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Amir R. Khoei ... 584 pages - Publisher: Wiley; (February, 2015) ... Language: English - ISBN-10: 1118457684 - ISBN-13: 978-1118457689.

The finite element method (FEM) technique has been developed to simulate and analyze complex engineering problems. However, there are a number of drawbacks with finite element simulation of discontinuous problems, such as fracture mechanics problems, including the computational cost of a very fine finite element mesh and the complex remeshing strategy in capturing discontinuity. The extended finite element method (XFEM) has therefore been developed to improve the performance of the conventional finite element method in discontinuity problems. Extended Finite Element Method: Theory and Applications introduces the theory and applications of XFEM in the linear and nonlinear problems of continua, structures, and geomechanics. It begins by introducing the concept of a partition of unity, various enrichment functions, and fundamentals of XFEM formulation. It then covers the theory and application of XFEM in large deformations, plasticity, and contact problems. The implementation of XFEM in fracture mechanics, including linear, cohesive, and ductile crack propagation, is also covered. Finally, the theory and applications of XFEM in multiphase fluid flow, including hydraulic fracturing in soil saturated media and crack propagation in thermo-hydro-mechanical porous media, are discussed in detail. Key features: Comprehensively introduces XFEM analysis + Explains the theory and applications of XFEM in various continuum and geo-mechanical problems + Includes worked examples + Accompanied by a website hosting source code and examples. Extended Finite Element Method: Theory and Applications is a comprehensive introduction to XFEM analysis for researchers and practitioners in industry, and is also an ideal textbook for graduate students in mechanical and civil engineering.ccompanied by a website hosting source code and examples

Mohammad Karamouz ... 924 pages - Language: English - Publisher: CRC Press; (December, 2021) - AmazonSIN: ‎B09LR3V8QJ.

This book presents three distinct pillars for analysis, design, and planning: urban water cycle and variability as the state of water being; landscape architecture as the medium for built-by-design; and total systems as the planning approach. The increasing demand for water and urban and industrial expansions have caused myriad environmental, social, economic, and political predicaments. More frequent and severe floods and droughts have changed the resiliency and ability of water infrastructure systems to operate and provide services to the public. These concerns and issues have also changed the way we plan and manage our water resources. Focusing on urban challenges and contexts, the book provides foundational information regarding water science and engineering while also examining topics relating to urban stormwater, water supply, and wastewater infrastructures. It also addresses critical emerging issues such as simulation and economic modeling, flood resiliency, environmental visualization, satellite data applications, and digital data model (DEM) advancements.

Features: Explores various theoretical, practical, and real-world applications of system analysis, design, and planning of urban water infrastructures + Discusses hydrology, hydraulics, and basic laws of water flow movement through natural and constructed environments + Describes a wide range of novel topics ranging from water assets, water economics, systems analysis, risk, reliability, and disaster management + Examines the details of hydrologic and hydrodynamic modeling and simulation of conceptual and data-driven models + Delineates flood resiliency, environmental visualization, pattern recognition, and machine learning attributes + Explores a compilation of tools and emerging techniques that elevate the reader to a higher plateau in water and environmental systems management.

Water Systems Analysis, Design, and Planning: Urban Infrastructure serves as a useful resource for advanced undergraduate and graduate students taking courses in the areas of water resources and systems analysis, as well as practicing engineers and landscape professionals.

Igor Griva, Stephen G. Nash, Ariela Sofer ... 764 pages - Publisher: Society for Industrial Mathematics; 2nd edition (December, 2008) ... Language: English - ISBN-10: 0898716616 - ISBN-13: 978-0898716610.

This book introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. Part I of Linear and Nonlinear Optimization, Second Edition provides fundamentals that can be taught in whole or in part at the beginning of a course on either topic and then referred to as needed. Part II on linear programming and Part III on unconstrained optimization can be used together or separately, and Part IV on nonlinear optimization can be taught without having studied the material in Part II. In the preface the authors suggest course outlines that can be adjusted to the requirements of a particular course on both linear and nonlinear optimization, or to separate courses on these topics. Three appendices provide information on linear algebra, other fundamentals, and software packages for optimization problems. A supplemental website offers auxiliary data sets that are necessary for some of the exercises.

Audience: This book is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate and graduate students. It is also appropriate as a tutorial for researchers and practitioners who need to understand the modern algorithms of linear and nonlinear optimization to apply them to problems in science and engineering. Contents: Preface; Part I: Basics; Chapter 1: Optimization Models; Chapter 2: Fundamentals of Optimization; Chapter 3: Representation of Linear Constraints; Part II: Linear Programming; Chapter 4: Geometry of Linear Programming; Chapter 5: The Simplex Method; Chapter 6: Duality and Sensitivity; Chapter 7: Enhancements of the Simplex Method; Chapter 8: Network Problems; Chapter 9: Computational Complexity of Linear Programming; Chapter 10: Interior-Point Methods of Linear Programming; Part III: Unconstrained Optimization; Chapter 11: Basics of Unconstrained Optimization; Chapter 12: Methods for Unconstrained Optimization; Chapter 13: Low-Storage Methods for Unconstrained Problems; Part IV: Nonlinear Optimization; Chapter 14: Optimality Conditions for Constrained Problems; Chapter 15: Feasible-Point Methods; Chapter 16: Penalty and Barrier Methods; Part V: Appendices; Appendix A: Topics from Linear Algebra; Appendix B: Other Fundamentals; Appendix C: Software; Bibliography; Index

Wenyu Sun, Ya-Xiang Yuan ... 688 pages - Publisher: Springer; (May, 2006) ... Language: English - ISBN-10: 0387249753 - ISBN-13: 978-0387249759.

This book, a result of the author's teaching and research experience in various universities and institutes over the past ten years, can be used as a textbook for an optimization course for graduates and senior undergraduates. It systematically describes optimization theory and several powerful methods, including recent results. For most methods, the authors discuss an idea’s motivation, study the derivation, establish the global and local convergence, describe algorithmic steps, and discuss the numerical performance. The book deals with both theory and algorithms of optimization concurrently. It also contains an extensive bibliography. Finally, apart from its use for teaching, Optimization Theory and Methods will be very beneficial as a research reference.

Dusan Teodorovic, Milan Janic ... 900 pages - Publisher: Butterworth-Heinemann; (October, 2016) - Language: ‎English - ISBN-10: 0128038187 - ISBN-13: 978-0128038185.


Transportation Engineering: Theory, Practice and Modeling is a guide for integrating multi-modal transportation networks and assessing their potential cost and impact on society and the environment. Clear and rigorous in its coverage, the authors begin with an exposition of theory related to traffic engineering and control, transportation planning, and an evaluation of transportation alternatives that is followed by models and methods for predicting travel and freight transportation demand, analyzing existing and planning new transportation networks, and developing traffic control tactics and strategies. Written by an author team with over thirty years of experience in both research and teaching, the book incorporates both theory and practice to facilitate greener solutions.

Richard W. Hamming ... Publisher: ‎Dover Publications; (November, 2004) - Language:‎ English - 880 pages - ISBN-10:‎ 0486439453 - ISBN-13:‎ 978-0486439457.


Understanding calculus is vital to the creative applications of mathematics in numerous areas. This text focuses on the most widely used applications of mathematical methods, including those related to other important fields such as probability and statistics. The four-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. In addition to three helpful appendixes, the text features answers to some of the exercises. Appropriate for advanced undergraduates and graduate students, it is also a practical reference for professionals. 1985 edition. 310 figures. 18 tables.

Jon Krohn, Grant Beyleveld, Aglaé Bassens ... Publisher: ‎ Addison-Wesley Professional; (September, 2019) - Language: ‎ English - 416 pages - ISBN-10: ‎ 0135116694 - ISBN-13: ‎ 978-0135116692.

Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical professionals and students want to start leveraging its power, but previous books on deep learning have often been non-intuitive, inaccessible, and dry. In Deep Learning Illustrated, three world-class instructors and practitioners present a uniquely visual, intuitive, and accessible high-level introduction to the techniques and applications of deep learning. Packed with vibrant, full-color illustrations, it abstracts away much of the complexity of building deep learning models, making the field more fun to learn, and accessible to a far wider audience.

Part I’s high-level overview explains what Deep Learning is, why it has become so ubiquitous, and how it relates to concepts and terminology such as Artificial Intelligence, Machine Learning, Artificial Neural Networks, and Reinforcement Learning. These opening chapters are replete with vivid illustrations, easy-to-grasp analogies, and character-focused narratives. Building on this foundation, the authors then offer a practical reference and tutorial for applying a wide spectrum of proven deep learning techniques. Essential theory is covered with as little mathematics as possible, and illuminated with hands-on Python code. Theory is supported with practical “run-throughs” available in accompanying Jupyter notebooks, delivering a pragmatic understanding of all major deep learning approaches and their applications: machine vision, natural language processing, image generation, and videogaming. To help readers accomplish more in less time, the authors feature several of today’s most widely-used and innovative deep learning libraries, including TensorFlow and its high-level API, Keras; PyTorch, and the recently-released high-level Coach, a TensorFlow API that abstracts away the complexity typically associated with building Deep Reinforcement Learning algorithms.

Ann Lehman, Norm O'Rourke, Larry Hatcher, Edward J. Stepanski ... 481 pages - Language: ‎ English - Publisher: ‎ SAS Institute; (February, 2005) - ISBN-10: ‎1590475763 - ISBN-13: 978-1590475768.


Doing statistics in JMP has never been easier! Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide, authored by Ann Lehman, Norm O'Rourke, Larry Hatcher, and Edward Stepanski. Clearly written instructions guide you through the basic concepts of research and data analysis, enabling you to easily perform statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results, perform a wide range of JMP analyses, interpret the results, and more. Topics include: screening data for errors and selecting subsets with the JMP Distribution platform, computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale, performing bivariate analyses for all types of variables, performing a one-way analysis of variance (ANOVA), performing a multiple regression, and using the JMP Fit Model platform to perform a one-way multivariate analysis of variance (MANOVA). This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.

Cameron Davidson-Pilon  ... 256 pages - Publisher: ‎Addison-Wesley Professional; (October, 2015) - Language: English -  ISBN-10: 0133902838 - ISBN-13: 978-0133902839.

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention.

Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects.

Coverage includes: • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available.

Randall Pruim ... 820 pages - Publisher: American Mathematical Society; 2nd Edition (April, 2018) - Language: English - ISBN-10: ‎1470428482 - ISBN-13: 978-1470428488.

Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment $\textsf{R}$ is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations.

Subal C. Kumbhakar, Hung-Jen Wang, Alan P. Horncastle ... 374 pages - Language: ‎ English - Publisher: ‎ Cambridge Univ. Press; (January, 2015) - ISBN-10: ‎ 1107609461 - ISBN-13: 978-1107609464.


Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.

Rémy Lentzner ... 111 pages - Language: ‎English - Publisher: Remylent; (April, 2021).

Excel makes life easier because its powerful functions are easily accessible. With the spreadsheet you can handle numbers, dates, formulas or simply text. This book will be an asset to improve your skills by learning more complex functions and finally to save a lot of time. The examples presented in this manual will help you to analyse data better. Do not hesitate to test them in order to discover excel's strengths. It reflects real management situations. You can reproduce them with all Excel versions. Accessible to all, this manual guides you, step by step, to increase your knowledge.

Russell Hibbeler ... 923 pages - Language: English - ISBN-10: 1292247304 - ISBN-13: 978-1292247304.

For Fluid Mechanics courses found in Civil and Environmental, General Engineering, and Engineering Technology and Industrial Management departments.Fluid Mechanics is intended to provide a comprehensive guide to a full understanding of the theory and many applications of fluid mechanics. The text features many of the hallmark pedagogical aids unique to Hibbeler texts, including its student-friendly, clear organization. The text supports the development of student problem-solving skills through a large variety of problems, representing a broad range of engineering disciplines that stress practical, realistic situations encountered in professional practice, and provide varying levels of difficulty. The text offers flexibility in that basic principles are covered in chapters 1-6, and the remaining chapters can be covered in any sequence without the loss of continuity.Updates to the 2nd Edition result from comments and suggestions from colleagues, reviewers in the teaching profession, and many of the author’s students, and include expanded topic coverage and new Example and Fundamental Problems intended to further students’ understanding of the theory and its applications.Pearson Mastering™ Engineering is not included. Students, if Pearson Mastering Engineering is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Mastering Engineering should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.Reach every student by pairing this text with Pearson Mastering EngineeringMastering is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, Mastering personalizes the learning experience and improves results for each student.

Jeffrey C. Evans, Michael A. Malusis ... 576 pages - Publisher: CRC Press; (March, 2017) ... Language: English - ISBN-10: 0415695155 - ISBN-13: 978-0415695152.

Ground improvement has been one of the most dynamic and rapidly evolving areas of geotechnical engineering over the past forty years. Moreover, increasing development of sites with marginal soils has made ground improvement an increasingly important core component of geotechnical engineering curricula. This textbook addresses the latest and most effective techniques for ground improvement, at a level designed for undergraduate and graduate-level university students and practitioners seeking fundamental background in these techniques. Thus, Fundamentals of Ground Improvement Engineering is for students and professionals. The book is written to, first, broadly introduce key ground improvement methods and, second, to provide readers with a thorough understanding of the theory, design principles, and construction approaches that underpin each method. Major topic areas covered include compaction, grouting, vibratory methods, soil mixing, stabilization and solidification, cut-off walls, dewatering, consolidation, geosynthetics, and earth retention. The book contains numerous problems and worked examples, and is well illustrated with photographs, schematics, charts and graphs.The rich companion website provides instructor resources and videos of the techniques, which are useful for students and for professionals to show clients.

T.J. Quirk ... 264 Pages - Language: ‎English - Publisher: ‎Springer; 2nd edition (March, 2021).


This textbook is a step-by-step guide for high school, community college, and undergraduate students who are taking a course in applied statistics and wish to learn how to use Excel to solve statistical problems. All of the statistics problems in this book come from the following fields of study: business, education, psychology, marketing, engineering and advertising. Students will learn how to perform key statistical tests in Excel without being overwhelmed by statistical theory.Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific statistics problems. The book offers guidance in using Excel in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel’s drop-down formula menus (e.g., simple linear regression, multiple correlations and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along with their solutions in an appendix. An additional practice test allows readers to test their understanding of each chapter by attempting to solve a specific statistics problem using Excel; the solution to each of these problems is also given in an appendix. This book is a tool that can be used either by itself or along with any good statistics book.​

Ahmed Sheikh ... 92 pages - Language: English - Publisher: Independently published; (December, 2019) - ISBN-10: ‎1651129436 - ISBN-13: 978-1651129432.


Excel has its immense purposeful applications. 95% of the users apply the basic form. There are functions and advanced excel formula that can be used for complex calculations. The functions are designed for easy lookup and formatting of large pool of data whereas the advanced excel formula are implemented to get new information from a given particular set of data.

Allan Murray ... 368 pages - Publisher: ‎Apress; (December, 2020) - Language: English - ISBN-10 : 1484264665 - ISBN-13:‎ 978-1484264669.


Learn the Advanced Excel features and skills that are not taught in classes. Advanced Excel tricks, XLOOKUP, SUMPRODUCT, Power Query, Power Pivot and much more. This book is perfect for anyone who uses Excel regularly and wants to take the step to the next level. If you are a Beginner to Intermediate level Excel user, this book is a must-have. You will learn the advanced Excel features and techniques that others do not know.

In this book, you will learn: - Tricks and innovative ways to boost your productivity in Excel. - The best functions in Excel including XLOOKUP, FILTER, SORTBY, SWITCH and more with 'real world' examples. - Advanced formatting techniques to take your formatting to another level. - Create dynamic, interactive, and effective charts. - Power Query - possibly the greatest and most-important upgrade in the history of Excel. - Power Pivot - no more lookups. Learn to model your data, handle large volumes with ease and perform powerful DAX calculations. 

This book it a must-have to stay ahead of the crowd and be a success in the workplace. Take advantage of the power in modern Excel.

Tonny J. Oyana ... 354 pages - Language: ‎English - Publisher: CRC Press; 2nd edition (September, 2020) - ISBN-10: 0367860856 - ISBN-13:‎ 978-0367860851.


In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.

New in the Second Edition: Includes new practical exercises and worked-out examples using R + Presents a wide range of hands-on spatial analysis worktables and lab exercises + All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences + Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods + Explains big data, data management, and data mining

Frederick J. Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano, James E. Witnauer ... 608 pages - Language: English - Publisher:‎ Cengage Learning; 10th edition (January, 2020) - ISBN-10: 0357365291 - ISBN-13: ‎978-0357365298.


Updated with the latest research, Gravetter/Wallnau/Forzano/Witnauer's Essentials of Statistics for the Behavioral Sciences, 10th Edition delivers straightforward instruction, hands-on learning tools and real-world examples to help you go beyond memorizing formulas to truly understanding the hows and whys of statistics. Giving extra focus to the topics students typically struggle with most, the authors take time to fully explain statistical concepts. Integrated applications reinforce concepts, offering further support to ensure that even those with a weak background in mathematics can fully grasp statistics. The authors also illustrate how an understanding of statistical procedures will help you comprehend published findings -- ultimately leading you to become a savvy consumer of information. Also available, the MindTap digital learning solution helps you learn on your own terms.

Zhishen Wu, Yufei Wu, Mohamed F. M. Fahmy ... 517 pages - Language: ‎ English - Publisher: ‎Woodhead Publishing; (July, 2020).


Structures Strengthened with Bonded Composites presents a comprehensive resource on the strengthening of concrete, reinforced and prestressed concrete, masonry, steel and other composite structures using externally-bonded FRP composites. The book emphasizes a systematic and fundamental investigation on bonding and debonding behavior of the FRP-concrete interface and structural performances of FRP-strengthened structures with a combination of experimental, theoretical and numerical studies. This book will appeal to all those concerned with strengthening and retrofitting of existing structures from the effect of additional anticipated loads in the civil sector.

Discusses the FRP strengthening of different types of structures, including bridges, tunnels, buildings, historic structures and underwater constructions + Establishes a systematic theory on interfacial fracture mechanics and clarifies different debonding mechanisms + Describes design methods and makes comparison of design considerations and methods among different countries + Presents temperature and fatigue effects and long-term behavior for different strengthening methods.

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