Results 151 to 160 of about 4,635 (193)
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Multivariate Data Analysis of Proteome Data
2006We present the background for multivariate data analysis on proteomics data with a hands-on section on how to transfer data between different software packages. The techniques can also be used for other biological and biochemical problems in which structures have to be found in a large amount of data. Digitalization of the 2D gels, analysis using image
Kåre, Engkilde +2 more
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Nature Ecology & Evolution, 2018
An audit of recent research on the scales of data collection in ecology highlights the field’s data limitations, which may hinder progress in linking processes across scales.
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An audit of recent research on the scales of data collection in ecology highlights the field’s data limitations, which may hinder progress in linking processes across scales.
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Optoelectronics, Instrumentation and Data Processing, 2009
This paper describes the Spektran software system intended for automated analysis of object-attribute data tables which implements data mining algorithms based on a function of rival similarity (FRiS). The Spektran system is used to analyze a set of objects (microparticles of a substance) described by spectral characteristics.
A. B. Bogdanov +7 more
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This paper describes the Spektran software system intended for automated analysis of object-attribute data tables which implements data mining algorithms based on a function of rival similarity (FRiS). The Spektran system is used to analyze a set of objects (microparticles of a substance) described by spectral characteristics.
A. B. Bogdanov +7 more
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Superparamagnetic Clustering of Data
Physical Review Letters, 1996We present a new approach for clustering, based on the physical properties of an inhomogeneous ferromagnetic model. We do not assume any structure of the underlying distribution of the data. A Potts spin is assigned to each data point and short range interactions between neighboring points are introduced.
, Blatt, , Wiseman, , Domany
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Data fusion of multisensor data
KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002The problem of data fusion of multisensor data for multitarget tracking is considered. A hierarchical fusion system is presented for fusion of numerical data from multiple local radar stations, and a fuzzy clustering technique is introduced. Simulation results are presented for a scenario having three local radar stations and three targets with ...
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Data-Entropy Analysis of Renal Transplantation Data
Transplantation Proceedings, 2007The terms entropy and robustness are currently used by biomedical investigators to predict the risk of change in a system. The former is the mathematical identification of uncertainty about a system, while the latter is the likelihood of system stability.
M-T, Hollisaaz +7 more
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Data Quality and Data Cleansing of Semantic Data
2018In this chapter, we first introduce the concepts of Linked Data quality and its dimensions and metrics. Then we provide definitions for 18 quality dimensions along with a total of 69 metrics to measure the dimensions. Thereafter, we provide an overview of tools currently available for Linked Data quality assessment followed by an introduction to the ...
Zaveri, A, Rula, A
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ACM SIGBIO Newsletter, 1998
Comparing inductive machine learning with neural nets and traditional statistical techniques for 'best' predictors of women at risk for PRETERM BIRTH. Preterm babies having higher mortality and morbidity outcomes and often cost in excess of $1 million in the first year of life.
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Comparing inductive machine learning with neural nets and traditional statistical techniques for 'best' predictors of women at risk for PRETERM BIRTH. Preterm babies having higher mortality and morbidity outcomes and often cost in excess of $1 million in the first year of life.
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2016
While it is tempting to proceed immediately to analysis and model-building, it is critically important to spend time to fully understand the dataset. Different types of data (nominal, ordinal, interval, and ratio) are suitable for only specific types of analysis.
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While it is tempting to proceed immediately to analysis and model-building, it is critically important to spend time to fully understand the dataset. Different types of data (nominal, ordinal, interval, and ratio) are suitable for only specific types of analysis.
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Biometrics, 1999
Summary.Survival data stand out as a special statistical field. This paper tries to describe what survival data is and what makes it so special. Survival data concern times to some events. A key point is the successive observation of time, which on the one hand leads to some times not being observed so that all that is known is that they exceed some ...
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Summary.Survival data stand out as a special statistical field. This paper tries to describe what survival data is and what makes it so special. Survival data concern times to some events. A key point is the successive observation of time, which on the one hand leads to some times not being observed so that all that is known is that they exceed some ...
openaire +3 more sources