Java Data Object

本商品為光盤一張，隨光盤附贈《Java EE高級工程Ⅱ培訓》書一本。《Java EE高級工程師II培訓》是針對Java EE 高級工程師II（也稱為Java EE 后臺開發工程師）的培訓，深入地講解了EJB、Web service、和JMS等技術，讓學員少走彎路，更快的學習，幫助學員快速的成為一名合格的Java EE后臺開發工程師。通過本培訓課程的學習，學員能夠獲得相當于三個月Java EE 高級

"Unmonumental: The Object in the 21st Century" is the first exhibition in the "Unmonumental" cycle, and explores the reinvention of sculptural assemblage. Using found, fragmented, and discarded materi

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

First book to address and assess performance of enterprise Java-based applications using the new Java EE 5Presents Java EE 5 Performance Management as a proven methodology, featuring a set of common p

First and only book on the Java 5, including new Java EE 5, for SAP/ABAB programmersThe author has given the first course of its kind in Belgium, and employs his experience and approach in this bookMo

Java 程式語言之所以這麼熱門，其中有一個很重要的因素是它具有"Write once, run anywhere"的特性，這項優點讓Java 程式能夠在不同平台、不同作業環境下暢行無阻，因而可以大量縮短程式開發的時程。 本書將以簡單、活潑的敘述及例子，引領您進入Java 的世界，讓不懂Java程式的您，能夠輕鬆、自在的學會使用這個功能強大的程式語言。

Intended for intermediate robot builders with a basic understanding of Java, this hobby book introduces RS-22 serial communication, and provides Java class examples for moving wheel robots, robot arms

This book provides complete coverage of fundamental IP networking in Java. It introduces the concepts behind TCP/IP and UDP, with their intended use and purpose; covers of Java networking APIs, and i

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

How Minimalism redefined the art object, featuring work by key artists and a reexamination of Minimalism by prominent art historians, critics, and scholars.

Concurrent and Distributed Computing in Java addresses fundamental concepts in concurrent computing with Java examples. The book consists of two parts. The first part deals with techniques for program

Glencoe’s Introduction to Computer Science Using Java provides students with a highly visual way of learning Java programming. This colorful text provides the information needed for students enrolled

Object-Process Methodology (OPM) is an intuitive approach to systems engineering. This book presents the theory and practice of OPM with examples from various industry segments and engineering discipl

A presentation of the formal underpinnings of object-oriented programminglanguages.

Inspired by Samuel Foote's poem, "The Grand Panjandrum," The Object-Lesson presents a stunning series of seemingly random and unrelated events. A missing artificial limb, ghostly spectres, and the sta

Integrating Graphics and Vision for Object Recognition serves as a reference for electrical engineers and computer scientists researching computer vision or computer graphics. Computer graphics an

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 definitive, official reference to the Java 1.1 class libraries for Java programmers. The extensive class and member descriptions contain details crucial for developing professional applets and app

The second part of a yearly series on simulation technology, OBJECT-ORIENTED SIMULATION presents an outstanding variety of the very latest advances in simulation techniques. This leading-edge volume c

This collection of research provides a survey of developments at the leading edge of concurrent object-oriented programming. It documents progress - from general concepts to specific descriptions - in

Theories of Object Relations: Bridges to Self Psychology discusses the work of the major American and British contributors to object relations theory, focusing on the ways in which these theories anti

"The object of life is impossible; one cuts out fabrication and creates reality. A mirror is held to the back of the head and one's hand has to move the opposite way from what was intended.&a

Object Relations Theory and Clinical Psychoanalysis is a collection of Kernberg's papers published or presented during the period from 1966 to 1975, with some new material included as well.

This commentary covers all topics and critical aspects elicited by the new European General Data Protection Regulation and its interpretation. The commentary focuses on the regulation itself, including cross-references to further provisions (eg the Police and Criminal Justice Data Protection Directive, the E-Privacy-Directive or the former Data Protection Directive 95/46/EC).Article by article the purpose of a provision is classified, its background, function and structure analysed and its content interpreted. The commentary provides an independent view of all topics, presenting both an overview and specific interpretation that provide far-reaching arguments.The editors and authors are outstanding experts in the field of data protection law well known for their practical as well as structured and thorough approach to data protection issues. They offer suitable solutions and sound arguments especially for international companies, legal councils and corporate lawyers as well as data prot

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.

This book assesses data protection rules that are applicable to the processing of personal data in a law enforcement context. It offers the first extensive analysis of the LED and Regulation (EU) 2018/1725. It illustrates the challenges arising from the unclear delineation between the different data protection instruments at both national and EU level. Taking a practical approach, it exemplifies situations where the application of data protection instruments could give rise to a lowering of data protection standards where the data protection rules applicable in the law enforcement context are interpreted broadly. The scope of data protection instruments applied by law enforcement authorities impacts processing for purposes of border control, migration management and asylum because there is an unclear delineation between the different data protection instruments.

A veteran British journalist living in Hong Kong investigates the disappearance of a student protester in this atmospheric novel from the New York Times notable author of The Forgiven―soon to be a major motion picture.“There came a sound of rubber bullets being fired along Java Road and the sad crowing of sirens as if to herald a future even more unpleasant than the present.”After twenty years as a journalist in Hong Kong, ex-pat Englishman Adrian Gyle has very little to show for it. Evenings are whiled away with soup dumplings and tea at Fung Shing, the restaurant downstairs from his home on Java Road, that “most melancholy street in the city, the street where the dead congregated.” It is through these jaded eyes that Gyle watches the city around him--once overflowing with wine dinners and private members’ clubs--erupt in violence as pro-democracy demonstrations hit ever closer to home. But just as Gyle prepares to turn his back on Hong Kong, he finds one last intrigue: the alluring R

Health research around the world relies on access to data, and much of the most valuable, reliable, and comprehensive data collections are held by governments. These collections, which contain data on whole populations, are a powerful tool in the hands of researchers, especially when they are linked and analyzed, and can help to address “wicked problems” in health and emerging global threats such as COVID-19. At the same time, these data collections contain sensitive information that must only be used in ways that respect the values, interests, and rights of individuals and their communities. Sharing Linked Data for Health Research provides a template for allowing research access to government data collections in a regulatory environment designed to build social license while supporting the research enterprise.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deplo

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

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; found

This collection explores the relevance of global trade law for data, big data and cross-border data flows. Contributing authors from different disciplines including law, economics and political science analyze developments at the World Trade Organization and in preferential trade venues by asking what future-oriented models for data governance are available and viable in the area of trade law and policy. The collection paints the broad picture of the interaction between digital technologies and trade regulation as well as provides in-depth analyses of critical to the data-driven economy issues, such as privacy and AI, and different countries' perspectives. This title is also available as Open Access on Cambridge Core.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

GDPR: Personal Data Protection in the European UnionMariusz KrzysztofekPersonal data protection has become one of the central issues in any understanding of the current world system. In this connection, the European Union (EU) has created the most sophisticated regime currently in force with the General Data Protection Regulation (GDPR) (EU) 2016/679. Following the GDPR's recent reform - the most extensive since the first EU laws in this area were adopted and implemented into the legal orders of the Member States - this book offers a comprehensive discussion of all principles of personal data processing, obligations of data controllers, and rights of data subjects, providing a thorough, up-to-date account of the legal and practical aspects of personal data protection in the EU.Coverage includes the recent Court of Justice of the European Union (CJEU) judgment on data transfers and new or updated data protection authorities' guidelines in the EU Member States. Among the broad spectrum o

The massive volume of data generated in modern applications can overwhelm our ability to conveniently transmit, store, and index it. For many scenarios, building a compact summary of a dataset that is vastly smaller enables flexibility and efficiency in a range of queries over the data, in exchange for some approximation. This comprehensive introduction to data summarization, aimed at practitioners and students, showcases the algorithms, their behavior, and the mathematical underpinnings of their operation. The coverage starts with simple sums and approximate counts, building to more advanced probabilistic structures such as the Bloom Filter, distinct value summaries, sketches, and quantile summaries. Summaries are described for specific types of data, such as geometric data, graphs, and vectors and matrices. The authors offer detailed descriptions of and pseudocode for key algorithms that have been incorporated in systems from companies such as Google, Apple, Microsoft, Netflix and T

How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and c

In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply collaborative, deeply creative process behind 24 unique data visualization projects, spanning 12 different topics. The book provides