Väsimusmurdude preventsioon maratonijooksjatel

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Slip-length measurement of confined air flow using dynamic atomic force microscopy

We present an experimental measurement of the slip length of air flow close to solid surfaces using an atomic force microscope (AFM) in dynamic mode. The air was confined between a glass surface and a spherical glass particle glued to an AFM cantilever. The Knudsen number was varied continuously over three decades by varying the distance between the two surfaces. Our results show that the effect of confining the air is purely dissipative. The data are described by an isothermal Maxwell slip-boundary condition, and the measured slip-length value was 118 nm

Une étude comparée de l’utilisation des emprunts et de leurs équivalents arabes dans la terminologie des réseaux sociaux

Cette étude cherche à relever l’usage réel des emprunts dans la terminologie des réseaux sociaux et de leurs doublets concurrents autochtones auprès des usagers arabophones et ceci en fonction de la fréquence attestée dans un corpus de presse. Ce corpus nous a permis de repérer les équivalents autochtones des emprunts choisis qui ont été par la suite attestés dans un corpus d’exclusion de dictionnaires bilingues spécialisés en informatique et de bases de données spécialisées comme la base de données de l’ONU, UNTERM. L’analyse terminologique de la langue de spécialité permet de suivre l’évolution d’une langue comme l’arabe et de relever l’effet de son contact avec les autres langues. Les constats linguistiques de l’étude ont souligné le recours à l’emprunt comme procédé de création néologique en arabe avec ses variantes : littéral et dialectal. Ceci s’explique par le fait que les académies de langue arabe accusent un certain retard quant à la normalisation.This study tries to determine the real use of the loanwords in the terminology of social networks and of their native rival doublets for the Arabic-speaking users and this according to the frequency attested in a corpus of press. This corpus allowed us to locate the native equivalents of the loans loanwords chosen which were afterward then been attested searched in a corpus of exclusion which made up with bilingual dictionaries specialized in computing and from databases such as the UN database UNTERM. The terminological analysis of the specialized language allows to follow the evolution of a language such as Arabic and to raise find the effect of its contacts with the other languages. This study shows that the loan borrowing is a process of neological creation in Arabic with its variants: literal and dialectal Arabic.Le présent ouvrage est financé par le CNRS (projet PICS – franco-polonais EmpNeo) et par l’Institut d’Études Romanes de l’Université de Łód

An automatic sleep apnea analysis with soft computing approaches

University of Technology, Sydney. Faculty of Engineering and Information Technology.Sleep Apnea (SA) is a common disorder without “age-specific” that affects approximately 2% of women and 4% of men; sleep apnea is characterized by repetitive cessation of breathing during sleep. The consequences of the sleep apnea include daytime sleepiness, impaired cognitive function, impaired memory, neurocognitive dysfunction, and development of cardiovascular disorders, metabolic dysfunction, and impaired quality of life. This thesis investigates the automated detection and prediction of sleep apnea. Many researchers have concentrated on automated detection of sleep apnea, but not much comprehensive or well-ordered work has been done on signal and feature selection or on predicting of the sleep apnea. The objective is to find the best set of signals as input and the best set of features from selected signals that can be used by a machine learning approaches to study sleep apnea. The best set here is not only refers to a smallest set of signals with a good performance in sleep apnea analysis but also consideration for a set of signals that can be easily acquired from patients. During the course of this thesis, several algorithms were developed. These algorithms can be used in sleep apnea studies or in wider machine learning areas. The most important contributions of this thesis can be summarized as below: -Developing a new signal segmentation algorithm designed specifically for sleep apnea by attention to its properties. This algorithm chose times windows with a greater probability of containing at least one sleep apnea event. After that these segmentations are generated, they should be reviewed by the machine learning approaches to be classified as sleep apnea or normal. -Developing a novel Support Vector Machine (SVM)-based approach named Self-Advising Support Vector Machine (SA-SVM) that transfers more knowledge from the training phase of SVM to the test phase. This idea helps SVM to learn from misclassified data in training phase and use this gained knowledge, in the testing phase. This approach can be used in any binary classification problems and it shows also high impact in sleep apnea detection. -Developing a new parallel structure for Particle Swarm Optimisation (PSO). Finding the best set of input signals or the best set of features required a huge amount of computation power which a single PSO – or other optimisation approaches- cannot deal with, so a new hierarchical multi-master structure for parallel PSO was developed in this thesis, which quickly revealed its advantages over previous parallel PSO structures. In this thesis real data has been used from Concord Repatriation General Hospital in Sydney. Obtained result shows a good performance in detection and classification of sleep apnea. Together with detection and classification, a prediction of sleep apnea was also considered. The prediction stage examines some famous neural networks structures and demonstrated how to improve the final result by taking advantage of multi neural network approach

Does corporate governance affect financial communication transparency? Empirical evidence in the Tunisian context

The present study is focused on investigating the relationship between intentional governance mechanisms (Directors' boards, Ownership structure and audit quality) and financial communication transparency. For this purpose, a model is used and applied to Tunisian firms' sample observed over the period 2006-2013. The achieved results reveal that intentional governance mechanisms are positively related to a higher transparency level noticeable in financial communication (voluntary disclosure and quality information). In addition, empirical tests indicate that financial communication transparency is highly dependent on the board size, ownership concentration, as well as on audit quality

Index finger motion recognition using self-advise support vector machine

Because of the functionality of an index finger, the disability of its motion in the modern age can decrease the person's quality of life. As a part of rehabilitation therapy, the recognition of the index finger motion for rehabilitation purposes should be done properly. This paper proposes a novel recognition system of the index finger motion suing a cutting-edge method and its improvements. The proposed system consists of combination of feature extraction method, a dimensionality reduction and well-known classifier, Support Vector Machine (SVM). An improvement of SVM, Self-advise SVM (SA-SVM), is tested to evaluate and compare its performance with the original one. The experimental result shows that SA-SVM improves the classification performance by on average 0.63 %

A geometrical sink-based cooperative coverage hole recovery strategy for WSNs

© 2015 IEEE. Unlike sporadic node failures, coverage holes emerging from multiple temporally-correlated node failures can severely affect quality of service in a network and put the integrity of entire wireless sensor networks at risk. Conventional topology control schemes addressing such undesirable topological changes have usually overlooked the status of participating nodes in the recovery process with respect to the deployed sink node(s) in the network. In this paper, a cooperative coverage hole recovery model is proposed which utilises the simple geometrical procedure of circle inversion. In this model, autonomous nodes consider their distances to the deployed sink node(s) in addition to their local status, while relocating towards the coverage holes. By defining suitable metrics, the performance of our proposed model performance is compared with a force-based approach

Change in drag, apparent slip and optimum air layer thickness for laminar flow over an idealised superhydrophobic surface

Analytic results are derived for the apparent slip length, the change in drag and the optimum air layer thickness of laminar channel and pipe flow over an idealised superhydrophobic surface, i.e. a gas layer of constant thickness retained on a wall. For a simple Couette flow the gas layer always has a drag reducing effect, and the apparent slip length is positive, assuming that there is a favourable viscosity contrast between liquid and gas. In pressure-driven pipe and channel flow blockage limits the drag reduction caused by the lubricating effects of the gas layer; thus an optimum gas layer thickness can be derived. The values for the change in drag and the apparent slip length are strongly affected by the assumptions made for the flow in the gas phase. The standard assumptions of a constant shear rate in the gas layer or an equal pressure gradient in the gas layer and liquid layer give considerably higher values for the drag reduction and the apparent slip length than an alternative assumption of a vanishing mass flow rate in the gas layer. Similarly, a minimum viscosity contrast of four must be exceeded to achieve drag reduction under the zero mass flow rate assumption whereas the drag can be reduced for a viscosity contrast greater than unity under the conventional assumptions. Thus, traditional formulae from lubrication theory lead to an overestimation of the optimum slip length and drag reduction when applied to superhydrophobic surfaces, where the gas is trapped