Search results for "cluster analysis."
showing 10 items of 805 documents
Oxidative stress response of tumor cells: microarray-based comparison between artemisinins and anthracyclines
2004
The antimalarial artemisinins also reveal profound cytotoxic activity against tumor cells. Artemisinins harbor an endoperoxide bridge whose cleavage results in the generation of reactive oxygen species (ROS) and/or artemisinin carbon-centered free radicals. Established cancer drugs such as anthracyclines also form ROS and free radicals that are responsible for the cardiotoxicity of anthracyclines. In contrast, artemisinins do not reveal cardiotoxicity. In the present investigation, we compared the cytotoxic activities of different artemisinins (artemisinin, artesunate, arteether, artemether, artemisitene, dihydroartemisinylester stereoisomers) in 60 cell lines of the National Cancer Institu…
Energy-efficient routing control algorithm in large-scale WSN for water environment monitoring with application to Three Gorges Reservoir area
2013
Published version of an article in the journal: The Scientific World Journal. Also available from the publisher at: http://dx.doi.org/10.1155/2014/802915 Open Access The typical application backgrounds of large-scale WSN (wireless sensor networks) for the water environment monitoring in the Three Gorges Reservoir are large coverage area and wide distribution. To maximally prolong lifetime of large-scale WSN, a new energy-saving routing algorithm has been proposed, using the method of maximum energy-welfare optimization clustering. Firstly, temporary clusters are formed based on two main parameters, the remaining energy of nodes and the distance between a node and the base station. Secondly,…
Comparison of Micro X-ray Computer Tomography Image Segmentation Methods: Artificial Neural Networks Versus Least Square Support Vector Machine
2013
Micro X-ray computer tomography (XCT) is a powerful non-destructive method for obtaining information about rock structures and mineralogy. A new methodology to obtain porosity from 2D XCT digital images using artificial neural network and least square support vector machine is demonstrated following these steps: the XCT image was first preprocessed, thereafter clustering algorithms such as K-means, Fuzzy c-means and self-organized maps was used for image segmentation. Then artificial neural network was applied for image classification. For comparison, least square support vector machine approach was used for classification labeling of the scan images. The methodology shows how artificial ne…
A Cluster Analysis of Stock Market Data Using Hierarchical SOMs
2016
The analysis of stock markets has become relevant mainly because of its financial implications. In this paper, we propose a novel methodology for performing a structured cluster analysis of stock market data. Our proposed method uses a tree-based neural network called the TTOSOM. The TTOSOM performs self-organization to construct tree-based clusters of vector data in the multi-dimensional space. The resultant tree possesses interesting mathematical properties such as a succinct representation of the original data distribution, and a preservation of the underlying topology. In order to demonstrate the capabilities of our method, we analyze 206 assets of the Italian stock market. We were able…
Clustering Quality and Topology Preservation in Fast Learning SOMs
2008
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original …
Discovering representative models in large time series databases
2004
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…
Searches for clustering in the time integrated skymap of the ANTARES neutrino telescope
2014
Adrián-Martínez, S. et al.
Detection of homogeneous precipitation regions at seasonal and annual time scales, northwest Iran
2017
Abstract Detection of homogeneous climate areas is a challenging issue, which can be affected by different criteria. One of the most prominent factors is choosing the time scale, which can lead to different spatial and temporal patterns. Total precipitation is a key factor in climatological studies, and studying its distribution is of utmost importance. The combination of principal components analysis and cluster analysis is used for homogeneous precipitation areas' detection. Hence, the spatial pattern of total precipitation was investigated in northwestern Iran during the past two decades (1991–2010) on seasonal and annual time scales. The results of clustering on each time scale were val…
Spatial diversity of chlorine residual in a drinking water distribution system: application of an integrated fuzzy logic technique
2014
A reduction in the concentration of chlorine, which is used as a chemical disinfectant for water in drinking water distribution systems, can be considered to be an index of the progressive deterioration of water quality. In this work, attention is given to the spatial distribution of the residual chlorine in drinking water distribution systems. The criterion for grouping the water-quality parameters normally used is highly subjective and often based on data that are not correctly identified. In this paper, a cluster analysis based on fuzzy logic is applied. The advantage of the proposed procedure is that it allows a user to identify (in an automatic way and without any specific assumption) …
Mitochondrial DNA Regionalism and Historical Demography in the Extant Populations of Chirocephalus kerkyrensis (Branchiopoda: Anostraca)
2012
BackgroundMediterranean temporary water bodies are important reservoirs of biodiversity and host a unique assemblage of diapausing aquatic invertebrates. These environments are currently vanishing because of increasing human pressure. Chirocephalus kerkyrensis is a fairy shrimp typical of temporary water bodies in Mediterranean plain forests and has undergone a substantial decline in number of populations in recent years due to habitat loss. We assessed patterns of genetic connectivity and phylogeographic history in the seven extant populations of the species from Albania, Corfu Is. (Greece), Southern and Central Italy.Methodology/principal findingsWe analyzed sequence variation at two mito…