Search results for "pattern"
showing 10 items of 4203 documents
Exposing the structure of an Arctic food web
2015
15 pages; International audience; How food webs are structured has major implications for their stability and dynamics. While poorly studied to date, arctic food webs are commonly assumed to be simple in structure, with few links per species. If this is the case, then different parts of the web may be weakly connected to each other, with populations and species united by only a low number of links. We provide the first highly resolved description of trophic link structure for a large part of a high-arctic food web. For this purpose, we apply a combination of recent techniques to describing the links between three predator guilds (insectivorous birds, spiders, and lepidopteran parasitoids) a…
Imprints of latitude, host taxon, and decay stage on fungus-associated arthropod communities
2022
Interactions among fungi and insects involve hundreds of thousands of species. While insect communities on plants have formed some of the classic model systems in ecology, fungus-based communities and the forces structuring them remain poorly studied by comparison. We characterize the arthropod communities associated with fruiting bodies of eight mycorrhizal basidiomycete fungus species from three different orders along a 1200-km latitudinal gradient in northern Europe. We hypothesized that, matching the pattern seen for most insect taxa on plants, we would observe a general decrease in fungal-associated species with latitude. Against this backdrop, we expected local communities to be struc…
A case study on feature sensitivity for audio event classification using support vector machines
2016
Automatic recognition of multiple acoustic events is an interesting problem in machine listening that generalizes the classical speech/non-speech or speech/music classification problem. Typical audio streams contain a diversity of sound events that carry important and useful information on the acoustic environment and context. Classification is usually performed by means of hidden Markov models (HMMs) or support vector machines (SVMs) considering traditional sets of features based on Mel-frequency cepstral coefficients (MFCCs) and their temporal derivatives, as well as the energy from auditory-inspired filterbanks. However, while these features are routinely used by many systems, it is not …
Source-Target Mapping Model of Streaming Data Flow for Machine Translation
2017
Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building automatic translation system that facilitates processing any of various abstract entities which combine to specify underlying phonological, morphological, semantic and syntactic properties of linguistic forms and that act as the targets of linguistic rules and operations in a source language foll…
Reference standard space hippocampus labels according to the European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative harm…
2017
Abstract Introduction A harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. Methods Manual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility and validity of these reference labels is demonstrated in a simple …
Non-negative blind source separation techniques for tumor tissue typing using HR-MAS signals.
2010
Given High Resolution Magic Angle Spinning (HR-MAS) signals from several glioblastoma tumor subjects, the goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, high cellular tumor and border tumor tissue, and providing the contribution (abundance) of each tumor tissue to the profile of the spectra. The problem is formulated as a non-negative source separation problem. We illustrate the effectiveness of the proposed methods and we analyze to which extent the dimension of the input space could influence the perfor…
Metabolomic Pattern Analysis after Mediterranean Diet Intervention in a Nondiabetic Population: A 1- and 3-Year Follow-up in the PREDIMED Study
2014
The Mediterranean diet (MD) is considered a dietary pattern with beneficial effects on human health. The aim of this study was to assess the effect of an MD on urinary metabolome by comparing subjects at 1 and 3 years of follow-up, after an MD supplemented with either extra-virgin olive oil (MD + EVOO) or nuts (MD + Nuts), to those on advice to follow a control low-fat diet (LFD). Ninety-eight nondiabetic volunteers were evaluated, using metabolomic approaches, corresponding to MD + EVOO (n = 41), MD + Nuts (n = 27), or LFD (n = 30) groups. The (1)H NMR urinary profiles were examined at baseline and after 1 and 3 years of follow-up. Multivariate data analysis (OSC-PLS-DA and HCA) methods we…
Quantification and classification of high-resolution magic angle spinning data for brain tumor diagnosis.
2007
The goal of this work is to propose a complete protocol (preprocessing, processing and classification) for classifying brain tumors with proton high-resolution magic-angle spinning ((1)H HR-MAS) data. The different steps of the procedure are detailed and discussed. Feature extraction techniques such as peak integration, including also the automated quantitation method AQSES, were combined with linear (LDA) and non-linear (least-squares support vector machine or LS-SVM) classifiers. Classification accuracy was assessed using a stratified random sampling scheme. The results suggest that LS-SVM performs better than LDA while AQSES performs better than the standard peak integration feature extr…
A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data
2013
Background: The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing \ud information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic \ud Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyses \ud single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single \ud voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of\ud tumor type classification from the spectroscopic signal.\ud Methodology/Princ…
Hyperspectral detection of citrus damage with Mahalanobis kernel classifier
2007
Presented is a full computer vision system for the identification of post-harvest damage in citrus packing houses. The method is based on the combined use of hyperspectral images and the Mahalanobis kernel classifier. More accurate and reliable results compared to other methods are obtained in several scenarios and acquired images.