Vijay Nair - Böcker

The Department of Defense (DoD) recently adopted evolutionary acquisition, a dynamic strategy for the development and acquisition of its defense systems. Evolutionary defense systems are planned, in advance, to be developed through several stages in a single procurement program. Each stage is planned to produce a viable system which could be fielded. The system requirements for each stage of development may be specified in advance of a given stage or may be decided at the outset of that stage's development. Due to the different stages that comprise an evolutionary system, there exists a need for careful reexamination of current testing and evaluation policies and processes, which were designed for single-stage developments. The Office of the Under Secretary of Defense for Acquisition, Technology and Logistics (USD-AT&L) and the Director of Operational Testing and Evaluation (DOT&E) asked the Committee on National Statistics (CNSTAT) of the National Academies to examine the key issues and implications for defense testing from the introduction of evolutionary acquisition.The CNSTAT was charged with planning and conducting a workshop to study test strategies for the evolutionary acquisition. The committee reviewed defense materials defining evolutionary acquisition and interviewed test officials from the three major test service agencies to understand the current approaches used in testing systems procured through evolutionary acquisition. The committee also examined possible alternatives to identify problems in implementation. At the workshop that took place on December 13-14, 2004, the committee tried to answer many questions including: What are the appropriate roles and objectives for testing in an evolutionary environment?, Can a systematic, disciplined process be developed for testing and evaluation in such a fluid and flexible environment?, and Is there adequate technical expertise within the acquisition community to fully exploit data gathered from previous stages to effectively combine information from various sources for test design and analysis?. Testing of Defense Systems in an Evolutionary Acquisition Environment provides the conclusions and recommendations of the CNSTAT following the workshop and its other investigations.

This is the first book to provide comprehensive coverage of hardware and circuit design specifically for engineers working in wireless communications. It serves as a reference for practicing engineers and technicians working in the areas of RF, microwaves, communications, solid-state devices, and radar.

See how Domain-Driven Design (DDD) combines with Jakarta EE MicroProfile or Spring Boot to offer a complete suite for building enterprise-grade applications. In this book you will see how these all come together in one of the most efficient ways to develop complex software, with a particular focus on the DDD process.   Practical Domain-Driven Design in Enterprise Java starts by building out the Cargo Tracker reference application as a monolithic application using the Jakarta EE platform. By doing so, you will map concepts of DDD (bounded contexts, language, and aggregates) to the corresponding available tools (CDI, JAX-RS, and JPA) within the Jakarta EE platform. Once you have completed the monolithic application, you will walk through the complete conversion of the monolith to a microservices-based architecture, again mapping the concepts of DDD and the corresponding available tools within the MicroProfile platform (config, discovery, and fault tolerance). To finish this section, you will examine the same microservices architecture on the Spring Boot platform. The final set of chapters looks at what the application would be like if you used the CQRS and event sourcing patterns. Here you’ll use the Axon framework as the base framework. What You Will LearnDiscover the DDD architectural principles and use the DDD design patternsUse the new Eclipse Jakarta EE platform Work with the Spring Boot frameworkImplement microservices design patterns, including context mapping, logic design, entities, integration, testing, and securityCarry out event sourcingApply CQRS Who This Book Is ForJunior developers intending to start working on enterprise Java; senior developers transitioning from monolithic- to microservices-based architectures; and architects transitioning to a DDD philosophy of building applications.

There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics.This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.