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Computer Network Simulation Using NS2
Computer Network Simulations Using NS2 provides a solid foundation of computer networking knowledge and skills, covering everything from simple operating system commands to the analysis of complex network performance metrics.The book begins with a discussion of the evolution of data communication techniques and the fundamental issues associated with performance evaluation. After presenting a preliminary overview of simulation and other performance evaluation techniques, the authors:Describe a number of computer network protocols and TCP/IP and OSI models, highlighting the networking devices usedExplain a socket and its use in network programming, fostering the development of network applications using C and socket APIIntroduce the NS2 network simulator, exhibiting its internal architecture, constituent software packages, and installation in different operating systemsDelve into simulation using NS2, elaborating on the use of Tcl and OTcl scripts as well as AWK scripting and plotting with GnuplotShow how to simulate wired and wireless network protocols step by step, layer by layerExplore the idea of simulating very large networks, identifying the challenges associated with measuring and graphing the various network parametersInclude nearly 90 example programs, scripts, and outputs, along with several exercises requiring application of the theory and programmingComputer Network Simulations Using NS2 emphasizes the implementation and simulation of real-world computer network protocols, affording readers with valuable opportunities for hands-on practice while instilling a deeper understanding of how computer network protocols work.
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Dynamic Mixed Models for Familial Longitudinal Data
This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing ‘working’ correlations based GEE (generalizedestimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of independent families by using the class of auto-correlation structures conditional on the random effects. The book also provides models and inferences for discrete longitudinal data in the adaptive clinical trial set up.The book is mathematically rigorous and provides details for the development of estimation approaches under selected familial and longitudinal models. Further, while the book provides special cares for mathematics behind the correlation models, it also presents theillustrations of the statistical analysis of various real life data. This book will be of interest to the researchers including graduate students in biostatistics and econometrics, among other applied statistics research areas. Brajendra Sutradhar is a University Research Professor at Memorial University in St. John’s, Canada. He is an elected member of the International Statistical Institute and a fellow of the American Statistical Association. He has published about 110 papers in statistics journals in the area of multivariate analysis, time series analysis including forecasting, sampling, survival analysis for correlated failure times, robust inferences in generalized linear mixed models with outliers, and generalized linear longitudinal mixed models with bio-statistical and econometric applications. He has served as an associate editor for six years for Canadian Journal of Statistics and for four years for the Journal of Environmental and Ecological Statistics. He has served for 3 years as a member of the advisory committee on statistical methods in Statistics Canada. Professor Sutradhar was awarded 2007 distinguished service award of Statistics Society of Canada for his many years of services to thesociety including his special services for society’s annual meetings.
R 3,071.10
Research Issues in Structured and Semistructured Database Programming
The Seventh International Workshop on Database Programming Languages (DBPL99) took place in Kinloch Rannoch,Perthshire,UK from the 1st to the 3rd of September 1999. This series of workshops focuses on the interaction of theory and practice in the design and development of database programming languages. The workshop has occurred biennially since 1987,and was previously held in: Rosco?,Finist'ere,France (1987) Salishan,Oregon,USA (1989) Nafplion,Argolida,Greece (1991) Manhattan,New York,USA (1993) Gubbio,Umbria,Italy (1995) Estes Park,Colorado,USA (1997) The workshop,as always,was organised as a mixture of invited speakers, informal paper presentations and discussion. Attendance at the workshop was limited to those who submitted papers and members of the Programme C- mittee,to ensure a su?ciently small forum for useful discussion. Before ?nding their way into this volume,papers were refereed by at least three members of the Programme Committee. Sixteen of the 31 submitted papers were accepted for presentation at the workshop.In the tradition of the series,authors were - couraged to improve their papers based on both referees' comments and ensuing discussion at the workshop,and resubmit them for publication in this volume, after which a further stage of refereeing took place. The result,we believe,is a volume of high-quality and well-polished papers. Two invited presentations were given,by Luca Cardelli (Microsoft Research Labs,Cambridge,UK) and Alon Levy (University of Washington).
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Foundations of Software Science and Computational Structures
The present volume contains the proceedings of the international conference Foundations of Software Science and Computation Structures(FOSSACS)2003, held in Warsaw, Poland, April 7-9, 2003. FOSSACS is an event of the Joint European Conferences on Theory and Practice of Software (ETAPS). The pre- ous ?ve FOSSACS conferences took place in Lisbon (1998), Amsterdam (1999), Berlin (2000), Genoa (2001), and Grenoble (2002). FOSSACS presents original papers on foundational researchwith a clear s- ni?cancetosoftwarescience.TheProgramCommitteeinvitedpapersontheories and methodsto supportthe analysis,integration,synthesis,transformation,and veri?cation of programs and software systems. We identi?ed the following t- ics, in particular: algebraic models; automata and language theory; behavioural equivalences; categorical models; computation processes over discrete and c- tinuous data; computation structures; logics of programs; modal, spatial, and temporallogics;modelsof concurrent,reactive,distributed, and mobile systems; processalgebrasandcalculi;semanticsofprogramminglanguages;softwaresp- i?cation and re?nement; transition systems; and type systems and type theory.We received 96 submissions, of which 2 were withdrawn. This proceedings consists of 27 papers. The ?rst-A Game Semantics for Generic Polymorphism-accompanies the invited lecture by Samson Abramsky, University of Oxford. The remaining 26 were selected for publication by the Program Committee during a week-long electronic discussion. I sincerely thank all the authors of papers submitted to FOSSACS 2003; the number and the quality of papers were exceptionally high this year. Moreover, I would like to thank all the members of the ProgramCommittee for the excellent job they did during a rather demanding selection process, and to thank all our subreferees for their invaluable contributions to this process.
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R 2,199.57
Fundamentals of Stream Processing
Stream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.
R 4,683.69
Advances in Non-destructive Evaluation
This book comprises the proceedings of the Conference and Exhibition on Non Destructive Evaluation, (NDE 2019). The contents of the book encompass a vast spectrum from Conventional to Advanced NDE including novel methods, instrumentation, sensors, procedures and data analytics as applied to all industry segments for quality control, periodic maintenance, life estimation, structural integrity and related areas. This book will be a useful reference for students, researchers and practitioners.
R 8,970.10
Data Mining in Structural Biology
Structural biology is becoming a routine technique for structure de termination in pharmaceutical industries. The advances in molecular biology, crystal handling and data collection techniques, tunable syn chrotron radiation sources, and high-performance computing have all contributed to developments such as the production and expression of tailored protein domains, the use of the MAD (Multiple Anomalous Dispersion) method, and the collection of X-ray data from tiny crystals at cryogenic temperature. The number of protein structures deposited in the Protein Databank has increased tremendously over the last 3-4 years. Since 1997, more than 1,500 structures have been deposited each year, and during the first 7 months of this year, 1,500 protein structures were already deposited. The numerous initiatives in the field of "structural genomics" distributed all over the world have led to the development of techniques for high-throughput structure determina tion, thereby contributing to the increase in the determination of three dimensional protein structures. This structural information is being ex plored in various ways in the drug discovery process. It is not only used in structure-based drug design of new low-molecular-weight li gands, but also in the early stages of target validation and assessment. With the number of protein sequences without significant homology to well-known proteins increasing, the technique of structure-sequence compatibility (threading) is increasingly used to assign a function to a given protein fold.
R 3,754.79
Biostatistics for Epidemiology and Public Health Using R
Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-by-step approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems drawn from such areas as nutrition, environmental health, and behavioural health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. Also included are an instructor's guide, student solutions manual, and downloadable data sets.
R 3,266.00
Women, Education, And Family Structure In India
Five decades of independence have produced dramatic increases in womens’ educational achievements in India; but education for girls beyond a certain level is still perceived as socially risky. Based on ethnographic data and historical documents, this book explores the origins of that paradox. Contributors probe the complex relationships between traditional Indian social institutions the joint family, arranged marriage, dowry, and purdah, or sexual segregation and girls schooling. They find that a patrifocal family structure and ideology are often at the root of different family approaches to educating sons and daughters, and that concern for marriageability still plays a central role in womens’ educational choices and outcomes.
R 2,557.16
Art of Assembly Language Programming Using PIC® Technology
The Art of Assembly Language Programming using PIC® Technology thoroughly covers assembly language as used in programming the PIC® Microcontroller (MCU). Using the minimal instruction set, characteristic of most PIC® products, the author elaborates on the nuances of how to execute loops. Fundamental design practices are presented based on Orr’s Structured Systems Development using four logical control structures. These control structures are presented in Flowcharting, Warnier-Orr® diagrams, State Diagrams, Pseudocode, and an extended example using SysML®. Basic math instructions of Add and Subtract are presented, along with a cursory presentation of advanced math routines provided as proven Microchip® utility Application Notes. Appendices are provided for completeness, especially for the advanced reader, including several Instruction Sets, ASCII character sets, Decimal-Binary-Hexadecimal conversion tables, and elaboration of ten ‘Best Practices.’ Two datasheets (one complete datasheet on the 10F20x series and one partial datasheet on the 16F88x series) are also provided in the Appendices to serve as an important reference, enabling the new embedded programmer to develop familiarity with the format of datasheets and the skills needed to assess the product datasheet for proper selection of a microcontroller family for any specific project. The Art of Assembly Language Programming Using PIC® Technology is written for an audience with a broad variety of skill levels, ranging from the absolute beginner completely new to embedded control to the embedded C programmer new to assembly language. With this book, you will be guided through the following areas: Symbols and terminology used by programmers and engineers in microcontroller applications Programming using assembly language through examples Familiarity with design and development practices Basics of mathematical knowledge in hexadecimal Resources for advanced mathematical functions Approaches to locate resources
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Multi-Paradigm Programming using C++
Aimed mainly at students, this self-contained reference book on C++ is of superb educational value. Starting from scratch, Vermeir explains the idea of address, value and type in C++ before quickly moving on to cover the more important aspects of the language such as classes, templates, generic programming and inheritance. He includes recent developments in C++, such as STL and the iostream library. There is also a chapter devoted to program design principles. By using plenty of examples the reader is stimulated and inspired to see how they can use what they have learnt in other more sophisticated applications. All the examples from the text, including some larger example programs are available on the author's website.
R 3,038.63
Algebraic Structures and Operator Calculus
In this volume we will present some applications of special functions in computer science. This largely consists of adaptations of articles that have appeared in the literature . Here they are presented in a format made accessible for the non-expert by providing some context. The material on group representations and Young tableaux is introductory in nature. However, the algebraic approach of Chapter 2 is original to the authors and has not appeared previously . Similarly, the material and approach based on Appell states, so formulated, is presented here for the first time . As in all volumes of this series, this one is suitable for self-study by researchers . It is as well appropriate as a text for a course or advanced seminar . The solutions are tackled with the help of various analytical techniques, such as g- erating functions, and probabilistic methods/insights appear regularly . An interesting feature is that, as has been the case in classical applications to physics, special functions arise- here in complexity analysis. And, as in physics, their appearance indicates an underlying Lie structure. Our primary audience is applied mathematicians and theoretical computer scientists . We are quite sure that pure mathematicians will find this volume interesting and useful as well .
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Managing and Mining Uncertain Data
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.
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New Data Structures and Algorithms for Logic Synthesis and Verification
This book introduces new logic primitives for electronic design automation tools. The author approaches fundamental EDA problems from a different, unconventional perspective, in order to demonstrate the key role of rethinking EDA solutions in overcoming technological limitations of present and future technologies. The author discusses techniques that improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. Readers will be enabled to accelerate formal methods by studying core properties of logic circuits and developing new frameworks for logic reasoning engines.
R 1,903.71
Thinking With Data
The chapters in Thinking With Data are based on presentations given at the 33rd Carnegie Symposium on Cognition. The Symposium was motivated by the confluence of three emerging trends: (1) the increasing need for people to think effectively with data at work, at school, and in everyday life, (2) the expanding technologies available to support people as they think with data, and (3) the growing scientific interest in understanding how people think with data.What is thinking with data? It is the set of cognitive processes used to identify, integrate, and communicate the information present in complex numerical, categorical, and graphical data. This book offers a multidisciplinary presentation of recent research on the topic. Contributors represent a variety of disciplines: cognitive and developmental psychology; math, science, and statistics education; and decision science. The methods applied in various chapters similarly reflect a scientific diversity, including qualitative and quantitative analysis, experimentation and classroom observation, computational modeling, and neuroimaging. Throughout the book, research results are presented in a way that connects with both learning theory and instructional application.The book is organized in three sections:Part I focuses on the concepts of uncertainty and variation and on how people understand these ideas in a variety of contexts.Part II focuses on how people work with data to understand its structure and draw conclusions from data either in terms of formal statistical analyses or informal assessments of evidence.Part III focuses on how people learn from data and how they use data to make decisions in daily and professional life.
R 2,396.92
Image Analysis of Food Microstructure
Image Analysis of Food Microstructure offers a condensed guide to the most common procedures and techniques by which quantitative microstructural information about food can be obtained from images. The images are selected from a broad range of food items, including macroscopic images of meat and finished products such as pizza, and the microstructures of cheeses, dough and baked goods, ice cream, fruits and vegetables, emulsions, foams, and gels.The book informs food scientists about the image processing and measurement tools used to characterize a variety of microstructures in foods, using high-quality image techniques to illustrate chemical composition, thermo-mechanical processing, and genetic and structural properties. These different types of images used to measure various aspects of structure include: macroscopic light photography, confocal light microscopy, electron microscopy, atomic force microscope images, magnetic resonance, and computed tomography. Then the text explains how to interpret images to produce data, plot the results in different graphs, and identify trends. Examples using these image analysis techniques show typical results that researchers can expect and recreate. Image Analysis of Food Microstructure summarizes the basic procedures that can be useful in various aspects of food research, from nutraceuticals to cooking and food processing. It presents the processing of images and mathematical principles needed for image analyses in a step-by-step approach to extract key information from the images obtained.
R 13,919.36
Algebraic Structures and Operator Calculus
In this volume we will present some applications of special functions in computer science. This largely consists of adaptations of articles that have appeared in the literature . Here they are presented in a format made accessible for the non-expert by providing some context. The material on group representations and Young tableaux is introductory in nature. However, the algebraic approach of Chapter 2 is original to the authors and has not appeared previously . Similarly, the material and approach based on Appell states, so formulated, is presented here for the first time . As in all volumes of this series, this one is suitable for self-study by researchers . It is as well appropriate as a text for a course or advanced seminar . The solutions are tackled with the help of various analytical techniques, such as g- erating functions, and probabilistic methods/insights appear regularly . An interesting feature is that, as has been the case in classical applications to physics, special functions arise- here in complexity analysis. And, as in physics, their appearance indicates an underlying Lie structure. Our primary audience is applied mathematicians and theoretical computer scientists . We are quite sure that pure mathematicians will find this volume interesting and useful as well .
R 1,534.32
Fitting Equations to Data
Helps any serious data analyst with a computer to recognize the strengths and limitations of data, to test the assumptions implicit in the least squares methods used to fit the data, to select appropriate forms of the variables, to judge which combinations of variables are most influential, and to state the conditions under which the fitted equations are applicable. This edition includes numerous extensions and new devices such as component and component-plus-residual plots, cross verification with a second sample, and an index of required x-precision; also, the search for better subset equations is enlarged to cover 262,144 alternatives. The methods described have been applied in agricultural, environmental, management, marketing, medical, physical, and social sciences. Mathematics is kept to the level of college algebra.
R 5,762.00
Social Network Data Analytics
Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.
R 6,349.26
Discrete Structures
Discrete Structures introduces readers to the mathematical structures and methods that form the foundation of computer science and features multiple techniques that readers will turn to regularly throughout their careers in computer and information sciences.Over the course of five modules, students learn specific skills including binary and modular arithmetic, set notation, methods of counting, evaluating sums, and solving recurrences. They study the basics of probability, proof by induction, growth of functions, and analysis techniques. The book also discusses general problem-solving techniques that are widely applicable to real problems. Each module includes motivation applications, technique, theory, and further opportunities for application.Informed by extensive experience teaching in computer science programs, Discrete Structures has been developed specifically for first-year students in those programs. The material is also suitable for courses in computer engineering, as well as those for students who are transferring from other disciplines and just beginning their computer science or engineering education.
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Structured Search for Big Data
The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big Data are arguably the most notable. Structured Search paradigm connects them via a fundamental concept of key-objects evolving out of keywords as the units of search. The key-object data model and KeySQL revamp the data independence principle making it applicable for Big Data and complement NoSQL with full-blown structured querying functionality. The ultimate goal is extracting Big Information from the Big Data. As a Big Data Consultant, Mikhail Gilula combines academic background with 20 years of industry experience in the database and data warehousing technologies working as a Sr. Data Architect for Teradata, Alcatel-Lucent, and PayPal, among others. He has authored three books, including The Set Model for Database and Information Systems and holds four US Patents in Structured Search and Data Integration.
R 882.00
Index Structures for Data Warehouses
Data warehouses differ significantly from traditional transaction-oriented operational database applications. Indexing techniques and index structures applied in the transaction-oriented context are not feasible for data warehouses.This work develops specific heuristic indexing techniques which process range queries on aggregated data more efficiently than those traditionally used in transaction-oriented systems. The book presents chapters on:- the state of the art in data warehouse research- data storage and index structures- finding optimal tree-based index structures- aggregated data in tree-based index structures- performance models for tree-based index structures- and techniques for comparing index structures.
R 1,531.82
Structure Discovery in Natural Language
Current language technology is dominated by approaches that either enumerate a large set of rules, or are focused on a large amount of manually labelled data. The creation of both is time-consuming and expensive, which is commonly thought to be the reason why automated natural language understanding has still not made its way into “real-life” applications yet. This book sets an ambitious goal: to shift the development of language processing systems to a much more automated setting than previous works. A new approach is defined: what if computers analysed large samples of language data on their own, identifying structural regularities that perform the necessary abstractions and generalisations in order to better understand language in the process?After defining the framework of Structure Discovery and shedding light on the nature and the graphic structure of natural language data, several procedures are described that do exactly this: let the computer discover structures without supervision in order to boost the performance of language technology applications. Here, multilingual documents are sorted by language, word classes are identified, and semantic ambiguities are discovered and resolved without using a dictionary or other explicit human input. The book concludes with an outlook on the possibilities implied by this paradigm and sets the methods in perspective to human computer interaction.The target audience are academics on all levels (undergraduate and graduate students, lecturers and professors) working in the fields of natural language processing and computational linguistics, as well as natural language engineers who are seeking to improve their systems.
R 3,021.76
Large-Scale Structures in the Universe Observational and Analytical Methods
This book will certainly be considered an important reference for astronomers and astrophysicists handling large amounts of data in observational and theoretical approaches to the large scale structures in the universe. The contributions are written with an emphasis on methods. The volume contains among many other topics recent observational results on redshift surveys of clusters and distributions of galaxies and quasars, together with articles on the importance of these findings for future standards and for theoretical predictions. A long historical chapter serves as an introduction. This mixture of textbook and review is aimed at the newcomer to the field as well as at the specialist. Graduate students will find it useful for additional reading.
R 4,399.29
Computing for Numerical Methods Using Visual C++
A visual, interdisciplinary approach to solving problems in numerical methods Computing for Numerical Methods Using Visual C++ fills the need for a complete, authoritative book on the visual solutions to problems in numerical methods using C++. In an age of boundless research, there is a need for a programming language that can successfully bridge the communication gap between a problem and its computing elements through the use of visual-ization for engineers and members of varying disciplines, such as biologists, medical doctors, mathematicians, economists, and politicians. This book takes an interdisciplinary approach to the subject and demonstrates how solving problems in numerical methods using C++ is dominant and practical for implementation due to its flexible language format, object-oriented methodology, and support for high numerical precisions. In an accessible, easy-to-follow style, the authors cover: Numerical modeling using C++ Fundamental mathematical tools MFC interfaces Curve visualization Systems of linear equations Nonlinear equations Interpolation and approximation Differentiation and integration Eigenvalues and Eigenvectors Ordinary differential equations Partial differential equations This reader-friendly book includes a companion Web site, giving readers free access to all of the codes discussed in the book as well as an equation parser called "MyParser" that can be used to develop various numerical applications on Windows. Computing for Numerical Methods Using Visual C++ serves as an excellent reference for students in upper undergraduate- and graduate-level courses in engineering, science, and mathematics. It is also an ideal resource for practitioners using Microsoft Visual C++.
R 5,730.00
Big Data Analytics in Chemoinformatics and Bioinformatics
Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information.
R 6,621.00
Algorithms and Data Structures
This volume presents the proceedings of the Second Workshop on Algorithms and Data Structures (WADS '91), held at Carleton University in Ottawa. The workshop was organized by the School of Computer Science at Carleton University. The workshop alternates with the Scandinavian Workshop on Algorithm Theory (SWAT), continuing the tradition of SWAT '88 (LNCS, Vol. 318), WADS '89 (LNCS, Vol. 382), and SWAT '90 (LNCS, Vol. 447). From 107 papers submitted, 37 were selected for presentation at the workshop. In addition, there were 5 invited presentations.
R 1,591.06
Dynamics of Self-Organized and Self-Assembled Structures
Physical and biological systems driven out of equilibrium may spontaneously evolve to form spatial structures. In some systems molecular constituents may self-assemble to produce complex ordered structures. This book describes how such pattern formation processes occur and how they can be modeled. Experimental observations are used to introduce the diverse systems and phenomena leading to pattern formation. The physical origins of various spatial structures are discussed, and models for their formation are constructed. In contrast to many treatments, pattern-forming processes in nonequilibrium systems are treated in a coherent fashion. The book shows how near-equilibrium and far-from-equilibrium modeling concepts are often combined to describe physical systems. This inter-disciplinary book can form the basis of graduate courses in pattern formation and self-assembly. It is a useful reference for graduate students and researchers in a number of disciplines, including condensed matter science, nonequilibrium statistical mechanics, nonlinear dynamics, chemical biophysics, materials science, and engineering.
R 4,113.84
Geographic Data Science with R
The burgeoning field of data science has provided a wealth of techniques for analysing large and complex geospatial datasets, including descriptive, explanatory, and predictive analytics. However, applying these methods is just one part of the overall process of geographic data science. Other critical steps include screening for suspect data values, handling missing data, harmonizing data from multiple sources, summarizing the data, and visualizing data and analysis results. Although there are many books available on statistical and machine learning methods, few encompass the broader topic of scientific workflows for geospatial data processing and analysis. The purpose of Geographic Data Science with R is to fill this gap by providing a series of tutorials aimed at teaching good practices for using geospatial data to address problems in environmental geography. It is based on the R language and environment, which currently provides the best option for working with diverse spatial and non-spatial data in a single platform. Fundamental techniques for processing and visualizing tabular, vector, and raster data are introduced through a series of practical examples followed by case studies that combine multiple types of data to address more complex problems. The book will have a broad audience. Both students and professionals can use it as a workbook to learn high-level techniques for geospatial data processing and analysis with R. It is also suitable as a textbook. Although not intended to provide a comprehensive introduction to R, it is designed to be accessible to readers who have at least some knowledge of coding but little to no experience with R. Key Features: Focus on developing practical workflows for processing and integrating multiple sources of geospatial data in R Example-based approach that teaches R programming and data science concepts through real-world applications related to climate, land cover and land use, and natural hazards. Consistent use of tidyverse packages for tabular data manipulation and visualization. Strong focus on analysing continuous and categorical raster datasets using the new terra package Organized so that each chapter builds on the topics and techniques covered in the preceding chapters Can be used for self-study or as the textbook for a geospatial science course.
R 5,165.00
Efficient Structures for Geometric Data Management
The efficient management of geometric data, such as points, curves, or polyhedra in arbitrary dimensions, is of great importance in many complex database applications like CAD/CAM, robotics, or computer vision. To provide optimal support for geometric operations, it is crucial to choose efficient data representation schemes. The first part of this book contains a taxonomy and critical survey of common operations and representation schemes for geometric data. Then several new schemes for the efficient support of set operations (union, intersection) and search operations (point location, range search) are presented.
R 2,149.50
Compilation Techniques for Reconfigurable Architectures
The extreme ?exibility of recon?gurable architectures and their performance pot- tial have made them a vehicle of choice in a wide range of computing domains, from rapid circuit prototyping to high-performance computing. The increasing availab- ity of transistors on a die has allowed the emergence of recon?gurable architectures with a large number of computing resources and interconnection topologies. To - ploit the potential of these recon?gurable architectures, programmers are forced to map their applications, typically written in high-level imperative programming l- guages, such as C or MATLAB, to hardware-oriented languages such as VHDL or Verilog. In this process, they must assume the role of hardware designers and software programmers and navigate a maze of program transformations, mapping, and synthesis steps to produce ef?cient recon?gurable computing implementations. The richness and sophistication of any of these application mapping steps make the mapping of computations to these architectures an increasingly daunting process. It is thus widely believed that automatic compilation from high-level programming languages is the key to the success of recon?gurable computing. This book describes a wide range of code transformations and mapping te- niques for programs described in high-level programming languages, most - tably imperative languages, to recon?gurable architectures.
R 3,027.48
Modeling, Learning, and Processing of Text-Technological Data Structures
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
R 5,553.78
Programming the Dynamic Analysis of Structures
This title presents a series of integrated computer programs in Fortran-90 for the dynamic analysis of structures, using the finite element method. Two dimensional continuum structures such as walls are covered along with skeletal structures such as rigid jointed frames and plane grids. Response to general dynamic loading of single degree freedom systems is calculated, and the author also examines multi degree of freedom systems (including earthquake analysis). Each chapter covers a different aspect of analytic theory and the corresponding program segments. It should be an essential tool for practising structural and civil engineers, whilst also being of interest to academics and postgraduate students.
R 12,348.60
Estimation of Structural Models Using Experimental Data From the Lab and the Field
Behavioral economics provides a rich set of explicit models of non-classical preferences and belief formation which can be used to estimate structural models of decision making. At the same time, experimental approaches allow the researcher to exogenously vary components of the decision making environment. The synergies between behavioral and experimental economics provide a natural setting for the estimation of structural models. This Element will cover examples supporting the following arguments 1) Experimental data allows the researcher to estimate structural models under weaker assumptions and can simplify their estimation, 2) many popular models in behavioral economics can be estimated without any programming skills using existing software, 3) experimental methods are useful to validate structural models. This Element aims to facilitate adoption of structural modelling by providing Stata codes to replicate some of the empirical illustrations that are presented. Examples covered include estimation of outcome-based preferences, belief-dependent preferences and risk preferences.
R 922.75
Data Mining in Structural Dynamic Analysis
This book highlights the applications of data mining technologies in structural dynamic analysis, including structural design, optimization, parameter identification, model updating, damage identification, in civil, mechanical, and aerospace engineering. These engineering applications require precise structural design, fabrication, inspection, and further monitoring to obtain a full life-cycle analysis, and by focusing on data processing, data mining technologies offer another aspect in structural dynamic analysis. Discussing techniques in time/frequency domain, such as Hilbert transforms, wavelet theory, and machine learning for structural dynamic analysis to help in structural monitoring and diagnosis, the book is an essential reference resource for beginners, graduates and industrial professionals in various fields.
R 3,399.07
Getting Structured Data from the Internet
Utilize web scraping at scale to quickly get unlimited amounts of free data available on the web into a structured format. This book teaches you to use Python scripts to crawl through websites at scale and scrape data from HTML and JavaScript-enabled pages and convert it into structured data formats such as CSV, Excel, JSON, or load it into a SQL database of your choice. This book goes beyond the basics of web scraping and covers advanced topics such as natural language processing (NLP) and text analytics to extract names of people, places, email addresses, contact details, etc., from a page at production scale using distributed big data techniques on an Amazon Web Services (AWS)-based cloud infrastructure. It book covers developing a robust data processing and ingestion pipeline on the Common Crawl corpus, containing petabytes of data publicly available and a web crawl data set available on AWS's registry of open data.Getting Structured Data from the Internet also includes a step-by-step tutorial on deploying your own crawlers using a production web scraping framework (such as Scrapy) and dealing with real-world issues (such as breaking Captcha, proxy IP rotation, and more). Code used in the book is provided to help you understand the concepts in practice and write your own web crawler to power your business ideas.What You Will LearnUnderstand web scraping, its applications/uses, and how to avoid web scraping by hitting publicly available rest API endpoints to directly get dataDevelop a web scraper and crawler from scratch using lxml and BeautifulSoup library, and learn about scraping from JavaScript-enabled pages using SeleniumUse AWS-based cloud computing with EC2, S3, Athena, SQS, and SNS to analyze, extract, and store useful insights from crawled pagesUse SQL language on PostgreSQL running on Amazon Relational Database Service (RDS) and SQLite using SQLalchemyReview sci-kit learn, Gensim, and spaCy to perform NLP tasks on scraped web pages such as name entity recognition, topic clustering (Kmeans, Agglomerative Clustering), topic modeling (LDA, NMF, LSI), topic classification (naive Bayes, Gradient Boosting Classifier) and text similarity (cosine distance-based nearest neighbors)Handle web archival file formats and explore Common Crawl open data on AWSIllustrate practical applications for web crawl data by building a similar website tool and a technology profiler similar to builtwith.comWrite scripts to create a backlinks database on a web scale similar to Ahrefs.com, Moz.com, Majestic.com, etc., for search engine optimization (SEO), competitor research, and determining website domain authority and rankingUse web crawl data to build a news sentiment analysis system or alternative financial analysis covering stock market trading signalsWrite a production-ready crawler in Python using Scrapy framework and deal with practical workarounds for Captchas, IP rotation, and moreWho This Book Is ForPrimary audience: data analysts and scientists with l
R 1,368.00
