Déploiement automatique d’une application de routage téléphonique d’une langue source vers une langue cible

Les modèles de compréhension statistiques appliqués à des applications vocales nécessitent beaucoup de données pour être entraînés. Souvent, une même application doit pouvoir supporter plusieurs langues, c’est le cas avec les pays ayant plusieurs langues officielles. Il s’agit donc de gérer les mêmes requêtes des utilisateurs, lesquelles présentent une sémantique similaire, mais dans plusieurs langues différentes. Ce projet présente des techniques pour déployer automatiquement un modèle de compréhension statistique d’une langue source vers une langue cible. Ceci afin de réduire le nombre de données nécessaires ainsi que le temps relié au déploiement d’une application dans une nouvelle langue. Premièrement, une approche basée sur les techniques de traduction automatique est présentée. Ensuite une approche utilisant un espace sémantique commun pour comparer plusieurs langues a été développée. Ces deux méthodes sont comparées pour vérifier leurs limites et leurs faisabilités. L’apport de ce projet se situe dans l’amélioration d’un modèle de traduction grâce à l’ajout de données très proche de l’application ainsi que d’une nouvelle façon d’inférer un espace sémantique multilingue.

The Use of Latent Semantic Indexing to Mitigate OCR Effects of Related Document Images

Due to both the widespread and multipurpose use of document images and the current availability of a high number of document images repositories, robust information retrieval mechanisms and systems have been increasingly demanded. This paper presents an approach to support the automatic generation of relationships among document images by exploiting Latent Semantic Indexing (LSI) and Optical Character Recognition (OCR). We developed the LinkDI (Linking of Document Images) service, which extracts and indexes document images content, computes its latent semantics, and defines relationships among images as hyperlinks. LinkDI was experimented with document images repositories, and its performance was evaluated by comparing the quality of the relationships created among textual documents as well as among their respective document images. Considering those same document images, we ran further experiments in order to compare the performance of LinkDI when it exploits or not the LSI technique. Experimental results showed that LSI can mitigate the effects of usual OCR misrecognition, which reinforces the feasibility of LinkDI relating OCR output with high degradation.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

A Procedure for Semantic Querying in the Adaptive Formalism

This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

Meat Quality of Lambs Fed on Palm Kernel Meal, a By-product of Biodiesel Production

This study aimed to establish the optimum level of palm kernel meal in the diet of Santa Ines lambs based on the sensorial characteristics and fatty acid profile of the meat. We used 32 lambs with a starting age of 4 to 6 months and mean weight of 22 2.75 kg, kept in individual stalls. The animals were fed with Tifton-85 hay and a concentrate mixed with 0.0, 6.5, 13.0 or 19.5% of palm kernel meal based on the dry mass of the complete diet. These levels formed the treatments. Confinement lasted 80 days and on the last day the animals were fasted and slaughtered. After slaughter, carcasses were weighed and sectioned longitudinally, along the median line, into two antimeres. Half-carcasses were then sliced between the 12th and 13th ribs to collect the loin (longissimus dorsi), which was used to determine the sensorial characteristics and fatty acid profile of the meat. For sensorial evaluation, samples of meat were given to 54 judges who evaluated the tenderness, juiciness, appearance, aroma and flavor of the meat using a hedonic scale. Fatty acids were determined by gas chromatography. The addition of palm kernel meal to the diet had no effect on the sensorial characteristics of meat juiciness, appearance, aroma or flavor. However, tenderness showed a quadratic relationship with the addition of the meal to the diet. The concentration of fatty acids C12:0, C14:0 and C16:0 increased with the addition of palm kernel meal, as did the sum of medium-chain fatty acids and the atherogenicity index. Up to of 19.5% of the diet of Santa Ines lambs can be made up of palm kernel meal without causing significant changes in sensorial characteristics. However, the fatty acid profile of the meat was altered.

Semantic molecules

This paper explains and explores the concept of "semantic molecules" in the NSM methodology of semantic analysis. A semantic molecule is a complex lexical meaning which functions as an intermediate unit in the structure of other, more complex concepts. The paper undertakes an overview of different kinds of semantic molecule, showing how they enter into more complex meanings and how they themselves can be explicated. It shows that four levels of "nesting" of molecules within molecules are attested, and it argues that while some molecules such as 'hands' and 'make', may well be language-universal, many others are language-specific.

Ecological interface design for pasteurizer II: A process description of semantic mapping

Ecological interface design (EID) is proving to be a promising approach to the design of interfaces for complex dynamic systems. Although the principles of EID and examples of its effective use are widely available, few readily available examples exist of how the individual displays that constitute an ecological interface are developed. This paper presents the semantic mapping process within EID in the context of prior theoretical work in this area. The semantic mapping process that was used in developing an ecological interface for the Pasteurizer II microworld is outlined, and the results of an evaluation of the ecological interface against a more conventional interface are briefly presented. Subjective reports indicate features of the ecological interface that made it particularly valuable for participants. Finally, we outline the steps of an analytic process for using EID. The findings presented here can be applied in the design of ecological interfaces or of configural displays for dynamic processes.

Episodic and semantic memory in children with mesial temporal sclerosis

The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. (C) 2011 Elsevier Inc. All rights reserved.

Semantic memory impairment in temporal lobe epilepsy associated with hippociampal sclerosis

Episodic memory impairment is a well-recognized feature of mesial temporal lobe epilepsy. Semantic memory has received much less attention in this patient population. In this study, semantic memory aspects (word-picture matching, word definition, confrontation and responsive naming, and word list generation) in 19 patients with left and right temporal lobe epilepsy secondary to mesial temporal sclerosis (MTS) were compared with those of normal controls. Patients with LMTS showed impaired performance in word definition (compared to controls and RMTS) and in responsive naming (compared to controls). RMTS and LMTS patients performed worse than controls in word-picture matching. Both patients with left and right mesial temporal lobe epilepsy performed worse than controls in word list generation and in confrontation naming tests. Attentional-executive dysfunction may have contributed to these deficits. We conclude that patients with left and right NITS display impaired aspects of semantic knowledge. A better understanding of semantic processing difficulties in these patients will provide better insight into the difficulties with activities of daily living in this patient population. (C) 2007 Elsevier Inc. All rights reserved.

From medical librarian to informacionist: semantic traces of their profiles and areas of performance

This literature review retakes the discussion of the profiles and competences of the information area professional, specifically, in the health field. Therefore, the aim here is to outline the new fields of performance for the informationist and the profiles required in the health context.