This volume constitutes the refereed proceedings of the IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference on Availability, Reliability and Security in Information Systems, CD-ARES 2016, and the Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016, co-located with the International Conference on Availability, Reliability and Security, ARES 2016, held in Salzburg, Austria, in September 2016. The 13 revised full papers and 4 short papers presented were carefully reviewed and selected from 23 submissions. They are organized in the following topical sections: Web and semantics; diagnosis, prediction and machine learning; security and privacy; visualization and risk management; and privacy aware machine learning for health data science.
Описание: This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making.
Описание: This book presents fresh research techniques, algorithms, methodologies and experimental results for high-level power estimation and power-aware high-level synthesis. The book will help get products to market quicker and facilitate low-power ASIC/FPGA design.
Автор: Progyna Khondkar Название: Low-Power Design and Power-Aware Verification ISBN: 3319882864 ISBN-13(EAN): 9783319882864 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Поставка под заказ.
Описание: Until now, there has been a lack of a complete knowledge base to fully comprehend Low power (LP) design and power aware (PA) verification techniques and methodologies and deploy them all together in a real design verification and implementation project. This book is a first approach to establishing a comprehensive PA knowledge base.LP design, PA verification, and Unified Power Format (UPF) or IEEE-1801 power format standards are no longer special features. These technologies and methodologies are now part of industry-standard design, verification, and implementation flows (DVIF). Almost every chip design today incorporates some kind of low power technique either through power management on chip, by dividing the design into different voltage areas and controlling the voltages, through PA dynamic and PA static verification, or their combination.The entire LP design and PA verification process involves thousands of techniques, tools, and methodologies, employed from the register transfer level (RTL) of design abstraction down to the synthesis or place-and-route levels of physical design. These techniques, tools, and methodologies are evolving everyday through the progression of design-verification complexity and more intelligent ways of handling that complexity by engineers, researchers, and corporate engineering policy makers.
Автор: Trent McConaghy; Pieter Palmers; Gao Peng; Michiel Название: Variation-Aware Analog Structural Synthesis ISBN: 9400726082 ISBN-13(EAN): 9789400726086 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes computational intelligence-based tools for robust design of analog circuits. It starts with global variation-aware sizing and knowledge extraction and progressively extends to variation-aware topology design.
Описание: This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. However, such real-time task schedules may be jeopardized due to hardware threats.
Описание: This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. However, such real-time task schedules may be jeopardized due to hardware threats.
Описание: RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Описание: The Evolution of Context-Aware RDF Knowledge Graphs.- Data Provenance and Accountability on the Web.- The Right (Provenance) Hammer for the Job: a Comparison of Data Provenance Instrumentation.- Contextualized Knowledge Graphs in Communication Network and Cyber-Physical System Modeling.- ProvCaRe: A Large-Scale Semantic Provenance Resource for Scientific Reproducibility.- Graph-Based Natural Language Processing for the Pharmaceutical Industry.
Автор: Ahmed Abdelgawad; Magdy Bayoumi Название: Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks ISBN: 1489987061 ISBN-13(EAN): 9781489987068 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces resource-aware data fusion algorithms that generate inferences by combining data from multiple sources-techniques useful in centralized and distributed systems to overcome sensor failure, technological limitations, and coverage problems.
Описание: This book offers a technology-oriented assessment of analog and mixed-signal circuits in emerging high-k and multi-gate CMOS technologies. Coverage includes transient threshold voltage variations and integration of tunnel transistors in a multi-gage process.
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