Time-dependent effects of indoor lighting on well-being and academic performance

Our knowledge of how changes in environmental lighting conditions affect non-visual processes in humans is less than adequate and based mainly on cross-sectional laboratory studies. Thus, the present research was designed to address the questions raised by the literature and clarify the non-visual effects of indoor lighting by carrying out two field studies at two different latitudes. During the period between the 8th of October 2008 and 10th of June 2009, the first field study was conducted in four similar classrooms of a junior school in Kent, U.K. The classrooms differed in the provision of artificial illumination and daylight. The study population consisted of fifty-six, fourth-grade students, aged between eight and nine years. Throughout the study, five main and five supplementary data collections were executed at approximately four-week intervals to assess participants’ sleep quality, mood and sleepiness by administering self-reports and also their diurnal melatonin and cortisol concentrations by collecting saliva samples. Additionally, data regarding participants’ performance on school examinations were collected to evaluate academic achievement. The results of the study revealed that natural light itself might be a potent factor in promoting the non-visual effects. Therefore, the second field study was conducted during the period between the 5th of January 2011 and 20th of January 2011 to verify the findings. The study was conducted in two similar classrooms of a junior school in Ankara, Turkey. The classrooms differed only in the provision of daylight. The study population consisted of seventy-nine, third-grade students, aged between eight and nine years. Throughout the study, two data collections were executed to assess participants’ sleep quality, mood and sleepiness by administering self-reports. Additionally, data regarding participants’ performance on school examinations were collected to assess academic progress. The second field study confirmed the findings form the previous field work. The participants who were exposed to more natural light at eye level reported significantly less daytime sleepiness and better sleep quality and overall mood. Moreover, their scholastic performance was comparatively better. Complementary information on the physiological, psychological and cognitive effects of indoor lighting that can be linked to our biophilic tendencies and Environment of Evolutionary Adaptedness is provided by the results of the two field studies

Extraction d'information, amélioration du SNR et compression des données dans les images SAR multifréquences multipolarisées

Une méthode statistique permettant d'obtenir une nouvelle représentation optimale des images SAR multifréquences multipolarisées est proposée. La méthode est inspirée de l'analyse en composantes principales à bruit additif ajusté (NAPC) et de la théorie de diagonalisation simultanée de deux matrices symétriques par une seule matrice. Un nombre restreint des nouvelles images transformées décrivant fidèlement les données image SAR originales avec un rapport signal sur bruit amélioré sont alors retenues. Le développement théorique ainsi que la mise en oeuvre de la méthode en question, avec les résultats obtenus sur des images SAR réelles des capteurs radar du système SIR-C, font l'objet de ce présent article

Dwell time optimization in switching control of parameter varying time delay systems

It has been shown that parameter varying systems with time delays can be robustly stabilized by switching control, provided that the plant's parameter varies slowly enough such that the dwell time conditions of the switched controllers can be satisfied. In this paper, the minimization of dwell time is considered, where an iterative search algorithm is developed from the singular value perspectives. The local minimal dwell time obtained in this paper can be used to estimate the upper bound on how fast the plant's parameters can vary. Meanwhile, the switching controller synthesis with optimal dwell time is also discussed, where robust stabilizer design algorithm is presented to achieve robust stability at certain operating range, as well as the local minimal dwell time for controller switching. A numerical example is given to illustrate the proposed algorithm. © 2011 IEEE

Restauration d'images SAR-ERS-1 par une méthode multi-échelle

Le problème de filtrage du bruit de type "speckle" a soulevé l'intérêt de plusieurs chercheurs. L'approche multirésolution a notamment permis d'améliorer les performances des filtres. Cet article introduit une nouvelle technique de filtrage du "speckle", dite "puzzle" qui est adaptative, efficace, simple à implanter et qui ne nécessite ni information sur le bruit ou l'image, ni une détermination de seuils. La méthode consiste à chercher en tout point représentatif de l'image, la version filtrée la plus adéquate prise à partir d'une représentation multi-échelle complète. Les tests effectués sur des images SAR ERS-1 ont donné des résultats dont l'évaluation quantitative et qualitative apparaît satisfaisante

Fusion de classifieurs en utilisant la théorie de l'évidence pour l'amélioration de la classification d'image

Le problème traité dans cet article concerne l'amélioration de la classification d'image dans les conditions d'insuffisance d'informations a priori déterministes et fiables sur l'état et la nature de la formation de l'image à l'instant de la prise de vue. Une méthode de fusion des classifieurs d'imagerie pour une meilleure classification des scènes imagées est proposée. La méthode est basée sur la théorie de l'évidence. Elle est générale et applicable à tout type de classifieur. On utilise le taux de fiabilité de la classification comme critère d'évaluation, les résultats obtenus, en utilisant des images simulées et réelles de télédétection, montrent que la méthode proposée donne de meilleurs résultats en comparaison avec les résultats des classifieurs considérés séparément

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability – identified with either hemodynamic or electrophysiological methods – reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ± 3 years, N = 135) and older (67 ± 4 years, N = 54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1–12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15–25 Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex

Approches neuronales pour l'extraction des composantes principales d'images multispectrales de télédétection

Le problème traité dans le présent article consiste en l'extraction des composantes principales les plus significatives d'images multispectrales de télédétection sans avoir à calculer la matrice de covariance des images spectrales. L'originalité du travail réside dans l'élaboration des algorithmes d'apprentissage spécifiques pour deux approches neuronales d'Analyse en Composantes Principales (ACP). Les deux approches possèdent des convergences rapides. L'application sur une image multispectrale réelle a montré leur efficacité dans l'extraction des composantes principales les plus significatives. The problem addressed in the présent paper is the most significant principal components extraction of remotely sensed multispectral images without having to calculate the covariance matrix of spectral images. The originality of the work resides in the elaboration of specific training algorithms for two neural network-based approaches of Principal Component Analysis (PCA). The convergence of a proposed approaches are rapid. The application on a real multispectral image has shown their efficiency in the extraction of the most significant principal components