%{search_type} search results

• Elements of time scale calculus
• Elements of fractional dynamic calculus on time scales
• Linear inequalities for Riemann-Liouville fractional delta integral operator
• Fractional Young and Holder inequalities
• Fractional inequalities for convex functions
• Opial-type inequalities
• Chebyshev-type inequalities
• Hardy-type fractional inequalities
• Reverse Hardy-type fractional inequalities
• Inequalities for generalized Riemann-Liouville fractional integrals
• Some inequalities
• Jensen inequalities.

Building great software requires outstanding teamwork across multiple disciplines. All teams and participants need to align behind clear goals that deliver real value (outcomes), not just lots of features (output). Sprint Goals are the most powerful tool Scrum/Agile teams have to pursue high-value outcomes, but many Scrum Teams avoid them, misuse them, or struggle to apply them. Succeeding with Sprint Goals covers everything you need to define, create, and execute on Sprint Goals that deliver outstanding value to customers and the business. Leading Scrum practitioner Maarten Dalmijn bridges the gap between theory and practice, offering a fresh, unique, and cohesive perspective on the Scrum framework that will be valuable to every Product Owner, Product Manager, Scrum Master, Agile coach, and technology executive. You will learn why Sprint Goals are so important, how to use them throughout the Sprint and at Review and Retrospective, how to overcome common obstacles to success, and how to use them to build high-performing teams. As Dalmijn presents critical Scrum and product management fundamentals through the lens of the Sprint Goal, he helps you move your entire organization from low-value "feature factories" to high-value outcomes

• Introduction
• Preparing the Development Environment
• Brief Introduction to HTML
• Brief Introduction to CSS, JavaScript, and Bootstrap
• Some C# Fundamentals
• Middleware, Services, and an Introduction to Dependency Injection
• Routing, Models, and Controllers
• Core on Controllers
• Razor Views, Razor Engine, and Model Binding
• Server Validation
• Persistent Data: Entity Framework (core) and Dependency Injection Revisited
• Consistent Look: Layouts, Friendly Error Pages, and Environments
• Working with Images
• Authentication
• References

This book introduces a simplified approach to web application development using the open-source ASP .Net Core MVC framework. Readers will learn to implement web applications using the following languages and frameworks: HTML, JavaScript, CSS, Bootstrap, C#, ASP .Net, and Entity Framework Core. In addition, this book addresses how to build a web application to create user accounts, store data in a database, manipulate data, and how to allow controlled access to certain parts of the application functionality. The author also covers both client-side and server-side development and the use of an object relational mapper to work with persistent data (using a database). Topics include: models, views, controllers, routing, entity framework core, identity, layouts, dependency injection and services, model binder, among others. This book: Introduces the development of web applications using the open-source ASP .Net Core MVC framework Implements web applications including HTML, JavaScript, CSS, Bootstrap, C#, ASP .Net, and Entity Framework Core Features client-side development, server-side development, and object relational mapper software

• Introduction and motivation
• Numerical methods for 1D hyperbolic problems
• Edge-based flux correction for continuous Galerkin methods
• Element-based algorithms for continuous Galerkin methods
• Flux and slope limiting for discontinuous Galerkin methods
• High-order finite elements and time discretizations
• Analysis of finite volume methods for hyperbolic problems
• Analysis of finite element schemes for hyperbolic problems.

• Local moves on knots : for beginners
• Four-dimensional space R⁴
• Local moves in higher-dimensional space : for beginners
• Knotted-objects in 4-space and beyond
• Local moves on high-dimensional knots and related invariants
• The Alexander and Jones polynomials of one-dimensional links in R³
• Local moves and knot polynomials in higher dimensions
• Important topics in knot theory.

Work on 10 practical projects, each with a blueprint for a different machine learning technique, and apply them in the real world to fight against cybercrime Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how to frame a cyber security problem as a machine learning problem Examine your model for robustness against adversarial machine learning Build your portfolio, enhance your resume, and ace interviews to become a cybersecurity data scientist Book Description Machine learning in security is harder than other domains because of the changing nature and abilities of adversaries, high stakes, and a lack of ground-truth data. This book will prepare machine learning practitioners to effectively handle tasks in the challenging yet exciting cybersecurity space. The book begins by helping you understand how advanced ML algorithms work and shows you practical examples of how they can be applied to security-specific problems with Python - by using open source datasets or instructing you to create your own. In one exercise, you'll also use GPT 3.5, the secret sauce behind ChatGPT, to generate an artificial dataset of fabricated news. Later, you'll find out how to apply the expert knowledge and human-in-the-loop decision-making that is necessary in the cybersecurity space. This book is designed to address the lack of proper resources available for individuals interested in transitioning into a data scientist role in cybersecurity. It concludes with case studies, interview questions, and blueprints for four projects that you can use to enhance your portfolio. By the end of this book, you'll be able to apply machine learning algorithms to detect malware, fake news, deep fakes, and more, along with implementing privacy-preserving machine learning techniques such as differentially private ML. What you will learn Use GNNs to build feature-rich graphs for bot detection and engineer graph-powered embeddings and features Discover how to apply ML techniques in the cybersecurity domain Apply state-of-the-art algorithms such as transformers and GNNs to solve security-related issues Leverage ML to solve modern security issues such as deep fake detection, machine-generated text identification, and stylometric analysis Apply privacy-preserving ML techniques and use differential privacy to protect user data while training ML models Build your own portfolio with end-to-end ML projects for cybersecurity Who this book is for This book is for machine learning practitioners interested in applying their skills to solve cybersecurity issues. Cybersecurity workers looking to leverage ML methods will also find this book useful. An understanding of the fundamental machine learning concepts and beginner-level knowledge of Python programming are needed to grasp the concepts in this book. Whether you're a beginner or an experienced professional, this book offers a unique and valuable learning experience that'll help you develop the skills needed to protect your network and data against the ever-evolving threat landscape.

This book contains accepted papers presented at SOCO 2022 conference held in the beautiful and historic city of Salamanca (Spain), in September 2022. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a thorough peer-review process, the 17th SOCO 2022 International Program Committee selected 64 papers which are published in these conference proceedings and represent an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as machine learning and computer vision in Industry 4.0; time series forecasting in industrial and environmental applications; optimization, modeling, and control by soft computing techniques; soft computing applied to renewable energy systems; preprocessing big data in machine learning; tackling real-world problems with artificial intelligence. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the program committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help.

This resource presents a series of compelling exercises of increasing difficulty in formal languages, automata and computation, key topics in theoretical computer science. Comprehensive solutions are provided for all problems, making it a perfect resource for self-study, as well as a source of examples and problems for instructors.

Kubernetes is a trending topic among engineers, CTOs, CIOs, and other technically sound professionals. Due to its proliferation and importance for all cloud technologies, DevOps engineers nowadays need a solid grasp of key Kubernetes concepts to help their organization thrive. This book equips you with all the requisite information about how Kubernetes works and how to use it for the best results. You'll learn everything from why cloud native is important to implementing Kubernetes clusters to deploying applications in production. This book takes you on a learning journey, starting from what cloud native is and how to get started with Kubernetes in the cloud, on-premises, and PaaS environments such as OpenShift. Next, you'll learn about deploying applications in many ways, including Deployment specs, Ingress Specs, and StatefulSet specs. Finally, you'll be comfortable working with Kubernetes monitoring, observability, and security. Each chapter of 50 Kubernetes Concepts Every DevOps Engineer Should Know is built upon the previous chapter, ensuring that you develop practical skills as you work through the code examples in GitHub, allowing you to follow along while giving you practical knowledge. By the end of this book, you'll be able to implement Kubernetes in any environment, whether it's an existing environment, a greenfield environment, or your very own lab running in the cloud or your home.

• Part I. Bigdata Services
• Chapter 1. Modelling Cognitive Scores for Alzheimer's Disease Progression Prediction Using Longitudinal MRI D
• Chapter 2. Various Physiological Methods to Identify Sleep Onset
• Chapter 3. IoT Adoption: Challenges among Small and Medium Enterprises
• Chapter 4. Performance evaluation of Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Cloud Service Provider
• Part II. Bigdata and Security
• Chapter 5. Online Covid-19 Risk Analysis System for Early Detection of Possible Infection
• Chapter 6. Application of Multi focused and Multi Modal image fusion using Guided Filter on Bio-Medical Images
• Chapter 7. Experimental Comparative Analysis on Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) on Aspect Level Sentiment Analysis
• Part III. Bigdata Emerging Applications
• Chapter 8. Data hiding in binary images for secret and secure communication using decision tree
• Chapter 9. Private and Secure Blockchain-based mechanism for an Online Voting System
• Chapter 10. AI-Enabled Pregnancy Risk Monitoring and Prediction: A Review
• Chapter 11. Finger Knuckle Print Recognition using Complex Conjugate Feature Vector
• Part IV. Bigdata and Technology
• Chapter 12. What Your Tweets Say about You – A case study of Extraversion and word usage
• Chapter 13. An Automated Cervical Cancer Detection mechanism using Pap smear images
• Chapter 14. A Systematic Literature Review on Data Freshness for reinforcing mutual authentication in Wireless Body Area Networks
• Chapter 15. Detection of Non-Technical Losses in Power Utilities Using Machine Learning
• Part V. Bigdata in Medical Applications
• Chapter 16. A Novel Real Time 3D Object Detection Network in Autonomous Driving using reformed rs-resnet network
• Chapter 17. Solar radiation prediction using the random forest regression algorithm
• Chapter 18. Vehicular Support System for User and Vehicle Accident Prevention.

This book features the proceedings of the 5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2022). The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.

• Foundational Methods Enabling Science in an Integrated Ecosystem.- Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models.- Self-learning Data Foundation for Scientific AI.- Preconditioners for batched iterative linear solvers on GPUs.- Mobility Aware Computation Offloading Model for Edge Computing.- Science and Engineering Applications Requiring and Motivating an Integrated Ecosystem.- Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials.- A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management.- At-the-edge Data Processing for Low Latency High Throughput Machine Learning Algorithms.- Implementation of a framework for deploying AI inference engines in FPGAs.- Systems and Software Advances Enabling an Integrated Science and Engineering Ecosystem.- Calvera: A Platform for the Interpretation and Analysis of Neutron Scattering Data.- Virtual Infrastructure Twins: Software Testing Platforms for Computing and Instrument Ecosystems.- The INTERSECT Open Federated Architecture for the Laboratory of the Future.- Real-Time Edge Processing During Data Acquisition.- Towards a Software Development Framework for Interconnected Science Ecosystems.- Deploying Advanced Technologies for an Integrated Science and Engineering Ecosystem.- Adrastea: An Efficient FPGA Design Environment for Heterogenous Scientific Computing and Machine Learning.- Toward an Autonomous Workflow for Bragg Peak Detection at SNS.- Industrial experience deploying heterogeneous platforms for use in multi-modal power systems design workflows.- Self-Describing Digital Assets and their applications in an Integrated Science and Engineering Ecosystem.- Simulation Workflows in Minutes, at Scale for Next-Generation HPC.- Scientific Data Challenges.- Machine Learning approaches to High Throughput Phenotyping.- SMC 2022 Data Challenge: Summit Spelunkers Solution for Challenge 2.- Usage Pattern Analysis for The Summit Login Nodes.- Finding Hidden Patterns in High Resolution Wind Flow Model Simulations.- Investigating Relationships in Environmental and Community Health: Correlations Of Environment, Urban Morphology, And Socio-Economic Factors In The Los Angeles Metropolitan Statistical Area.- Patterns and Predictions: Generative Adversarial Networks for Neighborhood Generation.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23-25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.
(source: Nielsen Book Data)

• Methods for Analyzing Cognitive Architecture.- Cognitive Resonance and the Architecture Issues of Cognitive Information Systems.- Dyspraxia: an experimental clinical model for the study of the embodied cognition.- Role of Presence, Memory and Spatial Ability in a Desktop Virtual Reality.- Experiences and guidelines for developing 3D VR curricula.
• (source: Nielsen Book Data)

Considering the emergence of artificial intelligence, virtual and augmented reality, 3D video and television, and holography, it is logical that we should also begin to create applications and businesses driven by these technologies. The 12 chapters of Accentuated Innovations in Cognitive Info-Communication focus on the research and development of state-of-the-art information in Cognitive Info-Communication. This interdisciplinary research area has emerged as a synergy between Info-Communication and Cognitive Sciences. It presents a synthetic, holistic combination of coherent technologies that will become increasingly important in the coming decade. It is a teaching and reference guide for VR, robotics, virtual classrooms and institutions, and medicine at the undergraduate and postgraduate levels. The discussed book is an immersive learning experience for students and teachers worldwide. In addition, it applies to other fields such as healthcare, performing arts, and television.
(source: Nielsen Book Data)

4+ Hours of Video Overview Acceptance Testing by Paul Stringer is from the cleancoders.com video series. Learn acceptance testing through these five dynamic episodes. The Magnificent Testing Pyramid Acceptance Test Driven Development - Part 1 Acceptance Test Driven Development - Part 2 Who, Why & When? Architecture, BDD & Adoption: Related Learning Content Video: Clean Code Fundamentals (Clean Coders Video Series) by Robert C. Martin Book: Clean Craftsmanship by Robert C. Martin - Chapter 8: Acceptance Tests Live Course: Advanced Test-Driven Development by Robert C. Martin Episode Descriptions The Magnificent Testing Pyramid: Where do Acceptance Tests fit? In this episode, you'll develop definitive understanding of the different layers of the pyramid, the different names, and meanings, what they're all for, and how to apply this technical discipline effectively. The episode covers Unit, Functional, Component, Acceptance System & UI tests to unravel the mysteries of the pyramid. With this episode, you'll see how Acceptance Tests turn out to be completely unique from all other tests in ONE very important way and have all the foundations in place to delve deeper into the specifics of Acceptance Testing in the rest of this series. Acceptance Test Driven Development - Part 1: This episode revisits the origins of Acceptance Testing. You'll learn about the breakthrough HP-35 pocket calculator which inspired the first example for how to implement the practice and see the very first stages of this development process. We'll be building our own HP-35 from scratch using the latest fang-dangled app technologies and the examples and requirements from the original HP-35's Quick Reference Guide! And what? You have in this episode Uncle Bob himself sharing how he discovered Acceptance Testing and how it provided the inspiration for him to create 'FitNesse' one of the first Acceptance Testing tools - You don't want to miss this! Acceptance Test Driven Development - Part 2: This episode picks up from where you left off in Part 1. You will continue to apply the practice of "Acceptance Test Driven Development" (ATDD) bringing to life HP-35. We put in place the first arithmetic features with development 'driven' by the quick reference card from an actual HP-35. In this episode. You'll see in fine detail how acceptance tests, fixtures, unit tests and software all come together in a step-by-step walkthrough of ATDD in action. Along the way, watch how Acceptance Tests are the thing that saves Paul from creating bugs in the code. It finishes up with a completed 'rudimentary' YET fully functional text-based user interface and early automated test regression suite capturing all the important business details of what the software should do. This episode is key to seeing how Acceptance Testing practically helps developers get the software right earlier by bridging the detailed gap between business & developer - from the get-go. Who, Why & When? When exactly these 'detailed' requirements should get written on a project? How detailed they should be? Where do they belong in the process and WHO exactly should be writing them? In this episode, we move on from the development side of Acceptance Test-Driven Development and turn to the fundamentals of how these 'requirements' get written in the first place. We'll consider the impact this 'additional' work might have on our team's velocity and how it actually helps planning and the accuracy of our estimates bringing greater predictability through the 'shifting left' of the QA process. Enjoy the chance to be a fly-on-the-wall, watching along as our intrepid team wrestle with the process of writing up-front new requirements specific enough and through example, for the development team to carry on the work of developing their HP-35 calculator. Architecture, BDD & Adoption: When is Acceptance Testing is worth the effort & when it's not! In this episode, Paul shares his own experiences with the adoption of Acceptance Testing and some things you can do to improve your chances of success including the importance of a SOLID software design and architecture when adopting Acceptance Tests. We'll check in on a close cousin of Acceptance Testing: BDD, and see where the two approaches overlap, actual differences between them, what problems they solve and which is right for you. The episode finishes it up by considering the kinds of projects where Acceptance Testing is valuable and reflects on some famous examples of software that went wrong owing to missing requirements and not bugs. You'll get a few last tips as to how to assess your own projects to see if they're likely to benefit from adopting Acceptance Testing. If you decide that Acceptance Tests might be right for your team, Paul proposes his own 3 laws of Acceptance Testing to guide your implementation. And finally, catch up with the team as they put the finishing touches to their HP-35 Calculator and see it all come together (including those pesky UI Tests!!) About Paul Stringer Paul started using his first computer, an Apple ][ in 1983. This began a programming journey that included all things from Basic to Swift. Paul has 20 years of development experience, working with technology startups and enterprises. He continues a passion for all things agile and clean as a lead iOS engineer for UK technology consultants 'Equal Experts'. About Clean Coders Clean Coders is the leading producer of instructional videos for software professionals, taught in a way that both educates and entertains developers. Founded in 2010 by Robert "Uncle Bob" Martin and Micah Martin, Clean Coders has expanded to include a myriad of authors teaching an ever-increasing array of subject matters pertaining to clean code. Our training videos have inspired countless viewers to become the best developers they can be. cleancoders.com.

Most organizations put more resources toward identification, protection, and detection rather than their ability to respond to and recover from a cyber breach, leaving themselves vulnerable. But because companies can’t protect against every new cyberattack, it’s critical that they reduce the potential impact by putting more focus on cyber resilience. The authors describe how leaders can apply seven biology-inspired adaptive design principles to become more resilient against cyberattacks.

This compendium discusses the adaptive enterprise architecture (AEA) as information to support decisions and actions for desired efficiency and innovation (outcomes and impacts). This comprehensive information-driven approach uses data, analytics, and intelligence (AI/ML) for architecting intelligent enterprises.The unique reference text includes practical artefacts and vivid examples based on both practice and research. It benefits chief information officers, chief data officers, chief enterprise architects, enterprise architects, business architects, information architects, data architects, and anyone who has an interest in adaptive and digital enterprise architecture.
(source: Nielsen Book Data)