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"The definitive market leader and decisive text for the field, Michael Barresi's Developmental Biology includes new features and active learning approaches to help students and instructors succeed, including electronic interviews, videos, tutorials, and case studies. Built on the excellent writing, accuracy, and enthusiasm of the original text, the new edition features on line resources that dynamically convey ideas and concepts, and creates an experience that meets the desires of those teaching Developmental Biology to a new generation"-- Provided by publisher.

• On some de novo type approaches to fuzzy decision making, optimization and control: an application to sustainable regional development
• Summarization of bimodal information from large data sets
• Multi-attribute decision making in material selection under Z-valued information
• Decision making on students performance estimation
• Decision making on selection of Ferritic stainless steel
• Forecasting demand in the commodity market of food products using neural networks
• Estimation of countries economic development by using Z-number theory
• Optimal implication-based fuzzy control system for a steam generator
• Prediction of energy consumption in residential buildings using Type-2 fuzzy wavelet Neural Network
• Analysis of knee osteoarthritis grading using Deep Learning
• Solving problem of unit commitment by exchange market algorithm and dynamic planning method
• Regular Identification Algorithms for a Special Class of Neuro-Fuzzy Models ANFIS.

The general scope of the book covers diverse areas of fuzzy systems, soft computing, AI tools such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of Soft Computing, Neuro-Fuzzy Technology, Intelligent Control, Deep Learning-Machine Learning, Fuzzy Logic in Data Analytics, Evolutionary Computing, Fuzzy logic and Artificial Intelligence in Engineering, Social Sciences, Business, Economics, Material Sciences, and others. This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2022, held in Budva, Montenegro, on August 26-27, 2022. This is a useful guide for academics, practitioners, and graduates in fields of fuzzy logic and soft computing. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.

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.

• Influence of COVID-19 Confinement and Pandemic on the Academic Performance of Students
• 3D with Artificial Intelligence Technology Contributes Science and Technology Education Development
• Enhancing Engineer and Engineering Perception Through Video Design in STEM Education
• Circulation as a Concept Graphically Represented in a Game-like Manner to Support the Design Process in Architecture
• The Blockchain Technology Applications in Higher Education
• Undergraduate Engineering Laboratories: A Study Exploring Laboratory Objectives and Student Experiences at an Irish University.

This volume of the series Proceedings in Engineering Mechanics - Research, Technology and Education provides selected papers presented at the 3rd International Conference on Science and Technology Education, held in Porto, Portugal, October 6-7, 2022. From the various topics covered at this conference, individual contributions have been selected for this book. These contributions focus on learning mechanisms, learning systems and assessment. The book presents the latest trends, new methods and ideas in science and technology education. An essential resource for lecturers and tutors working in this field.

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.

• 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.
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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.

• Frontmatter
• Theory. Pioneering History
• Seismic Wave Equation
• Forward Problem of Tomography
• Inverse Problem
• Subsurface Parameterization
• Seismic Travel Time Tomography
• Seismic Full Waveform Tomography
• Applications. Tomography of Synthetic Seismic Data
• Travel Time Tomography of Seismic Data
• Full Waveform Tomography of Seismic Data
• Advanced Seismic Processing Using Tomographic Results
• Future Scope
• References
• Index

"The seismic method is one of the most promising geophysical methods that can help to explore the earth's interior. Numerous technology developments have been introduced in seismic methods over the decades for either to understand or to use the full recorded seismic data from the field. Seismic tomography is one of the seismic imaging techniques to delineate the subsurface linked with structures and numerical values of different physical parameters such as the seismic velocity, density, etc."-- Provided by publisher.

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)

Adobe Acrobat DC Classroom in a Book, 4th edition uses real-world, project-based learning to cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. For beginners and experienced users alike, you can follow the book from start to finish or choose only those lessons that interest you.

Discover Adobe Acrobat's most important features and advanced functions that will help you to find easier ways to work Purchase of the print or Kindle book includes a free PDF eBook Key Features Make better use of Adobe Acrobat with this all-in-one reference guide for users in all industries and professions Build confidence by integrating Acrobat functions into day-to-day business tasks Understand issues that go beyond PDF, such as legal implications of accessibility compliance, document security, and copyright protection Book Description Adobe Acrobat can help you solve a wide variety of problems that crop up when you work with PDF documents on a daily basis. The most common file type for business and communication, this compact portable document format is widely used to collect as well as present information, as well as being equipped with many lesser-known features that can keep your content secure while making it easy to share. From archive features that will keep your documents available for years to come to features related to accessibility, organizing, annotating, editing, and whatever else you use PDFs for, Acrobat has the answer if you know where to look. Designed for professionals who likely already use Adobe Acrobat Pro, this guide introduces many ideas, features, and online services, sorted and organized for you to easily find the topics relevant to your work and requirements. You can jump to any chapter without sifting through prior pages to explore the tools and functions explained through step-by-step instructions and examples. The information in some chapters may build on existing knowledge, but you are not expected to have an advanced level of prior experience. By the end of this book, you'll have gained a solid understanding of the many capabilities of PDFs and how Acrobat makes it possible to work in a way that you will never miss good old ink and paper. What you will learn Use Adobe Acrobat Pro efficiently through shortcuts and preferences Expand your knowledge of the functions that you already use Understand the connection between PDFs, Acrobat, and other applications Find out about unique settings in Adobe InDesign to create high-quality fully featured PDFs Address legal concerns for information published in a digital format Confidently move away from the use of ink and paper and help preserve physical resources Who this book is for This book is for anyone working with PDFs on a daily basis, including skilled professionals such as analysts, administrators, architects, engineers, scientists, lawyers, and anyone who can be described as communications workers, including but not limited to artworkers, researchers, technical writers, and accessibility workers who routinely work with PDF and some version of Acrobat.

AI-powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. In this course about developing advanced chatbots with deep learning, we will understand their applications and build from scratch using deep learning with Python The course begins with a brief overview and the fundamentals of deep learning for chatbots. We will understand and compare conventional chatbots with deep learning-based chatbots. Then, we will explore self-learning chatbots, including generative chatbots and retrieval chatbots. You will learn more about deep learning-empowered chatbot features and compare and distinguish the abilities of conventional chatbots and self-learning chatbots in real action. We will focus on chatbot development with deep learning, tokenization, setting up an Encoder-Decoder, implementing RNN-based model development, and finally, training, testing, and validating the chatbot we developed. Upon completing this course successfully, you will relate concepts and understand theories of chatbots in various domains, understand and implement deep learning models for building real-world chatbots, and evaluate deep learning-based chatbot models. What You Will Learn Relate the concepts and theories for chatbots in various domains Compare conventional chatbots with deep learning-based chatbots Understand deep learning algorithms for chatbots Implement deep learning models for building real-world chatbots Learn about tokenization and setting up an encoder-decoder Implement recurrent neural network-based model development Audience This course is designed for individuals looking to advance their skills in applied deep learning, acquire knowledge regarding the relationships of data analysis with deep learning, wish to build customized chatbots for their applications, learn to implement deep learning algorithms for chatbots, and are passionate about rule-based and self-learning chatbots. Deep learning practitioners/scholars working on chatbot concepts would benefit from this course. No prior knowledge of chatbots, deep learning, data analysis, or mathematics is needed. Basic to intermediate Python knowledge is required. About The Author AI Sciences: AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences. Their courses have successfully helped more than 100,000 students master AI and data science.

• Introduction to SoC FPGAs.- Hello World.- Software Control of LEDs via Registers.- Audio Codec and headphone driver.- FIR Filtering.- Data Movements using Direct Memory Access (DMA).- Frequency Domain Processing using FFTs.- Time Domain Sound Effects Processors.- Frequency Domain Sound Effects Processor.- Hearing Aid.- Multiple Audio Personalities.
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This textbook teaches students techniques for the design of advanced digital systems using System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs). The author demonstrates design of custom hardware components for the FPGA fabric using VHDL, with implementation of custom hardware-software interfaces. Readers gain hands-on experience by writing programs and Linux device drivers in C to interact with custom hardware. This textbook enables laboratory experience in the design of custom digital systems using SoC FPGAs, emphasizing computational tasks such as digital signal processing, audio, or video processing.
(source: Nielsen Book Data)