A Guide to Graph Algorithms
Offers high-quality content in the research area of graph algorithms and explores the latest developments in graph algorithmics. The reader will gain a comprehensive understanding of how to use algorithms to explore graphs. It is a collection of texts that have proved to be trend setters and good examples of that. The book aims at providing the reader with a deep understanding of the structural properties of graphs that are useful for the design of efficient algorithms. These algorithms have applications in finite state machine modelling, social network theory, biology, and mathematics. The book contains many exercises, some up at present-day research-level. The exercises encourage the reader to discover new techniques by putting things in a clear perspective.
A First Course in Statistical Inference
Offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data.
A first course in differential equations with modeling applications
A comprehensive treatment of ordinary differential equations, concisely presenting basic and essential results in a rigorous manner. Including various examples from physics, mechanics, natural sciences, engineering and automatic theory, Differential Equations is a bridge between the abstract theory of differential equations and applied systems theory.
A Computer Scientists Guide to Cell Biology
Provides a succinct treatment of the general concepts of cell biology, furnishing the computer scientist with the tools necessary to read and understand current literature in the field.After a brief introduction to cell biology, the text focuses on the principles behind the most-widely used experimental procedures and mechanisms, relating them to well-understood concepts in computer science. The presentation of the material has been prepared for the reader’s quick grasp of the topic: comments on nomenclature and background notes can be ascertained at a glance, and essential vocabulary is boldfaced throughout the text for easy identification.
A Computational Model of Natural Language Communication : Interpretation, Inference, and Production in Database Semantics
Presents a high-level description of an artificial agent which humans can freely communicate with in their accustomed language. Part II analyzes the major constructions of natural language, i.e., intra- and extrapropositional functor - argument structure, coordination, and coreference, in the speaker and the hearer mode. Part III defines declarative specifications for fragments of English, which are used for an implementation in Java.
3-D Shape Estimation and Image Restoration : Exploiting Defocus and Motion-Blur
Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene—as well as its radiance properties—and which in turn can be used to generate novel images with better quality. 3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
3-D Computer vision : Principles, algorithms and applications
Offers advanced content on computer vision (basic content can be found in its prerequisite textbook, “2D Computer Vision: Principles, Algorithms and Applications”), including the basic principles, typical methods and practical techniques. It is intended for graduate courses on related topics, e.g. Computer Vision, 3-D Computer Vision, Graphics, Artificial Intelligence, etc. The book is mainly based on my lecture notes for several undergraduate and graduate classes I have offered over the past several years, while a number of topics stem from my research publications co-authored with my students. This book takes into account the needs of learners with various professional backgrounds, as well as those of self-learners. Furthermore, it can be used as a reference guide for practitioners and professionals in related fields.
17th International Conference on Information Technology–New Generations (ITNG 2020)
This volume presents the 17th International Conference on Information Technology—New Generations (ITNG), and chronicles an annual event on state of the art technologies for digital information and communications. The application of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and healthcare are among the themes explored by the ITNG proceedings. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help information flow to end users are of special interest. Specific topics include Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing. The conference features keynote speakers; a best student contribution award, poster award, and service award; a technical open panel, and workshops/exhibits from industry, government, and academia.
.NET Test Automation Recipes : A Problem-Solution Approach
If you develop, test, or manage .NET software, you will find .NET Test Automation Recipes: A Problem-Solution Approach very useful. The book presents practical techniques for writing lightweight software test automation in a .NET environment and covers API testing thoroughly. It also discusses lightweight, custom Windows application user interface automation and teaches you low-level web application user interface automation. Additional material covers SQL stored procedure testing techniques.
.NET 2.0 Interoperability Recipes : A Problem-Solution Approach
.NET represents a new and improved way of developing software for the Windows platform. Given the chance, you'd probably rewrite all of your existing code in the newer managed code environment that .NET provides. But it is difficult or impossible to throw out all existing legacy code and start over when a new technology arrives. Instead, you need to find a way to move forward with new .NET development while reusing existing pieces of tested, working code. You need a way to interoperate with the existing code until you have a chance to finally rewrite all of it in .NET.
.NET 2.0 for Delphi Programmers
.NET 2.0 for Delphi Programmers explores .NET from a Delphi programmers viewpoint, and it is ideal for Delphi programmers moving to .NET. It presents the core concepts of the .NET world in terms you are familiar with. This book will help you with Delphi for .NET as well as C#. Apress publishes migration books for both Visual Basic 6 and C++ programmers moving to .NET. Consider this the Delphi installment of Apress migration books! There is ample coverage of C# as well as Delphi for .NET inside this edition.











