Refine Results
Sort By
From
To
Page 8
Page 8
Case-Based Approximate Reasoning
Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'. Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.
Canadian Semantic Web
This book covers a variety of well known topics of interest to practitioners in industry and research scientists. The range of topics includes languages, tools and methodologies for the semantic Web, semantic Web-based ontology management and engineering, semantic Web services, practical applications of the semantic Web techniques, artificial intelligence methods and tools for the semantic Web, software agents on the semantic Web, visualization and modeling of the semantic Web. The goal of this book is to provide a state-of-the-art review of the research as well as to introduce topics of interest to experts.
Business process management : Concepts, languages, architectures
Business process management is usually treated from two different perspectives: business administration and computer science. While business administration professionals tend to consider information technology as a subordinate aspect for experts to handle, by contrast computer scientists often consider business goals and organizational regulations as terms that do not deserve much thought but require the appropriate level of abstraction.This textbook is ideally suited for classes on business process management, information systems architecture, and workflow management. It is also valuable for project managers and IT professionals working in business process management.
Building a Data Warehouse : With Examples in SQL Server
The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation.
Brain and Human Body Modeling : Computational Human Modeling at EMBC 2018
This book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner.
Boundary Representation Modelling Techniques
Boundary representation is the principle solid modelling method used in modern CAD/CAM systems. There have been a long series of developments on which currently available systems are based, full details of which are only partially known. Ian Stroud’s thorough coverage of these developments puts this technology in perspective. Ian Stroud started working with boundary representation solid modelling in 1977. Since then he has researched and is researching a wide variety of topics in and around this field. The information in the book comes from the results of this research.
Blockchain : Empowering Secure Data Sharing
The book explains the security architecture model and the practice of building data sharing from the blockchain infrastructure, allowing readers to understand the importance of data sharing security based on the blockchain framework, as well as the threats to security and privacy. Further, by presenting specific data sharing case studies, it offers insights into solving data security sharing problems in more practical fields. The book is intended for readers with a basic understanding of the blockchain infrastructure, consensus mechanisms, smart contracts, secure multiparty computing, homomorphic encryption and image retrieval technologies.
Biometrics, Computer Security Systems and Artificial Intelligence Applications
This book presents the most recent achievements in some fascinating and rapidly developing fields within Computer Science. The scientific works presented in this book have been partitioned into three topical groups: Image Analysis and Biometrics, Computer Security Systems, and Artificial Intelligence and Applications. Image Analysis and Biometrics is the branch of Computer Science dealing with the very difficult task of artificial, visual perception of objects and surroundings, as well as the problems connected with it. Computer Security and Safety is at present a very important and intensively investigated branch of Computer Science because of the menacing activity of hackers and computer viruses.
Biomedical data mining for information retrieval : Methodologies, techniques, and applications
Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.
Biologically Inspired Algorithms for Financial Modelling
Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures.
Biological and medical data analysis ; Vol. 3745 ; 6th International symposium, ISBMDA 2005, Aveiro, Portugal, November 10-11, 2005, Proceedings
The 6th International Symposium on Biological and Medical Data Analysisaimed to become a place where researchersinvolved in these diverse but increas-ingly complementary areas could meet topresent and discuss their scientificresults.The papers in this volume discuss issues from statistical models to archi-tectures and applications to bioinformatics and biomedicine. They cover bothpractical experience and novel research ideas and concepts.
Bioinformatics
In this textbook present mathematical models in bioinformatics and they describe the biological problems that inspire the computer science tools used to handle the enormous data sets involved. The first part of the book covers the mathematical and computational methods, while the practical applications are presented in the second part. The mathematical presentation is descriptive and avoids unnecessary formalism, and yet remains clear and precise. Emphasis is laid on motivation through biological problems and cross applications. Each of the four chapters in the first part is accompanied by exercises and problems to support an understanding of the techniques presented. Each of the six chapters of the second part is devoted to some specific application domain: sequence alignment, molecular phylogenetics and coalescence theory, genomics, proteomics, RNA, and DNA microarrays. Each chapter concludes with a problems and projects section, to deepen the reader's understanding and to allow for the design of derived methods. Many of the projects involve publicly available software and/or Web-based bioinformatics depositories. Finally, the book closes with a thorough bibliography, reaching from classic research results to very recent findings, providing many pointers for future research.Overall, this volume is ideally suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on its mathematical and computer science background.
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
Best practices in software measurement : How to use metrics to improve project and process performance
Not everything that counts can be counted. Not everything that is counted counts. Albert Einstein This is a book about software measurement from the practitioner’s point of view and it is a book for practitioners. Software measurement needs a lot of practical guidance to build upon experiences and to avoid repeating errors. This book t- gets exactly this need, namely to share experiences in a constructive way that can be followed. It tries to summarize experiences and knowledge about software measurement so that it is applicable and repeatable. It extracts experiences and lessons learned from the narrow context of the specific industrial situation, thus facilitating transfer to other contexts. Software measurement is not at a standstill. With the speed software engine- ing is evolving, software measurement has to keep pace. While the underlying theory and basic principles remain invariant in the true sense (after all, they are not specific to software engineering), the application of measurement to specific contexts and situations is continuously extended. The book thus serves as a ref- ence on these invariant principles as well as a practical guidance on how to make software measurement a success.
Beginning xml with C# 2008 : From novice to professional
Beginning XML with C# 2008 focuses on XML and how it is used within .NET 3.5. As you'd expect of a modern application framework, .NET 3.5 has extensive support for XML in everything from data access to configuration, from raw parsing to code documentation. This book demystifies all of this. It explains the basics of XML as well as the namespaces and objects you need to know in order to work efficiently with XML. You will see clear, practical examples that illustrate best practices in action. With this book, you'll learn everything you need to know from the basics of reading and writing XML data to using the DOM, from LINQ and SQL Server integration to SOAP and web services.
Beginning relational data modeling
Data storage design, and awareness of how data needs to be utilized within an organization, is of prime importance in ensuring that company data systems work efficiently. 'Beginning Data Modeling' leads readers you step by step through the process of developing an effective logical data model for a relational database model.
Beginning Object-Oriented Programming with VB 2005 : From novice to professional
Beginning Object-Oriented Programming with VB 2005 is a comprehensive resource of correct coding procedures. Author Daniel Clark takes you through all the stages of a programming project, including analysis, modeling, and development, all using object-oriented programming techniques and Visual Basic .NET. Clark explores the structure of classes and their hierarchies, as well as inheritance and interfaces. He also introduces the .NET Framework and the Visual Studio integrated development environment, or IDE. A real-world case study walks you through the design of a solution. You can then transform the design into a functional VB .NET application. The application includes a graphical user interface (GUI), a business logic class library, and integration with a back-end database. Throughout the book, you'll explore the fundamentals of software design, object-oriented programming, Visual Basic .NET 2.0, and the Unified Modeling Language (UML).
Beginning Java Objects : From concepts to code
Learning to design objects effectively with Java is the goal of Beginning Java Objects: From Concepts to Code, Second Edition. Plenty of titles dig into the Java language in massive detail, but this one takes the unique approach of stepping back and looking at fundamental object concepts first. Mastery of Java—from understanding the basic language features to building complete industrial-strength Java applications—emerges only after a thorough tour of thinking in objects. The first edition of Beginning Java Objects has been a bestseller; this second edition includes material on the key features of J2SE 5, conceptual introductions to JDBC and J2EE, and an in-depth treatment of the critical design principles of model-data layer separation and model-view separation.
Beginning deep learning with TensorFlow : Work with Keras, MNIST data sets, and advanced neural networks
Stats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! You will: Develop using deep learning algorithms Build deep learning models using TensorFlow 2 Create classification systems and other, practical deep learning applications
Beginning Database Design : From novice to professional
Beginning Database Design: From Novice to Professional provides short, easy-to-read explanations of how to get database design right the first time. Through the help of use cases and class diagrams modeled in the UML, youll learn how to discover and represent the details and scope of the problem in question.
