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Astronomical surveys produce large amounts of photometric, spectroscopic and time-series data. Object classification, parameter determination, novelty detection and the discovery of structure in these are challenging tasks. This book, featuring contributions from both astronomers and computer scientists, discusses a broad range of astronomical problems and shows how various machine learining and statistical analysis techniques are being used to solve them.
Book Synopsis Classification and Discovery in Large Astronomical Surveys by : Coryn Bailer-Jones
Download or read book Classification and Discovery in Large Astronomical Surveys written by Coryn Bailer-Jones and published by American Institute of Physics. This book was released on 2008-12-11 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Astronomical surveys produce large amounts of photometric, spectroscopic and time-series data. Object classification, parameter determination, novelty detection and the discovery of structure in these are challenging tasks. This book, featuring contributions from both astronomers and computer scientists, discusses a broad range of astronomical problems and shows how various machine learining and statistical analysis techniques are being used to solve them.
Identifying Emerging Trends in Technological Innovation Doctoral programs in science and engineering are important sources of innovative ideas and techniques that might lead to new products and technological innovation. Certainly most PhD students are not experienced researchers and are in the process of learning how to do research. Nevertheless, a number of empiric studies also show that a high number of technological innovation ideas are produced in the early careers of researchers. The combination of the eagerness to try new approaches and directions of young doctoral students with the experience and broad knowledge of their supervisors is likely to result in an important pool of innovation potential. The DoCEIS doctoral conference on Computing, Electrical and Industrial En- neering aims at creating a space for sharing and discussing ideas and results from doctoral research in these inter-related areas of engineering. Innovative ideas and hypotheses can be better enhanced when presented and discussed in an encouraging and open environment. DoCEIS aims to provide such an environment, releasing PhD students from the pressure of presenting their propositions in more formal contexts.
Book Synopsis Emerging Trends in Technological Innovation by : Luis M. Camarinha-Matos
Download or read book Emerging Trends in Technological Innovation written by Luis M. Camarinha-Matos and published by Springer. This book was released on 2010-02-26 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identifying Emerging Trends in Technological Innovation Doctoral programs in science and engineering are important sources of innovative ideas and techniques that might lead to new products and technological innovation. Certainly most PhD students are not experienced researchers and are in the process of learning how to do research. Nevertheless, a number of empiric studies also show that a high number of technological innovation ideas are produced in the early careers of researchers. The combination of the eagerness to try new approaches and directions of young doctoral students with the experience and broad knowledge of their supervisors is likely to result in an important pool of innovation potential. The DoCEIS doctoral conference on Computing, Electrical and Industrial En- neering aims at creating a space for sharing and discussing ideas and results from doctoral research in these inter-related areas of engineering. Innovative ideas and hypotheses can be better enhanced when presented and discussed in an encouraging and open environment. DoCEIS aims to provide such an environment, releasing PhD students from the pressure of presenting their propositions in more formal contexts.
The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Albert Bifet
Download or read book Machine Learning and Knowledge Discovery in Databases written by Albert Bifet and published by Springer. This book was released on 2015-08-28 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.
Book Synopsis Advances in Machine Learning and Data Mining for Astronomy by : Michael J. Way
Download or read book Advances in Machine Learning and Data Mining for Astronomy written by Michael J. Way and published by CRC Press. This book was released on 2012-03-29 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.
Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. Addresses both astronomy and geosciences in parallel, from a big data perspective Includes introductory information, key principles, applications and the latest techniques Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields
Book Synopsis Knowledge Discovery in Big Data from Astronomy and Earth Observation by : Petr Skoda
Download or read book Knowledge Discovery in Big Data from Astronomy and Earth Observation written by Petr Skoda and published by Elsevier. This book was released on 2020-04-23 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. Addresses both astronomy and geosciences in parallel, from a big data perspective Includes introductory information, key principles, applications and the latest techniques Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. Bridges the gap between radio astronomy and computer science Includes coverage of the observation lifecycle as well as data collection, processing and analysis Presents state-of-the-art research and techniques in big data related to radio astronomy Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)
Book Synopsis Big Data in Astronomy by : Linghe Kong
Download or read book Big Data in Astronomy written by Linghe Kong and published by Elsevier. This book was released on 2020-06-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. Bridges the gap between radio astronomy and computer science Includes coverage of the observation lifecycle as well as data collection, processing and analysis Presents state-of-the-art research and techniques in big data related to radio astronomy Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)
This book shows that astronomical discovery is a complex and ongoing process comprising various stages of research, interpretation and understanding.
Book Synopsis Discovery and Classification in Astronomy by : Steven J. Dick
Download or read book Discovery and Classification in Astronomy written by Steven J. Dick and published by Cambridge University Press. This book was released on 2013-09-09 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows that astronomical discovery is a complex and ongoing process comprising various stages of research, interpretation and understanding.
This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases. Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
Book Synopsis Astrostatistics and Data Mining by : Luis Manuel Sarro
Download or read book Astrostatistics and Data Mining written by Luis Manuel Sarro and published by Springer Science & Business Media. This book was released on 2012-08-04 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases. Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
The idea of holding a colloquium on Schmidt telescopes (techniques and science) originated from the observation that, in the last ten years and in spite of the remarkable developments and achievements in this field of astronomical research, there had been no specific opportunity for the experts to meet together, make the point on the state of the art, discuss and coordinate future plans. Therefore, Prof. L. Rosino, one of the pioneers in the use of wide-field telescopes, driven also by the wish of honouring the over four decades of activity of the Asiago Observatory, proposed to the Executive Committee of the International Astronomical Union to sponsor a colloquium on 'Astronomy with Schmidt type telescopes I to be held at Asiago at the end of the summer of 1983. Details about the composition of the Scientific Organizing Committee and the sponsoring organizations are given in Prof. Rosino's 'Welcome to the Participants • The granting of this proposal was the beginning of a ' number of headaches tor the members of the Local Organizing Committee, R. Barbon, F. Ciatti, P. Rafanelli and myself. If, organlzationwise, the colloquium was successful, this is truly due to the generous efforts of my colleagues of the SOC and to the efficient organization of the Linta Park, the hotel hosting the meeting.
Book Synopsis Astronomy with Schmidt-Type Telescopes by : M. Capaccioli
Download or read book Astronomy with Schmidt-Type Telescopes written by M. Capaccioli and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of holding a colloquium on Schmidt telescopes (techniques and science) originated from the observation that, in the last ten years and in spite of the remarkable developments and achievements in this field of astronomical research, there had been no specific opportunity for the experts to meet together, make the point on the state of the art, discuss and coordinate future plans. Therefore, Prof. L. Rosino, one of the pioneers in the use of wide-field telescopes, driven also by the wish of honouring the over four decades of activity of the Asiago Observatory, proposed to the Executive Committee of the International Astronomical Union to sponsor a colloquium on 'Astronomy with Schmidt type telescopes I to be held at Asiago at the end of the summer of 1983. Details about the composition of the Scientific Organizing Committee and the sponsoring organizations are given in Prof. Rosino's 'Welcome to the Participants • The granting of this proposal was the beginning of a ' number of headaches tor the members of the Local Organizing Committee, R. Barbon, F. Ciatti, P. Rafanelli and myself. If, organlzationwise, the colloquium was successful, this is truly due to the generous efforts of my colleagues of the SOC and to the efficient organization of the Linta Park, the hotel hosting the meeting.
Book Synopsis Astronomical Data Analysis Software and Systems XVIII by : David A. Bohlender
Download or read book Astronomical Data Analysis Software and Systems XVIII written by David A. Bohlender and published by . This book was released on 2009 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt:
