Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry. A basic trade-off exists between the use of one or a small number of such complex processors, at one extreme, and a moderate to very large number of simpler processors, at the other. When combined with a high-bandwidth, interprocessor communication facility leads to significant simplification of the design process. However, two major roadblocks prevent the widespread adoption of such moderately to massively parallel architectures: the interprocessor communication bottleneck, and the difficulty and high cost of algorithm/software development. One of the most important reasons for studying parallel computing architectures is to learn how to extract the best performance from parallel systems. Specifically, you must understand its architectures so that you will be able to exploit those architectures during programming via the standardized APIs. This book would be useful for analysts, designers and developers of high-throughput computing systems essential for big data stream processing emanating from IoT-driven cyber-physical systems (CPS). This pragmatic book: Devolves uniprocessors in terms of a ladder of abstractions to ascertain (say) performance characteristics at a particular level of abstraction Explains limitations of uniprocessor high performance because of Moore's Law Introduces basics of processors, networks and distributed systems Explains characteristics of parallel systems, parallel computing models and parallel algorithms Explains the three primary categorical representatives of parallel computing architectures, namely, shared memory, message passing and stream processing Introduces the three primary categorical representatives of parallel programming APIs, namely, OpenMP, MPI and CUDA Provides an overview of Internet of Things (IoT), wireless sensor networks (WSN), sensor data processing, Big Data and stream processing Provides introduction to 5G communications, Edge and Fog computing Parallel Computing Architectures and APIs: IoT Big Data Stream Processing discusses stream processing that enables the gathering, processing and analysis of high-volume, heterogeneous, continuous Internet of Things (IoT) big data streams, to extract insights and actionable results in real time. Application domains requiring data stream management include military, homeland security, sensor networks, financial applications, network management, web site performance tracking, real-time credit card fraud detection, etc.

Application program interfaces (Computer software)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The emerging possibilities of information technology and data communication, the globalization of markets, and the ongoing specialization of firms have paved the way for network enterprises as an organizational model of collaboration and coordination across loosely connected individual companies. This book explores the varous types of business networks and explains the underlying technology used to create them. It covers customer newtorks, supply chain networks, manufacturing networks, and aggregator networks. Supporting technology includes enterprise process management, component architectures, and web services. The book also covers systems science to give readers a theoretical background.

Business networks. --- Knowledge management. --- Information technology --- Management.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

""Vivek Kale has written a great book on performance management that focuses on decision-making; on continuous, incremental improvement; and on identifying common patterns in becoming a more intelligent organization."--James Taylor, CEO of Decision Management Solutions and author of Real-World Decision Modeling with DMN. Introducing the concepts of decision patterns and performance intelligence, Vivek Kale has written another important book on the issues faced by contemporary organizations.--Gary Cokins, author of Predictive Business Analytics and Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics: Enterprise Performance Intelligence and Decision Patterns unravels the mystery of enterprise performance intelligence (EPI) and explains how it can transform the operating context of business enterprises. It provides a clear understanding of what EPI means, what it can do, and application areas where it is practical to use.The need to be responsive to evolving customer needs and desires creates organizational structures where business intelligence (BI) and decision making is pushed out to operating units that are closest to the scene of the action. Closed-loop decision making resulting from a combination of on-going performance management with on-going BI can lead to an effective responsive enterprise; hence, the need for performance intelligence (PI).This pragmatic book:Introduces the technologies such as data warehousing, data mining, analytics, and business intelligence systems that are a first step toward enabling data-driven enterprises.Details decision patterns and performance decision patterns that pave the road for performance intelligence applications.Introduces the concepts, principles, and technologies related to performance measurement systems.Describes the concepts and principles related to balance scorecard systems (BCS).Introduces aspects of performance intelligence for the real-time enterprises.Enterprise Performance Intelligence and Decision Patterns shows how a company can design and implement instruments ranging from decision patterns to PI systems that can enable continuous correction of business unit behavior so companies can enhance levels of productivity and profitability."--Provided by publisher.

Performance technology. --- Decision support systems. --- Business intelligence.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

It is well known that high-tech startups need to innovate to survive, yet the failure rate for innovation is shockingly high. Nearly three out of four new products or services, i.e., their startups, miss their revenue and profit goals–or fail entirely. It’s a misconception that high-tech startups fail only because of the failing products or finances. The failures could also be because of erroneous choice of technology platforms, development teams or methodology, or even the project execution. Accordingly, this book takes a holistic view of a startups’ aesthetics that enables it to become attractive for all stakeholders especially investors in all aspects of its operations at all stages of its lifecycle.

New business enterprises. --- High technology industries. --- Strategic planning. --- Privacy. --- Trust. --- Blockchain. --- Startup. --- Unicorn. --- Confluence of exponentials. --- Exponential technologies. --- McKinsey 7S model. --- Extended 9S model. --- Venture capital. --- Valuation. --- Term sheet. --- Customer centricity. --- Capitalization tables. --- Mass innovation. --- Cognitive advantage. --- Built_to_innovate organizations. --- Intellectual capital. --- Innovative entrepreneurship. --- Ambidexterity. --- Continuous innovation. --- Business model. --- Learning organizations. --- Experimental software development. --- Multiparadigm development. --- Nature-inspired strategies and solutions. --- Bias. --- Safety. --- Offerings of products. --- Services and experiences. --- TRIZ. --- Network businesses. --- Network of projects. --- Management by teams. --- Talent management. --- Employee engagement. --- Narrow. --- General and super AI. --- Chatbots. --- OpenAI GPT-3. --- Modeling and simulations (M&S) --- Digital twins. --- Design thinking. --- DevSecOps. --- Networks. --- Sensors. --- Platforms. --- Internet of things (IoT) --- Ecosystems bio. --- Nano and industry 4.0. --- Governance. --- Decentralized accounting. --- Decentralized finance (DeFi) --- Security.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This books documents the salient characters of the tectonic evolution of the Indian subcontinent. It showcases the well investigated subcontinent of Gondwana. The book is linked to an updated geological and tectonic map of this region on 1:12,000,000 in scale. The Indian subcontinent displays almost uninterrupted and unique the geological history since about Eo-Archean (~3800 Ma) to recent, with the development of many Proterozoic deformed and metamorphosed fold belts around Archean nuclei, and enormously thick undeformed platform deposits. After their stabilization during late Proterozoic, the subcontinent underwent Paleozoic rifting and deposition of coal-bearing thick sequences, followed by enormously-thick outpouring of Deccan volcanics as a consequence of huge mantle plume. The youngest event in its evolution is the Cenozoic Himalayan Orogenic Mountains, spanning the area between Nanga Parbat and Namcha Barwah; a part of which extends both in Pakistan and Myanmar.

Geophysics --- Geology. Earth sciences --- Geography --- GIS (geografisch informatiesysteem) --- geologie --- geofysica