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Automatic Flight Control Systems (Synthesis Lectures on Mechanical Engineering)

by Mohammad Sadraey

This book provides readers with a design approach to the automatic flight control systems (AFCS). The AFCS is the primary on-board tool for long flight operations, and is the foundation for the airspace modernization initiatives. In this text, AFCS and autopilot are employed interchangeably. It presents fundamentals of AFCS/autopilot, including primary subsystems, dynamic modeling, AFCS categories/functions/modes, servos/actuators, measurement devices, requirements, functional block diagrams, design techniques, and control laws. The book consists of six chapters. The first two chapters cover the fundamentals of AFCS and closed-loop control systems in manned and unmanned aircraft. The last four chapters present features of Attitude control systems (Hold functions), Flight path control systems (Navigation functions), Stability augmentation systems, and Command augmentation systems, respectively.

Automatic for the City: Designing for People In the Age of The Driverless Car

by Riccardo Bobisse Andrea Andrea Pavia

How will automated vehicles change our lives? Where are the opportunities and challenges? Future streets require planning today. This timely book envisions ways in which changes to urban mobility and technology will transform city streetscapes and, importantly, how cities can prepare. It is a reflection on the relationship between new technologies and urbanism, as well as an agile urban design manual with pictures illustrating potential spatial arrangements enabled by the new technologies. Two case studies in the central urban cores of London and Los Angeles will be presented to show how neighborhoods can be redesigned for the better and how to apply good urban design principles across towns and cities worldwide.

Automatic for the City: Designing for People In the Age of The Driverless Car

by Riccardo Bobisse Andrea Andrea Pavia

How will automated vehicles change our lives? Where are the opportunities and challenges? Future streets require planning today. This timely book envisions ways in which changes to urban mobility and technology will transform city streetscapes and, importantly, how cities can prepare. It is a reflection on the relationship between new technologies and urbanism, as well as an agile urban design manual with pictures illustrating potential spatial arrangements enabled by the new technologies. Two case studies in the central urban cores of London and Los Angeles will be presented to show how neighborhoods can be redesigned for the better and how to apply good urban design principles across towns and cities worldwide.

Automatic Gain Control: Techniques and Architectures for RF Receivers (Analog Circuits and Signal Processing)

by Juan Pablo Alegre Pérez Santiago Celma Pueyo Belén Calvo López

This book analyzes automatic gain control (AGC) loop circuits and demonstrates AGC solutions in the environment of wireless receivers, mainly in wireless receivers with stringent constraints in settling-time and wide dynamic range, such as WLAN and Bluetooth receivers. Since feedforward AGCs present great advantages in this context, as an alternative to conventional feedback AGCs, this book includes a detailed study of feedforward AGCs design –at the level of basic AGC cells, as well as the system level, including their main characteristics and performance.

Automatic Generation of Combinatorial Test Data (SpringerBriefs in Computer Science)

by Jian Zhang Zhiqiang Zhang Feifei Ma

This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing, combinatorics, constraint solving and evolutionary computation.

Automatic Generation of Computer Animation: Using AI for Movie Animation (Lecture Notes in Computer Science #2160)

by Ruqian Lu Songmao Zhang

We are both fans of watching animated stories. Every evening, before or after d- ner, we always sit in front of the television and watch the animation program, which is originally produced and shown for children. We find ourselves becoming younger while immerged in the interesting plot of the animation: how the princess is first killed and then rescued, how the little rat defeats the big cat, etc. But what we have found in those animation programs are not only interesting plots, but also a big chance for the application of computer science and artificial intelligence techniques. As is well known, the cost of producing animated movies is very high, even with the use of computer graphics techniques. Turning a story in text form into an animated movie is a long and complicated procedure. We came to the c- clusion that many parts of this process could be automated by using artificial - telligence techniques. It is actually a challenge and test for machine intelligence. So we decided to explore the possibility of a full life cycle automation of c- puter animation generation. By full life cycle we mean the generation process of computer animation from a children s story in natural language text form to the final animated movie. It is of course a task of immense difficulty. However, we decided to try our best and to see how far we could go.

Automatic Generation of Morphological Set Recognition Algorithms (Springer Series in Perception Engineering)

by Robert C. Vogt

Since the early days of computers, machine learning and automatic programming have attracted researchers in computer science and related fields, particularly pattern recognition and automatic control theory. Most of the learning concepts in machine perception have been inspired by pattern recognition approaches that rely on statistical techniques. These statistical techniques have applicability in limited recognition tasks. Automatic programming in perception systems has generally been limited to interfaces that allow easy specification of the task using natural language. Clearly, machine learning and automatic programming can make percep­ tion systems powerful and easy to use. Vogt's book addresses both these tasks in the context of machine vision. He uses morphological operations to implement his approach which was developed for solving the figure-ground problem in images. His system selects the correct se­ quence of operators to accept or reject pixels for fmding objects in an image. The sequence of operators is selected after a user specifies what the correct objects are. On the surface it may appear that the problem solved by the system is not very interesting, however, the contribution ofVogt' s work should not be judged by the images that the system can segment. Its real contribution is in demonstrat­ ing, possibly for'the frrst time, that automatic programming is possible in computer vision systems. The selection of morphological operators demonstrates that to implement an automatic programming-based approach, operators whose behavior is clearly defined in the image space are required.

Automatic Indexing and Abstracting of Document Texts (The Information Retrieval Series #6)

by Marie-Francine Moens

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.

Automatic Item Generation: Theory and Practice

by Mark J. Gierl Thomas M. Haladyna

Automatic item generation (AIG) represents a relatively new and unique research area where specific cognitive and psychometric theories are applied to test construction practices for the purpose of producing test items using technology. The purpose of this book is to bring researchers and practitioners up-to-date on the growing body of research on AIG by organizing in one volume what is currently known about this research area. Part I begins with an overview of the concepts and topics necessary for understanding AIG by focusing on both its history and current applications. Part II presents two theoretical frameworks and practical applications of these frameworks in the production of item generation. Part III summarizes the psychological and substantive characteristics of generated items . Part IV concludes with a discussion of the statistical models that can be used to estimate the item characteristics of generated items, features one future application of AIG, describes the current technologies used for AIG, and also highlights the unresolved issues that must be addressed as AIG continues to mature as a research area. Comprehensive – The book provides a comprehensive analysis of both the theoretical concepts that define automatic item generation and the practical considerations required to implement these concepts. Varied Applications – Readers are provided with novel applications in diverse content areas (e.g., science and reading comprehension) that range across all educational levels – elementary through university.

Automatic Item Generation: Theory and Practice

by Mark J. Gierl Thomas M. Haladyna

Automatic item generation (AIG) represents a relatively new and unique research area where specific cognitive and psychometric theories are applied to test construction practices for the purpose of producing test items using technology. The purpose of this book is to bring researchers and practitioners up-to-date on the growing body of research on AIG by organizing in one volume what is currently known about this research area. Part I begins with an overview of the concepts and topics necessary for understanding AIG by focusing on both its history and current applications. Part II presents two theoretical frameworks and practical applications of these frameworks in the production of item generation. Part III summarizes the psychological and substantive characteristics of generated items . Part IV concludes with a discussion of the statistical models that can be used to estimate the item characteristics of generated items, features one future application of AIG, describes the current technologies used for AIG, and also highlights the unresolved issues that must be addressed as AIG continues to mature as a research area. Comprehensive – The book provides a comprehensive analysis of both the theoretical concepts that define automatic item generation and the practical considerations required to implement these concepts. Varied Applications – Readers are provided with novel applications in diverse content areas (e.g., science and reading comprehension) that range across all educational levels – elementary through university.

Automatic Language Identification in Texts (Synthesis Lectures on Human Language Technologies)

by Tommi Jauhiainen Marcos Zampieri Timothy Baldwin Krister Lindén

This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature. LI is the problem of determining the language in which a document is written and is a crucial part of many text processing pipelines. The authors use a unified notation to clarify the relationships between common LI methods. The book introduces LI performance evaluation methods and takes a detailed look at LI-related shared tasks. The authors identify open issues and discuss the applications of LI and related tasks and proposes future directions for research in LI.

Automatic Layout Modification: Including design reuse of the Alpha CPU in 0.13 micron SOI technology

by Michael Reinhardt

This volume is a welcome effort towards improving some of the practices in chip design today. The authors provide a comprehensive reference work on Automatic Layout Modification which will be valuable to VLSI courses at universities, and to CAD and circuit engineers and engineering managers.

Automatic Learning Techniques in Power Systems (Power Electronics and Power Systems)

by Louis A. Wehenkel

Automatic learning is a complex, multidisciplinary field of research and development, involving theoretical and applied methods from statistics, computer science, artificial intelligence, biology and psychology. Its applications to engineering problems, such as those encountered in electrical power systems, are therefore challenging, while extremely promising. More and more data have become available, collected from the field by systematic archiving, or generated through computer-based simulation. To handle this explosion of data, automatic learning can be used to provide systematic approaches, without which the increasing data amounts and computer power would be of little use. Automatic Learning Techniques in Power Systems is dedicated to the practical application of automatic learning to power systems. Power systems to which automatic learning can be applied are screened and the complementary aspects of automatic learning, with respect to analytical methods and numerical simulation, are investigated. This book presents a representative subset of automatic learning methods - basic and more sophisticated ones - available from statistics (both classical and modern), and from artificial intelligence (both hard and soft computing). The text also discusses appropriate methodologies for combining these methods to make the best use of available data in the context of real-life problems. Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field.

Automatic Logic Synthesis Techniques for Digital Systems

by Martyn D. Edwards

Recent advances in microelectronics technology have led to the increasing utilisation of integrated circuit components in virtually all sectors of society. One particular component is the Application-Specific Integrated Circuit, ASIC, which is employed in such diverse products as washing machines, car engines and mainframe computers. The successful use of ASICs in products is due to the exploitation of computer-aided design tools, especially automatic synthesis tools, which reduce design time and cost. This book reviews the state-of-the-art in logic synthesis techniques, which have recently been developed for ASIC components.

Automatic Malware Analysis: An Emulator Based Approach (SpringerBriefs in Computer Science)

by Heng Yin Dawn Song

Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems. Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.

Automatic Methods for the Refinement of System Models: From the Specification to the Implementation (SpringerBriefs in Electrical and Computer Engineering)

by Julia Seiter Robert Wille Rolf Drechsler

This book provides a comprehensive overview of automatic model refinement, which helps readers close the gap between initial textual specification and its desired implementation. The authors enable readers to follow two “directions” for refinement: Vertical refinement, for adding detail and precision to single description for a given model and Horizontal refinement, which considers several views on one level of abstraction, refining the system specification by dedicated descriptions for structure or behavior. The discussion includes several methods which support designers of electronic systems in this refinement process, including verification methods to check automatically whether a refinement has been conducted as intended.

The Automatic Millionaire: A Powerful One-step Plan to Live and Finish Rich

by David Bach

Making your money work for you ... automaticallyIn The Automatic Millionaire David Bach unlocks the secret to getting rich. Cutting through the jargon, it's full of common-sense advice and practical strategies to help you take control of your finances. The step-by-step guide and no-budget, no-discipline, no-nonsense system makes reaching financial security amazingly simple and easy, no matter what your income. You can get rid of the debt that's holding you down. You can get on top of your day-to-day expenses. You can create a safety net that will protect you from life's unknowns. You can have the money to get the things you want. You can build a seven-figure nest egg that will keep you secure and comfortable for the rest of your life.This book has the power to secure your financial future and change your life. All you have to do is follow the one-step programme - the rest is automatic!

Automatic Modulation Classification: Principles, Algorithms and Applications

by Zhechen Zhu Asoke K. Nandi

Automatic Modulation Classification (AMC) has been a key technology in many military, security, and civilian telecommunication applications for decades. In military and security applications, modulation often serves as another level of encryption; in modern civilian applications, multiple modulation types can be employed by a signal transmitter to control the data rate and link reliability. This book offers comprehensive documentation of AMC models, algorithms and implementations for successful modulation recognition. It provides an invaluable theoretical and numerical comparison of AMC algorithms, as well as guidance on state-of-the-art classification designs with specific military and civilian applications in mind. Key Features: Provides an important collection of AMC algorithms in five major categories, from likelihood-based classifiers and distribution-test-based classifiers to feature-based classifiers, machine learning assisted classifiers and blind modulation classifiers Lists detailed implementation for each algorithm based on a unified theoretical background and a comprehensive theoretical and numerical performance comparison Gives clear guidance for the design of specific automatic modulation classifiers for different practical applications in both civilian and military communication systems Includes a MATLAB toolbox on a companion website offering the implementation of a selection of methods discussed in the book

Automatic Modulation Classification: Principles, Algorithms and Applications

by Zhechen Zhu Asoke K. Nandi

Automatic Modulation Classification (AMC) has been a key technology in many military, security, and civilian telecommunication applications for decades. In military and security applications, modulation often serves as another level of encryption; in modern civilian applications, multiple modulation types can be employed by a signal transmitter to control the data rate and link reliability. This book offers comprehensive documentation of AMC models, algorithms and implementations for successful modulation recognition. It provides an invaluable theoretical and numerical comparison of AMC algorithms, as well as guidance on state-of-the-art classification designs with specific military and civilian applications in mind. Key Features: Provides an important collection of AMC algorithms in five major categories, from likelihood-based classifiers and distribution-test-based classifiers to feature-based classifiers, machine learning assisted classifiers and blind modulation classifiers Lists detailed implementation for each algorithm based on a unified theoretical background and a comprehensive theoretical and numerical performance comparison Gives clear guidance for the design of specific automatic modulation classifiers for different practical applications in both civilian and military communication systems Includes a MATLAB toolbox on a companion website offering the implementation of a selection of methods discussed in the book

Automatic Modulation Recognition of Communication Signals

by Elsayed Azzouz A.K. Nandi

Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types. Automatic Modulation Recognition of Communications Signals is the first comprehensive book on automatic modulation recognition. It is essential reading for researchers and practising engineers in the field. It is also a valuable text for an advanced course on the subject.

Automatic Nonuniform Random Variate Generation (Statistics and Computing)

by Wolfgang Hörmann Josef Leydold Gerhard Derflinger

The recent concept of universal (also called automatic or black-box) random variate generation can only be found dispersed in the literature. Being unique in its overall organization, the book covers not only the mathematical and statistical theory but also deals with the implementation of such methods. All algorithms introduced in the book are designed for practical use in simulation and have been coded and made available by the authors. Examples of possible applications of the presented algorithms (including option pricing, VaR and Bayesian statistics) are presented at the end of the book.

The Automatic Packaging Machinery Sector in Italy and Germany (SpringerBriefs in Business)

by Marco Fortis Monica Carminati

This book analyzes the wrapping and packaging machinery sector in the Emilia/Bologna district in Italy and compares the most recent trends with those in the industry in Schwäbisch Hall and Waiblingen, Baden-Württemberg, Germany, which represents a direct rival. In a detailed and original study, the authors trace the evolution of manufacturing in Bologna during a period that witnessed extraordinary growth in automatic wrapping and packaging machines, leading the sector to become a central pillar of Italian mechanical engineering. Similarly, the history of the industry in the Emilia district is described, highlighting the factors that led to its success. A comprehensive comparative analysis of the German and Italian sectors is then performed. Export figures and the trade balance for the sector are examined based on Eurostat data, and the significance of the two districts in terms of global trade is identified with reference to UN data. In addition, the number of companies, sales, and the size of the workforces are thoroughly compared. The book will be of interest to economists and others with an interest in the development and importance of the automatic packaging machinery sector.

Automatic Parallelization: New Approaches to Code Generation, Data Distribution, and Performance Prediction

by Christoph W. Kessler

Distributed-memory multiprocessing systems (DMS), such as Intel's hypercubes, the Paragon, Thinking Machine's CM-5, and the Meiko Computing Surface, have rapidly gained user acceptance and promise to deliver the computing power required to solve the grand challenge problems of Science and Engineering. These machines are relatively inexpensive to build, and are potentially scalable to large numbers of processors. However, they are difficult to program: the non-uniformity of the memory which makes local accesses much faster than the transfer of non-local data via message-passing operations implies that the locality of algorithms must be exploited in order to achieve acceptable performance. The management of data, with the twin goals of both spreading the computational workload and minimizing the delays caused when a processor has to wait for non-local data, becomes of paramount importance. When a code is parallelized by hand, the programmer must distribute the program's work and data to the processors which will execute it. One of the common approaches to do so makes use of the regularity of most numerical computations. This is the so-called Single Program Multiple Data (SPMD) or data parallel model of computation. With this method, the data arrays in the original program are each distributed to the processors, establishing an ownership relation, and computations defining a data item are performed by the processors owning the data.

Automatic Parallelization: An Overview of Fundamental Compiler Techniques (Synthesis Lectures on Computer Architecture)

by Samuel Midkiff

Compiling for parallelism is a longstanding topic of compiler research. This book describes the fundamental principles of compiling "regular" numerical programs for parallelism. We begin with an explanation of analyses that allow a compiler to understand the interaction of data reads and writes in different statements and loop iterations during program execution. These analyses include dependence analysis, use-def analysis and pointer analysis. Next, we describe how the results of these analyses are used to enable transformations that make loops more amenable to parallelization, and discuss transformations that expose parallelism to target shared memory multicore and vector processors. We then discuss some problems that arise when parallelizing programs for execution on distributed memory machines. Finally, we conclude with an overview of solving Diophantine equations and suggestions for further readings in the topics of this book to enable the interested reader to delve deeper into the field. Table of Contents: Introduction and overview / Dependence analysis, dependence graphs and alias analysis / Program parallelization / Transformations to modify and eliminate dependences / Transformation of iterative and recursive constructs / Compiling for distributed memory machines / Solving Diophantine equations / A guide to further reading

Automatic Performance Prediction of Parallel Programs

by Thomas Fahringer

Automatic Performance Prediction of Parallel Programs presents a unified approach to the problem of automatically estimating the performance of parallel computer programs. The author focuses primarily on distributed memory multiprocessor systems, although large portions of the analysis can be applied to shared memory architectures as well. The author introduces a novel and very practical approach for predicting some of the most important performance parameters of parallel programs, including work distribution, number of transfers, amount of data transferred, network contention, transfer time, computation time and number of cache misses. This approach is based on advanced compiler analysis that carefully examines loop iteration spaces, procedure calls, array subscript expressions, communication patterns, data distributions and optimizing code transformations at the program level; and the most important machine specific parameters including cache characteristics, communication network indices, and benchmark data for computational operations at the machine level. The material has been fully implemented as part of P3T, which is an integrated automatic performance estimator of the Vienna Fortran Compilation System (VFCS), a state-of-the-art parallelizing compiler for Fortran77, Vienna Fortran and a subset of High Performance Fortran (HPF) programs. A large number of experiments using realistic HPF and Vienna Fortran code examples demonstrate highly accurate performance estimates, and the ability of the described performance prediction approach to successfully guide both programmer and compiler in parallelizing and optimizing parallel programs. A graphical user interface is described and displayed that visualizes each program source line together with the corresponding parameter values. P3T uses color-coded performance visualization to immediately identify hot spots in the parallel program. Performance data can be filtered and displayed at various levels of detail. Colors displayed by the graphical user interface are visualized in greyscale. Automatic Performance Prediction of Parallel Programs also includes coverage of fundamental problems of automatic parallelization for distributed memory multicomputers, a description of the basic parallelization strategy and a large variety of optimizing code transformations as included under VFCS.

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