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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.
This book offers an overview of the clinical applications of PET/MR imaging through a case-based format. Hybrid PET/MRI provides functional and anatomical information via one setting offering superior imaging quality with lower radiation dose being administered to the patient. The cases in this book focus on the use of this technique in the diagnosis of oncologic, neurologic, cardiovascular, infectious and inflammatory, and pediatric diseases. Each case is presented with the patient history, protocols, interpretation of findings, and pearls and pitfalls accompanied by high quality PET/MR images. The major strength of this book is the discussion of both MRI and PET findings pertinent to each particular case. It expands the discussion of oncologic applications of this modality through a variety of cases that highlight staging, treatment response, and follow up. Illustrating a spectrum of PET/MRI clinical applications, PET/MR Imaging: A Case-Based Approach is a valuable resource for radiologists, nuclear medicine physicians, and residents.
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.
Perhaps nothing characterizes the inherent heterogeneity in embedded sys tems than the ability to choose between hardware and software implementations of a given system function. Indeed, most embedded systems at their core repre sent a careful division and design of hardware and software parts of the system To do this task effectively, models and methods are necessary functionality. to capture application behavior, needs and system implementation constraints. Formal modeling can be valuable in addressing these tasks. As with most engineering domains, co-design practice defines the state of the it seeks to add new capabilities in system conceptualization, mod art, though eling, optimization and implementation. These advances -particularly those related to synthesis and verification tasks -direct1y depend upon formal under standing of system behavior and performance measures. Current practice in system modeling relies upon exploiting high-level programming frameworks, such as SystemC, EstereI, to capture design at increasingly higher levels of ab straction and attempts to reduce the system implementation task. While raising the abstraction levels for design and verification tasks, to be really useful, these approaches must also provide for reuse, adaptation of the existing intellectual property (IP) blocks."
Pain management is a vast subject and is changing rapidly. Finding a good resource for learning, however, is difficult. Most of the available books are lengthy volumes including many details irrelevant to physicians sitting for examinations or assessment. Furthermore, books aimed at assisting preparation for entire anaesthesia exams typically address pain management in only one chapter or a few pages. This book covers the entire curriculum relating to pain management and will make it easy to learn all aspects of the subject by covering key concepts in a reader-friendly manner. It comprises nine concise and simple chapters that aim to impart the maximum information within a limited space. These chapters address anatomy, assessment of pain, diagnosis of pain, pharmacology, non- pharmacological pain management, acute and chronic pain management, pain management in special groups, and special techniques. Pain Management: Essential Topics for Examinations will be an ideal resource for those who plan to sit for examinations, wherever they are based in the world. In addition, it will be an invaluable reference for higher and advanced pain trainees, residents, and physicians working in chronic pain.
Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data Key Features A beginner's guide for performing data analysis loaded with numerous rich, practical examples Access to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysis Develop applications in Scala for real-time analysis and machine learning in Apache Spark Book DescriptionEfficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights What you will learn Techniques to determine the validity and confidence level of data Apply quartiles and n-tiles to datasets to see how data is distributed into many buckets Create data pipelines that combine multiple data lifecycle steps Use built-in features to gain a deeper understanding of the data Apply Lasso regression analysis method to your data Compare Apache Spark API with traditional Apache Spark data analysis Who this book is forIf you are a data scientist or a data analyst who wants to learn how to perform data analysis using Scala, this book is for you. All you need is knowledge of the basic fundamentals of Scala programming.
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