Search results for "cluster analysis."

Testing for local structure in spatiotemporal point pattern data

2017

The detection of clustering structure in a point pattern is one of the main focuses of attention in spatiotemporal data mining. Indeed, statistical tools for clustering detection and identification of individual events belonging to clusters are welcome in epidemiology and seismology. Local second-order characteristics provide information on how an event relates to nearby events. In this work, we extend local indicators of spatial association (known as LISA functions) to the spatiotemporal context (which will be then called LISTA functions). These functions are then used to build local tests of clustering to analyse differences in local spatiotemporal structures. We present a simulation stud…

Sample size in cluster-randomized trials with time to event as the primary endpoint

2011

In cluster-randomized trials, groups of individuals (clusters) are randomized to the treatments or interventions to be compared. In many of those trials, the primary objective is to compare the time for an event to occur between randomized groups, and the shared frailty model well fits clustered time-to-event data. Members of the same cluster tend to be more similar than members of different clusters, causing correlations. As correlations affect the power of a trial to detect intervention effects, the clustered design has to be considered in planning the sample size. In this publication, we derive a sample size formula for clustered time-to-event data with constant marginal baseline hazards…

RabbitMash: accelerating hash-based genome analysis on modern multi-core architectures

2020

Abstract Motivation Mash is a popular hash-based genome analysis toolkit with applications to important downstream analyses tasks such as clustering and assembly. However, Mash is currently not able to fully exploit the capabilities of modern multi-core architectures, which in turn leads to high runtimes for large-scale genomic datasets. Results We present RabbitMash, an efficient highly optimized implementation of Mash which can take full advantage of modern hardware including multi-threading, vectorization and fast I/O. We show that our approach achieves speedups of at least 1.3, 9.8, 8.5 and 4.4 compared to Mash for the operations sketch, dist, triangle and screen, respectively. Furtherm…

Assessing local differences between the spatio-temporal second-order structure of two point patterns occurring on the same linear network

2021

Abstract We introduce Local Indicators of Spatio-Temporal Association (LISTA) functions on linear networks and use them to build a statistical test for local second-order structure. This allows to identify differences in the spatio-temporal clustering behaviour of two point patterns, a point pattern of interest and a background one, both occurring on the same linear network. We assess the performance of the testing procedure for local second-order structure through simulation studies under a variety of scenarios that also account for different generating point processes. We show that the proposed local test is able to correctly identify the spatio-temporal difference in the local second-ord…

Animal rennets as sources of dairy lactic acid bacteria

2014

ABSTRACT The microbial composition of artisan and industrial animal rennet pastes was studied by using both culture-dependent and -independent approaches. Pyrosequencing targeting the 16S rRNA gene allowed to identify 361 operational taxonomic units (OTUs) to the genus/species level. Among lactic acid bacteria (LAB), Streptococcus thermophilus and some lactobacilli, mainly Lactobacillus crispatus and Lactobacillus reuteri , were the most abundant species, with differences among the samples. Twelve groups of microorganisms were targeted by viable plate counts revealing a dominance of mesophilic cocci. All rennets were able to acidify ultrahigh-temperature-processed (UHT) milk as shown by pH …

Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners

2012

The availability of large volumes of protein-protein interaction data has allowed the study of biological networks to unveil the complex structure and organization in the cell. It has been recognized by biologists that proteins interacting with each other often participate in the same biological processes, and that protein modules may be often associated with specific biological functions. Thus the detection of protein complexes is an important research problem in systems biology. In this review, recent graph-based approaches to clustering protein interaction networks are described and classified with respect to common peculiarities. The goal is that of providing a useful guide and referenc…

Semi-supervised Hyperspectral Image Classification with Graphs

2006

This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed to exploit the spatial/contextual information in the im- ages through composite kernels. The proposed method produces smoother classifications with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. Good accuracy in high dimensional spaces and low number of labeled samples (ill-posed situations) are produced as compared to standard inductive support vector machines.

A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images

2022

Abstract In precision agriculture, the accurate segmentation of crops and weeds in agronomic images has always been the center of attention. Many methods have been proposed but still the clean and sharp segmentation of crops and weeds is a challenging issue for the images with a high presence of weeds. This work proposes a segmentation method based on the combination of semantic segmentation and K-means algorithms for the segmentation of crops and weeds in color images. Agronomic images of two different databases were used for the segmentation algorithms. Using the thresholding technique, everything except plants was removed from the images. Afterward, semantic segmentation was applied usin…

A Student's t‐based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

2020

Compared regimes of NDVI and Rainfall in semi-arid regions of Africa

2006

International audience; Bi-monthly normalized difference vegetation index (NDVI) at an 8km spatial resolution from the advanced very high resolution radiometers (AVHRR) was used from 1981 to 1995 to analyse the vegetation response to rainfall supply in semi-arid regions of Africa. Within the 200-600 mm annual rainfall belt, for which the apparent NDVI response to rainfall was the strongest, three regions were selected which exhibited different patterns in their NDVI regimes and/or relationships with rainfall. The regions, located in western, southern and eastern Africa, were split into coherent sub-regions in terms of mean regime of photosynthetic activity through a cluster analysis. Overal…