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Data Information And Time
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Book Synopsis Data, Information, and Time by : Hermann Kopetz
Download or read book Data, Information, and Time written by Hermann Kopetz and published by Springer Nature. This book was released on 2022-03-17 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief presents the data- information-and-time (DIT) model that precisely clarifies the semantics behind the terms data, information and their relations to the passage of real time. According to the DIT model a data item is a symbol that appears as a pattern (e.g., visual, sound, gesture, or any bit pattern) in physical space. It is generated by a human or a machine in the current contextual situation and is linked to a concept in the human mind or a set of operations of a machine. An information item delivers the sense or the idea that a human mind extracts out of a given natural language proposition that contains meaningful data items. Since the given tangible, intangible and temporal context are part of the explanation of a data item, a change of context can have an effect on the meaning of data and the sense of a proposition. The DIT model provides a framework to show how the flow of time can change the truth-value of a proposition. This book compares our notions of data, information, and time in differing contexts: in human communication, in the operation of a computer system and in a biological system. In the final Section a few simple examples demonstrate how the lessons learned from the DIT-model can help to improve the design of a computer system.
Book Synopsis Analyzing Time Interval Data by : Philipp Meisen
Download or read book Analyzing Time Interval Data written by Philipp Meisen and published by Springer. This book was released on 2016-09-28 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data.
Book Synopsis Time-Integrative Geographic Information Systems by : Thomas Ott
Download or read book Time-Integrative Geographic Information Systems written by Thomas Ott and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book deals with the integration of temporal information in Geographic Information Systems. The main purpose of an historical or time-integrative GIS is to reproduce spatio- temporal processes or sequents of events in the real world in the form of a model. The model thus making them accessible for spatial query, analysis and visualization. This volume reflects both theoretical thoughts on the interrelations of space and time, as well as practical examples taken from various fields of application (e.g. business data warehousing, demographics, history and spatial analysis).
Book Synopsis Big Data Analytics for Time-Critical Mobility Forecasting by : George A. Vouros
Download or read book Big Data Analytics for Time-Critical Mobility Forecasting written by George A. Vouros and published by Springer Nature. This book was released on 2020-06-23 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating and noisy data streams from moving entities, correlating them with data from archived data sources expressing e.g. entities’ characteristics, geographical information, mobility patterns, mobility regulations and intentional data. The book is divided into six parts: Part I discusses the motivation and background of mobility forecasting supported by trajectory-oriented analytics, and includes specific problems and challenges in the aviation (air-traffic management) and the maritime domains. Part II focuses on big data quality assessment and processing, and presents novel technologies suitable for mobility analytics components. Next, Part III describes solutions toward processing and managing big spatio-temporal data, particularly enriching data streams and integrating streamed and archival data to provide coherent views of mobility, and storing of integrated mobility data in large distributed knowledge graphs for efficient query-answering. Part IV focuses on mobility analytics methods exploiting (online) processed, synopsized and enriched data streams as well as (offline) integrated, archived mobility data, and highlights future location and trajectory prediction methods, distinguishing between short-term and more challenging long-term predictions. Part V examines how methods addressing data management, data processing and mobility analytics are integrated in big data architectures with distinctive characteristics compared to other known big data paradigmatic architectures. Lastly, Part VI covers important ethical issues that research on mobility analytics should address. Providing novel approaches and methodologies related to mobility detection and forecasting needs based on big data exploration, processing, storage, and analysis, this book will appeal to computer scientists and stakeholders in various application domains.
Book Synopsis Time Granularities in Databases, Data Mining, and Temporal Reasoning by : Claudio Bettini
Download or read book Time Granularities in Databases, Data Mining, and Temporal Reasoning written by Claudio Bettini and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Calendar and time units and specialized units, such as business days and academic years, play a major role in a wide range of information system applications. System support for reasoning about these units, called granularities, is important for the efficient design, use, and implementation of such applications. This book deals with several aspects of temporal information and provides a unifying model for granularities. Practitioners can learn about critical aspects that must be taken into account when designing and implementing databases supporting temporal information.
Book Synopsis Analyzing Neural Time Series Data by : Mike X Cohen
Download or read book Analyzing Neural Time Series Data written by Mike X Cohen and published by MIT Press. This book was released on 2014-01-17 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.
Book Synopsis Visualization of Time-Oriented Data by : Wolfgang Aigner
Download or read book Visualization of Time-Oriented Data written by Wolfgang Aigner and published by Springer Science & Business Media. This book was released on 2011-05-30 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time is an exceptional dimension that is common to many application domains such as medicine, engineering, business, or science. Due to the distinct characteristics of time, appropriate visual and analytical methods are required to explore and analyze them. This book starts with an introduction to visualization and historical examples of visual representations. At its core, the book presents and discusses a systematic view of the visualization of time-oriented data along three key questions: what is being visualized (data), why something is visualized (user tasks), and how it is presented (visual representation). To support visual exploration, interaction techniques and analytical methods are required that are discussed in separate chapters. A large part of this book is devoted to a structured survey of 101 different visualization techniques as a reference for scientists conducting related research as well as for practitioners seeking information on how their time-oriented data can best be visualized.
Download or read book Data Science written by Ivo D. Dinov and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-12-06 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
Book Synopsis Right-Time Experiences by : Maribel Lopez
Download or read book Right-Time Experiences written by Maribel Lopez and published by John Wiley & Sons. This book was released on 2014-10-06 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book illustrates how businesses can use mobility, big data, and analytics to enhance or change business processes, improve margins through better insight, transform customer experiences, and empower employees with real-time, actionable insights. The author depicts how companies can create competitive differentiation using mobile, cloud computing big data, and analytics to improve commerce, customer service, and communications with employees and consumers"--
Book Synopsis Measure, Use, Improve! by : Christina A. Russell
Download or read book Measure, Use, Improve! written by Christina A. Russell and published by IAP. This book was released on 2020-10-01 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measure, Use, Improve! Data Use in Out-of-School Time shares the experience and wisdom from a broad cross-section of out-of-school time professionals, ranging from internal evaluators, to funders, to researchers, to policy advocates. Key themes of the volume include building support for learning and evaluation within out-of-school time programs, creating and sustaining continuous quality improvement efforts, authentically engaging young people and caregivers in evaluation, and securing funder support for learning and evaluation. This volume will be particularly useful to leadership-level staff in out-of-school time organizations that are thinking about deepening their own learning and evaluation systems, yet aren’t sure where to start. Authors share conceptual frameworks that have helped inform their thinking, walk through practical examples of how they use data in out-of-school time, and offer advice to colleagues.
Download or read book Visualizing Time written by Graham Wills and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depictions of data with a view to help people understand it and take action. In this book, Graham Wills bridges the gap between the art and the science of visually representing data. He does not simply give rules and advice, but bases these on general principles and provide a clear path between them This book is concerned with the graphical representation of time data and is written to cover a range of different users. A visualization expert designing tools for displaying time will find it valuable, but so also should a financier assembling a report in a spreadsheet, or a medical researcher trying to display gene sequences using a commercial statistical package.
Book Synopsis Pattern Recognition and Classification in Time Series Data by : Volna, Eva
Download or read book Pattern Recognition and Classification in Time Series Data written by Volna, Eva and published by IGI Global. This book was released on 2016-07-22 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.
Book Synopsis Practical Real-time Data Processing and Analytics by : Shilpi Saxena
Download or read book Practical Real-time Data Processing and Analytics written by Shilpi Saxena and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.
Book Synopsis Linear Time Varying Systems and Sampled-data Systems by : Akira Ichikawa
Download or read book Linear Time Varying Systems and Sampled-data Systems written by Akira Ichikawa and published by Springer Science & Business Media. This book was released on 2001-02-26 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph considers linear optimal regulators, differential games and develops the theory for time-varying systems and jump systems.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Time Series Databases by : Ted Dunning
Download or read book Time Series Databases written by Ted Dunning and published by O'Reilly Media. This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors Ted Dunning and Ellen Friedman provide a detailed examination of open source tools such as OpenTSDB and new modifications that greatly speed up data ingestion. You'll learn: A variety of time series use cases The advantages of NoSQL databases for large-scale time series data NoSQL table design for high-performance time series databases The benefits and limitations of OpenTSDB How to access data in OpenTSDB using R, Go, and Ruby How time series databases contribute to practical machine learning projects How to handle the added complexity of geo-temporal data For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from Ted Dunning and Ellen Friedman.
Book Synopsis Time Series Data Analysis Using EViews by : I. Gusti Ngurah Agung
Download or read book Time Series Data Analysis Using EViews written by I. Gusti Ngurah Agung and published by John Wiley & Sons. This book was released on 2011-08-31 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extendible to cross-section data sets. The author: Provides step-by-step directions on how to apply EViews software to time series data analysis Offers guidance on how to develop and evaluate alternative empirical models, permitting the most appropriate to be selected without the need for computational formulae Examines a variety of times series models, including continuous growth, discontinuous growth, seemingly causal, regression, ARCH, and GARCH as well as a general form of nonlinear time series and nonparametric models Gives over 250 illustrative examples and notes based on the author's own empirical findings, allowing the advantages and limitations of each model to be understood Describes the theory behind the models in comprehensive appendices Provides supplementary information and data sets An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource.
