This book presents select proceedings of the International Conference on Future Learning Aspects of Mechanical Engineering (FLAME 2020). This book, in particular, focuses on characterizing materials using novel techniques. It covers a variety of advanced materials, viz. composites, coatings, nanomaterials, materials for fuel cells, biomaterials among others. The book also discusses advanced characterization techniques like X-ray photoelectron, UV spectroscopy, scanning electron, atomic power, transmission electron and laser confocal scanning fluorescence microscopy, and gel electrophoresis chromatography. This book gives the readers an insight into advanced material processes and characterizations with special emphasis on nanotechnology.

Rapid advances in microelectronic integration and the advent of Systems-on-Chip have fueled the need for high-level synthesis, i.e., an automated approach to the synthesis of hardware from behavioral descriptions.
SPARK: A Parallelizing Approach to the High - Level Synthesis of Digital Circuits presents a novel approach to the high-level synthesis of digital circuits -- that of parallelizing high-level synthesis (PHLS). This approach uses aggressive code parallelizing and code motion techniques to discover circuit optimization opportunities beyond what is possible with traditional high-level synthesis. This PHLS approach addresses the problems of the poor quality of synthesis results and the lack of controllability over the transformations applied during the high-level synthesis of system descriptions with complex control flows, that is, with nested conditionals and loops.
Also described are speculative code motion techniques and dynamic compiler transformations that optimize the circuit quality in terms of cycle time, circuit size and interconnect costs. We describe the SPARK parallelizing high-level synthesis framework in which we have implemented these techniques and demonstrate the utility of SPARK's PHLS approach using designs derived from multimedia and image processing applications. We also present a case study of an instruction length decoder derived from the Intel Pentium-class of microprocessors. This case study serves as an example of a typical microprocessor functional block with complex control flow and demonstrates how our techniques are useful for such designs.
SPARK: A Parallelizing Approach to the High - Level Synthesis of Digital Circuits is targeted mainlyto embedded system designers and researchers. This includes people working on design and design automation. The book is useful for researchers and design automation engineers who wish to understand how the main problems hindering the adoption of high-level synthesis among designers.

This book initiates with an introduction to polymeric materials, followed by various classifications and properties of polymeric implant material including various development methods of polymeric materials and their characterization techniques. An overview of various toxicology assessments of polymeric materials and polymeric materials for drug delivery system is also included. Design and Analysis of Polymeric Materials based Components using Ansys Software along with polymeric materials for additively manufactured artificial organs is also discussed. Features: Addresses assessment of polymeric materials in biomedical sciences including classification, properties, and development of polymeric implants. Covers various topics in the field of tissue regeneration. Discusses the biocompatibility, toxicity, and biodegradation of polymeric materials. Explores wide scale characterization to study the effect of inclusion size on mechanical properties of polymeric materials. Reviews limitations and future directions on polymeric material with emphasis on biocompatibility. This book is aimed at graduate students and researchers in biomaterials, biomedical engineering, composites, and polymers.

Explores different processing methods of green and eco-friendly composites Discusses development and optimization of green nanocomposites for sustainable manufacturing Collates modern green and eco-friendly composites research from theory to application Covers hybridization of reinforced fibers on the performance of green and eco-friendly composites Analyses and discusses calculation of carbon footprint and Life Cycle Assessment of composite materials

This book presents select proceedings of the International Conference on Future Learning Aspects of Mechanical Engineering (FLAME 2020). This book, in particular, focuses on characterizing materials using novel techniques. It covers a variety of advanced materials, viz. composites, coatings, nanomaterials, materials for fuel cells, biomaterials among others. The book also discusses advanced characterization techniques like X-ray photoelectron, UV spectroscopy, scanning electron, atomic power, transmission electron and laser confocal scanning fluorescence microscopy, and gel electrophoresis chromatography. This book gives the readers an insight into advanced material processes and characterizations with special emphasis on nanotechnology.

Rapid advances in microelectronic integration and the advent of Systems-on-Chip have fueled the need for high-level synthesis, i.e., an automated approach to the synthesis of hardware from behavioral descriptions.
SPARK: A Parallelizing Approach to the High - Level Synthesis of Digital Circuits presents a novel approach to the high-level synthesis of digital circuits -- that of parallelizing high-level synthesis (PHLS). This approach uses aggressive code parallelizing and code motion techniques to discover circuit optimization opportunities beyond what is possible with traditional high-level synthesis. This PHLS approach addresses the problems of the poor quality of synthesis results and the lack of controllability over the transformations applied during the high-level synthesis of system descriptions with complex control flows, that is, with nested conditionals and loops.
Also described are speculative code motion techniques and dynamic compiler transformations that optimize the circuit quality in terms of cycle time, circuit size and interconnect costs. We describe the SPARK parallelizing high-level synthesis framework in which we have implemented these techniques and demonstrate the utility of SPARK's PHLS approach using designs derived from multimedia and image processing applications. We also present a case study of an instruction length decoder derived from the Intel Pentium-class of microprocessors. This case study serves as an example of a typical microprocessor functional block with complex control flow and demonstrates how our techniques are useful for such designs.
SPARK: A Parallelizing Approach to the High - Level Synthesis of Digital Circuits is targeted mainly to embedded system designers and researchers. This includes people working on design and design automation. The book is useful for researchers and design automation engineers who wish to understand how the main problems hindering the adoption of high-level synthesis among designers.

Learn how to bring your data to life with this hands-on guide to visual analytics with Tableau Key Features Master the fundamentals of Tableau Desktop and Tableau Prep Learn how to explore, analyze, and present data to provide business insights Build your experience and confidence with hands-on exercises and activities Book DescriptionLearning Tableau has never been easier, thanks to this practical introduction to storytelling with data. The Tableau Workshop breaks down the analytical process into five steps: data preparation, data exploration, data analysis, interactivity, and distribution of dashboards. Each stage is addressed with a clear walkthrough of the key tools and techniques you'll need, as well as engaging real-world examples, meaningful data, and practical exercises to give you valuable hands-on experience. As you work through the book, you'll learn Tableau step by step, studying how to clean, shape, and combine data, as well as how to choose the most suitable charts for any given scenario. You'll load data from various sources and formats, perform data engineering to create new data that delivers deeper insights, and create interactive dashboards that engage end-users. All concepts are introduced with clear, simple explanations and demonstrated through realistic example scenarios. You'll simulate real-world data science projects with use cases such as traffic violations, urban populations, coffee store sales, and air travel delays. By the end of this Tableau book, you'll have the skills and knowledge to confidently present analytical results and make data-driven decisions. What you will learn Become an effective user of Tableau Prep and Tableau Desktop Load, combine, and process data for analysis and visualization Understand different types of charts and when to use them Perform calculations to engineer new data and unlock hidden insights Add interactivity to your visualizations to make them more engaging Create holistic dashboards that are detailed and user-friendly Who this book is forThis book is for anyone who wants to get started on visual analytics with Tableau. If you're new to Tableau, this Workshop will get you up and running. If you already have some experience in Tableau, this book will help fill in any gaps, consolidate your understanding, and give you extra practice of key tools.

Metaphysical Anatomy Technique Volume 2 explains the core foundation and healing technique behind Metaphysical Anatomy Volume 1 which describes step-by-step guide for identifying the psychosomatic pattern related to 679 medical conditions.

These conditions can be activated by circumstances in your present life, your ancestry, conception, womb, birth trauma, childhood or adult life. Volume 2 teaches you the foundation of Volume 1 including a powerful healing technique.

Design, process, and analyze large sets of complex data in real time About This Book * Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm * Implement strategies to solve the challenges of real-time data processing * Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn * Explore big data technologies and frameworks * Work through practical challenges and use cases of real-time analytics versus batch analytics * Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm * Handle and process real-time transactional data * Optimize and tune Apache Storm for varied workloads and production deployments * Process and stream data with Amazon Kinesis and Elastic MapReduce * Perform interactive and exploratory data analytics using Spark SQL * Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with "Amazon Kinesis" for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.

About This Book Develop a set of common applications and solutions with Neo4j and Python Secure and deploy the Neo4j database in production A step-by-step guide on implementing and deploying interactive Python-based web applications on graph data model Who This Book Is ForIf you are a Python developer and want to expand your understanding of Python-based web applications over Neo4j graph data models, this is the book for you. What You Will Learn Understand the licensing and installation of the Neo4j database and work with its various tools and utilities Learn the intricacies of Cypher as a graph query language Work with Cypher to create and modify graph data models Integrate Python and Neo4j using Py2neo Develop REST-based services over social network data using Flask and object graph models over Neo4j Integrate Django-based web applications over graph data models using Neomodel Explore different deployment models and their applicability with existing applications In DetailPy2neo is a simple and pragmatic Python library that provides access to the popular graph database Neo4j via its RESTful web service interface. This brings with it a heavily refactored core, a cleaner API, better performance, and some new idioms. You will begin with licensing and installing Neo4j, learning the fundamentals of Cypher as a graph query language, and exploring Cypher optimizations. You will discover how to integrate with various Python frameworks such as Flask and its extensions: Py2neo, Neomodel, and Django. Finally, the deployment aspects of your Python-based Neo4j applications in a production environment is also covered. By sequentially working through the steps in each chapter, you will quickly learn and master the various implementation details and integrations of Python and Neo4j, helping you to develop your use cases more quickly.