The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Nowadays, cardiovascular disease (CVD) has become a disease of the majority. As an important instrument for diagnosing CVD, electrocardiography (ECG) is used to extract useful information about the functioning status of the heart. In the domain of ECG analysis, cluster analysis is a commonly applied approach to gain an overview of the data, detect outliers or pre-process before further analysis. In...
This paper presents a novel color quantization method based on Normalized Cut clustering algorithm, in order to generate a quantized image with the minimum loss of information and the maximum compression ratio, which benefits the storage and transmission of the color image. This new method uses a deformed Median Cut algorithm as a coarse partition of color pixels in the RGB color space, and then take...
Understanding the genotype-phenotype association is a fundamental problem in genetics. A major open problem in mapping complex traits is identifying a set of interacting genetic variants (such as single nucleotide polymorphisms or SNPs) that influence disease susceptibility. Logic regression (LR) is a statistical approach that has been proposed to model interactions of SNPs. Several LR-based association...
Social media, e.g. Weblog and Internet forum, generate rich historical textual datasets which record lots of valuable events. Automatic event detection tries to discover important and interesting events and their related documents. Existing solutions to event detection, however, are mostly proposed for high quality news stories and may not work well when they are applied to noisy social media datasets,...
SENSC algorithm is a newly proposed stable and efficient NSC algorithm. In this paper the SENSC algorithm is evaluated for the task of image clustering. A series of experiments are conducted on two different kinds of image datasets, including face images and natural images, and SENSC is compared with some other commonly used clustering methods. Experimental results show that SENSC is better suited...
Unrepresentative data samples are likely to reduce the utility of data classifiers in practical application. This study presents a multi-approaches-guided preprocess algorithm in the design of an effective chance discovery model, which bases on data crystallization, clustering and neural network techniques. We used data crystallization to discover unobservable events of the input samples with the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.