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Theory and Applications of Relational Structures as Knowledge Instruments
Relational structures abound in our daily environment: relational databases, data mining, scaling procedures, preference relations, etc. As the documentation of scientific results achieved within the European COST Action 274, TARSKI, this book advances the understanding of relational structures and the use of relational methods in various application fields.The 12 revised full papers were carefully reviewed and selected for presentations. The papers are devoted to mechanization of relational reasoning, relational scaling and preferences, and algebraic and logical foundations of real world relations.
R 2,339.06
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
Building AI-Powered Distributed Architectures with Aspire
Build cloud-native distributed .NET applications with Aspire, ASP.NET Core microservices, generative AI, semantic search, and Azure deployment.Key FeaturesBuild an end-to-end distributed e-commerce system with AI capabilitiesIntegrate PostgreSQL, Redis, RabbitMQ, Keycloak, and Ollama with AspireDeploy secure, AI-enabled microservices to Azure Container AppsBook DescriptionBuild practical AI-powered distributed applications by seeing how microservices, messaging, security, data services, and generative AI work together in one project. This book guides you through building a cloud-native e-commerce application with independently deployed services, reliable communication, specialized data stores, and intelligent features.You’ll use Aspire to orchestrate Catalog and Basket microservices, configure service discovery, and integrate PostgreSQL and Redis. You’ll implement synchronous communication and asynchronous messaging with RabbitMQ and MassTransit, secure Basket APIs with Keycloak and JWT bearer tokens, and connect a Blazor frontend to the distributed backend. You’ll then add generative AI capabilities using Microsoft.Extensions.AI, Microsoft Agent Framework, and Ollama. You’ll build customer-support Q&A and semantic product search using embeddings and vector storage before deploying the application to Azure Container Apps. Written by software and solutions architect Mehmet Ozkaya, who has more than 15 years of industry experience and has taught more than 200,000 students, this book combines hands-on development with architectural guidance. By the end, you’ll be able to design, orchestrate, secure, enhance, and deploy AI-enabled distributed .NET applications. What you will learnDesign cloud-native distributed systems with AspireBuild Catalog and Basket microservices with ASP.NET CoreOrchestrate PostgreSQL and Redis as backing servicesImplement event-driven messaging with RabbitMQ and MassTransitSecure microservice endpoints with Keycloak and JWT bearer tokensBuild enterprise AI features with Microsoft.Extensions.AI, Ollama, and Microsoft Agent FrameworkImplement semantic search with embeddings and vector storageDeploy distributed applications to Azure Container AppsWho this book is for.NET developers, software engineers, and solution architects who want to build cloud-native distributed applications and add generative AI capabilities will benefit from this book. It is also suited to developers exploring microservices, event-driven architecture, Aspire, and AI integration. Basic knowledge of C# and programming concepts is required.
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Operating Systems In Depth
This book is designed for a one-semester operating-systems course for advanced undergraduates and beginning graduate students. Prerequisites for the course generally include an introductory course on computer architecture and an advanced programming course. The goal of this book is to bring together and explain current practice in operating systems. This includes much of what is traditionally covered in operating-system textbooks: concurrency, scheduling, linking and loading, storage management (both real and virtual), file systems, and security. However, the book also covers issues that come up every day in operating-systems design and implementation but are not often taught in undergraduate courses. For example, the text includes: Deferred work, which includes deferred and asynchronous procedure calls in Windows, tasklets in Linux, and interrupt threads in Solaris.The intricacies of thread switching, on both uniprocessor and multiprocessor systems.Modern file systems, such as ZFS and WAFL.Distributed file systems, including CIFS and NFS version 4. The book and its accompanying significant programming projects make students come to grips with current operating systems and their major operating-system components and to attain an intimate understanding of how they work.
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Algorithms and Architectures for Parallel Processing
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
R 2,946.60
Algorithms and Architectures for Parallel Processing
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
R 2,949.98
Algorithms and Architectures for Parallel Processing
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
R 2,949.67
Algorithms and Architectures for Parallel Processing
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
R 2,945.70
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
Medical Image Computing and Computer Assisted Intervention – MICCAI 2025
The 16-volume set LNCS 15960 - 15975 constitutes the refereed proceedings of the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea, during September 23-27, 2025. The total of 1027 papers included in the proceedings was carefully reviewed and selected from 3447 submissions. They were organized in topical parts as follows: Part I, LNCS Volume 15960: Multimodal Fusion and Contextual Reasoning in Medical Imaging Part II, LNCS Volume 15961: Surgical Navigation, Scene Understanding, and Video Modeling Part III, LNCS Volume 15962: Learning and Augmented Reality for Surgical and Endoscopic Applications (I) Part IV, LNCS Volume 15963: Learning and Augmented Reality for Surgical and Endoscopic Applications (II) Part V, LNCS Volume 15964: Graph-Based Methods in Medical Imaging Part VI, LNCS Volume 15965: Datasets and Methods for Image Quality Enhancement Part VII, LNCS Volume 15966: Trustworthy and Responsible AI for Medical Imaging Part VIII, LNCS Volume 15967: Multimodal Learning for Diagnosis, Risk Prediction, and Survival Analysis Part IX, LNCS Volume 15968: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (I) Part X, LNCS Volume 15969: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (II) Part XI, LNCS Volume 15970: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (III) Part XII, LNCS Volume 15971: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (IV) Part XIII, LNCS Volume 15972: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (I) Part XIV, LNCS Volume 15973: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (II) Part XV, LNCS Volume 15974: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (III) Part XVI, LNCS Volume 15975: Statistical Techniques in Medical Imaging: Causality, Imputation, Weak Supervision, and Other Methods
R 3,577.08
Advances in Computer Science - ASIAN 2005. Data Management on the Web
The series of annual Asian Computing Science Conferences (ASIAN) was ini- ated in 1995 by AIT, INRIA and UNU/IIST to provide a forum for researchers in computer science from the Asian region and to promote interaction with - searchers from other regions. The ?rst nine conferences were held respectively in Bangkok, Singapore, Katmandu, Manila, Phuket, Penang, Hanoi, Mumbai and Chiang Mai. The 10th ASIAN conference was held in Kunming, China, December 7-9, 2005. Each year, the conference focuses on a di?erent theme at the cutting edge of computer science research. The theme of ASIAN 2005 was data management on the Web. Four distinguished speakers were invited to the conference: M- iano Consens (University of Toronto), Richard Hull (Bell Laboratories, Lucent Technologies),TovaMilo(TelAvivUniversity)andPrabhakarRaghavan(Yahoo Research and Stanford University). This year, 91 papers were submitted from 11 countries. The Program C- mittee selected 17 regular papers and 21 short papers. This volume contains the papers based on the invited talks, the regular papers, and the short papers.We wish to thank the Program Committee and the external referees for their work in selecting the contributed papers.
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Univariate, Bivariate, and Multivariate Statistics Using R
A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate Statistics Using R offers a practical and very user-friendly introduction to the use of R software that covers a range of statistical methods featured in data analysis and data science. The author— a noted expert in quantitative teaching —has written a quick go-to reference for performing essential statistical analyses and data management tasks in R. Requiring only minimal prior knowledge, the book introduces concepts needed for an immediate yet clear understanding of statistical concepts essential to interpreting software output. The author explores univariate, bivariate, and multivariate statistical methods, as well as select nonparametric tests. Altogether a hands-on manual on the applied statistics and essential R computing capabilities needed to write theses, dissertations, as well as research publications. The book is comprehensive in its coverage of univariate through to multivariate procedures, while serving as a friendly and gentle introduction to R software for the newcomer. This important resource: Offers an introductory, concise guide to the computational tools that are useful for making sense out of data using R statistical softwareProvides a resource for students and professionals in the social, behavioral, and natural sciencesPuts the emphasis on the computational tools used in the discovery of empirical patternsFeatures a variety of popular statistical analyses and data management tasks that can be immediately and quickly applied as needed to research projectsShows how to apply statistical analysis using R to data sets in order to get started quickly performing essential tasks in data analysis and data science Written for students, professionals, and researchers primarily in the social, behavioral, and natural sciences, Univariate, Bivariate, and Multivariate Statistics Using R offers an easy-to-use guide for performing data analysis fast, with an emphasis on drawing conclusions from empirical observations. The book can also serve as a primary or secondary textbook for courses in data analysis or data science, or others in which quantitative methods are featured.
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Self-Assembly of Nano- and Micro-structured Materials Using Colloidal Engineering
Self-assembly of Nano- and Micro-structured Materials Using Colloidal Engineering, Volume 12, covers the recent breakthroughs in the design and manufacture of functional colloids at the micro- and nanoscale level. In addition, it provides analyses on how these functionalities can be exploited to develop self-assembly pathways towards nano- and micro-structured materials. As we seek increasingly complex functions for colloidal superstructures, in silico design will play a critical role in guiding experimental fabrication by reducing the element of trial-and-error that would otherwise be involved. In addition to novel experimental approaches, recent developments in computational modelling are also presented, along with an overview of the arsenal of designing tools that are available to the modern materials scientist.
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Mining Text Data
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
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Analysis and Computation of Microstructure in Finite Plasticity
This book addresses the need for a fundamental understanding of the physical origin, the mathematical behavior and the numerical treatment of models which include microstructure. Leading scientists present their efforts involving mathematical analysis, numerical analysis, computational mechanics, material modelling and experiment. The mathematical analyses are based on methods from the calculus of variations, while in the numerical implementation global optimization algorithms play a central role. The modeling covers all length scales, from the atomic structure up to macroscopic samples. The development of the models ware guided by experiments on single and polycrystals and results will be checked against experimental data.
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Machine and Deep Learning Using MATLAB
MACHINE AND DEEP LEARNING In-depth resource covering machine and deep learning methods using MATLAB tools and algorithms, providing insights and algorithmic decision-making processes Machine and Deep Learning Using MATLAB introduces early career professionals to the power of MATLAB to explore machine and deep learning applications by explaining the relevant MATLAB tool or app and how it is used for a given method or a collection of methods. Its properties, in terms of input and output arguments, are explained, the limitations or applicability is indicated via an accompanied text or a table, and a complete running example is shown with all needed MATLAB command prompt code. The text also presents the results, in the form of figures or tables, in parallel with the given MATLAB code, and the MATLAB written code can be later used as a template for trying to solve new cases or datasets. Throughout, the text features worked examples in each chapter for self-study with an accompanying website providing solutions and coding samples. Highlighted notes draw the attention of the user to critical points or issues. Readers will also find information on: Numeric data acquisition and analysis in the form of applying computational algorithms to predict the numeric data patterns (clustering or unsupervised learning)Relationships between predictors and response variable (supervised), categorically sub-divided into classification (discrete response) and regression (continuous response)Image acquisition and analysis in the form of applying one of neural networks, and estimating net accuracy, net loss, and/or RMSE for the successive training, validation, and testing stepsRetraining and creation for image labeling, object identification, regression classification, and text recognition Machine and Deep Learning Using MATLAB is a useful and highly comprehensive resource on the subject for professionals, advanced students, and researchers who have some familiarity with MATLAB and are situated in engineering and scientific fields, who wish to gain mastery over the software and its numerous applications.
R 5,699.00
Advances in Computing and Data Sciences
This two-volume set (CCIS 1045 and CCIS 1046) constitutes the refereed proceedings of the Third International Conference on Advances in Computing and Data Sciences, ICACDS 2019, held in Ghaziabad, India, in April 2019.The 112 full papers were carefully reviewed and selected from 621 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations.
R 2,806.42
Algorithms and Architectures for Parallel Processing
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29–31, 2024.The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.
R 2,951.58
Medical Image Computing and Computer Assisted Intervention – MICCAI 2025
The 16-volume set LNCS 15960 - 15975 constitutes the refereed proceedings of the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea, during September 23-27, 2025. The total of 1027 papers included in the proceedings was carefully reviewed and selected from 3447 submissions. They were organized in topical parts as follows: Part I, LNCS Volume 15960: Multimodal Fusion and Contextual Reasoning in Medical Imaging Part II, LNCS Volume 15961: Surgical Navigation, Scene Understanding, and Video Modeling Part III, LNCS Volume 15962: Learning and Augmented Reality for Surgical and Endoscopic Applications (I) Part IV, LNCS Volume 15963: Learning and Augmented Reality for Surgical and Endoscopic Applications (II) Part V, LNCS Volume 15964: Graph-Based Methods in Medical Imaging Part VI, LNCS Volume 15965: Datasets and Methods for Image Quality Enhancement Part VII, LNCS Volume 15966: Trustworthy and Responsible AI for Medical Imaging Part VIII, LNCS Volume 15967: Multimodal Learning for Diagnosis, Risk Prediction, and Survival Analysis Part IX, LNCS Volume 15968: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (I) Part X, LNCS Volume 15969: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (II) Part XI, LNCS Volume 15970: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (III) Part XII, LNCS Volume 15971: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (IV) Part XIII, LNCS Volume 15972: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (I) Part XIV, LNCS Volume 15973: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (II) Part XV, LNCS Volume 15974: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (III) Part XVI, LNCS Volume 15975: Statistical Techniques in Medical Imaging: Causality, Imputation, Weak Supervision, and Other Methods
R 3,573.86
PLC Programming In Instruction List According To IEC 61131-3
This textbook and exercise book provides a solid basic knowledge and comprehensive practical skills in dealing with PLC programming. Numerous exercises help to deepen the material. With the accompanying simulation software and sample solutions, the acquired knowledge can be applied immediately. The software can be downloaded via the Internet.The knowledge of number systems and digital technology conveyed in the book is an important prerequisite for skilful and clever PLC programming. The programming language used, "Instruction list according to IEC 61131-3", provides the best insights into the functioning of a PLC. The didactically prepared programming examples for switching networks, signal memories, time functions, counters, function blocks and functions, program structures, sequence controls, data types and much more enable systematic learning of programming.The 5th, corrected edition experiences an expansion of the exercises with a didactically prepared project for the control of a mountain railway. The associated simulation software "PLC-lite" enables the realisation of controls for the mountain railway and the "realistic" representation of the cableway movements on the screen.
R 3,212.41
Medical Image Computing and Computer Assisted Intervention – MICCAI 2025
The 16-volume set LNCS 15960 - 15975 constitutes the refereed proceedings of the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea, during September 23-27, 2025. The total of 1027 papers included in the proceedings was carefully reviewed and selected from 3447 submissions. They were organized in topical parts as follows: Part I, LNCS Volume 15960: Multimodal Fusion and Contextual Reasoning in Medical Imaging Part II, LNCS Volume 15961: Surgical Navigation, Scene Understanding, and Video Modeling Part III, LNCS Volume 15962: Learning and Augmented Reality for Surgical and Endoscopic Applications (I) Part IV, LNCS Volume 15963: Learning and Augmented Reality for Surgical and Endoscopic Applications (II) Part V, LNCS Volume 15964: Graph-Based Methods in Medical Imaging Part VI, LNCS Volume 15965: Datasets and Methods for Image Quality Enhancement Part VII, LNCS Volume 15966: Trustworthy and Responsible AI for Medical Imaging Part VIII, LNCS Volume 15967: Multimodal Learning for Diagnosis, Risk Prediction, and Survival Analysis Part IX, LNCS Volume 15968: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (I) Part X, LNCS Volume 15969: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (II) Part XI, LNCS Volume 15970: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (III) Part XII, LNCS Volume 15971: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (IV) Part XIII, LNCS Volume 15972: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (I) Part XIV, LNCS Volume 15973: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (II) Part XV, LNCS Volume 15974: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (III) Part XVI, LNCS Volume 15975: Statistical Techniques in Medical Imaging: Causality, Imputation, Weak Supervision, and Other Methods
R 3,582.83
Computer Aided Learning and Instruction in Science and Engineering
This book constitutes the refereed proceedings of the Third International Conference on Computer Aided Learning and Instruction in Science and Engineering, CALICSE '96, held in San Sebastián, Spain in July 1996.The 42 revised full papers presented in the book were selected from a total of 134 submissions; also included are the abstracts of full papers of four invited talks and 17 poster presentations. The papers are organized in topical sections on learning environments: modelling and design, authoring and development tools and techniques, CAL in distance learning, multimedia and hypermedia in CAL, and applications in science and engineering.
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Introduction to Public Key Infrastructures
The introduction of public key cryptography (PKC) was a critical advance in IT security. In contrast to symmetric key cryptography, it enables confidential communication between entities in open networks, in particular the Internet, without prior contact. Beyond this PKC also enables protection techniques that have no analogue in traditional cryptography, most importantly digital signatures which for example support Internet security by authenticating software downloads and updates. Although PKC does not require the confidential exchange of secret keys, proper management of the private and public keys used in PKC is still of vital importance: the private keys must remain private, and the public keys must be verifiably authentic. So understanding so-called public key infrastructures (PKIs) that manage key pairs is at least as important as studying the ingenious mathematical ideas underlying PKC. In this book the authors explain the most important concepts underlying PKIs and discuss relevant standards, implementations, and applications. The book is structured into chapters on the motivation for PKI, certificates, trust models, private keys, revocation, validity models, certification service providers, certificate policies, certification paths, and practical aspects of PKI.This is a suitable textbook for advanced undergraduate and graduate courses in computer science, mathematics, engineering, and related disciplines, complementing introductory courses on cryptography. The authors assume only basic computer science prerequisites, and they include exercises in all chapters and solutions in an appendix. They also include detailed pointers to relevant standards and implementation guidelines, so the book is also appropriate for self-study and reference by industrial and academic researchers and practitioners.
R 2,731.65
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.
R 4,393.24
Nature Inspired Computing for Data Science
This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
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Structure of the Relational Database Model
This book presents an overview of the most fundamental aspects of the theory that underlies the Relational Database Model. As such it is self-contained though experience with formal models and abstract data manipulating on the one hand and with the practical use of a relational system on the other hand can help the reader. Such experience will offer the reader a better understanding of and a motivation for the different concepts, theories and results mentioned in the book. We have focussed on the most basic concepts and aspects of the relational model, without trying to give a complete overview of the state of the art of database theory. Recently a lot of books on databases in general and on the relational model in particular have been published. Most of them describe the use of database systems. 'Some clarify how information has to be structured and organized before it can be used to build applications. Others help the user in writing down his applications or in finding tricky ways to optimize the running time or the necessary space. Another category of books treat more fundamental and more general aspects such as the description of the relational model, independent of any implementation, the decomposition in normal forms or the global design of distributed databases. Few, however, are the books that describe in a formal way some of the subjects mentioned above.
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Using Communication Technology
Communication technology not only changes the face of organizations, but can support organizations in their strive to become learning organizations. In Using Communication Technology , Bettina Büchel examines the relationship between information technology and organizations from a range of perspectives, and highlights the managerial implications stemming from this relationship. Analysis is based on theoretical work in organizational studies, management and computer science, and draws upon case studies from companies in Europe and Asia. This book provides managers with guidelines for individual choice among communication media and goes on to suggest means of evaluating the outcome of communication technology strategy. The author shows how organizational use of communication technologies can lead the way towards the creation of knowledge organizations.
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Design of Embedded Robust Control Systems Using MATLAB® / Simulink®
Robust control theory allows for changes in a system whilst maintaining stability and performance. Applications of this technique are very important for dependable embedded systems, making technologies such as drones and other autonomous systems with sophisticated embedded controllers and systems relatively common-place. The aim of this book is to present the theoretical and practical aspects of embedded robust control design and implementation with the aid of MATLAB® and SIMULINK®. It covers methods suitable for practical implementations, combining knowledge from control system design and computer engineering to describe the entire design cycle. Three extended case studies are developed in depth: embedded control of a tank physical model; robust control of a miniature helicopter; and robust control of two-wheeled robots. These are taken from the area of motion control but the book may be also used by designers in other areas. Some knowledge of Linear Control Theory is assumed and knowledge of C programming is desirable but to make the book accessible to engineers new to the field and to students, the authors avoid complicated mathematical proofs and overwhelming computer architecture technical details. All programs used in the examples and case studies are freely downloadable to help with the assimilation of the book contents.
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Energy Efficient Hardware-Software Co-Synthesis Using Reconfigurable Hardware
Rapid energy estimation for energy efficient applications using field-programmable gate arrays (FPGAs) remains a challenging research topic. Energy dissipation and efficiency have prevented the widespread use of FPGA devices in embedded systems, where energy efficiency is a key performance metric. Helping overcome these challenges, Energy Efficient Hardware-Software Co-Synthesis Using Reconfigurable Hardware offers solutions for the development of energy efficient applications using FPGAs.The book integrates various high-level abstractions for describing hardware and software platforms into a single, consistent application development framework, enabling users to construct, simulate, and debug systems. Based on these high-level concepts, it proposes an energy performance modeling technique to capture the energy dissipation behavior of both the reconfigurable hardware platform and the target applications running on it. The authors also present a dynamic programming-based algorithm to optimize the energy performance of an application running on a reconfigurable hardware platform. They then discuss an instruction-level energy estimation technique and a domain-specific modeling technique to provide rapid and fairly accurate energy estimation for hardware-software co-designs using reconfigurable hardware. The text concludes with example designs and illustrative examples that show how the proposed co-synthesis techniques lead to a significant amount of energy reduction.This book explores the advantages of using reconfigurable hardware for application development and looks ahead to future research directions in the field. It outlines the range of aspects and steps that lead to an energy efficient hardware-software application synthesis using FPGAs.
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Advances in Computing and Data Sciences
This two-volume book constitutes the post-conference proceedings of the 5th International Conference on Advances in Computing and Data Sciences, ICACDS 2021, held in Nashik, India, in April 2021.*The 103 full papers were carefully reviewed and selected from 781 submissions. The papers in Part I and II are centered around topics like distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations database management system engines, data mining, information retrieval query processing, database and storage security, ubiquitous and mobile computing, parallel computing methodologies, and others. *The conference was held virtually due to the COVID-19 pandemic.
R 3,652.83
Advances in Computing and Data Sciences
This two-volume book constitutes the post-conference proceedings of the 5th International Conference on Advances in Computing and Data Sciences, ICACDS 2021, held in Nashik, India, in April 2021.*The 103 full papers were carefully reviewed and selected from 781 submissions. Part II is devoted to data sciences, organizing principles, medical technologies, computational linguistics etc.*The conference was held virtually due to the COVID-19 pandemic.
R 3,915.24
Nature-Inspired Computation in Data Mining and Machine Learning
This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
R 4,242.87
Methods of Environmental Data Analysis
ENVIRONMENTAL MANAGEMENT SERIES The current expansion of both public and scientific interest in environ mental issues has not been accompanied by a commensurate production of adequate books, and those which are available are widely variable in approach and depth. The Environmental Management Series has been established with a view to co-ordinating a series of volumes dealing with each topic within the field in some depth. It is hoped that this Series will provide a uniform and quality coverage and that, over a period of years, it will build up to form a library of reference books covering most of the major topics within this diverse field. It is envisaged that the books will be of single, or dual authorship, or edited volumes as appropriate for respective topics. The level of presentation will be advanced, the books being aimed primarily at a research/consultancy readership. The coverage will include all aspects of environmental science and engineering pertinent to manage ment and monitoring of the natural and man-modified environment, as well as topics dealing with the political, t:conomic, legal and social con siderations pertaining to environmental management.
R 1,560.21
Advances in Computing and Data Sciences
This two-volume set (CCIS 905 and CCIS 906) constitutes the refereed proceedings of the Second International Conference on Advances in Computing and Data Sciences, ICACDS 2018, held in Dehradun, India, in April 2018.The 110 full papers were carefully reviewed and selected from 598 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations.
R 1,601.48
Big Data and Visual Analytics
This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
R 3,841.23
Innovation and Structural Change in Post-Socialist Countries: A Quantitative Approach
This book uses a range of S&T and structural indicators to analyse the transfonnation process, in particular the transfonnation of science, technology and industry, in the fonner communist countries. The book originates from a sense of the tremendous need for quantitative indicators for assessing trends and perfonnance in the post-socialist economies. S&T systems in the region have passed through the first phase of rapid deterioration, or as it is called by some analysts 'implosion'. After ten years of transfonnation we are witnessing a process of increasing differentiation of these countries in tenns of general patterns of growth and structural change, as well as specific lines of restructuring in their S&T systems. The question of sources of growth - or indeed of stagnation - is an increasingly urgent one, from both the policy and academic perspectives. In that context there is a pressing need for in-depth assessment of restructuring patterns in science, technology and industry in the region, as a basis for understanding how restructuring in S&T is linked to industrial restructuring, and to general economic and social transfonnation. As the contributions to this volume show, there is now a critical mass of quantitative data across the post-socialist countries which deserves to be studied more thoroughly in a comparative manner. The changes of the last ten years have produced varying patterns of adjustment which are now clearly visible in S&T and structural indicators.
R 8,992.00
Medical Image Computing and Computer Assisted Intervention – MICCAI 2025
The 16-volume set LNCS 15960 - 15975 constitutes the refereed proceedings of the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea, during September 23-27, 2025. The total of 1027 papers included in the proceedings was carefully reviewed and selected from 3447 submissions. They were organized in topical parts as follows: Part I, LNCS Volume 15960: Multimodal Fusion and Contextual Reasoning in Medical Imaging Part II, LNCS Volume 15961: Surgical Navigation, Scene Understanding, and Video Modeling Part III, LNCS Volume 15962: Learning and Augmented Reality for Surgical and Endoscopic Applications (I) Part IV, LNCS Volume 15963: Learning and Augmented Reality for Surgical and Endoscopic Applications (II) Part V, LNCS Volume 15964: Graph-Based Methods in Medical Imaging Part VI, LNCS Volume 15965: Datasets and Methods for Image Quality Enhancement Part VII, LNCS Volume 15966: Trustworthy and Responsible AI for Medical Imaging Part VIII, LNCS Volume 15967: Multimodal Learning for Diagnosis, Risk Prediction, and Survival Analysis Part IX, LNCS Volume 15968: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (I) Part X, LNCS Volume 15969: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (II) Part XI, LNCS Volume 15970: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (III) Part XII, LNCS Volume 15971: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (IV) Part XIII, LNCS Volume 15972: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (I) Part XIV, LNCS Volume 15973: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (II) Part XV, LNCS Volume 15974: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (III) Part XVI, LNCS Volume 15975: Statistical Techniques in Medical Imaging: Causality, Imputation, Weak Supervision, and Other Methods
R 3,582.10
