Java Data Object

Dale, Joyce, and Weems present the algorithmic, programming, and structuring techniques of a traditional data structures course in an object-oriented context. They stress software engineering principl

Written to present the algorithmic, programming, and structuring techniques of traditional data structures courses in an object-oriented context, this text presents the familiar topics, but with an em

Java is a language that is very well suited to object oriented programming and design. Java applications are stand-alone applications similar to the application we develop using other object oriented

A relatable and friendly introduction to data structures and their implementation The 5th Edition of Data Structures and Abstractions with Java introduces readers to data structures (CS-2) i

Data Structures and Algorithm Analysis in Java is an “advanced algorithms” book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was

Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different gr

For courses in Software Engineering, Software Development, or Object-Oriented Design and Analysis at the Junior/Senior or Graduate level. This text can also be utilized in short technical courses or i

Data Structures and Algorithms in Java, Second Edition is designed to be easy to read and understand although the topic itself is complicated. Algorithms are the procedures that software programs use

Jia (software engineering, DePaul University) helps readers develop skills in designing software, and especially in writing object-oriented programs using Java. The text provides broad coverage of obj

With this book, Tim Budd looks at data structures by providing a solid foundation on the abstract data type (ADT), and uses the graphical elements found in Java when possible. The beginning chapters

ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist

ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered

Requiring only a background in mathematical statistics or analysis, this book provides the first comprehensive look at the statistics of manifolds. It presents location and spread parameters for distr

Although traditional texts present isolated algorithms and data structures, they do not provide a unifying structure and offer little guidance on how to appropriately select among them. Furthermore, t

Develop and manage chemical information systems This text provides a comprehensive overview of analyzing chemical problems using computer-aided methods for both newcomers and advanced computer scient

Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of corres

Fundamentals of OOP and Data Structures in Java is a text for an introductory course on classical data structures. Part One of the book presents the basic principles of Object-Oriented Programming (OOP) and Graphical User Interface (GUI) programming with Java as the example language. Part Two introduces each of the major data structures with supporting, GUI-based laboratory programs designed to reinforce the basic concepts and principles of the text. These laboratories allow the reader to explore and experiment with the properties of each data structure. All source code for the laboratories is available on the web. By integrating the principles of OOP and GUI programming, this book takes the unique path of presenting the fundamental issues of data structures within the context of paradigms that are essential to today's professional software developer. The authors assume the reader has only an elementary understanding of Java and no experience with OOP.

This textbook provides an in depth course on data structures in the context of object oriented development. Its main themes are abstraction, implementation, encapsulation, and measurement: that is, th

This book focuses on recent developments in representational and processing aspects of complex data-intensive applications. Until recently, information systems have been designed around different bu

The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich and Tomassia's approach to this classic topic is based on

This book analyses the phenomenon of digitally mediated property and considers how it problematises the boundary between human and nonhuman actors. The book addresses the increasingly porous border between personhood and property in digitized settings and considers how the increased commodification of knowledge makes visible a rupture in the liberal concept of the property owning, free, person. Engaging with the latest work in posthumanist and new materialist theory, it shows, how property as a concept as well as a means for control, changes fundamentally under advanced capitalism.Such change is exemplified by the way in which data, as an object of commodification, is extracted from human activities yet is also directly used to affectively control - or nudge - humans. Taking up a range of human engagements with digital platforms and coded architectures, as well as the circulation of affects through practices of artificial intelligence that are employed to shape behaviour, the book argu

A textbook that uses a hands-on approach to teach principles of programming languages, with Java as the implementation language.This introductory textbook teaches the principles of programming languages by using an experiential learning style, in which students learn about language features by realizing those features in a pedagogical compiler. Students use Java―the most commonly used programming language in the first two years of the computer science curriculum―as the implementation language throughout. The book also discusses a range of emerging topics in programming languages missing from existing textbooks, including concurrency, Big Data, and event-driven programming. The goal is to prepare students to design, implement, analyze, and understand both domain-specific and general-purpose programming languages. The book first develops basic concepts in languages, including means of computation using primitive values, means of combination such as variable definition and functions, an

In the first half of the nineteenth century autobiography became, for the first time, an explicitly commercial genre. Drawing together quantitative data on the Victorian book market, insights from the business ledgers of Victorian publishers and close readings of mid-century novels, Sean Grass demonstrates the close links between these genres and broader Victorian textual and material cultures. This book offers fresh perspectives on major works by Charles Dickens, George Eliot, Mary Elizabeth Braddon, Wilkie Collins and Charles Reade, while also featuring archival research that reveals the volume, diversity, and marketability of Victorian autobiographical texts for the first time. Grass presents life-writing not as a stand-alone genre, but as an integral part of a broader movement of literary, cultural, legal and economic practices through which the Victorians transformed identity into a textual object of capitalist exchange.

Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

Thinking Big Data in Geography offers a practical state-of-the-field overview of big data as both a means and an object of research, with essays from prominent and emerging scholars such as Rob K