Influence of copolymer composition on non-fickian water transport through glassy copolymers

The dynamic swelling behavior of poly(2-hydroxyethyl methacrylate-co-methyl methacrylate) and poly(2-hydroxyethyl methacrylate-co-N-vinyl-2-pyrrolidone) in water was followed at 37°C. The results were analyzed in terms of a simple non-Fickian transport equation, which expresses the fractional penetrant uptake as an exponential function of the diffusion time. The exponent n, which indicates Fickian or non-Fickian transport mechanism, was correlated to the content of the more hydrophilic component of the copolymer. Photomicrographs obtained with polarized light offer new information about the position and movement of the penetrant front in glassy, hydrophilic polymers.     

Hand dexterity assessment based on mouse pointer trajectory measurements in children with learning disabilities

Universal Access in the Information Society - We present an investigation of the systematic differences in upper limb motor skills between children with learning disabilities (LDs) and children...     

Worker Exposure Monitoring of Suspended Particles in a Thermal Spray Industry

The purpose of the present work was the investigation and characterization of the quality of air in a thermal spray industry, in Greece. The activities that take place in the specific facility, as well as in most other similar industries, include thermal spraying and several mechanical and metallurgical tasks that generate airborne particles, such as grit-blasting, cutting and grinding of metallic components. Since the main focus of this work was the workers exposure to airborne particles and heavy metals, portable air samplers with quartz fiber filters, were used daily for 8 h. Three samplers, carried from different employees, were used for a period of 1 month. Results showed that both particles and heavy metals concentrations were low, even in the production site, which was the most susceptible area. The only exceptions were observed in the case of cleaning and maintenance activities in the thermal spray booth and in the case of spraying outside the booth. The main reason for the low concentrations is the fact that most of the activities that could produce high-particle concentrations are conducted in closed, well-ventilated systems. Statistical elaboration of results showed that particles are correlated with Ni, Cu, Co. The same conclusion is extracted for Fe, Mn. These correlations indicate possible common sources.     

3D measures exploitation for a monocular semi-supervised fall detection system

Falls have been reported as the leading cause of injury-related visits to emergency departments and the primary etiology of accidental deaths in elderly. Thus, the development of robust home surveillance systems is of great importance. In this article, such a system is presented, which tries to address the fall detection problem through visual cues. The proposed methodology utilizes a fast, real-time background subtraction algorithm, based on motion information in the scene and pixels intensity, capable to operate properly in dynamically changing visual conditions, in order to detect the foreground object. At the same time, it exploits 3D space’s measures, through automatic camera calibration, to increase the robustness of fall detection algorithm which is based on semi-supervised learning approach. The above system uses a single monocular camera and is characterized by minimal computational cost and memory requirements that make it suitable for real-time large scale implementations.     

Approximate variational inference based on a finite sample of Gaussian latent variables

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.     

Dynamic disturbance rejection controllers for neutral time delay systems with application to a central heating system

In the present paper the problem of disturbance rejection of single input-single output neutral time delay systems with multiple measurable disturbances is solved via dynamic controllers. In particular, the general form of the controller matrices is presented, while the necessary and sufficient conditions for the controller to be realizable are offered. The proposed technique is applied to a test case neutral time delay central heating system. In particular, the nonlinear model of the plant and its linearized approximation are presented. Based on the linearized model, a two-stage controller is designed in order to regulate the room temperature and the boiler effluent temperature. The performance of the closed loop system is investigated through computational experiments.     

Segmentation of historical machine-printed documents using Adaptive Run Length Smoothing and skeleton segmentation paths

In this paper, we strive towards the development of efficient techniques in order to segment document pages resulting from the digitization of historical machine-printed sources. This kind of documents often suffer from low quality and local skew, several degradations due to the old printing matrix quality or ink diffusion, and exhibit complex and dense layout. To face these problems, we introduce the following innovative aspects: (i) use of a novel Adaptive Run Length Smoothing Algorithm (ARLSA) in order to face the problem of complex and dense document layout, (ii) detection of noisy areas and punctuation marks that are usual in historical machine-printed documents, (iii) detection of possible obstacles formed from background areas in order to separate neighboring text columns or text lines, and (iv) use of skeleton segmentation paths in order to isolate possible connected characters. Comparative experiments using several historical machine-printed documents prove the efficiency of the proposed technique.     

Spatially Varying Mixtures Incorporating Line Processes for Image Segmentation

Spatially varying mixture models are characterized by the dependence of their mixing proportions on location (contextual mixing proportions) and they have been widely used in image segmentation. In this work, Gauss-Markov random field (MRF) priors are employed along with spatially varying mixture models to ensure the preservation of region boundaries in image segmentation. To preserve region boundaries, two distinct models for a line process involved in the MRF prior are proposed. The first model considers edge preservation by imposing a Bernoulli prior on the normally distributed local differences of the contextual mixing proportions. It is a discrete line process model whose parameters are computed by variational inference. The second model imposes Gamma prior on the Student’s-t distributed local differences of the contextual mixing proportions. It is a continuous line process whose parameters are also automatically estimated by the Expectation-Maximization (EM) algorithm. The proposed models are numerically evaluated and two important issues in image segmentation by mixture models are also investigated and discussed: the constraints to be imposed on the contextual mixing proportions to be probability vectors and the MRF optimization strategy in the frameworks of the standard and variational EM algorithm.