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"This book discusses knowledge representation in semantic web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies."

"This book constitutes the proceedings of the 8th International Conference on Spatial Cognition, SC 2012, held in Kloster Seeon, Germany, in August/September 2012. The 31 papers presented in this volume were carefully reviewed and selected from 59 submissions. The conference deals with spatial cognition, biological inspired systems, spatial learning, communication, robotics, and perception."

"The main aim of this book is to introduce different signal processing models which have been used in analyzing periodic data, and different statistical and computational issues. This book discuss in detail the sinusoidal frequency model which has been used extensively in analyzing periodic data occuring in various fields. This book have tried to introduce different associated models and higher dimensional statistical signal processing models which have been further discussed in the literature. Different real data sets have been analyzed to illustrate how different models can be used in practice. Several open problems have been indicated for future research."

"Doing data science is difficult. Projects are typically very dynamic with requirements that change as data understanding grows. The data itself arrives piecemeal, is added to, replaced, contains undiscovered flaws and comes from a variety of sources. Teams also have mixed skill sets and tooling is often limited. Despite these disruptions, a data science team must get off the ground fast and begin demonstrating value with traceable, tested work products. This is when you need Guerrilla analytics.In this book, you will learn about :The Guerrilla analytics principles, simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting.Reproducible, traceable analytics, how to design and implement work products that are reproducible, testable and stand up to external scrutiny.Practice tips and war stories, 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and research.Preparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventions.Data gymnastics, over a dozen analytics patterns that your team will encounter again and again in projects."

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ABSTRACTDoing data science is difficult. Projects are typically very dynamic with requirements that change as data understanding grows. The data itself arrives piecemeal, is added to, replaced, contains undiscovered flaws and comes from a variety of sources. Teams also have mixed skill sets and tooling is often limited. Despite these disruptions, a data science team must get off the ground fast and begin demonstrating value with traceable, tested work products. This is when you need Guerrilla Analytics. n this book, you will learn about:The Guerrilla Analytics Principles: simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting.Reproducible, traceable analytics: how to design and implement work products that are reproducible, testable and stand up to external scrutiny.Practice tips and war stories 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and research.Preparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventions.Data gymnastics: over a dozen analytics patterns that your team will encounter again and again in projectsThe Guerrilla Analytics Principles: simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reportingReproducible, traceable analytics: how to design and implement work products that are reproducible, testable and stand up to external scrutinyPractice tips and war stories: 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and researchPreparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventionsData gymnastics: over a dozen analytics patterns that your team will encounter again and again in projects."

"This proceedings book presents selected papers from the 4th Conference on Signal and Information Processing, Networking and Computers (ICSINC) held in Qingdao, China on May 23-25, 2018. It focuses on the current research in a wide range of areas related to information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource anyone interested in this field."

"This book addresses reliability and energy efficiency of on-chip networks using cooperative error control. It describes an efficient way to construct an adaptive error control codec capable of tracking noise conditions and adjusting the error correction strength at runtime. Methods are also presented to tackle joint transient and permanent error correction, exploiting the redundant resources already available on-chip. A parallel and flexible network simulator is also introduced, which facilitates examining the impact of various error control methods on network-on-chip performance."

"Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes.Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization problems (e.g. the task durations) are typically unknown at the time the decision problem arises.This monograph investigates solution techniques for optimization problems in temporal networks that explicitly account for this parameter uncertainty. We study several formulations, each of which requires different information about the uncertain problem parameters."

"Organizations in ever-changing environments depend upon their knowledge, as their survival depends upon effective thinking and agile actions. Any organization’s knowledge is its prime asset yet its true value requires the activations of structure, query, search and decision. Shaping Knowledge provides an introduction to the key tools for thinking required by decision-making professionals in today’s knowledge-intensive landscapes, and equips them with key skills to capitalize on knowledge resources. This book provides practical methods and critical insights for modelling knowledge-driven domains, providing a rich resource for exploration in professional development and practice."