Search results for " recognition"
showing 10 items of 3220 documents
Review: the Use of Electromyography on Food Texture Assessment
2001
Sensory evaluation (SE) involves evoking, measuring and interpreting human responses to the properties of foods. Among these properties texture is an important one for food acceptability. Texture is mainly perceived through mastication, a process that changes food characteristics throughout time by comminuting and salivation. Electromyography (EMG) has emerged as a new tool in sensory evaluation mainly for assessing texture characteristics. Thus, it is interesting to analyze the knowledge so far generated and the procedures employed. Bipolar surface electrodes are placed on the four main masticatory muscles (masseter right-left and temporalis right-left) and their electric activity recorded…
Automatic detection and measurement of nuchal translucency.
2017
In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…
PRR signaling during in vitro macrophage differentiation from progenitors modulates their subsequent response to inflammatory stimuli.
2017
Toll-like receptor (TLR) agonists drive hematopoietic stem and progenitor cells (HSPCs) to differentiate along the myeloid lineage in vitro and also in vivo following infection. In this study, we used an in vitro model of HSPC differentiation to investigate the functional consequences (cytokine production) that exposing HSPCs to various pathogen-associated molecular patterns (PAMPs) and Candida albicans cells have on the subsequently derived macrophages. Mouse HSPCs (Lin- cells) were cultured with GM-CSF to induce macrophage differentiation in the presence or absence of the following pattern recognition receptor (PRR) agonists: Pam3CSK4 (TLR2 ligand), LPS (TLR4 ligand), depleted zymosan (wh…
Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors
2017
International audience; The perception of odor is an important component of smell; the first step of odor detection, and the discrimination of structurally diverse odorants depends on their interactions with olfactory receptors (ORs). Indeed, the perception of an odor's quality results from a combinatorial coding, in which the deciphering remains a major challenge. Several studies have successfully established links between odors and odorants by categorizing and classifying data. Hence, the categorization of odors appears to be a promising way to manage odors. In the proposed study, we performed a computational analysis using odor descriptions of the odorants present in Flavor-Base 9th Edit…
Chemical Profiles of Integumentary and Glandular Substrates in Australian Sea Lion Pups ( Neophoca cinerea )
2019
International audience; Recognition of individuals or classes of individuals plays an important role in the communication systems of many mammals. The ability of otariid (i.e., fur seal and sea lion) females to locate and identify their offspring in colonies after returning from regular foraging trips is essential to successful pup rearing. It has been shown that olfaction is used to confirm the identity of the pup by the mother when they reunite, yet the processes by which this chemical recognition occurs remain unclear. Using gas chromatography-mass spectrometry, we examined chemical profiles of integumentary and glandular secretions/excretions from pre- and post-molt Australian sea lion …
Bacteria classification using minimal absent words
2017
Bacteria classification has been deeply investigated with different tools for many purposes, such as early diagnosis, metagenomics, phylogenetics. Classification methods based on ribosomal DNA sequences are considered a reference in this area. We present a new classificatier for bacteria species based on a dissimilarity measure of purely combinatorial nature. This measure is based on the notion of Minimal Absent Words, a combinatorial definition that recently found applications in bioinformatics. We can therefore incorporate this measure into a probabilistic neural network in order to classify bacteria species. Our approach is motivated by the fact that there is a vast literature on the com…
Defining classifier regions for WSD ensembles using word space features
2006
Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…
Betweenness Centrality for Networks with Non-Overlapping Community Structure
2018
Evaluating the centrality of nodes in complex networks is one of the major research topics being explored due to its wide range of applications. Among the various measures that have been developed over the years, Betweenness centrality is one of the most popular. Indeed, it has proved to be efficient in many real-world situations. In this paper, we propose an extension of the Betweenness centrality designed for networks with nonoverlapping community structure. It is a linear combination of the so-called “local” and “global” Betweenness measures. The Local measure takes into account the influence of a node at the community level while the global measure depends only on the interactions betwe…
Building an Optimal WSD Ensemble Using Per-Word Selection of Best System
2006
In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method c…
genuMet: distinguish genuine untargeted metabolic features without quality control samples
2019
AbstractMotivationLarge-scale untargeted metabolomics experiments lead to detection of thousands of novel metabolic features as well as false positive artifacts. With the incorporation of pooled QC samples and corresponding bioinformatics algorithms, those measurement artifacts can be well quality controlled. However, it is impracticable for all the studies to apply such experimental design.ResultsWe introduce a post-alignment quality control method called genuMet, which is solely based on injection order of biological samples to identify potential false metabolic features. In terms of the missing pattern of metabolic signals, genuMet can reach over 95% true negative rate and 85% true posit…