for centuries, the cornerstone of human information acquisition. The wide adoption of smartphone, tablets, e-readers and personal computers has shifted the bulk of this reading from inflexible paper to digital content. The control provided by digital displays over how visual information is presented to readers has the potential to improve reading for each and every reader, regardless of ability or diagnosis. This represents a profound shift in how we think about reading because text is no longer rendered immutable by writers, designers, or publishers at a single stage, and human-computer interaction research is key to realizing its potential. Readability research takes a fundamentally individual approach to what each reader needs. Each reader has their own individual needs. Meanwhile, adapting the written word to the individual reader has never been easier, and the goal of maximizing individual reading efficacy is increasingly attainable. No one discipline or field has all the tools or answers, and readability work is inherently interdisciplinary. The authors of this monograph include vision scientists, technology experts, educators, designers, typographers, and data scientists. Together they represent voices from academia, the tech industry, and non-profit institutions, driven by common goals to improve the reading interfaces of today. In this review, they provide a comprehensive introduction to interdisciplinary methodologies, tools, and materials required for readability research focused on the individual reader. They call on the HCI community to contribute to the growing understanding of readers' needs; to study the interactions between text, user, and task; and to build the tools and interfaces needed to improve reading outcomes for all.
Practical Philosophy of Ai-Assistants, The: An Engineering-Humanities Conversation
The Practical Philosophy of AI-Assistants presents a formal conversation between an AI engineer, Peter, and a humanities researcher, Suman. The book ensures that specialist concepts in AI research are made comprehensible to a humanities researcher, while humanities theories can be easily grasped by an AI engineer.The authors establish ground rules to design an AI-Assistant, that is, an AI system that could act as a personal friend, consultant and confidante for every individual, to be integrated into our daily lives. These rules apply to four large areas of AI development: recognition and identification, communication, explanation, and civility.In discussing these areas, this book provides an accessible account of the current state of AI research, as well as adding nuance to the underpinning assumptions informing the relevant technologies, reflecting on their social implications.The broader ideological objective of The Practical Philosophy of AI-Assistants is captured by the phrase 'practical philosophy', which expresses a commitment to bringing AI development to work towards a good life for all.
Practical Philosophy of Ai-Assistants, The: An Engineering-Humanities Conversation
The Practical Philosophy of AI-Assistants presents a formal conversation between an AI engineer, Peter, and a humanities researcher, Suman. The book ensures that specialist concepts in AI research are made comprehensible to a humanities researcher, while humanities theories can be easily grasped by an AI engineer.The authors establish ground rules to design an AI-Assistant, that is, an AI system that could act as a personal friend, consultant and confidante for every individual, to be integrated into our daily lives. These rules apply to four large areas of AI development: recognition and identification, communication, explanation, and civility.In discussing these areas, this book provides an accessible account of the current state of AI research, as well as adding nuance to the underpinning assumptions informing the relevant technologies, reflecting on their social implications.The broader ideological objective of The Practical Philosophy of AI-Assistants is captured by the phrase 'practical philosophy', which expresses a commitment to bringing AI development to work towards a good life for all.
Synthetic Data for Deep Learning
Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? That's where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect. Synthetic Data for Deep Learning begins by tracing the need for and development of synthetic data before delving into the role it plays in machine learning and computer vision. You'll gain insight into how synthetic data can be used to study the benefits of autonomous driving systems and to make accurate predictions about real-world data. You'll work through practical examples of synthetic data generation using Python and R, placing its purpose and methods in a real-world context. Generative Adversarial Networks (GANs) are also covered in detail, explaining how they work and their potential applications. After completing this book, you'll have the knowledge necessary to generate and use synthetic data to enhance your corporate, scientific, or governmental decision making. What You Will LearnCreate synthetic tabular data with R and PythonUnderstand how synthetic data is important for artificial neural networksMaster the benefits and challenges of synthetic dataUnderstand concepts such as domain randomization and domain adaptation related to synthetic data generationWho This Book Is ForThose who want to learn about synthetic data and its applications, especially professionals working in the field of machine learning and computer vision. This book will also be useful for graduate and doctoral students interested in this subject.
Hypergraph Computation
This open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complexthan pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate thehigh-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.
Neural Networks
This book is all about how to use deep learning for computer vision using convolutional neural networks. These are the state of the art when it comes to image classification and they beat vanilla deep networks at tasks like mnist.In this course we are going to up the ante and look at the streetview house number (svhn) dataset - which uses larger color images at various angles - so things are going to get tougher both computationally and in terms of the difficulty of the classification task. Benefits of reading this book that you're not going to find anywhere else: Introduction to neural networksStructures of neural networksBuilding a neural networkThe construction of artificial neuronsThe biological neurons modelHow they workThe capabilities of neural network structureOrganizing your networkDeep learning is a new concept that has emerged since the 2000s. While deep learning is new to it, this is not the case with artificial neural networks, a concept on which deep learning is based. We hear about the first artificial neuron in 1943 when warren mcculloch and walterpitts published their first mathematical and computer model of the biological neuron: the formal neuron. The formal neuron is directly inspired by the biological neuron.
Hypergraph Computation
This open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complexthan pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate thehigh-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.
Automated Alert System for Drowsiness Detection Using Image Mining Techniques
Image mining is one of the growing field in all research domain. Various research workis done in the research data. Image mining study is used to analyzing and detecting theimage data. Image mining is larger than an expansion of image domain. The variousbranches of image mining are computer-vision, image-mining, image-acquisition, imageretrieval, data-mining, machine-learning, database and artificial-intelligence. Image mining techniques main key areas are image information extractions, substance base image recovery, capture recovery, video chain study, adjust detection, reproduction knowledge and object detection. Image stored in numeric database and relational database. Primary storage spacecapacity data is needs low storage space. Further image information is being gathered withStandard statistics. There is extremely considerable knowledge of Image\pictureinformation that might be learn a new and understanding knowledge of images..Image is pre-process image data within a figure of function of image mining.Picture information is using in our everyday life like C-T image sets, Cardio-gramimage sets, MRI image sets, Mammogram image sets, X-ray image sets and UltrasoundImage sets etc. These images occupy a large numbers of information is stored in variousplace. Image mining might find out this image or object information's along with pattern ofimages. Image mining is classified into double major guidelines image area.
Clear-cut as the words
Clear-cut as the words is a 'novel' written in a unique process of artificially intelligent conservation and destruction. The algorithm givethm and the algorithm takethm away. If you enjoy the writing of W.G. Sebald, Eric Newby, Leo Tolstoy, Erich Maria Remarque, Svetlana Alexievich, F. Scott Fitzgerald, Jordan Peterson, Amos Oz, or Loren Eiseley then you will probably hate this 'novel'.As much as it is a cautionary tale of what not to do with AI it is also the story of a second-generation migrant's son who visits his mother's nursing home for one last parting visit against his mother's wishes. As she nears the end of her life, she starts to recall bits and pieces of her early years, which had been kept secret until then and included experiences throughout both World Wars and unspeakable tragedies. Having lost his wife and kid and feeling abandoned, the son takes solace in his uncomfortable but strongly felt connection to the nurse who cares for his mother.Memory and inter-generational trauma are explored in depth, as well as the impact that a long-kept secret may have on the present, in this thought-provoking tome. An algorithm-aided ambiguity and compassion concerning guilt and forgiveness, filial ties, moral issues, care and agency, knowledge and generational repetitions are the hallmarks of 'Lieblich's' 'writing' in this book. This 'novel' is also a tale of love and an examination of complicated end-of-life concerns.
Image and Vision Computing
This book constitutes the proceedings of the 37th International Conference, IVCNZ 2022, which took place in Auckland, New Zealand, in November 2022.The 37 papers (14 accepted for long oral presentation, 23 for short oral presentation) included in this volume were carefully reviewed and selected from 79 submissions. The conference presents papers on all aspects of computer vision, image processing, computer graphics, virtual and augmented reality, visualization, and HCI applications related to these fields.
Test Automation Engineering Handbook
Understand test automation and implement it in Web, Mobile, and APIs effectivelyKey Features: Learn how to automate your tests with the help of practical examplesUnderstand how to bridge the gap between testing and test automationExplore test automation strategies for different platformsBook Description: This book helps you build a better understanding of test automation and aids in bridging the gap between testing and test automation.The book has been divided into three sections with the first section focusing on preparing you for testing and test automation fundamentals. By the end of this section, you'll have an understanding of some common automation terms, definitions, and roles. The second section covers the practical implementation of test automation for mobile, web, API and performance. The third section will help you understand how test automation works with CI/CD, and explore the common issues and pitfalls when executing test automation.By the end of this book, you'll have a better understanding of automation, addressing the common pain points and best practices around test automation.What You Will Learn: Gain a solid understanding of test automationUnderstand how automation fits into a test strategyExplore essential design patterns for test automationDesign and implement highly reliable automated testsUnderstand issues and pitfalls when executing test automationDiscover the commonly used test automation tools/frameworksWho this book is for: This book is for manual testers who want to enter the field of test automation and developers who want to learn more about test automation.
The Complete Works of Ralph Waldo Emerson
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Overcoming It Complexity
The cloud promises cost savings, agility, and more. But the increasing complexity of modern IT systems often prevents businesses from realizing the outcomes they sought by moving to the cloud in the first place. At the core of this complexity is technical debt. Ad hoc decisions, traditional approaches, and "quick and dirty" solutions add up to fragile, more complex systems (and organizations)--reducing the pace of change, driving up costs, and degrading security. To succeed in the cloud, you first have to manage the problems IT complexity creates. This practical guide will help. If you're tasked with designing, delivering, or approving IT systems that support business growth, this book will teach you the principles and strategies you need to break out of silos, reassess traditional thinking, provide the business a better competitive position, and achieve cloud success across the company. You'll learn: How to assess your current IT environment to identify complexity-centered risks How to structure cross-functional teams to reduce friction points How to create a framework for IT investments that's aligned with your business goals How to measure your outcomes for continued success
Time Series Algorithms Recipes
This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book, you will have a foundational understanding of various concepts relating to time series and its implementation in Python. What You Will LearnImplement various techniques in time series analysis using Python.Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting Understand univariate and multivariate modeling for time series forecastingForecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory) Who This Book Is ForData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.
Innovations in Intelligent Computing and Communication
This book contains the papers presented at the First International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021, held in Bhubaneswar, Odisha, India, in December, 2022. The 31 full papers presented were thoroughly reviewed and selected from 78 submissions. They are divided in three tracks with the following topics: ​Intelligent Computing; Communications; and Machine Learning and Data Analytics.
Beginner’s Guide to Streamlit with Python
This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. What You Will Learn How to start developing web applications using Streamlit What are Streamlit's components Media elements in Streamlit How to visualize data using various interactive and dynamic Python librariesHow to implement models in Streamlit web applicationsWho This Book Is ForProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.
Development of Intelligent Framework. Image Steganalysis using Deep Level Features
Master's Thesis from the year 2020 in the subject Computer Sciences - Artificial Intelligence, grade: 9.30, language: English, abstract: The application of DL techniques in steganography has greatly increased the efficiency of steganographic concealment systems, leading to a substantial improvement in safety risks. To counter this, the researchers shifted to steganalysis, the method of detecting steganographic material. In practice, steganalysis is being used in a security framework that operates like a spam-filter to prevent the transmission of malicious steganographic content through networks. Newer steganalysis methods, however, have shown promising results, but they remain both fairly inefficient and non-robust. Steganography is the mechanism by which data are hidden inside an ordinary (non-secret) file to evade detection. Although encryption is intended to hide data information, steganography is intended to conceal data existence. Steganography can also hide new form of communication by hiding the existence of data, and thus provide behavioral protection. Steganography provides behavioral protection and plays a critical role in safeguarding the privacy of information. Although steganographic concealment systems are routinely used for benign activities, bad actors can also use them to transmit malicious information using ordinary files such as photographs, thus posing a risk to security. Because current network defenses do not search images for steganographic content, the transmission of malicious steganographic content cannot be effectively blocked. Hackers may thus use steganography to transfer vulnerabilities or other compromising data in an untraceable fashion through networks.
