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For one/two semester courses in Engineering and Computer Science at the freshman/sophomore level.
Engineering Problem Solving With C++, Fourth Edition provides a clear, concise introduction to engineering problem solving with C++ as well as the object-oriented features of the C++ programming language. The authors’ proven five-step problem solving methodology is presented and then incorporated in every chapter of the text. The chapters in this text are designed to give the instructor flexibility in the ordering of topics with chapter topics covering the essentials of mathematical computations, character data, control structures, functions, arrays, classes, and pointers. Outstanding engineering and scientific applications are used throughout; all applications are centered around the theme of engineering challenges in the 21st century with an emphasis on incorporating real-world engineering and scientific examples and problems.
Uniquely focusing on intersections of social problems, multilevel statistical modeling, and causality; the substantively and methodologically integrated chapters of this book clarify basic strategies for developing and testing multilevel linear models (MLMs), and drawing casual inferences from such models. These models are also referred to as hierarchical linear models (HLMs) or mixed models. The statistical modeling of multilevel data structures enables researchers to combine contextual and longitudinal analyses appropriately. But researchers working on social problems seldom apply these methods, even though the topics they are studying and the empirical data call for their use. By applying multilevel modeling to hierarchical data structures, this book illustrates how the use of these methods can facilitate social problems research and the formulation of social policies. It gives the reader access to working data sets, computer code, and analytic techniques, while at the same time carefully discussing issues of causality in such models. This book innovatively: *Develops procedures for studying social, economic, and human development. * Uses typologies to group (i.e., classify or nest) the level of random macro-level factors. * Estimates models with Poisson, binomial, and Gaussian end points using SAS's generalized linear mixed models (GLIMMIX) procedure. * Selects appropriate covariance structures for generalized linear mixed models. * Applies difference-in-differences study designs in the multilevel modeling of intervention studies. *Calculates propensity scores by applying Firth logistic regression to Goldberger-corrected data. * Uses the Kenward-Rogers correction in mixed models of repeated measures. * Explicates differences between associational and causal analysis of multilevel models. * Consolidates research findings via meta-analysis and methodological critique. *Develops criteria for assessing a study's validity and zone of causality. Because of its social problems focus, clarity of exposition, and use of state-of-the-art procedures; policy researchers, methodologists, and applied statisticians in the social sciences (specifically, sociology, social psychology, political science, education, and public health) will find this book of great interest. It can be used as a primary text in courses on multilevel modeling or as a primer for more advanced texts.
Recent years have been characterized by the increasing amountofpublications in the field ofso-called ill-posed problems. This is easilyunderstandable because we observe the rapid progress of a relatively young branch ofmathematics, ofwhich the first results date back to about 30 years ago. By now, impressive results have been achieved both in the theory ofsolving ill-posed problems and in the applicationsofalgorithms using modem computers. To mention just one field, one can name the computer tomography which could not possibly have been developed without modem tools for solving ill-posed problems. When writing this book, the authors tried to define the place and role of ill- posed problems in modem mathematics. In a few words, we define the theory of ill-posed problems as the theory of approximating functions with approximately given arguments in functional spaces. The difference between well-posed and ill- posed problems is concerned with the fact that the latter are associated with discontinuous functions. This approach is followed by the authors throughout the whole book. We hope that the theoretical results will be of interest to researchers working in approximation theory and functional analysis. As for particular algorithms for solving ill-posed problems, the authors paid general attention to the principles ofconstructing such algorithms as the methods for approximating discontinuous functions with approximately specified arguments. In this way it proved possible to define the limits of applicability of regularization techniques.
The transfer function approach is widely used in classical control theory for its easy handling and physical meaning. Although the use of transfer functions is well-established for linear time-invariant systems, it is not suitable for non-stationary systems among which are sampled-data systems and processes with periodically varying coefficients. Computer-controlled continuous-time processes are a very important subset of periodic sampled-data systems which are not treatable using ordinary transfer functions.
Having established the ability of the parametric transfer function to solve this problem for single-input, single-output systems in previous work, the authors extend these methods, which incorporate time-dependence, to the idea of the parametric transfer matrix in a complete exposition of analysis and design methods for multiple-input, multiple-output (MIMO) sampled-data systems.
Multivariable Computer-controlled Systems is divided into three parts:
Appendices covering basic mathematical formulae and the description of two MATLAB(r) toolboxes round out this self-contained guide to multivariable control systems.
Of special interest to researchers in automatic control and to development engineers working with advanced control technology, Multivariable Computer-controlled Systems will also interest mathematical control theorists and graduate students studying advanced methods of computer-based control.
Spend just 10 minutes a day learning and master your maths skills Set the clock and off you go! Young learners excel in short bursts, so 10 Minutes a Day Problem Solving KS2 Ages 9-11 from Carol Vorderman is the perfect maths workbook for children. Games and tests take a short amount of time so you get maximum fun for maximum effect. There are 10 minute activities on negative amounts, ratio problems and a mind-over-maths challenge! Plus the "parents' notes" section gives the answers, explains common pitfalls and gives guidance on how to avoid them. 10 Minutes a day workbooks are the perfect at home reinforcement for subjects learned in school and support the new National Curriculum. So, set the funky orange timer to test your child in fun 'beat the clock' exercises - and let 10 Minutes a Day Problem Solving KS2 Ages 9-11 with Carol Vorderman show your child how much fun maths can be.
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