Search results for "Cluster Analysis"

Visualizing Confidence in Cluster-based Ensemble Weather Forecast Analyses

2020

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we — a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enab…

Analysis of dietary patterns and nutritional adequacy in lactating women : a multicentre European cohort (ATLAS study)

2021

Abstract Eating habits of lactating women can influence the nutrient composition of human milk, which in turn influences nutrient intake of breastfed infants. The aim of the present study was to identify food patterns and nutritional adequacy among lactating women in Europe. Data from a multicentre European longitudinal cohort (ATLAS study) were analysed to identify dietary patterns using cluster analysis. Dietary information from 180 lactating women was obtained using 3-d food diaries over the first 4 months of lactation. Four dietary patterns were identified: ‘vege-oils’, ‘fish-poultry’, ‘confectionery-salads’ and ‘mixed dishes’. Nutrition adequacy was not significantly different between …

2014

Codebook is an effective image representation method. By clustering in local image descriptors, a codebook is shown to be a distinctive image feature and widely applied in object classification. In almost all existing works on codebooks, the building of the visual vocabulary follows a basic routine, that is, extracting local image descriptors and clustering with a user-designated number of clusters. The problem with this routine lies in that building a codebook for each single dataset is not efficient. In order to deal with this problem, we investigate the influence of vocabulary sizes on classification performance and vocabulary universality with the kNN classifier. Experimental results in…

Optimal imaging of multi-channel EEG features based on a novel clustering technique for driver fatigue detection

2020

Abstract Fatigue may cause a decrease in mental and physical performance capacity, which is a serious safety risk for the drivers in the transportation system. Recently, various studies have demonstrated the deviations of electroencephalogram (EEG) indicators from normal vigilant state during fatigue in time and frequency domains. However, when considering spatial information, these feature descriptors are not satisfying the demand for reliable detection due to the well-known challenge of signal mixing. In this paper, we propose a novel approach based on clustering on brain networks (CBNs) to alleviate the problem to improve the performance of driver fatigue detection. The clustering algori…

Distribution patterns of particulate trace metals in the water column and nepheloid layer of the Gulf of Riga.

2004

The dynamics (fate) of trace metals in suspended particulate matter within the Gulf of Riga has not yet been adequately addressed in the scientific literature. Therefore, during a two year period (2001-2002) samples of suspended particulate matter and surface sediments for trace metal analysis were collected in the Gulf of Riga and the Daugava river, and these data were combined with background information from the national marine monitoring program in Latvia. This paper presents a descriptive study of solid phase trace metals (aluminium, iron, cadmium, chromium, copper, manganese, nickel, lead and zinc) dynamics and their spatial distribution within the Gulf of Riga based on Principal Comp…

Non-Technological Aspects on Web Searching Success

2008

This paper studies the influence of social, cultural and emotional background of typical Web users into the web searching process. Several variables, describing such aspects, are represented and statistically analyzed with well known clustering and classifying algorithms such, as COBWEB, J48, Bayes classification, and Correspondence analysis. Results indicate that the efficiency of the complete process of Information Retrieval will not be fully understood without considering subjectivity and personality facts.

Identifying legitimate Web users and bots with different traffic profiles — an Information Bottleneck approach

2020

Abstract Recent studies reported that about half of Web users nowadays are intelligent agents (Web bots). Many bots are impersonators operating at a very high sophistication level, trying to emulate navigational behaviors of legitimate users (humans). Moreover, bot technology continues to evolve which makes bot detection even harder. To deal with this problem, many advanced methods for differentiating bots from humans have been proposed, a large part of which relies on supervised machine learning techniques. In this paper, we propose a novel approach to identify various profiles of bots and humans which combines feature selection and unsupervised learning of HTTP-level traffic patterns to d…

Foto2Events: From Photos to Event Discovery and Linking in Online Social Networks

2014

International audience; — Online social networking has become the predominant activity in the digital world thanks to multimedia data (mainly photos) sharing (e.g., photos now represent 93% of the top posts on Facebook). Discovering events where users are involved using their own posts and those shared by their friends would be of great importance. In this paper, we address this issue by providing an original approach able to detect, enrich and also link user's events using photos shared within his online social networks. Using metadata, our approach provides a multi-dimensional gathering of similar photos using their temporal, geographical, and social facets. To validate our approach, we i…

Effects of particle clustering on the plastic deformation and damage initiation of particulate reinforced composite utilizing X-ray CT data and finit…

2018

In this paper, a new simulation technique which can include microstructural inhomogeneity of particulate reinforced composites is proposed to accurately study deformation pattern and damage mechanism in these composites. Three dimensional microstructures constructed from XCT images incorporated into finite element modeling codes with minimal approximation to capture the effects of cluster size, local volume fraction of particles in the cluster and the distance between clusters as relevant statistical quantities describing the microstructural inhomogeneity of particulate reinforced composites. A quantitative parameter as degree of clustering is defined to consider particle clustering effect.…

Overlapping community detection versus ground-truth in AMAZON co-purchasing network

2015

International audience; Objective evaluation of community detection algorithms is a strategic issue. Indeed, we need to verify that the communities identified are actually the good ones. Moreover, it is necessary to compare results between two distinct algorithms to determine which is most effective. Classically, validations rely on clustering comparison measures or on quality metrics. Although, various traditional performance measures are used extensively. It appears very clearly that they cannot distinguish community structures with different topological properties. It is therefore necessary to propose an alternative methodology more sensitive to the community structure variations in orde…