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Analysis At Large


Analysis At Large
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Risk Analysis For Large Projects


Risk Analysis For Large Projects
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Author : Dale Cooper
language : en
Publisher:
Release Date : 1987-05-06

Risk Analysis For Large Projects written by Dale Cooper and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-05-06 with Business & Economics categories.


Considers what risk analysis is, the nature of the risk engineering approach to risk analysis, where risk analysis might be necessary and some of the benefits which arise from its use. Risk is evaluated through both models and case studies.



Large Scale Graph Analysis System Algorithm And Optimization


Large Scale Graph Analysis System Algorithm And Optimization
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Author : Yingxia Shao
language : en
Publisher: Springer Nature
Release Date : 2020-07-01

Large Scale Graph Analysis System Algorithm And Optimization written by Yingxia Shao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Computers categories.


This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.



Anticipating Future Innovation Pathways Through Large Data Analysis


Anticipating Future Innovation Pathways Through Large Data Analysis
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Author : Tugrul U. Daim
language : en
Publisher: Springer
Release Date : 2016-07-25

Anticipating Future Innovation Pathways Through Large Data Analysis written by Tugrul U. Daim and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-25 with Business & Economics categories.


This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes: The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I). The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests. Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP. Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.



Spectral Analysis Of Large Dimensional Random Matrices


Spectral Analysis Of Large Dimensional Random Matrices
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Author : Zhidong Bai
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-10

Spectral Analysis Of Large Dimensional Random Matrices written by Zhidong Bai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-10 with Mathematics categories.


The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate F matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.



Sentiment Analysis And Its Application In Educational Data Mining


Sentiment Analysis And Its Application In Educational Data Mining
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Author : Soni Sweta
language : en
Publisher: Springer Nature
Release Date : 2024-04-20

Sentiment Analysis And Its Application In Educational Data Mining written by Soni Sweta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-20 with Computers categories.


The book delves into the fundamental concepts of sentiment analysis, its techniques, and its practical applications in the context of educational data. The book begins by introducing the concept of sentiment analysis and its relevance in educational settings. It provides a thorough overview of the various techniques used for sentiment analysis, including natural language processing, machine learning, and deep learning algorithms. The subsequent chapters explore applications of sentiment analysis in educational data mining across multiple domains. The book illustrates how sentiment analysis can be employed to analyze student feedback and sentiment patterns, enabling educators to gain valuable insights into student engagement, motivation, and satisfaction. It also examines how sentiment analysis can be used to identify and address students' emotional states, such as stress, boredom, or confusion, leading to more personalized and effective interventions. Furthermore, the book explores the integration of sentiment analysis with other educational data mining techniques, such as clustering, classification, and predictive modeling. It showcases real-world case studies and examples that demonstrate how sentiment analysis can be combined with these approaches to improve educational decision-making, curriculum design, and adaptive learning systems.



A Course In Mathematical Statistics And Large Sample Theory


A Course In Mathematical Statistics And Large Sample Theory
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Author : Rabi Bhattacharya
language : en
Publisher: Springer
Release Date : 2016-08-14

A Course In Mathematical Statistics And Large Sample Theory written by Rabi Bhattacharya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-14 with Mathematics categories.


This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics. Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.



An Economic Analysis Of Large Dairying Operations In Wisconsin


An Economic Analysis Of Large Dairying Operations In Wisconsin
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Author : Robert John Rades
language : en
Publisher:
Release Date : 1960

An Economic Analysis Of Large Dairying Operations In Wisconsin written by Robert John Rades and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1960 with categories.




Big Data In Complex And Social Networks


Big Data In Complex And Social Networks
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Author : My T. Thai
language : en
Publisher: CRC Press
Release Date : 2016-12-01

Big Data In Complex And Social Networks written by My T. Thai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-01 with Business & Economics categories.


This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.



Data Just Right


Data Just Right
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Author : Michael Manoochehri
language : en
Publisher: Pearson Education
Release Date : 2014

Data Just Right written by Michael Manoochehri and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computers categories.


Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on "Big Data" have been little more than business polemics or product catalogs. Data Just Right is different: It's a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist. Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that's where you can derive the most value. Manoochehri shows how to address each of today's key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You'll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today's leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Coverage includes Mastering the four guiding principles of Big Data success--and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically "Building for infinity" to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist



3000 Years Of Analysis


3000 Years Of Analysis
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Author : Thomas Sonar
language : en
Publisher: Springer Nature
Release Date : 2020-12-27

3000 Years Of Analysis written by Thomas Sonar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-27 with Mathematics categories.


What exactly is analysis? What are infinitely small or infinitely large quantities? What are indivisibles and infinitesimals? What are real numbers, continuity, the continuum, differentials, and integrals? You’ll find the answers to these and other questions in this unique book! It explains in detail the origins and evolution of this important branch of mathematics, which Euler dubbed the “analysis of the infinite.” A wealth of diagrams, tables, color images and figures serve to illustrate the fascinating history of analysis from Antiquity to the present. Further, the content is presented in connection with the historical and cultural events of the respective epochs, the lives of the scholars seeking knowledge, and insights into the subfields of analysis they created and shaped, as well as the applications in virtually every aspect of modern life that were made possible by analysis.