Search results for "Clustering"
showing 10 items of 446 documents
An original way to evaluate daily rainfall variability simulated by a regional climate model: the case of South African austral summer rainfall
2014
We discuss the value of a clustering approach as a tool for evaluating daily rainfall output from climate models. Ascendant hierarchical clustering is used to evaluate how well South African recurrent daily rainfall patterns are simulated during the austral summer (December to February 1970–1971 to 1998–1999). A set of 35-km regional climate simulations, run with the WRF model and driven by the ERA40 reanalysis, is chosen as a case study. Six recurrent patterns are identified and compared to the observed clusters obtained by applying the same methodology to 5352 daily rain gauge records. Two of the WRF clusters describe either a persistent and widespread dryness (65% of the days) or pattern…
An Analysis of Regional and Intra-annual Precipitation Variability over Iran using Multivariate Statistical Methods
1998
The temporal and spatial precipitation regime of Iran was analysed using multivariate analyses of monthly mean precipitation records for 71 stations. A Principal Component Analysis was applied to the correlation matrix in order to describe the intra-annual variations of precipitation. The Principal Component scores were mapped to visualize the spatial structure of the three derived precipitation regimes. By applying an agglomerative clustering (WARD) of the three Principal Component scores, five homogeneous spatial clusters, representing five precipitation regions, were developed. The intra-annual types of precipitation distribution, shown by the five clusters, are described and discussed.
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) …
A Comparative Study on Fuzzy-Clustering-Based Lip Region Segmentation Methods
2011
As the first step of many lip-reading or visual speaker authentication systems, lip region segmentation is of vital importance. And fuzzy clustering based methods have been widely used in lip segmentation. In this paper, four fuzzy clustering based lip segmentation methods have been elaborated with their underlying rationale. Experiments have been carried out evaluate their performance comparatively. From the experimental results, SFCM has the best efficiency and FCMST has the best segmentation accuracy.
Sequential Lip Region Segmentation Using Fuzzy Clustering with Spatial and Temporal Information
2012
For many visual speech recognition and visual speaker authentication systems, lip region extraction is of vital important. In order to segment the lip region accurately and robustly from a lip sequence, a new fuzzy-clustering based algorithm is proposed. In the proposed method, a new dissimilarity measure is introduced to take all the color, spatial and temporal information into consideration. An iterative optimization method is employed to derive the optimal lip region membership map and the final segmentation result. From the experimental results, it is observed that the proposed algorithm can provide superior results compared with other traditional methods.
Semantic Verbal Fluency in Children with and without Autism Spectrum Disorder: Relationship with Chronological Age and IQ
2016
We administered a semantic verbal fluency (SVF) task to two groups of children (age range from 5 to 8): 47 diagnosed with Autism Spectrum Disorder (ASD Group) and 53 with typical development (Comparison Group), matched on gender, chronological age, and non-verbal IQ. Four specific indexes were calculated from the SVF task, reflecting the different underlying cognitive strategies used: clustering (component of generativity and lexical-semantic access), and switching (executive component, cognitive flexibility). First, we compared the performance of the two groups on the different SVF task indicators, with the ASD group scoring lower than the Comparison Group, although the difference was grea…
Medical news aggregation and ranking of taking into account the user needs
2019
The purpose of this work is to develop an intelligent information system that is designed for aggregation and ranking of news taking into account the needs of the user. The online market for mass media and the needs of readers, the purpose of their searches and moments is not enough to find the news is analyzed. A conceptual model of the information aggression system and ranking of news that would enable presentation of the work of the future intellectual information system, to show its structure is constructed. The methods and means for implementation of the intellectual information system are selected. An online resource for aggregation and ranking of news, news feeds and flexible setting…
PINCoC: a Co-Clustering based Method to Analyze Protein-Protein Interaction Networks
2007
Anovel technique to search for functionalmodules in a protein-protein interaction network is presented. The network is represented by the adjacency matrix associated with the undirected graph modelling it. The algorithm introduces the concept of quality of a sub-matrix of the adjacency matrix, and applies a greedy search technique for finding local optimal solutions made of dense submatrices containing the maximum number of ones. An initial random solution, constituted by a single protein, is evolved to search for a locally optimal solution by adding/removing connected proteins that best contribute to improve the quality function. Experimental evaluations carried out on Saccaromyces Cerevis…
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…