%{search_type} search results

• 1. Introduction
• Part I. Hypothesis Testing: 2. Binary hypothesis testing
• 3. Multiple hypothesis testing
• 4. Composite hypothesis testing
• 5. Signal detection
• 6. Convex statistical distances
• 7. Performance bounds for hypothesis testing
• 8. Large deviations and error exponents for hypothesis testing
• 9. Sequential and quickest change detection
• 10. Detection of random processes
• Part II. Estimation: 11. Bayesian parameter estimation
• 12. Minimum variance unbiased estimation
• 13. Information inequality and Cramer-Rao lower bound
• 14. Maximum likelihood estimation
• 15. Signal estimation.
• (source: Nielsen Book Data)

This book is a mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals. With a wealth of illustrations and examples to explain the key features of the theory and to connect with real-world applications, additional material to explore more advanced concepts, and numerous end-of-chapter problems to test the reader's knowledge, this textbook is the 'go-to' guide for learning about the core principles of statistical inference and its application in engineering and data science. The password-protected solutions manual and the image gallery from the book are available online.
(source: Nielsen Book Data)

• Introduction: The world of animal motion
• Chapter 1: Walking on water
• Chapter 2: Swimming under sand
• Chapter 3: The shape of a flying snake
• Chapter 4: Of eyelashes and sharkskin
• Chapter 5: Dead fish swimming
• Chapter 6: Flying in the rain
• Chapter 7: The brain behind the brawn
• Chapter 8: Are ants a fluid or a solid?
• Conclusion: The future.

Discovering the secrets of animal movement and what they can teach us Insects walk on water, snakes slither, and fish swim. Animals move with astounding grace, speed, and versatility: how do they do it, and what can we learn from them? In How to Walk on Water and Climb up Walls, David Hu takes readers on an accessible, wondrous journey into the world of animal motion. From basement labs at MIT to the rain forests of Panama, Hu shows how animals have adapted and evolved to traverse their environments, taking advantage of physical laws with results that are startling and ingenious. In turn, the latest discoveries about animal mechanics are inspiring scientists to invent robots and devices that move with similar elegance and efficiency. Hu follows scientists as they investigate a multitude of animal movements, from the undulations of sandfish and the way that dogs shake off water in fractions of a second to the seemingly crash-resistant characteristics of insect flight. Not limiting his exploration to individual organisms, Hu describes the ways animals enact swarm intelligence, such as when army ants cooperate and link their bodies to create bridges that span ravines. He also looks at what scientists learn from nature's unexpected feats--such as snakes that fly, mosquitoes that survive rainstorms, and dead fish that swim upstream. As researchers better understand such issues as energy, flexibility, and water repellency in animal movement, they are applying this knowledge to the development of cutting-edge technology. Integrating biology, engineering, physics, and robotics, How to Walk on Water and Climb up Walls demystifies the remarkable mechanics behind animal locomotion.
(source: Nielsen Book Data)

• Mathematics education in EU in STEM disciplines.- Case Study Methodology.- Overview of Math Education for STEM in RUSSIA.- Overview of Math Education for STEM in Georgia.- Overview of Math Education for STEM in Armenia.- Overview of Math Education for STEM in EU.- Use cases in Russia.- Use cases in Georgia and Armenia.- Lessons Learnt.
• (source: Nielsen Book Data)

This open access book provides a comprehensive overview of the core subjects comprising mathematical curricula for engineering studies in five European countries and identifies differences between two strong traditions of teaching mathematics to engineers. The collective work of experts from a dozen universities critically examines various aspects of higher mathematical education. The two EU Tempus-IV projects - MetaMath and MathGeAr - investigate the current methodologies of mathematics education for technical and engineering disciplines. The projects aim to improve the existing mathematics curricula in Russian, Georgian and Armenian universities by introducing modern technology-enhanced learning (TEL) methods and tools, as well as by shifting the focus of engineering mathematics education from a purely theoretical tradition to a more applied paradigm. MetaMath and MathGeAr have brought together mathematics educators, TEL specialists and experts in education quality assurance form 21 organizations across six countries. The results of a comprehensive comparative analysis of the entire spectrum of mathematics courses in the EU, Russia, Georgia and Armenia has been conducted, have allowed the consortium to pinpoint and introduce several modifications to their curricula while preserving the generally strong state of university mathematics education in these countriesThe book presents the methodology, procedure and results of this analysis. This book is a valuable resource for teachers, especially those teaching mathematics, and curriculum planners for engineers, as well as for a general audience interested in scientific and technical higher education.
(source: Nielsen Book Data)

• 1 Basic Concepts Related to Intuitionistic Fuzzy Numbers.- 2 Derivatives and Differentials of Intuitionistic Fuzzy Functions.- 3 Integrals of Intuitionistic Fuzzy Functions.- 4 Aggregation Operations of Continuous Intuitionistic Fuzzy Information.- 5 Relationships among IFWA Operator, IFIA Operator and Definite Integrals of IFFs.- 6 Complement Theory of Intuitionistic Fuzzy Calculus.- References.
• (source: Nielsen Book Data)

This book offers a comprehensive and systematic review of the latest research findings in the area of intuitionistic fuzzy calculus. After introducing the intuitionistic fuzzy numbers' operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions. It also discusses some of the methods that have been successfully used to deal with continuous intuitionistic fuzzy information or data, which are different from the previous aggregation operators focusing on discrete information or data. Mainly intended for engineers and researchers in the fields of fuzzy mathematics, operations research, information science and management science, this book is also a valuable textbook for postgraduate and advanced undergraduate students alike.
(source: Nielsen Book Data)

Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors).
(source: Nielsen Book Data)

• 1. OVERVIEW AND DESCRIPTIVE STATISTICS. Populations, Samples, and Processes. Pictorial and Tabular Methods in Descriptive Statistics. Measures of Location. Measures of Variability.
• 2. PROBABILITY. Sample Spaces and Events. Axioms, Interpretations, and Properties of Probability. Counting Techniques. Conditional Probability. Independence.
• 3. DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Random Variables. Probability Distributions for Discrete Random Variables. Expected Values. The Binomial Probability Distribution. Hypergeometric and Negative Binomial Distributions. The Poisson Probability Distribution.
• 4. CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Probability Density Functions. Cumulative Distribution Functions and Expected Values. The Normal Distribution. The Exponential and Gamma Distributions. Other Continuous Distributions. Probability Plots.
• 5. JOINT PROBABILITY DISTRIBUTIONS AND RANDOM SAMPLES. Jointly Distributed Random Variables. Expected Values, Covariance, and Correlation. Statistics and Their Distributions. The Distribution of the Sample Mean. The Distribution of a Linear Combination.
• 6. POINT ESTIMATION. Some General Concepts of Point Estimation. Methods of Point Estimation.
• 7. STATISTICAL INTERVALS BASED ON A SINGLE SAMPLE. Basic Properties of Confidence Intervals. Large-Sample Confidence Intervals for a Population Mean and Proportion. Intervals Based on a Normal Population Distribution. Confidence Intervals for the Variance and Standard Deviation of a Normal Population.
• 8. TESTS OF HYPOTHESIS BASED ON A SINGLE SAMPLE. Hypotheses and Test Procedures. z Tests for Hypotheses About a Population Mean. The One-Sample t Test. Tests Concerning a Population Proportion. Further Aspects of Hypothesis Testing.
• 9. INFERENCES BASED ON TWO SAMPLES. z Tests and Confidence Intervals for a Difference between Two Population Means. The Two-Sample t Test and Confidence Interval. Analysis of Paired Data. Inferences Concerning a Difference between Population Proportions. Inferences Concerning Two Population Variances.
• 10. THE ANALYSIS OF VARIANCE. Single-Factor ANOVA. Multiple Comparisons in ANOVA. More on Single-Factor ANOVA.
• 11. MULTIFACTOR ANALYSIS OF VARIANCE. Two-Factor ANOVA with Kij =
• 1. Two-Factor ANOVA with Kij >
• 1. Three-Factor ANOVA
• 11. 4 2p Factorial Experiments.
• 12. SIMPLE LINEAR REGRESSION AND CORRELATION. The Simple Linear Regression Model. Estimating Model Parameters. Inferences About the Slope Parameter s
• s1. Inferences Concerning Y*x* and the Prediction of Future Y Values. Correlation.
• 13. NONLINEAR AND MULTIPLE REGRESSION. Assessing Model Adequacy. Regression with Transformed Variables. Polynomial Regression. Multiple Regression Analysis. Other Issues in Multiple Regression.
• 14. GOODNESS-OF-FIT TESTS AND CATEGORICAL DATA ANALYSIS. Goodness-of-Fit Tests When Category Probabilities Are Completely Specified. Goodness-of-Fit Tests for Composite Hypotheses. Two-Way Contingency Tables
• 15. DISTRIBUTION-FREE PROCEDURES. The Wilcoxon Signed-Rank Test. The Wilcoxon Rank-Sum Test. Distribution-Free Confidence Intervals. Distribution-Free ANOVA.
• 16. QUALITY CONTROL METHODS. General Comments on Control Charts. Control Charts for Process Location. Control Charts for Process Variation. Control Charts for Attributes. CUSUM Procedures. Acceptance Sampling.
• (source: Nielsen Book Data)

Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition. Always a market favorite, this calculus-based book offers a comprehensive introduction to probability and statistics while demonstrating how to apply concepts, models, and methodologies in today's engineering and scientific workplaces. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations. Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate book, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition also includes graphics and screen shots from SAS(R), MINITAB(R), and Java(TM) Applets to give you a solid perspective of statistics in action.
(source: Nielsen Book Data)

• 1. OVERVIEW AND DESCRIPTIVE STATISTICS. Populations, Samples, and Processes. Pictorial and Tabular Methods in Descriptive Statistics. Measures of Location. Measures of Variability.
• 2. PROBABILITY. Sample Spaces and Events. Axioms, Interpretations, and Properties of Probability. Counting Techniques. Conditional Probability. Independence.
• 3. DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Random Variables. Probability Distributions for Discrete Random Variables. Expected Values. The Binomial Probability Distribution. Hypergeometric and Negative Binomial Distributions. The Poisson Probability Distribution.
• 4. CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Probability Density Functions. Cumulative Distribution Functions and Expected Values. The Normal Distribution. The Exponential and Gamma Distributions. Other Continuous Distributions. Probability Plots.
• 5. JOINT PROBABILITY DISTRIBUTIONS AND RANDOM SAMPLES. Jointly Distributed Random Variables. Expected Values, Covariance, and Correlation. Statistics and Their Distributions. The Distribution of the Sample Mean. The Distribution of a Linear Combination.
• 6. POINT ESTIMATION. Some General Concepts of Point Estimation. Methods of Point Estimation.
• 7. STATISTICAL INTERVALS BASED ON A SINGLE SAMPLE. Basic Properties of Confidence Intervals. Large-Sample Confidence Intervals for a Population Mean and Proportion. Intervals Based on a Normal Population Distribution. Confidence Intervals for the Variance and Standard Deviation of a Normal Population.
• 8. TESTS OF HYPOTHESIS BASED ON A SINGLE SAMPLE. Hypotheses and Test Procedures. z Tests for Hypotheses About a Population Mean. The One-Sample t Test. Tests Concerning a Population Proportion. Further Aspects of Hypothesis Testing.
• 9. INFERENCES BASED ON TWO SAMPLES. z Tests and Confidence Intervals for a Difference between Two Population Means. The Two-Sample t Test and Confidence Interval. Analysis of Paired Data. Inferences Concerning a Difference between Population Proportions. Inferences Concerning Two Population Variances.
• 10. THE ANALYSIS OF VARIANCE. Single-Factor ANOVA. Multiple Comparisons in ANOVA. More on Single-Factor ANOVA.
• 11. MULTIFACTOR ANALYSIS OF VARIANCE. Two-Factor ANOVA with Kij =
• 1. Two-Factor ANOVA with Kij >
• 1. Three-Factor ANOVA
• 11. 4 2p Factorial Experiments.
• 12. SIMPLE LINEAR REGRESSION AND CORRELATION. The Simple Linear Regression Model. Estimating Model Parameters. Inferences About the Slope Parameter s
• s1. Inferences Concerning Y*x* and the Prediction of Future Y Values. Correlation.
• 13. NONLINEAR AND MULTIPLE REGRESSION. Assessing Model Adequacy. Regression with Transformed Variables. Polynomial Regression. Multiple Regression Analysis. Other Issues in Multiple Regression.
• 14. GOODNESS-OF-FIT TESTS AND CATEGORICAL DATA ANALYSIS. Goodness-of-Fit Tests When Category Probabilities Are Completely Specified. Goodness-of-Fit Tests for Composite Hypotheses. Two-Way Contingency Tables
• 15. DISTRIBUTION-FREE PROCEDURES. The Wilcoxon Signed-Rank Test. The Wilcoxon Rank-Sum Test. Distribution-Free Confidence Intervals. Distribution-Free ANOVA.
• 16. QUALITY CONTROL METHODS. General Comments on Control Charts. Control Charts for Process Location. Control Charts for Process Variation. Control Charts for Attributes. CUSUM Procedures. Acceptance Sampling.
• (source: Nielsen Book Data)

Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition. Always a market favorite, this calculus-based book offers a comprehensive introduction to probability and statistics while demonstrating how to apply concepts, models, and methodologies in today's engineering and scientific workplaces. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations. Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate book, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition also includes graphics and screen shots from SAS(R), MINITAB(R), and Java(TM) Applets to give you a solid perspective of statistics in action.
(source: Nielsen Book Data)

Higher education is coming under increasing scrutiny, both publically and within academia, with respect to its ability to appropriately prepare students for the careers that will make them competitive in the 21st-century workplace. At the same time, there is a growing awareness that many global issues will require creative and critical thinking deeply rooted in the technical STEM (science, technology, engineering, and mathematics) disciplines. However, the existing and ingrained structures of higher education, particularly in the STEM fields, are not set up to provide students with extensive skill development in communication, teamwork, and divergent thinking, which is needed for success in the knowledge economy. In 2011 and again in 2014, an international conference was convened to bring together university leaders, educational policymakers and researchers, and funding agency representatives to discuss the issue of institutional transformation in higher education, particularly in the STEM disciplines. Central to the issue of institutional transformation is the ability to provide new forms of instruction so that students can gain the variety of skills and depth of knowledge they will need. However, radically altering approaches to instruction sets in motion a domino effect that touches on learning space design, instructional technology, faculty training and reward structures, course scheduling, and funding models. In order for one piece to move, there must be coordinated movement in the others, all of which are part of an entrenched and interconnected system. Transforming Institutions brings together chapters from the scholars and leaders who were part of the 2011 and 2014 conferences. It provides an overview of the context and challenges in STEM higher education, contributed chapters describing programs and research in this area, and a reflection and summary of the lessons from the many authors' viewpoints, leading to suggested next steps in the path toward transformation.
(source: Nielsen Book Data)

• Preface.- 1 Introduction to the Geometric Theory of ODEs with Applications to Chemical Processes, Dietrich Flockerzi.- 2 Mathematical Modeling and Analysis of Nonlinear Time-Invariant RLC Circuits, Timo Reis.- 3 Interacting with Networks of Mobile Agents, Magnus Egerstedt, Jean-Pierre de la Croix, Hiroaki Kawashima, and Peter Kingston.- 4 Combinatorial optimization: the interplay of graph theory, linear and integer programming illustrated on network flow, Annegret K. Wagler.- 5 Stoichiometric and Constraint-based Analysis of Biochemical Reaction Networks, Steffen Klamt, Oliver Hadicke and Axel von Kamp.- 6 A Petri Net based Framework for Biomodel Engineering, Mary Ann Blatke, Christian Rohr, Monika Heiner and Wolfgang Marwan.- 7 Hybrid Modeling for Systems Biology: Theory and Practice, Moritz von Stosch, Nuno Carinhas and Rui Oliveira.
• (source: Nielsen Book Data)

This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines. The book originates from the interdisciplinary summer school "Large Scale Networks in Engineering and Life Sciences" hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of interest to mathematicians, engineers, physicists, biologists, chemists, and anyone involved in the network sciences. In particular, due to their introductory nature the chapters can serve individually or as a whole as the basis of graduate courses and seminars, future summer schools, or as reference material for practitioners in the network sciences.
(source: Nielsen Book Data)

• Why Study Scientific Computing?.- Finite Precision Arithmetic.- Linear Systems of Equations.- Interpolation.- Nonlinear Equations.-Least Squares Problems.- Eigenvalue Problems.- Differentiation.- Quadrature.- Numerical Ordinary Differential Equations.- Iterative Methods for Linear Systems.- Optimization.- Bibliography.- Index.
• (source: Nielsen Book Data)

Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple - Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material "hands-on".
(source: Nielsen Book Data)

• Preface
• Introduction
• Notation and symbols
• 1. Polynomials
• 2. Bezier curves
• 3. Rational Bezier curves
• 4. B-splines
• 5. Approximation
• 6. Spline curves
• 7. Multivariate splines
• 8. Surfaces and solids
• 9. Finite elements
• Notes and comments
• Appendix
• Bibliography
• Index.
• (source: Nielsen Book Data)

B-splines are fundamental to approximation and data fitting, geometric modeling, automated manufacturing, computer graphics and numerical simulation. With an emphasis on key results and methods that are most widely used in practice, this book provides a unified introduction to the basic components of B-spline theory: approximation methods, modeling techniques and geometric algorithms. Topics discussed include the Bezier form; approximation and interpolation; error estimates; spline representations of curves, surfaces and solids; hierarchical bases; and finite element simulation. This book is ideal as an advanced undergraduate or first-year graduate text for courses on splines or approximation and geometric modeling for students in mathematics, engineering and computer science. A supplementary web site provides a collection of problems with selected solutions, slides for use in lectures, and programs with demos. This book also represents a valuable resource for practitioners whose work involves B-splines in the context of numerical simulations, computer-aided design, or visualization.
(source: Nielsen Book Data)

• The post-world war ll science and engineering research enterprise
• Adjusting to new playing field
• Recommendations.

This volume tackles a broad set of issues facing the U.S. science and technology communitry.

Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: * Several appendices include related material on integration, important inequalities and identities, frequency-domain transforms, and linear algebra. These topics have been included so that the book is relatively self-contained. One appendix contains an extensive summary of 33 random variables and their properties such as moments, characteristic functions, and entropy. * Unlike most books on probability, numerous figures have been included to clarify and expand upon important points. Over 600 illustrations and MATLAB plots have been designed to reinforce the material and illustrate the various characterizations and properties of random quantities. * Sufficient statistics are covered in detail, as is their connection to parameter estimation techniques. These include classical Bayesian estimation and several optimality criteria: mean-square error, mean-absolute error, maximum likelihood, method of moments, and least squares. * The last four chapters provide an introduction to several topics usually studied in subsequent engineering courses: communication systems and information theory; optimal filtering (Wiener and Kalman); adaptive filtering (FIR and IIR); and antenna beamforming, channel equalization, and direction finding. This material is available electronically at the companion website. Probability, Random Variables, and Random Processes is the only textbook on probability for engineers that includes relevant background material, provides extensive summaries of key results, and extends various statistical techniques to a range of applications in signal processing.
(source: Nielsen Book Data)

• Introduction / Katherine O'Clair and Jeanne Davidson
• Engineering / Sheila Young
• Life and health sciences / Elizabeth (Betsy) Hopkins
• Chemistry / Olivia Bautista Sparks
• Human nutrition / Rebecca K. Miller
• Patents / John J. Meier
• Interdisciplinary science courses : remote sensing / Linda Blake and Timothy A. Warner
• Community colleges / Amanda Bird and Anna Montgomery Johnson.

• ch. 1.
• Modeling methodology using COMSOL Multiphysics 4.x --ch. 2. Materials properties using COMSOL Multiphysics 4.x --ch. 3. 0D electrical circuit interface modeling using COMSOL Multiphysics 4.x --ch. 4. 1D modeling using COMSOL Multiphysics 4.x --ch. 5. 2D modeling using COMSOL Multiphysics 4.x --ch. 6. 2D axisymmetric modeling using COMSOL Multiphysics 4.x --ch. 7. 2D simple mixed mode modeling using COMSOL Multiphysics 4.x --ch. 8. 2D complex mixed mode modeling using COMSOL Multiphysics 4.x --ch. 9. 3D modeling using COMSOL Multiphysics 4.x --ch. 10. Perfectly matched layer models using COMSOL Multiphysics 4.x --ch. 11. Bioheat models using COMSOL Multiphysics 4.x.

• 1. Basic concepts
• 2. Thermodynamic properties
• 3. Energy and energy transport
• 4. General application of the first law
• 5. The second law of thermodynamics
• 6. Entropy
• 7. Exergy
• 8. Power cycles
• 9. Refrigeration and heat pump cycles
• 10. Property relations for pure fluids
• 11. Mixtures and multi-component phase equilibrium
• 12. Psychometrics
• 13. Combustion
• 14. Chemical equilibrium
• 15. Statistical thermodynamics
• 16. Compressible flow.
• (source: Nielsen Book Data)

This book differs from other thermodynamics texts in its objective which is to provide engineers with the concepts, tools, and experience needed to solve practical real-world energy problems. The presentation integrates computer tools (e.g., EES) with thermodynamic concepts to allow engineering students and practising engineers to solve problems they would otherwise not be able to solve. The use of examples, solved and explained in detail, and supported with property diagrams that are drawn to scale, is ubiquitous in this textbook. The examples are not trivial, drill problems, but rather complex and timely real world problems that are of interest by themselves. As with the presentation, the solutions to these examples are complete and do not skip steps. Similarly the book includes numerous end of chapter problems, both typeset and online. Most of these problems are more detailed than those found in other thermodynamics textbooks. The supplements include complete solutions to all exercises, software downloads, and additional content on selected topics. These are available at the book web site www.cambridge.org/KleinandNellis.
(source: Nielsen Book Data)

• Overview
• Form and structure
• Process and time
• Compare and contrast
• Case studies
• Interactive graphics
• Visual index
• Appendix.

Any scientist or engineer who communicates research results will immediately recognize this practical handbook as an indispensable tool. The guide sets out clear strategies and offers abundant examples to assist researchers-even those with no previous design training-with creating effective visual graphics for use in multiple contexts, including journal submissions, grant proposals, conference posters, or presentations. Visual communicator Felice Frankel and systems biologist Angela DePace, along with experts in various fields, demonstrate how small changes can vastly improve the success of a graphic image. They dissect individual graphics, show why some work while others don't, and suggest specific improvements. The book includes analyses of graphics that have appeared in such journals as Science, Nature, Annual Reviews, Cell, PNAS, and the New England Journal of Medicine, as well as an insightful personal conversation with designer Stefan Sagmeister and narratives by prominent researchers and animators.
(source: Nielsen Book Data)

• MATHEMATICS Arithmetic and Elementary Algebra Elementary Functions Elementary Geometry Analytic Geometry Algebra Limits and Derivatives Integrals Series Functions of Complex Variables Integral Transforms Ordinary Differential Equations Partial Differential Equations Special Functions and Their Properties Probability Theory PHYSICS Physical Foundations of Mechanics Molecular Physics and Thermodynamics Electrodynamics Oscillations and Waves Optics Quantum Mechanics. Atomic Physics Quantum Theory of Crystals Elements of Nuclear Physics ELEMENTS OF APPLIED AND ENGINEERING SCIENCES Dimensions and Similarity Mechanics of Point Particles and Rigid Bodies Elements of Strength of Materials Hydrodynamics Mass and Heat Transfer Electrical Engineering Empirical and Engineering Formulas and Criteria for Their Applicability SUPPLEMENTS Integrals Integral Transforms Orthogonal Curvilinear Systems of Coordinates Ordinary Differential Equations Some Useful Electronic Mathematical Resources Index References appear at the end of each chapter.
• (source: Nielsen Book Data)

A Concise Handbook of Mathematics, Physics, and Engineering Sciences takes a practical approach to the basic notions, formulas, equations, problems, theorems, methods, and laws that most frequently occur in scientific and engineering applications and university education. The authors pay special attention to issues that many engineers and students find difficult to understand. The first part of the book contains chapters on arithmetic, elementary and analytic geometry, algebra, differential and integral calculus, functions of complex variables, integral transforms, ordinary and partial differential equations, special functions, and probability theory. The second part discusses molecular physics and thermodynamics, electricity and magnetism, oscillations and waves, optics, special relativity, quantum mechanics, atomic and nuclear physics, and elementary particles. The third part covers dimensional analysis and similarity, mechanics of point masses and rigid bodies, strength of materials, hydrodynamics, mass and heat transfer, electrical engineering, and methods for constructing empirical and engineering formulas. The main text offers a concise, coherent survey of the most important definitions, formulas, equations, methods, theorems, and laws. Numerous examples throughout and references at the end of each chapter provide readers with a better understanding of the topics and methods. Additional issues of interest can be found in the remarks. For ease of reading, the supplement at the back of the book provides several long mathematical tables, including indefinite and definite integrals, direct and inverse integral transforms, and exact solutions of differential equations.
(source: Nielsen Book Data)

• 1. Basic principles of reliability, human error, and other general issues
• 2. Mathematical calculations
• 3. Basic issues concerning hardware systems
• 4. Obtaining items from commercial sources
• 5. General points regarding the design and construction of apparatus
• 6. Vacuum system leaks and related problems
• 7. Vacuum pumps and gauges, and other vacuum-system concerns
• 8. Mechanical devices and systems
• 9. Cryogenic systems
• 10. Visible and near-visible optics
• 11. Electronic systems
• 12. Interconnecting, wiring, and cabling for electronics
• 13. Computer hardware and software, and stored information
• 14. Experimental method.
• (source: Nielsen Book Data)

Covering many techniques widely used in research, this book will help researchers in the physical sciences and engineering solve troublesome - and potentially very time consuming - problems in their work. The book deals with technical difficulties that often arise unexpectedly during the use of various common experimental methods, as well as with human error. It provides preventive measures and solutions for such problems, thereby saving valuable time for researchers. Some of the topics covered are: sudden leaks in vacuum systems, electromagnetic interference in electronic instruments, vibrations in sensitive equipment, and bugs in computer software. The book also discusses mistakes in mathematical calculations, and pitfalls in designing and carrying out experiments. Each chapter contains a summary of its key points, to give a quick overview of important potential problems and their solutions in a given area.
(source: Nielsen Book Data)

• The Iterative Modeling Process and Inverse Problems
• Statistical Hypothesis Testing in Inverse Problems
• Mass Balance and Mass Transport
• Heat Conduction
• Force/Moments Balance (Structural Modeling)
• Wave Equations
• Size-Structured Population Models
• Appendices: An Introduction to Fourier Techniques, Fourier Series, Fourier Transforms, Review of Vector Calculus.
• (source: Nielsen Book Data)

Through several case study problems from industrial and scientific research laboratory applications, "Mathematical and Experimental Modeling of Physical and Biological Processes" provides students with a fundamental understanding of how mathematics is applied to problems in science and engineering. For each case study problem, the authors discuss why a model is needed and what goals can be achieved with the model. Exploring what mathematics can reveal about applications, the book focuses on the design of appropriate experiments to validate the development of mathematical models. It guides students through the modeling process, from empirical observations and formalization of properties to model analysis and interpretation of results. The authors also describe the hardware and software tools used to design the experiments so faculty/students can duplicate them. Integrating real-world applications into the traditional mathematics curriculum, this textbook deals with the formulation and analysis of mathematical models in science and engineering. It gives students an appreciation of the use of mathematics and encourages them to further study the applied topics.
(source: Nielsen Book Data)

• PART 1: General Techniques
• PART 2: Data Analysis
• PART 3: Plotting Data
• PART 4: Regression Analysis
• PART 5: Statistical Analysis INDEX.
• (source: Nielsen Book Data)

With examples from the world of science and engineering, this reference teaches scientists how to create graphs, analyze statistics and regressions, and plot and organize scientific data. Physicists and engineers can learn the tips and techniques of Excel-and tailor them specifically to their experiments, designs, and research. They will learn when to use NORMDIST vs NORMSDist and CONFIDENCE vs Z, how to keep data-validation lists on a hidden worksheet, use pivot tables to chart frequency distribution, generate random samples with various characteristics, and much more. Ideal for students and professionals alike, this handbook will enable greater productivity and efficiency.
(source: Nielsen Book Data)

• Sampling and descriptive statistics
• Probability
• Propagation of error
• Commonly used distributions
• Confidence intervals
• Hypothesis testing
• Correlation and simple linear regression
• Multiple regression
• Factorial experiments
• Statistical quality control.

• Preface.
• 1. Introduction.
• 2. Probability Basics.
• 3. Statistics Basics.
• 4. Bayesian Statistics.
• 5. Order Statistics.
• 6. Goodness of Fit.
• 7. Rank Tests.
• 8. Designed Experiments.
• 9. Categorical Data.
• 10. Estimating Distribution Functions.
• 11. Density Estimation.
• 12. Beyond Linear Regression.
• 13. Curve Fitting Techniques.
• 14. Wavelets.
• 15. Bootstrap.
• 16. EM Algorithm.
• 17. Statistical Learning.
• 18. Nonparametric Bayes. A. MATLAB. B. WinBUGS. MATLAB Index. Author Index. Subject Index.
• (source: Nielsen Book Data)

This is a thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics. This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. "Nonparametric Statistics with Applications to Science and Engineering" begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.
(source: Nielsen Book Data)

For engineering statistics courses in departments of Statistics and Engineering. This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitalby, once these studenrts graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials. The assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus. Datasets and other resources (where applicable) for this book are available here.
(source: Nielsen Book Data)

This book will be an important resource for both new graduates and mid-career scientists, engineers, and technicians. Through taking stock of existing or desired skills and goals, it provides both general advice and concrete examples to help assess a current job situation or prospect, and to effectively pursue and attain new ones. Many examples of properly adapted resumes and interview techniques, as well as plenty of practical advice about adaptation to new workplace cultural paradigms, such as team-based management, make this book an invaluable reference for the professional scientist in today's volatile job market.
(source: Nielsen Book Data)

• Career Transformations. Career Well Being: Your Career Well Being. Internal Hindrances to Career Transitions. Trained Incapacity Among Professionals. Even the Best of Times. Beyond Credentialism. Greener Pastures? On Behalf of Integrity, Ambition, and Self-Marketing. Career Renewal: What to Ask Yourself When Developing a Career. Career Decision-Making Patterns. Values: Personal Priorities. Skills. A Preliminary Career Check-List: Taking Your Temperature. Non-Traditional Careers Using Science/Technology Skills. Your Interests: Future Skills Development. Career Options Exploration Research and Trend-Tracking. Quintessential Informational Interviews. Biographies are Better than Resumes for Contacts. Exponential Interviews, Mentors, Recruiters, and Career Counselors. Job Search Research: Get Real Before You Go Virtual. Letters: Cover, Contact, Thank You, Unorthodox. The Lengthy Process of Resume R&D. Preparation for Job Interviews, Negotiations, and Decisions. Career Transition Update: Where Are You Now? Good Career Planning Habits and Hygiene. Appendices: Career Search Selection Criteria. Total Compensation Summary Checklist. Reference/Research Material. Selected Books to Help You Explore Your Career Options. Use and Misuse of the Internet for Career Transitions. An Actual Online Search by a Real Scientist Undergoing a Real Career Transition. Subject Index.
• (source: Nielsen Book Data)

Career Renewal is a practical career guide which shows you how to get the job you want. Designed specifically for scientists, engineers, and other medical and legal professionals, this book contains the information you need to rejuvenate your career. It will help you find a satisfying career in today's market. It includes numerous assessment surveys, identifies career resources for professional networking, outlines how to write a winning resume, and features numerous personal case histories of those who have successfully made the transition from academia to the business world. The authors' step-by-step techniques have been field-tested on thousands and will help you to discover new career perspective.
(source: Nielsen Book Data)

Presents the facts, history, names and dates behind 1250 major accomplishments in science and technology. Each subject is covered in 150-600 words, and may be found through any one of four indexes: personal name; chronological; geographical; and field of study.
(source: Nielsen Book Data)

Not only will this bilingual glossary save time, but users will find the terms easy to look up, pronounce and understand. Covers 120 subject fields. There are 3,000 chemical, 1,600 mathematical, 3,700 physics, 900 computer and logic, 3,200 engineering and 3,700 biological terms. Includes numerous words used in light of today's ecology and features ''kanji'' (Chinese characters) and ''kana'' (Japanese letters).
(source: Nielsen Book Data)

• Not Obtainable.
• (source: Nielsen Book Data)

When a translator of scientific and technical literature from Russian into English seeks the counterpart of some specialized term he turns to a dictionary or an original source in English. But terms are not the whole problem. They must be couched in the language of the particular branch of science or technology. A translation should be free of unidiomatic or amateurish passages. "The right word in the right place" is the translators' motto". The present dictionary is an attempt to supply word combinations and expressions that may be of help in achieving this aim. It is not a dictionary of terms or idioms, but a collection of typical examples from scientific and technical sources. The words that make up the combinations are usually common to a number of branches of science and technology. The remaining words of illustrative context are not so important since they are only meant as "fillers" to link the combination elements together. The user's attention should be focussed on the words in bold type. The system of arrangement is strictly alphabetical (hyphenated combinations are considered as one word), but there are many cross-references to assist the user. These are given merely for general guidance and the translator should not confine himself to the item referred to, but should examine carefully the entry in question and several adjacent entries. Synonymous words or expressions are given in brackets.
(source: Nielsen Book Data)