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  • SensorSimII is the framework of a simulator that I have been working on to study how future sensor n

    SensorSimII is the framework of a simulator that I have been working on to study how future sensor networks should operate. the simulator is written in a modular fashion so that it can be adapted to serve a number of needs. However, please remember that it is still a work in progress. This web page is here just to give a glimpse of the approach we ve taken with this simulator. Likewise this web page is simply preliminary information to attempt to answer some of the Questions that researchers might have about this project.

    標(biāo)簽: SensorSimII framework simulator working

    上傳時間: 2013-12-26

    上傳用戶:wsf950131

  • Exploring C++ uses a series of self–directed lessons to divide C++ into bite–sized chunks that you c

    Exploring C++ uses a series of self–directed lessons to divide C++ into bite–sized chunks that you can digest as rapidly as you can swallow them. The book assumes only a basic understanding of fundamental programming concepts (variables, functions, expressions, statements) and requires no prior knowledge of C or any other particular language. It reduces the usually considerable complexity of C++. The included lessons allow you to learn by doing, as a participant of an interactive education session. You’ll master each step in a one sitting before you proceed to the next. Author Ray Lischner has designed Questions to promote learning new material. And by responding to Questions throughout the text, youll be engaged every step of the way.

    標(biāo)簽: Exploring directed lessons series

    上傳時間: 2014-11-15

    上傳用戶:caiiicc

  • 手寫代碼必備手冊_C

    shell script面試問題, Top 50 Shell Scripting Interview Questions 

    標(biāo)簽: shell script面試問題

    上傳時間: 2015-11-08

    上傳用戶:1羅志權(quán)

  • DAKOTA

    Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance Questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms

    標(biāo)簽: Optimization and Uncertainty Quantification

    上傳時間: 2016-04-08

    上傳用戶:huhu123456

  • Adaptive Array Systems Fundamentals

    Firstly, this book is set at a level suitable for senior undergraduate and postgraduate students who wish to understand the fundamentals and applications of adaptive array antenna systems. Array fundamentals are described in the text, and examples which demonstrate theoretical concepts are included throughout the book, as well  as  summaries and Questions at the end of each chapter.

    標(biāo)簽: Applications Fundamentals Adaptive Systems Array and

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • ComSoc+Guide+to+Next+Generation+Optical+Transport

    Many times I have been asked to explain “ briefl y ” how SDH, SONET, and the OTN “ exactly ” work. The Questions came mainly from new colleagues, stu- dents, and users of these technologies, personally or via the usenet newsgroup comp.dcom.sdh - sonet. I could have referred them to the standards documents, but to provide a more consistent and clear answer I decided to write this pocket guide. The objective of this book is that it can be used both as an introduction as well as a reference guide to these technologies and their spe- cifi c standards documents.

    標(biāo)簽: Generation Transport Optical ComSoc Guide

    上傳時間: 2020-05-27

    上傳用戶:shancjb

  • System+Design+for+Telecommunication+Gateways

    The idea for this book was born during one of my project-related trips to the beautiful city of Hangzhou in China, where in the role of Chief Architect I had to guide a team of very young, very smart and extremely dedicated software developers and verification engineers. Soon it became clear that as eager as the team was to jump into the coding, it did not have any experience in system architecture and design and if I did not want to spend all my time in constant travel between San Francisco and Hangzhou, the only option was to groom a number of local junior architects. Logically, one of the first Questions being asked by these carefully selected future architects was whether I could recommend a book or other learning material that could speed up the learning cycle. I could not. Of course, there were many books on various related topics, but many of them were too old and most of the updated information was either somewhere on the Internet dispersed between many sites and online magazines, or buried in my brain along with many years of experience of system architecture.

    標(biāo)簽: Telecommunication Gateways System Design for

    上傳時間: 2020-06-01

    上傳用戶:shancjb

  • Basic+ESD+and+IO+Design

    This effort started as an answer to the numerous Questions the authors have repeatedly had to answer about electrostatic discharge (ESD) protection and input/output (1/0) designs. In the past no comprehensive book existed suffi- ciently covering these areas, and these topics were rarely taught in engineering schools. Thus first-time I/O and ESD protection designers have had consider- able trouble getting started. This book is in part an answer to such needs.

    標(biāo)簽: Design Basic ESD and IO

    上傳時間: 2020-06-05

    上傳用戶:shancjb

  • Electricity+Markets+Theories

    Why did an electricity market emerge? How does it really work? What are the perfor- mance measures that we can use to tell that the electricity market under consideration is well functioning? These are the Questions that will be explored in this book. The main purpose of this book is to introduce the fundamental theories and concepts that underpintheelectricitymarketswhicharebasedonthreemajordisciplines:electrical power engineering, economics, and optimization methods.

    標(biāo)簽: Electricity Theories Markets

    上傳時間: 2020-06-07

    上傳用戶:shancjb

  • A Course in Machine Learning

    Machine learning is a broad and fascinating field. Even today, machine learning technology runs a substantial part of your life, often without you knowing it. Any plausible approach to artifi- cial intelligence must involve learning, at some level, if for no other reason than it’s hard to call a system intelligent if it cannot learn. Machine learning is also fascinating in its own right for the philo- sophical Questions it raises about what it means to learn and succeed at tasks.

    標(biāo)簽: Learning Machine Course in

    上傳時間: 2020-06-10

    上傳用戶:shancjb

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