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الصفحة 20
Building an Enterprise Architecture Practice : Tools, Tips, Best Practices, Ready-to-Use Insights
This book clearly describes how to establish an architecture practice that delivers value for an organization. The authors demonstrate a wealth of experience and a deep understanding of the multifaceted nature of this challenging task and they provide sound advice on how to avoid the many pitfalls that may be encountered along the way. Building an Enterprise Architecture Practice provides practical advice on how to develop your enterprise architecture practice.
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-inspired computing ; 4th International Workshop, BrainComp 2019, Cetraro, Italy, July 15–19, 2019, Revised Selected Papers
The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
Blockchains For Network Security : Principles, technologies and applications
Blockchain technology is a powerful, cost-effective method for network security. Essentially, it is a decentralized ledger for storing all committed transactions in trustless environments by integrating several core technologies such as cryptographic hash, digital signature and distributed consensus mechanisms. Over the past few years, blockchain technology has been used in a variety of network interaction systems such as smart contracts, public services, Internet of Things (IoT), social networks, reputation systems and security and financial services. With its widespread adoption, there has been increased focus on utilizing blockchain technologies to address network security concerns and vulnerabilities as well as understanding real-world security implications.
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.
Bio-Materials & Prototyping Applications in Medicine
Bio-Materials and Prototyping Applications in Medicine focuses on bio-materials and prototyping applications in medical environments. The applications that ardiscussed integrate bio-materials, CAD, and physical prototyping techniques.
Biologically Inspired Approaches to Advanced Information Technology ; 2nd International Workshop, BioADIT 2006, Osaka, Japan 26-27, 2006, Proceedings
This book contains 30 articles and three abstracts of invited talks presented at The Second International Workshop on Biologically Inspired Approaches for Advanced Information Technology,The workshop is intended to provide an e?ective forum for original research results in the ?eld of bio-inspired approaches to advanced information technologies. It also serves to foster the connection between biological paradigms and solutions to building the next-generation information systems.
Big data-enabled internet of things
Covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions. The fields of Big Data and the Internet of Things (IoT) have seen tremendous advances, developments, and growth in recent years. The IoT is the inter-networking of connected smart devices, buildings, vehicles and other items which are embedded with electronics, software, sensors and actuators, and network connectivity that enable these objects to collect and exchange data. The IoT produces a lot of data. Big data describes very large and complex data sets that traditional data processing application software is inadequate to deal with, and the use of analytical methods to extract value from data. This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions.
Big Data Recommender Systems ; Vol.1 : Algorithms, Architectures, Big Data, Security and Trust
Combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools.
Big Data – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Beginning Database-Driven Application Development in Java EE : Using GlassFish™
The book explains in detail how you can organize your Java EE solution into a multilayer architecture, placing most emphasis on how to implement the persistence and database tiers of an application. Through many examples, this book shows how you can efficiently use the Java Persistence features available in the Java EE platform. Find out how you can greatly simplify the task of building the persistence layer of your Java EE application by moving some application logic into the underlying database, utilizing database views, stored programs, and triggers. The book also explains how to deploy Java EE applications to GlassFish, a free, open source Java EE 5–compliant application server.
Autonomous intelligent systems : Multi-agents and data mining ; 2nd International workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings
MAS offiers powerful metaphors for information system conceptualization, a range of new techniques, and technologies specifically focused on the design and implementation of lar- scale open distributed intelligent systems. KDD also provides intelligent inf- mation technology with powerful ideas, algorithms, and software means to help cope with the main problem of artificial intelligence, formulated in the we- known question “Where does the knowledge come from?”, thus actually making modern applications intelligent and adaptive. The evident recent trend in both science and industry is to integrate and take advantage of both technologies. The existing experience with combined application of multi-agent technology to design architectures of distributed (- erarchical and peer-to-peer) data mining and KDD systems, as well as the u- lization of data mining and KDD achievements to provide enhanced intelligence of MAS, confirms the fact that both technologies are capable of mutual enri- ment and their integrateduse may result in intelligent information systems with new emergent properties.
Autonomous intelligent systems : Agents and data mining ; International workshop, AIS-ADM 2005
This book constitutes the refereed proceedings of the International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2005, held in St. Petersburg, Russia in June 2005. The 17 revised full papers presented together with 5 invited papers and the abstract of an invited talk were carefully reviewed and selected from 29 submissions. The papers are organized in topical sections on agent-based data mining issues, ontologies and Web mining, and applications and case studies.
Autonomous driving : Technical, legal and social aspects
This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies?
Autonomic principles of IP operations and management ; 6th IEEE International Workshop on IP Operations and Management, IPOM 2006, Dublin, Ireland, October 23-25, 2006, Proceedings
th This volume presents the proceedings of the 6 IEEE International Workshop on IP Operations and Management (IPOM 2006), which was held as part of Manweek 2006 rd th in Dublin, Ireland from October 23 to 25 , 2006. In line with its reputation as one ofthe pre-eminent venues for the discussion and debate of advances of management of IP networks and services, the 2006 iteration of IPOM brought together an international audience of researchers and practitioners from both industry and academia. The overall theme of Manweek 2006 was “Autonomic Component and System Management”,with IPOM taking this to be the application of autonomic principles to the IP operations, administration, maintenance and provisioning.
Autonomic communication ; Vol. 3457 ; 1st International IFIP Workshop, WAC 2004, Berlin, Germany, October 18-19, 2004, Revised Selected Papers
The ?rst IFIP Workshop on Autonomic Communication (WAC 2004) was held 2004 in Berlin, Germany. The purpose of this workshop was to discuss Autonomic Communication—a new communication paradigm to assist the design of the next-generation n- works. WAC 2004 was explicitly focused on the principles that help to achieve purposeful behavior on top of self-organization (self-management, self-healing, self-awareness, etc. ). The workshop intended to derive these common principles from submissions that study network element’s autonomic behavior exposed by innovative (cross-layer optimized, context-aware, and securely programmable) protocol stack (or its middleware emulations) in its interaction with numerous, often dynamic network groups and communities. The goals were to understand how autonomic behaviors are learned, in?uenced or changed, and how, in turn, these a?ect other elements, groups and the network. Panel reports were compiled by panel moderators and conclude this volume.
Automotive software - connected services in mobile networks ; 1st Automotive software workshop, ASWSD 2004, San Diego, CA, USA, January 10-12, 2004, Revised Selected Papers
Software development for the automotive domain is currently subject to a silent revolution. On the one hand, software has become the enabling technology for almost all safety-critical and comfort functions o?ered to the customer. A total of 90 % of all innovations in automotive systems are directly or indirectly - abled by software. the following list highlights three of the corresponding challenges: First, the dependencies between safety-critical and comfort functions are rapidly increasing;a simple example is the interplay of airbag controland power seat control in the case of an accident. Careful analysis and design of these dependencies are necessary to yield correct software solutions. Second, advances in wired and wireless networking infrastructures enable - terconnection between cars and backend service providers .
Automatic speech recognition on mobile devices and over communication networks
This book brings together leading academic researchers and industrial practitioners to address the issues in this emerging realm and presents the reader with a comprehensive introduction to the subject of speech recognition in devices and networks.
Automated technology for verification and analysis ; 18th International Symposium, ATVA 2020, Hanoi, Vietnam, October 19–23, 2020, Proceedings
This book constitutes the refereed proceedings of the 18th International Symposium on Automated Technology for Verification and Analysis, ATVA 2020, held in Hanoi, Vietnam, in October 2020. The 27 regular papers presented together with 5 tool papers and 2 invited papers were carefully reviewed and selected from 75 submissions.
Automated machine learning : Methods, systems, challenges
This book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself.
