157 research outputs found
An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization
No full textThis paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation
First detection of Leishmania major in dogs living in an endemic area of zoonotic cutaneous leishmaniasis in Tunisia
Get PDFBackground: Dogs are considered the main domestic animals that may be a reservoir for Leishmania infantum, the agent of zoonotic visceral leishmaniasis (ZVL) in several countries of the world. The dog may host other Leishmania species, but its epidemiological role in the maintenance and spreading of these parasites is not completely elucidated. Zoonotic cutaneous leishmaniasis (ZCL), caused by Leishmania major, affects thousands of people every year and is particularly diffused in many countries of North Africa and Middle East Asia. In ZCL endemic countries, few reports of L. major-positive dogs have been reported, probably because most human cases occur in poor rural areas where the social role of the dog and its medical management is not well considered. The aim of the present study is to better understand the possible involvement of domestic dogs in the epidemiology of ZCL. Methods: Our research focused on a well-established endemic focus of ZCL, in the area of Echrarda, Kairouan Governorate, central Tunisia. A total of 51 dogs with no or mild clinical signs of vector borne diseases were selected in small villages where human cases of ZCL are yearly present. All dogs were sampled for the Leishmania spp. diagnosis, by using the following procedures: blood sample for serology and buffy coat quantitative polymerase chain reaction (qPCR), popliteal fine needle aspiration, and cutaneous biopsy punch for lymph node and skin qPCR. Results: The results demonstrated a high percentage (21.6%) of dogs positive at least at one or more test; the most sensitive technique was the lymph node qPCR that detected 8/11 positive dogs. Nine, out of the eleven positive dogs, resulted as infected by Leishmania infantum; ITS1-PCR-sequencing allowed Leishmania major identification in the remaining two cases, both from the popliteal lymph node samples, which can suggest a possible visceral spread of a cutaneous Leishmania species in the dog. Interestingly, one of the two L. major-positive dogs was living in the same house where 6-year-old children showed cutaneous lesions referred to as ZCL. Conclusions: To our knowledge, this is the first report of L. major-positive dogs in Tunisia, the epidemiological role of which remains under investigation
Reiteration in Pichi: Forms, functions and areal-typological perspectives
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Observation des surfaces continentales par télédétection optique : techniques et méthodes
No full textAspects de la syntaxe de l'haïtien
Get PDFThis dissertation presents a number of Haitian constructions, some of which have so far been left undescribed in the linguistic literature on this language. Special care is devoted to expliciting the interpretive effects associated with the strings generated by the syntax. The Haitian data are drawn from recently-published texts or made up by the author and assessed by himself and other native speakers of Haitian. The body of the text is subdivided into three parts. Part I deals with polarity, TMA and modals. Part II deals with various types of simplex clauses: de-transitivised clauses; reflexive and reciprocal clauses; double-object constructions; serial verbs; questions. Part III deals with the structure and interpretation of noun phrases — bare, simplex, and possessivized
Pour un modèle diglossique de description du français : quelques implications théoriques, didactiques et méthodologiques
No full text25 p.International audienceThe author argues that French (wherever it is spoken) nowadays exhibits the properties regarded as characteristic of a diglossic situation, as classically defined by Ferguson (1959) : the High variety is instanstiated by the grammar of Standard French (prescriptive grammar), and the Low varieties by the various 'dialectal' grammars, activated by speakers in informal situations. The article provides empirical evidence in support of a diglossic approach to French and explores some advantages and implications of such an approach for the description and teaching of French.Cet article défend l'hypothèse que le français (toutes zones géographiques confondues) présente aujourd'hui les propriétés caractérisant la situation diglossique, selon la définition classique de ce concept formulée par Ferguson (1959) : la variété H est incarnée par la grammaire standard, et les variétés L par les grammaires appelées ici dialectales, activées par les locuteurs en situation informelle. Dans une optique générative de la grammaire, il est proposé de représenter la compétence linguistique des francophones par deux grammaires en intersection, schéma rendant compte de l'intuition que les deux algorithmes génèrent "la même langue". L'article s'emploie à justifier pour le français l'hypothèse diglossique et la formalisation proposée, et à en explorer quelques avantages et implications pour la description et l'enseignement de cette langue
Comparative Analysis between Two Operational Irrigation Mapping Models over Study Sites in Mediterranean and Semi-Oceanic Regions
No full textInternational audienceAccurate information about the irrigated surface is essential to help assess the impact of irrigation on water consumption, the hydrological cycle and regional climate. In this study, we compare recently developed operational and spatially transferrable classification models proposed for irrigation mapping. The first model suggests the use of spatio-temporal soil moisture indices derived from the Sentinel-1/2 soil moisture product (S2MP) at plot scale to map irrigated areas using the unsupervised K-means clustering algorithm (Dari model). The second model called the Sentinel-1/2 Irrigation mapping (S2IM) is a classification model based on the use the Sentinel-1 (S1) and Sentinel-2 (S2) time series data. Five study cases were examined including four studied years in a semi-oceanic area in north-central France (between 2017 and 2020) and one year (2020) in a Mediterranean context in south France. Main results showed that the soil-moisture based model using K-means clustering (Dari model) performs well for irrigation mapping but remains less accurate than the S2IM model. The overall accuracy of the Dari model ranged between 72.1% and 78.4% across the five study cases. The Dari model was found to be limited over humid conditions as it fails to correctly distinguish rain-fed plots from irrigated plots with an accuracy of the rain-fed class reaching 24.2% only. The S2IM showed the best accuracy in the five study cases with an overall accuracy ranging between 72.8% and 93.0%. However, for humid climatic conditions, the S2IM had an accuracy of the rain-fed class reaching 62.0%. The S2IM is thus superior in terms of accuracy but with higher complexity for application than the Dari model that remains simple yet effective for irrigation mapping
Seed priming with calcium chloride improves the photosynthesis performance of faba bean plants subjected to cadmium stress
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