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Analytical Chemistry, 2020
Nontargeted mass spectrometry (MS) is widely used in life sciences and environmental chemistry to investigate large sets of samples. A major problem for larger-scale MS studies is data gaps or missing values in aligned data sets. The main causes for these data gaps are the absence of the compound from the sample, issues related to chromatography or ...
Erik Müller +4 more
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Nontargeted mass spectrometry (MS) is widely used in life sciences and environmental chemistry to investigate large sets of samples. A major problem for larger-scale MS studies is data gaps or missing values in aligned data sets. The main causes for these data gaps are the absence of the compound from the sample, issues related to chromatography or ...
Erik Müller +4 more
openaire +2 more sources
RA-SAX: Resource-Aware Symbolic Aggregate Approximation for Mobile ECG Analysis
2011 IEEE 12th International Conference on Mobile Data Management, 2011There is a growing focus on 24/7 cardiac monitoring that leverages state of the art mobile phones and commercial-off-the-shelf (COTS) wearable bio-sensors. While many signal processing techniques for mobile ECG analysis have been developed, these techniques tend to be computationally intensive. In this paper, we propose, develop and evaluate a resource-
Hossein Tayebi +4 more
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Storm intensity estimation using symbolic aggregate approximation and artificial neural network
2014 International Computer Science and Engineering Conference (ICSEC), 2014A storm disaster is one of the most destructive natural hazards on earth and the main cause of death or injury to humans as well as damage or loss of valuable goods or properties, such as buildings, communication systems, agricultural land and etc. Storm intensity estimation is also important in evaluating the storm track prediction and risk area that ...
Arthit Buranasing, Akara Prayote
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Symbolic Aggregate Approximation Method Using Updated Lookup Tables
2010Similarity search in time series data mining is a problem that has attracted increasing attention recently. The high dimensionality and large volume of time series databases make sequential scanning inefficient to tackle this problem. There are many representation techniques that aim at reducing the dimensionality of these time series so that the ...
Muhammad Fuad, Muhammad Marwan +1 more
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Dynamic Biometric Recognition of Handwritten Digits Using Symbolic Aggregate Approximation
Proceedings of the SouthEast Conference, 2017Symbolic aggregate approximation (SAX) is an ideal technique for dynamic biometric recognition of handwritten digits. The manipulation of time series in SAX readily lends itself to analysis of the spatial coordinate data acquired from a digit written on the touchscreen of a smartphone or tablet. SAX generates a sequence of alphabetic characters derived
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An improved symbolic aggregate approximation distance measure based on its statistical features
Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services, 2016The challenges in efficient data representation and similarity measures on massive amounts of time series have enormous impact on many applications. This paper addresses an improvement on Symbolic Aggregate approXimation (SAX), is one of the efficient representations for time series mining. Because SAX represents its symbols by the average (mean) value
Chaw Thet Zan, Hayato Yamana
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Cancer statistics for adolescents and young adults, 2020
Ca-A Cancer Journal for Clinicians, 2020Kimberly D Miller +2 more
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