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Structural Equation Modeling for Health and Medicine
Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examplesAs SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.
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Damage Models and Algorithms for Assessment of Structures under Operating Conditions
Extensive amounts of operational data are generated over time by the health monitoring system of a structure’s management system, yet there are few analysis algorithms which can tell the exact working state of the structure on-line. Good maintenance engineers need to know the exact location and state of the structural components after an earthquake or some attack or accident involving the structure, possibly within a matter of hours, and the client also demands a rapid diagnosis of the structure before making decisions on any necessary remedial work. This book is devoted to the condition assessment of a structure under operational loading, with most of the illustrations related to a bridge deck under a group of moving vehicular loads. More generally, a wide variety of excitation forces can be exerted on a structure, from earthquake excitation, wind loading, vehicular loading or ambient excitation at the supports. Different algorithms may be used to enable real time identification with deterministic results on the state of the structure. This book also covers a group of damage-detection-oriented-models developed by the author, including a new decomposition of the system matrices of the beam element and plate element. Methods for extending the deterministic condition assessment to provide statistical information are also included. The methods and algorithms described can be implemented for the on-line condition assessment of a structure through model updating of the structure during the course of extreme loading such as an earthquake, or when under normal ambient excitation or operation excitation. Different sample structures are described and analysed, supplemented with major references.This leading-edge work will be especially useful for researchers and graduate students, and it is also heavily rooted in advanced engineering practice.Series: Structures and Infrastructures Series Structures and Infrastructures comprises advanced-level books dealing with the maintenance, management, and cost analysis of structures and infrastructures. Topics treated include research, development and application of the most advanced technologies for analyzing, predicting, and optimizing the performance of structures and infrastructures, such as buildings, bridges, dams, underground construction, offshore platforms, pipelines, naval vessels, ocean structures, and nuclear power plants, as well as airplanes, aerospace, and automotive structures. Themes featured are mathematical modeling, computer and experimental methods, practical applications in assessment and evaluation, construction and design for durability, decision making, deterioration modeling and aging, failure analysis, field testing, financial planning, inspection and diagnostics, life-cycle analysis and prediction, loads, maintenance strategies, management systems, nondestructive testing, maintenance and management optimization, specifications and codes, structural safety and reliability, system analysis,
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Digital Computer Arithmetic Datapath Design Using Verilog HDL
The role of arithmetic in datapath design in VLSI design has been increasing in importance over the last several years due to the demand for processors that are smaller, faster, and dissipate less power. Unfortunately, this means that many of these datapaths will be complex both algorithmically and circuit wise. As the complexity of the chips increases, less importance will be placed on understanding how a particular arithmetic datapath design is implemented and more importance will be given to when a product will be placed on the market. This is because many tools that are available today, are automated to help the digital system designer maximize their efficiently. Unfortunately, this may lead to problems when implementing particular datapaths. The design of high-performance architectures is becoming more compli cated because the level of integration that is capable for many of these chips is in the billions. Many engineers rely heavily on software tools to optimize their work, therefore, as designs are getting more complex less understanding is going into a particular implementation because it can be generated automati cally. Although software tools are a highly valuable asset to designer, the value of these tools does not diminish the importance of understanding datapath ele ments. Therefore, a digital system designer should be aware of how algorithms can be implemented for datapath elements. Unfortunately, due to the complex ity of some of these algorithms, it is sometimes difficult to understand how a particular algorithm is implemented without seeing the actual code.
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Exploring the Mathematical Education of Teachers Using TEDS-M Data
This book uses the publicly available TEDS-M data to answer such questions as: How does teacher education contribute to the learning outcomes of future teachers? Are there programs that are more successful than others in helping teachers learn to teach mathematics? How does the local and national policy environment contribute to teacher education outcomes? It invites readers to explore these questions across a large number of international settings.The importance of preparing future mathematics teachers has become a priority across many nations. Across the globe nations have allocated resources and expertise to this endeavour. Yet in spite of the importance accorded to teacher education not much is known about different approaches to preparing knowledgeable teachers and whether these approaches do in fact achieve their purpose. The Mathematics Teacher Education and Development Study (TEDS-M) is the first, and to date the only, cross-national study using scientific and representative samples to provide empirical data on the knowledge that future mathematics teachers of primary and secondary school acquire in their teacher education programs. The study addresses the central importance of teacher knowledge in learning to teach mathematics by examining variation in the nature and influence of teacher education programs within and across countries.The study collected data on teacher education programs structure, curriculum and opportunities to learn, on teacher educators’ characteristics and beliefs, and on future mathematics teachers’ individual characteristics, beliefs, and mathematics and pedagogical knowledge across 17 countries providing a unique opportunity to explore enduring questions in the field.
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Emergence, Analysis and Evolution of Structures
In May 2002 a number of about 20 scientists from various disciplines were invited by the Berlin-Brandenburg Academy of Sciences and Humanities to participate in an interdisciplinary workshop on structures and structure generating processes. The site was the beautiful little castle of Blankensee, south of Berlin. The disciplines represented ranged from mathematics and information theory, over various ?elds of engineering, biochemistry and biology, to the economic and social sciences. All participants presented talks explaining the nature of structures considered in their ?elds and the associated procedures of analysis. It soon became evident that the study of structures is indeed a common c- cern of virtually all disciplines. The motivation as well as the methods of analysis, however, differ considerably. In engineering, the generation of artifacts, such as infrastructures or technological processes, are of primary interest. Frequently, the analysis aims there at de?ning a simpli?ed mathematical model for the optimization of the structures and the structure generating processes. Mathematical or heuristic methods are applied, the latter preferably of the type of biology based evolutionary algorithms. On the other hand, setting up complex technical structures is not pos- ble by such simpli?ed model calculations but requires a different and less model but rather knowledge-based type of approach, using empirical rules rather than formal equations. In biochemistry, interest is frequently focussed on the structures of molecules, such as proteins or ribonucleic acids. Again, optimal structures can usually be de?ned.
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Michell Structures
The book covers the theory of Michell structures being the lightest and fully stressed systems of bars, designed within a given domain, possibly within the whole space, transmitting a given load towards a given support. Discovered already in 1904 by A.G.M. Michell, the structures named after him have attracted constant attention due to their peculiar feature of disclosing the optimal streams of stresses equilibrating a given load and thus determining the optimal layout of bars. The optimal layouts emerge from among all possible structural topologies, thus constituting unique designs being simultaneously light and stiff. The optimal structures turn out to be embedded in optimal vector fields covering the whole feasible domain. Key features include: a variationally consistent theory of bar systems, thin plates in bending and membrane shells; recapitulation of the theory of optimum design of trusses of minimum weight or of minimal compliance; the basis of 2D Michell theory for a single load case; kinematic and static approaches; 2D benchmark constructions including Hemp’s structures and optimal cantilevers; L-shape domain problems, three forces problem in 2D, bridge problems; revisiting the old - and delivering new - 3D benchmark solutions; extension to multiple load conditions; Prager-Rozvany grillages; the theory of funiculars and archgrids; the methods of optimum design of shape and material inspired by the theory of Michell structures, industrial applications. The book can be useful for graduate students, professional engineers and researchers specializing in the Optimum Design and in Topology Optimization in general.
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Impact of Reform Instruction on Student Mathematics Achievement
Summarizing data derived from a four-year combined longitudinal/ cross-sectional comparative study of the implementation of one standards-based middle school curriculum program, Mathematics in Context, this book demonstrates the challenges of conducting comparative longitudinal research in the reality of school life. The study was designed to answer three questions: What is the impact on student performance of the Mathematics in Context instructional approach, which differs from most conventional mathematics texts in both content and expected pedagogy? How is this impact different from that of traditional instruction on student performance? What variables associated with classroom instruction account for variation in student performance?The researchers examined a range of variables that affected data collection. These variations highlight the need to study the effects of the culture in which student learning is situated when analyzing the impact of standards-based curricula on student achievement.This book is directed to educational researchers interested in curriculum implementation, mathematics educators interested in the effects of using reform curriculum materials in classrooms, evaluators and research methodologists interested in structural modeling and scaling of instructional variables, and educational policy makers concerned about reform efforts.
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Foundational and Applied Statistics for Biologists Using R
Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts.Assuming only familiarity with algebra and general calculus, the text offers a flexible structure for both introductory and graduate-level biostatistics courses. The first seven chapters address fundamental topics in statistics, such as the philosophy of science, probability, estimation, hypothesis testing, sampling, and experimental design. The remaining four chapters focus on applications involving correlation, regression, ANOVA, and tabular analyses.Unlike classic biometric texts, this book provides students with an understanding of the underlying statistics involved in the analysis of biological applications. In particular, it shows how a solid statistical foundation leads to the correct application of procedures, a clear understanding of analyses, and valid inferences concerning biological phenomena. Web ResourceAn R package (asbio) developed by the author is available from CRAN. Accessible to those without prior command-line interface experience, this companion library contains hundreds of functions for statistical pedagogy and biological research. The author’s website also includes an overview of R for novices.
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Probabilistic Methods for Structural Design
This text contains contributions from various authors on topics related to probabilistic methods used for the design of structures. Several of the papers were initially prepared for advanced courses on structural reliability or on probabilistic methods for structural design. These courses have been held in several countries and have been given by various groups of lecturers. They were aimed at engineers and researchers that had already been exposed to structural reliability methods, and presented overviews of the various topics. The book includes a selection of these contributions, which should be of use to future courses or for engineers and researchers who want an up-to-date overview. It is complementary to the existing textbooks on structural reliability, which normally cover the basic topics but exclude the more specialized aspects. In addition, several papers have been specially prepared for this book, complementing the others in providing an overall account of recent advances in the field.Among the topics covered are modelling of uncertainty, prediction of the strength of components, load modelling and combination, assessment of structural systems, stochastic finite elements and design consideration. This volume is directed at practitioners as well as researchers.
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Mathematical Structures of Ergodicity and Chaos in Population Dynamics
This book concerns issues related to biomathematics, medicine, or cybernetics as practiced by engineers. Considered population dynamics models are still in the interest of researchers, and even this interest is increasing, especially now in the time of SARS-CoV-2 coronavirus pandemic, when models are intensively studied in order to help predict its behaviour within human population. The structures of population dynamics models and practical methods of finding their solutions are discussed. Finally, the hypothesis of the existence of non-trivial ergodic properties of the model of erythropoietic response dynamics formulated by A. Lasota in the form of delay differential equation with unimodal feedback is analysed. The research can be compared with actual medical data, as well as shows that the structures of population models can reflect the dynamic structures of reality.
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Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient. It explains in what sense the existing approach touncertainty as a combination of random and systematic components is only anapproximation, presents a more adequate three-component model with an additionalperiodic error component, and explains how uncertainty propagation techniques canbe extended to this model. The book provides a justification for a practically efficientheuristic technique (based on fuzzy decision-making). It explains how the computationalcomplexity of uncertainty processing can be reduced. The book also shows how totake into account that in real life, the information about uncertainty is often onlypartially known, and, on several practical examples, explains how to extract the missinginformation about uncertainty from the available data.
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Stability Analysis and Design of Structures
This advanced and graduate-level text and self-tutorial teaches readers to understand and to apply analytical design principles across the breadth of the engineering sciences. Emphasizing fundamentals, the book addresses the stability of key engineering elements such as rigid-body assemblage, beam-column, beam, rigid frame, thin plate, arch, ring, and shell. Each chapter contains numerous worked-out problems that clarify practical application and aid comprehension of the basics of stability theory, plus end-of-chapter review exercises. Others key features are the citing and comparison of different national building standards, use of non-dimensional parameters, and many tables with much practical data and simplified formula, that enable readers to use them in the design of structural components.First six chapters most suitable for undergraduate-level study and remaining chapters for graduate-level courses.
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Applied Structural Equation Modeling Using AMOS
This updated edition provides an essential how-to guide on the application of structural equation modeling (SEM) techniques with the AMOS software, focusing on the practical applications of both simple and advanced topics.Written in an easy-to-understand conversational style, the book covers everything from data collection and screening to confirmatory factor analysis, structural model analysis, mediation, moderation, and more advanced topics such as mixture modeling, censored date, and non-recursive models. Through step-by-step instructions, screen shots, and suggested guidelines for reporting, Collier cuts through abstract definitional perspectives to give insight on how to actually run analysis. Unlike other SEM books, the examples used will often start in SPSS and then transition to AMOS so that the reader can have full confidence in running the analysis from beginning to end. Best practices are also included on topics like how to determine if your SEM model is formative or reflective, making it not just an explanation of SEM topics, but a guide for researchers on how to develop a strong methodology while studying their respective phenomenon of interest. With a focus on practical applications of both basic and advanced topics, and with detailed work-through examples throughout, this book is ideal for experienced researchers and beginners across the behavioral and social sciences.
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Structure Determination by X-Ray Crystallography
Crystallography may be described as the science of the structure of materi als, using this word in its widest sense, and its ramifications are apparent over a broad front of current scientific endeavor. It is not surprising, therefore, to find that most universities offer some aspects of crystallography in their undergraduate courses in the physical sciences. It is the principal aim of this book to present an introduction to structure determination by X-ray crystal lography that is appropriate mainly to both final-year undergraduate studies in crystallography, chemistry, and chemical physics, and introductory post graduate work in this area of crystallography. We believe that the book will be of interest in other disciplines, such as physics, metallurgy, biochemistry, and geology, where crystallography has an important part to play. In the space of one book, it is not possible either to cover all aspects of crystallography or to treat all the subject matter completely rigorously. In particular, certain mathematical results are assumed in order that their applications may be discussed. At the end of each chapter, a short bibliog raphy is given, which may be used to extend the scope of the treatment given here. In addition, reference is made in the text to specific sources of information. We have chosen not to discuss experimental methods extensively, as we consider that this aspect of crystallography is best learned through practical experience, but an attempt has been made to simulate the interpretive side of experimental crystallography in both examples and exercises.
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Learn Python by Building Data Science Applications
Understand the constructs of the Python programming language and use them to build data science projectsKey FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook DescriptionPython is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production.This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice.By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is forIf you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.
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Elements of the Theory of Structures
A good grasp of the theory of structures - the theoretical basis by which the strength, stiffness and stability of a building can be understood - is fundamental to structural engineers and architects. Yet most modern structural analysis and design is carried out by computer, with the user isolated from the processes in action. This book provides a broad introduction to the mathematics behind a range of structural processes. The basic structural equations have been known for at least 150 years, but modern plastic theory has opened up a fundamentally new way of advancing structural theory. Paradoxically, the powerful plastic theorems can be used to examine 'classic' elastic design activity, and strong mathematical relationships exist between these two approaches. Some of the techniques used in this book may be familiar to the reader, and some may not, but each of the topics examined will give the structural engineer valuable insight into the basis of the subject. This lucid volume provides a valuable read for structural engineers and others who wish to deepen their knowledge of the structural analysis and design of buildings.
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Morphological Structure in Language Processing
This volume brings together a series of studies of morphological processing in Germanic (English, German, Dutch), Romance (French, Italian), and Slavic (Polish, Serbian) languages. The question of how morphologically complex words are organized and processed in the mental lexicon is addressed from different theoretical perspectives (single and dual route models), for different modalities (auditory and visual comprehension, writing), and for language development. Experimental work is reported, as well as computational and statistical modeling. Thus, this volume provides a useful overview of the range of issues currently attracting reseach at the intersection of morphology and psycholinguistics.
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Communication Systems Principles Using MATLAB
Discover the basic telecommunications systems principles in an accessible learn-by-doing format Communication Systems Principles Using MATLAB covers a variety of systems principles in telecommunications in an accessible format without the need to master a large body of theory. The text puts the focus on topics such as radio and wireless modulation, reception and transmission, wired networks and fiber optic communications. The book also explores packet networks and TCP/IP as well as digital source and channel coding, and the fundamentals of data encryption. Since MATLAB® is widely used by telecommunications engineers, it was chosen as the vehicle to demonstrate many of the basic ideas, with code examples presented in every chapter. The text addresses digital communications with coverage of packet-switched networks. Many fundamental concepts such as routing via shortest-path are introduced with simple and concrete examples. The treatment of advanced telecommunications topics extends to OFDM for wireless modulation, and public-key exchange algorithms for data encryption. Throughout the book, the author puts the emphasis on understanding rather than memorization. The text also: Includes many useful take-home skills that can be honed while studying each aspect of telecommunicationsOffers a coding and experimentation approach with many real-world examples providedGives information on the underlying theory in order to better understand conceptual developmentsSuggests a valuable learn-by-doing approach to the topic Written for students of telecommunications engineering, Communication Systems Principles Using MATLAB® is the hands-on resource for mastering the basic concepts of telecommunications in a learn-by-doing format.
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Spaces of Measures and their Applications to Structured Population Models
Structured population models are transport-type equations often applied to describe evolution of heterogeneous populations of biological cells, animals or humans, including phenomena such as crowd dynamics or pedestrian flows. This book introduces the mathematical underpinnings of these applications, providing a comprehensive analytical framework for structured population models in spaces of Radon measures. The unified approach allows for the study of transport processes on structures that are not vector spaces (such as traffic flow on graphs) and enables the analysis of the numerical algorithms used in applications. Presenting a coherent account of over a decade of research in the area, the text includes appendices outlining the necessary background material and discusses current trends in the theory, enabling graduate students to jump quickly into research.
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Multilevel Modeling Using R
Like its bestselling predecessor, Multilevel Modeling Using R, Third Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment.After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data.The third edition of the book includes several new topics that were not present in the second edition. Specifically, a new chapter has been included, focussing on fitting multilevel latent variable modeling in the R environment. With R, it is possible to fit a variety of latent variable models in the multilevel context, including factor analysis, structural models, item response theory, and latent class models. The third edition also includes new sections in chapter 11 describing two useful alternatives to standard multilevel models, fixed effects models and generalized estimating equations. These approaches are particularly useful with small samples and when the researcher is interested in modeling the correlation structure within higher level units (e.g., schools). The third edition also includes a new section on mediation modeling in the multilevel context, in chapter 11. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research.
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Using SPSS Syntax
SPSS syntax is the command language used by SPSS to carry out all of its commands and functions. In this book, Jacqueline Collier introduces the use of syntax to those who have not used it before, or who are taking their first steps in using syntax. Without requiring any knowledge of programming, the text outlines: - how to become familiar with the syntax commands; - how to create and manage the SPSS journal and syntax files; - and how to use them throughout the data entry, management and analysis process. Collier covers all aspects of data management from data entry through to data analysis, including managing the errors and the error messages created by SPSS. Syntax commands are clearly explained and the value of syntax is demonstrated through examples. This book also supports the use of SPSS syntax alongside the usual button and menu-driven graphical interface (GIF) using the two methods together, in a complementary way. The book is written in such a way as to enable you to pick and choose how much you rely on one method over the other, encouraging you to use them side-by-side, with a gradual increase in use of syntax as your knowledge, skills and confidence develop. This book is ideal for all those carrying out quantitative research in the health and social sciences who can benefit from SPSS syntax′s capacity to save time, reduce errors and allow a data audit trail.
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Multiple Factor Analysis by Example Using R
Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distinction. Focusing on MFA, subsequent chapters examine the key points of MFA in the context of quantitative variables as well as qualitative and mixed data. The author also compares MFA and Procrustes analysis and presents a natural extension of MFA: hierarchical MFA (HMFA). The final chapter explores several elements of matrix calculation and metric spaces used in the book.
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ISS-2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers
This proceedings volume contains nine selected papers that were presented in the International Symposium in Statistics, 2012 held at Memorial University from July 16 to 18. These nine papers cover three different areas for longitudinal data analysis, four dealing with longitudinal data subject to measurement errors, four on incomplete longitudinal data analysis, and the last one for inferences for longitudinal data subject to outliers. Unlike in the independence setup, the inferences in measurement errors, missing values, and/or outlier models, are not adequately discussed in the longitudinal setup. The papers in the present volume provide details on successes and further challenges in these three areas for longitudinal data analysis. This volume is the first outlet with current research in three important areas in the longitudinal setup. The nine papers presented in three parts clearly reveal the similarities and differences in inference techniques used for three different longitudinal setups. Because the research problems considered in this volume are encountered in many real life studies in biomedical, clinical, epidemiology, socioeconomic, econometrics, and engineering fields, the volume should be useful to the researchers including graduate students in these areas.
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Matrix Analysis Of Framed Structures
Intended for structural engineers, this third edition text, a source on the use of matrix analysis for structures of all types, has been revised and updated.
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Cancer: Cell Structures, Carcinogens and Genomic Instability
This volume began with an invitation from the publishers to edit a volume of EXS on Cancer. This invitation undoubtedly derived from my articles in Cellular and Molecular Life Sciences in 2002 and 2003 on the relationships between the morphology, aetiology and pathogenesis of tumours, especially in relation to genetic instability. After many years of teaching the theories of c- cer in undergraduate medical school courses, it seemed to me that the variably chaotic histopathologic features of tumours parallel in some way, the variably unstable genomes of tumour cells, which were being discovered in the 1990s. Thus the title of the volume has come to include morphology, carcinogenesis and genetic instability. The invitation came while I was working with Herrn Dr. med. Hubertus Jersmann (MD Düsseldorf, PhD, now Senior Lecturer in Medicine of the University of Adelaide) and Professor Brian Coghlan (Emeritus Professor of German, the University of Adelaide), on the work of the nineteenth century cancer pathologists, especially David Paul von Hansemann (1858–1920). With the delivery of the manuscripts from the authors of the chapters, it became obvious that a background chapter for the volume could include some of the material which we had “uncovered” together. Because of this, chapter 1 is authored by the three of us, and the “new” material figures prominently.
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Algebraic Structures and Operator Calculus
This series presents some tools of applied mathematics in the areas of proba bility theory, operator calculus, representation theory, and special functions used currently, and we expect more and more in the future, for solving problems in math ematics, physics, and, now, computer science. Much of the material is scattered throughout available literature, however, we have nowhere found in accessible form all of this material collected. The presentation of the material is original with the authors. The presentation of probability theory in connection with group represen tations is new, this appears in Volume I. Then the applications to computer science in Volume II are original as well. The approach found in Volume III, which deals in large part with infinite-dimensional representations of Lie algebras/Lie groups, is new as well, being inspired by the desire to find a recursive method for calcu lating group representations. One idea behind this is the possibility of symbolic computation of the matrix elements. In this volume, Representations and Probability Theory, we present an intro duction to Lie algebras and Lie groups emphasizing the connections with operator calculus, which we interpret through representations, principally, the action of the Lie algebras on spaces of polynomials. The main features are the connection with probability theory via moment systems and the connection with the classical ele mentary distributions via representation theory. The various systems of polynomi als that arise are one of the most interesting aspects of this study.
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Synthesis, Modelling and Characterization of 2D Materials and their Heterostructures
Synthesis, Modelling and Characterization of 2D Materials and Their Heterostructures provides a detailed discussion on the multiscale computational approach surrounding atomic, molecular and atomic-informed continuum models. In addition to a detailed theoretical description, this book provides example problems, sample code/script, and a discussion on how theoretical analysis provides insight into optimal experimental design. Furthermore, the book addresses the growth mechanism of these 2D materials, the formation of defects, and different lattice mismatch and interlayer interactions. Sections cover direct band gap, Raman scattering, extraordinary strong light matter interaction, layer dependent photoluminescence, and other physical properties.
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Structure from Motion using the Extended Kalman Filter
The fully automated estimation of the 6 degrees of freedom camera motion and the imaged 3D scenario using as the only input the pictures taken by the camera has been a long term aim in the computer vision community. The associated line of research has been known as Structure from Motion (SfM). An intense research effort during the latest decades has produced spectacular advances; the topic has reached a consistent state of maturity and most of its aspects are well known nowadays. 3D vision has immediate applications in many and diverse fields like robotics, videogames and augmented reality; and technological transfer is starting to be a reality. This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic: As usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme; namely projective models, spurious rejection, model selection and self-calibration.
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Data Driven e-Science
ISGC 2010, The International Symposium on Grid Computing was held at Academia Sinica, Taipei, Taiwan, March, 2010. The 2010 symposium brought together prestigious scientists and engineers worldwide to exchange ideas, present challenges/solutions and to discuss new topics in the field of Grid Computing. Data Driven e-Science: Use Cases and Successful Applications of Distributed Computing Infrastructures (ISGC 2010), an edited volume, introduces the latest achievements in grid technology for Biomedicine Life Sciences, Middleware, Security, Networking, Digital Library, Cloud Computing and more. This book provides Grid developers and end users with invaluable information for developing grid technology and applications. The last section of this book presents future development in the field of Grid Computing. This book is designed for a professional audience composed of grid users, developers and researchers working in the field of grid computing. Advanced-level students focused on computer science and engineering will also find this book valuable as a reference or secondary text book.
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Poisson Structures
Poisson structures appear in a large variety of contexts, ranging from string theory, classical/quantum mechanics and differential geometry to abstract algebra, algebraic geometry and representation theory. In each one of these contexts, it turns out that the Poisson structure is not a theoretical artifact, but a key element which, unsolicited, comes along with the problem that is investigated, and its delicate properties are decisive for the solution to the problem in nearly all cases. Poisson Structures is the first book that offers a comprehensive introduction to the theory, as well as an overview of the different aspects of Poisson structures. The first part covers solid foundations, the central part consists of a detailed exposition of the different known types of Poisson structures and of the (usually mathematical) contexts in which they appear, and the final part is devoted to the two main applications of Poisson structures (integrable systems and deformation quantization). The clear structure of the book makes it adequate for readers who come across Poisson structures in their research or for graduate students or advanced researchers who are interested in an introduction to the many facets and applications of Poisson structures.
R 6,211.47
Structural Equation Modelling with Partial Least Squares Using Stata and R
Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods for PLS-SEM are now readily facilitated by both open-source and commercial software packages.This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications. What makes the book unique is the fact that it thoroughly explains and extensively uses comprehensive Stata (plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM analysis. The book aims to help the reader understand the mechanics behind PLS-SEM as well as performing it for publication purposes. Features: Intuitive and technical explanations of PLS-SEM methods Complete explanations of Stata and R packages Lots of example applications of the methodology Detailed interpretation of software output Reporting of a PLS-SEM study Github repository for supplementary book materialThe book is primarily aimed at researchers and graduate students from statistics, social science, psychology, and other disciplines. Technical details have been moved from the main body of the text into appendices, but it would be useful if the reader has a solid background in linear regression analysis.
R 7,594.52
Digital Computer Arithmetic Datapath Design Using Verilog HDL
The role of arithmetic in datapath design in VLSI design has been increasing in importance over the last several years due to the demand for processors that are smaller, faster, and dissipate less power. Unfortunately, this means that many of these datapaths will be complex both algorithmically and circuit wise. As the complexity of the chips increases, less importance will be placed on understanding how a particular arithmetic datapath design is implemented and more importance will be given to when a product will be placed on the market. This is because many tools that are available today, are automated to help the digital system designer maximize their efficiently. Unfortunately, this may lead to problems when implementing particular datapaths. The design of high-performance architectures is becoming more compli cated because the level of integration that is capable for many of these chips is in the billions. Many engineers rely heavily on software tools to optimize their work, therefore, as designs are getting more complex less understanding is going into a particular implementation because it can be generated automati cally. Although software tools are a highly valuable asset to designer, the value of these tools does not diminish the importance of understanding datapath ele ments. Therefore, a digital system designer should be aware of how algorithms can be implemented for datapath elements. Unfortunately, due to the complex ity of some of these algorithms, it is sometimes difficult to understand how a particular algorithm is implemented without seeing the actual code.
R 3,021.03
