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Topics in Mathematical Modeling is an introductory textbook on mathematical modeling. The book teaches how simple mathematics can help formulate and solve real problems of current research interest in a wide range of fields, including biology, ecology, computer science, geophysics, engineering, and the social sciences. Yet the prerequisites are minimal: calculus and elementary differential equations. Among the many topics addressed are HIV; plant phyllotaxis; global warming; the World Wide Web; plant and animal vascular networks; social networks; chaos and fractals; marriage and divorce; and El Niño. Traditional modeling topics such as predator-prey interaction, harvesting, and wars of attrition are also included. Most chapters begin with the history of a problem, follow with a demonstration of how it can be modeled using various mathematical tools, and close with a discussion of its remaining unsolved aspects. Designed for a one-semester course, the book progresses from problems that can be solved with relatively simple mathematics to ones that require more sophisticated methods. The math techniques are taught as needed to solve the problem being addressed, and each chapter is designed to be largely independent to give teachers flexibility. The book, which can be used as an overview and introduction to applied mathematics, is particularly suitable for sophomore, junior, and senior students in math, science, and engineering.

This collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena. Topics covered include stochastic evolutionary models of cancer initiation and progression, tumor cords and their response to anticancer agents, and immune competition in tumor progression and prevention. The complexity of modeling living matter requires the development of new mathematical methods and ideas. This volume, written by first-rate researchers in the field of mathematical biology, is one of the first steps in that direction.

This collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena. Topics covered include stochastic evolutionary models of cancer initiation and progression, tumor cords and their response to anticancer agents, and immune competition in tumor progression and prevention. The complexity of modeling living matter requires the development of new mathematical methods and ideas. This volume, written by first-rate researchers in the field of mathematical biology, is one of the first steps in that direction.

219 pages. 9.92x7.05x0.59 inches. In Stock.

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This textbook mainly addresses beginners and readers with a basic knowledge of object-oriented programming languages like Java or C#, but with little or no modeling or software engineering experience – thus reflecting the majority of students in introductory courses at universities. Using UML, it introduces basic modeling concepts in a highly precise manner, while refraining from the interpretation of rare special cases. After a brief explanation of why modeling is an indispensable part of software development, the authors introduce the individual diagram types of UML (the class and object diagram, the sequence diagram, the state machine diagram, the activity diagram, and the use case diagram), as well as their interrelationships, in a step-by-step manner. The topics covered include not only the syntax and the semantics of the individual language elements, but also pragmatic aspects, i.e., how to use them wisely at various stages in the software development process. To this end, the work is complemented with examples that were carefully selected for their educational and illustrative value.Overall, the book provides a solid foundation and deeper understanding of the most important object-oriented modeling concepts and their application in software development. An additional website offers a complete set of slides to aid in teaching the contents of the book, exercises and further e-learning material.

This textbook mainly addresses beginners and readers with a basic knowledge of object-oriented programming languages like Java or C#, but with little or no modeling or software engineering experience – thus reflecting the majority of students in introductory courses at universities. Using UML, it introduces basic modeling concepts in a highly precise manner, while refraining from the interpretation of rare special cases. After a brief explanation of why modeling is an indispensable part of software development, the authors introduce the individual diagram types of UML (the class and object diagram, the sequence diagram, the state machine diagram, the activity diagram, and the use case diagram), as well as their interrelationships, in a step-by-step manner. The topics covered include not only the syntax and the semantics of the individual language elements, but also pragmatic aspects, i.e., how to use them wisely at various stages in the software development process. To this end, the work is complemented with examples that were carefully selected for their educational and illustrative value.Overall, the book provides a solid foundation and deeper understanding of the most important object-oriented modeling concepts and their application in software development. An additional website offers a complete set of slides to aid in teaching the contents of the book, exercises and further e-learning material.

Presents critical accounts of heterocyclic compounds. Topics include applications of flexible molecular descriptors in the QSPR-QSAR study of heterocyclic drugs; predicting pharmacological and toxicological activity of heterocyclic compounds using QSAR and molecular modeling; and more. For researchers.

This classroom-tested textbook provides an accessible introduction to the design, formal modeling, and analysis of distributed computer systems. The book uses Maude, a rewriting logic-based language and simulation and model checking tool, which offers a simple and intuitive modeling formalism that is suitable for modeling distributed systems in an attractive object-oriented and functional programming style.Topics and features: introduces classical algebraic specification and term rewriting theory, including reasoning about termination, confluence, and equational properties; covers object-oriented modeling of distributed systems using rewriting logic, as well as temporal logic to specify requirements that a system should satisfy; provides a range of examples and case studies from different domains, to help the reader to develop an intuitive understanding of distributed systems and their design challenges; examples include classic distributed systems such as transport protocols, cryptographic protocols, and distributed transactions, leader election, and mutual execution algorithms; contains a wealth of exercises, including larger exercises suitable for course projects, and supplies executable code and supplementary material at an associated website.This self-contained textbook is designed to support undergraduate courses on formal methods and distributed systems, and will prove invaluable to any student seeking a reader-friendly introduction to formal specification, logics and inference systems, and automated model checking techniques.

Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.

Thoroughly revised and updated in this second edition, The Engineering of Chemical Reactions focuses explicitly on developing the skills necessary to design a chemical reactor for any application, including chemical production, materials processing, and environmental modeling. This edition also features two new chapters on biological and environmental reaction engineering that provide an exciting introduction to these increasingly important areas of today's chemical engineering market.Streamlined to enhance the logical flow of the subject, The Engineering of Chemical Reactions, 2/e, is easy for instructors to navigate and students to follow. Using real reactions from chemical engineering, the first seven chapters cover such fundamentals as multiple reactions, energy management, and catalytic processes. The final five chapters explore more advanced topics including environmental, polymer, solids processing, biological, and combustion reactions. Practical, real-world examples throughout the text consider reactor and process choices in ways that encourage students to think creatively and build on previous knowledge.The Engineering of Chemical Reactions, 2/e, is ideal for upper-level undergraduate courses in chemical reactor engineering, chemical reactor design, and kinetics.

Thoroughly revised and updated in this second edition, The Engineering of Chemical Reactions focuses explicitly on developing the skills necessary to design a chemical reactor for any application, including chemical production, materials processing, and environmental modeling. This edition also features two new chapters on biological and environmental reaction engineering that provide an exciting introduction to these increasingly important areas of today's chemical engineering market.Streamlined to enhance the logical flow of the subject, The Engineering of Chemical Reactions, 2/e, is easy for instructors to navigate and students to follow. Using real reactions from chemical engineering, the first seven chapters cover such fundamentals as multiple reactions, energy management, and catalytic processes. The final five chapters explore more advanced topics including environmental, polymer, solids processing, biological, and combustion reactions. Practical, real-world examples throughout the text consider reactor and process choices in ways that encourage students to think creatively and build on previous knowledge.The Engineering of Chemical Reactions, 2/e, is ideal for upper-level undergraduate courses in chemical reactor engineering, chemical reactor design, and kinetics.

Help your child get ahead of the curve with this fun, vibrant workbook! Created by IXL, a trusted leader in math education, this workbook covers the must-know decimal skills for fifth graders, from modeling and comparison to adding, subtracting, multiplying, and dividing with decimals. Our instructional guidance and relevant, real-world content provide the tools your child needs to learn new concepts independently. And, you'll feel confident knowing our carefully crafted material is setting them up for success in the classroom and beyond.

Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.

The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines.

The Second Edition of this classic text introduces the main methods, techniques, and issues involved in carrying out multilevel modeling and analysis. Snijders and Boskers? book is an applied, authoritative, and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book has been comprehensively revised and updated since the last edition, and now includes guides to modeling using Hlm, MlwiN, Sas, Stata including Gllamm, R, Spss, Mplus, WinBugs, Latent Gold, and Mix.

Based on the research that has been conducted at Wharton Risk Management Center over the past five years on catastrophic risk. Covers a hot topic in the light of recent terroristic activities and nature catastrophes. Develops risk management strategies for reducing and spreading the losses from future disasters. Provides glossary of definitions and terms used throughout the book.

Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and Matlab™.

Looking for an easy-to-understand text to guide you through the tough topic of regression modeling? INTRODUCTION TO REGRESSION MODELING (WITH CD-ROM) offers a blend of theory and regression applications and will give you the practice you need to tackle this subject through exercises, case studies. and projects that have you identify a problem of interest and collect data relevant to the problem's solution. The book goes beyond linear regression by covering nonlinear models, regression models with time series errors, and logistic and Poisson regression models.

Based on the research that has been conducted at Wharton Risk Management Center over the past five years on catastrophic risk. Covers a hot topic in the light of recent terroristic activities and nature catastrophes. Develops risk management strategies for reducing and spreading the losses from future disasters. Provides glossary of definitions and terms used throughout the book.