U ovom radu nastoji se odrediti značaj standarda za razvoj softvera. Takvi standardi trebaju doprinijeti razvoju kvalitetnijeg softvera, a posljedica takvog softvera je jeftinije održavanje, odnosno ...veća produktivnost programera na održavanju softvera. Da bi se razvio kvalitetniji softver, razvijena je disciplina softversko inženjerstvo koje se bavi metodama i tehnikama za razvoj kvalitetnijeg i jeftinijeg softvera. U radu su prikazane neke od tehnika softverskog inženjerstva, a opisuje se i jedan standard za razvoj softvera.
Open Source GIS Mitasova, Helena; Neteler, Markus
2008, 2007
eBook
With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release that includes substantial new code developed by the International GRASS Development ...Team. The dramatic growth in open source software libraries has made the GRASS6 development more efficient, and has enhanced GRASS interoperability with a wide range of open source and proprietary geospatial tools. Thoroughly updated with material related to the GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters were updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.
This text is carefully designed to provide a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts. The authors have been involved in the ...development of DEA from the beginning. William Cooper (with Abraham Charnes and Edwardo Rhodes) is a founder of DEA. Lawrence Seiford and Kaoru Tone have been actively involved as researchers and practitioners from its earliest beginnings. This new volume reviews and extends the basic principles taught in the authors' highly successful textbook, Data Envelopment Analysis.
Utilize R to uncover hidden patterns in your Big Data. Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on ...Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the marketWho This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R.What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platformIn Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.
There are typically two main reasons why you may consider migrating SAP to Azure: You need to replace the infrastructure that is currently running SAP, or you want to migrate SAP to a new database. ...This book will guide you through migrating your SAP data to Azure simply and successfully.
The computer program exclusion from Article 52 of the European Patent Convention (EPC) proved impossible to uphold as industry moved over to digital technology, and the Boards of Appeal of the ...European Patent Organisation (EPO) felt emboldened to circumvent the EPC in Vicom by creating the legal fiction of 'technical effect'. This 'engineer's solution' emphasised that protection should be available for a device, a situation which has led to software and business methods being protected throughout Europe when the form of application, rather than the substance, is acceptable. Since the Article 52 exclusion has effectively vanished, this text examines what makes examination of software invention difficult and what leads to such energetic opposition to protecting inventive activity in the software field. Leith advocates a more programming-centric approach, which recognises that software examination requires different strategies from that of other technical fields.
Supply Chain Event Management (SCEM) is one of the major topics in application-oriented Supply Chain Management. However, many solutions lack conceptual precision and currently available ...client-server SCEM-systems are ill-suited for complex supply networks in today's business environment. Agent-based proactive information logistics promises to overcome existing deficits by providing event-related information to all participants in the distributed environment. Hence, follow-up costs of disruptive events are significantly reduced for all network participants and performance of a supply network is increased. In this book a thorough analysis of the event management problem domain is the starting point to develop a generic agent-based approach to Supply Network Event Management. The main focus lies on practical issues of event management (e.g., semantic interoperability) and economic benefits to be achieved with agent technology in this state-of-the-art problem domain. Written for: Supply Chain Management professionals, IT-professionals, researchers in applied agent technology and business administration Keywords: Agent technology Network event management
This is one of the first books on the use of software agents to simulate bidding behavior in electronic auctions. It introduces market theory and computational economics together, and gives an ...overview on the most common and up-to-date agent-based simulation methods. The book will help the reader learn more about simulations in economics in general and common agent-based methods and tools in particular.
This book introduces major agent platforms, frameworks, systems, tools, and applications. Each system is described by their developers in sufficient detail so that the reader can get a good ...understanding of the architecture, functionality, and application areas of the system. All systems are running systems. One main focus of the book lies on agent platforms and toolkits. They form the basis for the development of agent-based systems, thus, are a convenient starting point for everybody who wants to apply agent technology. Another focus lies on agent-based applications. These systems prove that agent technology is mature enough to permit the development of sophisticated applications, like electronic marketplaces, environments for computer-supported cooperative work, or transportation systems.
