A pratical implementation of deep neural network for facial emotion recognition

People's emotions are rarely put into words, far more often they are expressed through other cues. The key to intuiting another's feelings is in the ability to read nonverbal channels, tone of voice, gesture, facial expression and the like. Facial expressions are used by humans to convey various types of meaning in a variety of contexts. The range of meanings extends from basic, probably innate, social-emotional concepts such as "surprise" to complex, culture-specific concepts such as "neglect". The range of contexts in which humans use facial expressions extends from responses to events in the environment to specific linguistic constructs in sign languages. In this paper, we will use an artificial neural network to classify each image into seven facial emotion classes. The model is trained on a database of FER+ images that we assume is large and diverse enough to indicate which model parameters are generally preferable. The overall results show that, the CNN model is efficient to be able to classify the images according to the state of emotions even in real time

Circular dielectric cavity and its deformations

The construction of perturbation series for slightly deformed dielectric circular cavity is discussed in details. The obtained formulae are checked on the example of cut disks. A good agreement is found with direct numerical simulations and far-field experiments.Comment: 17 pages, 12 figure

Un système data mining en ligne pour la maintenance ontologique d'une mémoire corporative DM

L'intégration de la connaissance dans la mémoire corporative (Ribière et Matta, 1998), (Dieng et al., 1998) fait face à l'hétérogénéité des données (Visser, Jones et al., 1997). L'utilisation de l'ontologie est une approche possible pour surmonter ce problème. Cependant, l'ontologie est une structure de donnée comme n'importe quelle structure informatique, elle est donc dynamique et évolue dans le temps à cause des conditions dynamiques résultant des changements du domaine conceptuel, les changements de conceptualisation, les changements de spécification, les changements descendants, etc. (Yildiz, 2006). Ces dernières années, plusieurs approches ont été proposées pour résoudre le problème de la maintenance des ontologies. Cependant, la précision et le rappel ne permettent pas de satisfaire les besoins des utilisateurs. De plus, ces approches ne prennent pas en compte toute l'information disponible pour prendre une décision réaliste. Pour résoudre le problème de l'évolution de la connaissance dans les ontologies, nous proposons une approche hybride qui utilise l'apprentissage machine et un processus d'alignement qui contrôle les relations syntaxiques entre les entrées dans l'ontologie. De plus, des règles structurelles et des heuristiques sont appliquées pour améliorer le degré de similitude entre les entités ontologiques. Ce processus hybride crée des règles de correspondance qui définissent comment transformer les entrées dans l'ontologie en définissant tous les types d'associations possibles entre les entités ontologiques. L'approche d'enrichissement de l'ontologie exploite les techniques de la fouille de données, les techniques du traitement automatique du langage naturel et la recherche d'information pour améliorer la performance d'apprentissage durant la tâche d'enrichissement du domaine conceptuel. L'évaluation des ontologies demeure un problème important et le choix d'une approche appropriée dépend des critères utilisés. Dans notre approche, nous adoptons la vérification de la cohérence décrite dans (Maziar Amirhosseini et al., 2011) et (Abderrazak et al., 2011).\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Data Mining, Traitement automatique du langage naturel, Apprentissage machine, Recherche d'information, Intégration, Ontologie, Mémoire corporative, Web sémantique

Wastewater Assessment and Biochemical Oxygen Demand Value Prediction from Mining Operations: A Case Study

Wastewater is a byproduct of industrial or household waste processes, and its contamination level must be determined before treatment. Discharges of liquid effluents generated by mining operations, one of the most prevalent forms of industrial waste water, pose a risk to human health and the environment. This study evaluates the physicochemical quality of industrial liquid effluent discharges from the Boukhadra mine (Algeria). Samples were collected from the washing water to identify the level of contamination of these liquid discharges and to measure physicochemical parameters such as temperature (T), hydrogen potential (pH), Electrical Conductivity (EC), Suspended Solids (SS), Chemical Oxygen Demand (COD), Biological Oxygen Demand for 5 days (BOD5), Oils and Greases (O&G), iron (Fe+2) and Kjeldahl Nitrogen (NTK). It was found that the concentration values of those effluents exceeded the maximum contamination limits specified by international industrial waste standards. A simple and reliable prediction model was developed to estimate DBO5, based on MES, COD, and O&G, by using classical regression analysis and fitting Design of Experiments (DOE) methodology. When comparing the analytical results, it was found that the quadratic model provided a better estimation, with a high correlation coefficient (R2) of 0.9976. The parameters determined in this study will enable engineers to quickly estimate the degree of wastewater contamination and choose adequate treatment strategies

Gain properties of dye-doped polymer thin films

Hybrid pumping appears as a promising compromise in order to reach the much coveted goal of an electrically pumped organic laser. In such configuration the organic material is optically pumped by an electrically pumped inorganic device on chip. This engineering solution requires therefore an optimization of the organic gain medium under optical pumping. Here, we report a detailed study of the gain features of dye-doped polymer thin films. In particular we introduce the gain efficiency $K$, in order to facilitate comparison between different materials and experimental conditions. The gain efficiency was measured with various setups (pump-probe amplification, variable stripe length method, laser thresholds) in order to study several factors which modify the actual gain of a layer, namely the confinement factor, the pump polarization, the molecular anisotropy, and the re-absorption. For instance, for a 600 nm thick 5 wt\% DCM doped PMMA layer, the different experimental approaches give a consistent value $K\simeq$ 80 cm.MW$^{-1}$. On the contrary, the usual model predicting the gain from the characteristics of the material leads to an overestimation by two orders of magnitude, which raises a serious problem in the design of actual devices. In this context, we demonstrate the feasibility to infer the gain efficiency from the laser threshold of well-calibrated devices. Besides, temporal measurements at the picosecond scale were carried out to support the analysis.Comment: 15 pages, 17 figure

Inferring periodic orbits from spectra of simple shaped micro-lasers

Dielectric micro-cavities are widely used as laser resonators and characterizations of their spectra are of interest for various applications. We experimentally investigate micro-lasers of simple shapes (Fabry-Perot, square, pentagon, and disk). Their lasing spectra consist mainly of almost equidistant peaks and the distance between peaks reveals the length of a quantized periodic orbit. To measure this length with a good precision, it is necessary to take into account different sources of refractive index dispersion. Our experimental and numerical results agree with the superscar model describing the formation of long-lived states in polygonal cavities. The limitations of the two-dimensional approximation are briefly discussed in connection with micro-disks.Comment: 13 pages, 19 figures, accepted for publication in Physical Review

Trace formula for dielectric cavities II: Regular, pseudo-integrable, and chaotic examples

Dielectric resonators are open systems particularly interesting due to their wide range of applications in optics and photonics. In a recent paper [PRE, vol. 78, 056202 (2008)] the trace formula for both the smooth and the oscillating parts of the resonance density was proposed and checked for the circular cavity. The present paper deals with numerous shapes which would be integrable (square, rectangle, and ellipse), pseudo-integrable (pentagon) and chaotic (stadium), if the cavities were closed (billiard case). A good agreement is found between the theoretical predictions, the numerical simulations, and experiments based on organic micro-lasers.Comment: 18 pages, 32 figure