Search results for "cluster analysis"
showing 10 items of 848 documents
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…
Clustering-Assisted 3D Beamforming for Throughput Maximization in mmWave Networks
2021
Beamforming schemes have been widely used to improve network throughput in 5G mmWave networks. However, 3D beamforming schemes have hereto not been investigated in this context. In this work, a cluster-assisted 3D beamforming scheme is proposed to optimize the downtilt angle for network coverage and throughput maximization. User Equipment (UEs) are clustered based on inter-user and the inter-cluster distances. The interference is accounted from the adjacent clusters and thus frequency resources can be assigned to the non-adjacent clusters. Optimal downtilt angles are obtained for every cluster to maximize the throughput while considering the interference from adjacent clusters. 3D beam patt…
Cluster-based active learning for compact image classification
2010
In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer…
Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.
2013
Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single…
A Coclustering Approach for Mining Large Protein-Protein Interaction Networks
2012
Several approaches have been presented in the literature to cluster Protein-Protein Interaction (PPI) networks. They can be grouped in two main categories: those allowing a protein to participate in different clusters and those generating only nonoverlapping clusters. In both cases, a challenging task is to find a suitable compromise between the biological relevance of the results and a comprehensive coverage of the analyzed networks. Indeed, methods returning high accurate results are often able to cover only small parts of the input PPI network, especially when low-characterized networks are considered. We present a coclustering-based technique able to generate both overlapping and nonove…
Association between WHO cut-offs for childhood overweight and obesity and cardiometabolic risk
2012
AbstractObjectiveTo examine the association between cardiovascular risk and childhood overweight and obesity using the BMI cut-offs recommended by the WHO.DesignChildren were classified as normal weight, overweight and obese according to the WHO BMI-for-age reference. Blood pressure, lipids, glucose, insulin, homeostasis model assessment–insulin resistance (HOMA-IR) and uric acid levels were compared across BMI groups. ANOVA and tests of linearity were used to assess overall mean differences across groups. Crude and adjusted odds ratios were calculated for adverse plasma levels of biochemical variables.SettingPaediatric care centres.SubjectsChildren (n149) aged 8–18 years.ResultsAbout 37 %,…