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Ycasd - a tool for capturing and scaling data from graphical representationsGross, Arnd, Schirm, Sibylle, Scholz, Markus 02 July 2014 (has links) (PDF)
Background: Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. Results:
After describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling. Conclusions:
We conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses.
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Ycasd - a tool for capturing and scaling data from graphical representationsGross, Arnd, Schirm, Sibylle, Scholz, Markus 18 August 2014 (has links) (PDF)
Background: Mathematical modelling of biological processes often requires a large variety of different data sets for parameter estimation and validation. It is common practice that clinical data are not available in raw formats but are provided as graphical representations. Hence, in order to include these data into environments used for model simulations and statistical analyses, it is necessary to extract them from their presentations in the literature. For this purpose, we developed the freely available open source tool ycasd. After establishing a coordinate system by simple axes definitions, it supports convenient retrieval of data points from arbitrary figures. Results:
After describing the general functionality and providing an overview of the programme interface, we demonstrate on an example how to use ycasd. A major advantage of ycasd is that it does not require a certain input file format to open and process figures. All options of ycasd are accessible through a single window which eases handling and speeds up data extraction. For subsequent processing of extracted data points, results can be formatted as a Matlab or an R matrix. We extensively compare the functionality and other features of ycasd with other publically available tools. Finally, we provide a short summary of our experiences with ycasd in the context of modelling. Conclusions:
We conclude that our tool is suitable for convenient and accurate data retrievals from graphical representations such as papers. Comparison of tools reveals that ycasd is a good compromise between easy and quick capturing of scientific data from publications and complexity. Our tool is routinely applied in the context of biological modelling, where numerous time series data are required to develop models. The software can also be useful for other kinds of analyses for which published data are required but are not available in raw formats such as systematic reviews and meta-analyses.
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Untersuchung des Informationsverlustes von Zeitreihen beim Übergang von Minuten- zu ViertelstundendurchschnittswertenSchmiedel, Anne 18 January 2012 (has links) (PDF)
Es erfolgte die Untersuchung der Eigenschaften der gegebenen Zeitreihen der Wirkleistung von zwei Windenergieanlagen sowie des gesamten Windparks. Außerdem analysiert wurden die entsprechenden Eigenschaften der auf Viertelstundendaten konvertierten Reihen. Diese Eigenschaften, wie z.B. Mittelwert, Varianz o.a. Maximum wurden als Informationen angesehen und so ermöglichte die Gegenüberstellung einen Rückschluss auf dem Informationsverlust. Da die gegebene Einspeiseleistung keine Periodizitäten aufwies, erfolgte anschließend die Erzeugung synthetischer Daten.
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User centered social software model and characteristics of a software family for social information management /Lehel, Vanda. Unknown Date (has links) (PDF)
München, Techn. University, Diss., 2007.
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Privatsphäre durch die Delegation von Rechten /Wohlgemuth, Sven. January 2009 (has links)
Zugl.: Freiburg i. Br., Universiẗat, Diss., 2008. / Literaturverz. S. [179] - 187.
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Fehlende Daten in Additiven Modellen /Nittner, Thomas. January 2003 (has links) (PDF)
Univ., Diss.--München, 2003. / Zsfassung in engl. Sprache.
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Unscharfe Validierung strukturierter Daten ein Modell auf der Basis unscharfer LogikSchlarb, Sven January 2007 (has links)
Zugl.: Köln, Univ., Diss., 2007
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RFID-Techniken und Datenschutzrecht Perspektiven der RegulierungPolenz, Sven January 2008 (has links)
Chemnitz, Techn. Univ., Diss., 2008
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User-centered social software model and characteristics of a software family for social information managementLehel, Vanda January 2007 (has links)
Zugl.: München, Techn. Univ., Diss., 2007 / Hergestellt on demand
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Datenschutz in Europa und den USA : eine rechtsvergleichende Untersuchung unter besonderer Berücksichtigung der Safe-Harbor-Lösung /Genz, Alexander. January 2004 (has links)
Universiẗat, Diss., 2004--Gießen.
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