Superfluid Contributions to General Turbulence Theory

We analyse a numerical solution of a mathematical model of thermal superfluid turbulence. We elaborate on key points of the statistical phenomenology and point out their impact on fundamental issues of general turbulence theory.     

Face detection and recognition of natural human emotion using Markov random fields

This paper presents an integrated system for emotion detection. In this research effort, we have taken into account the fact that emotions are most widely represented with eye and mouth expressions. The proposed system uses color images and it is consisted of three modules. The first module implements skin detection, using Markov random fields models for image segmentation and skin detection. A set of several colored images with human faces have been considered as the training set. A second module is responsible for eye and mouth detection and extraction. The specific module uses the HLV color space of the specified eye and mouth region. The third module detects the emotions pictured in the eyes and mouth, using edge detection and measuring the gradient of eyes’ and mouth’s region figure. The paper provides results from the system application, along with proposals for further research.     

A well‐conditioned and optimally convergent XFEM for 3D linear elastic fracture

A variation of the extended finite element method for three‐dimensional fracture mechanics is proposed. It utilizes a novel form of enrichment and point‐wise and integral matching of displacements of the standard and enriched elements in order to achieve higher accuracy, optimal convergence rates, and improved conditioning for two‐dimensional and three‐dimensional crack problems. A bespoke benchmark problem is introduced to determine the method's accuracy in the general three‐dimensional case where it is demonstrated that the proposed approach improves the accuracy and reduces the number of iterations required for the iterative solution of the resulting system of equations by 40% for moderately refined meshes and topological enrichment. Moreover, when a fixed enrichment volume is used, the number of iterations required grows at a rate which is reduced by a factor of 2 compared with standard extended finite element method, diminishing the number of iterations by almost one order of magnitude. Copyright © 2015 John Wiley & Sons, Ltd.     

Dietary patterns analysis using data mining method. An application to data from the CYKIDS study

Data mining is a computational method that permits the extraction of patterns from large databases. We applied the data mining approach in data from 1140 children (9-13years), in order to derive dietary habits related to children's obesity status. Rules emerged via data mining approach revealed the detrimental influence of the increased consumption of soft dinks, delicatessen meat, sweets, fried and junk food. For example, frequent (3-5times/week) consumption of all these foods increases the risk for being obese by 75%, whereas in children who have a similar dietary pattern, but eat >2times/week fish and seafood the risk for obesity is reduced by 33%. In conclusion patterns revealed from data mining technique refer to specific groups of children and demonstrate the effect on the risk associated with obesity status when a single dietary habit might be modified. Thus, a more individualized approach when translating public health messages could be achieved.     

Minimum Moment Method for Resource Leveling Using Entropy Maximization

The minimum moment method for resource leveling is revisited and restated as an entropy-maximization problem. The minimum moment method assumes that the moment of the daily resource demands about the horizontal axis of a project’s resource histogram is a good measure of the resource utilization and that the optimal resource allocation exists when the total moment is at a minimum, thus when the resource histogram is of rectangular shape. The entropy-maximization method proposed in this paper makes use of the general theory of entropy and two of its principal properties (subadditivity and maximality) to revisit the minimum moment method for resource leveling. The entropy-maximization method presented allows for activity stretching and provides resource allocation solutions that show improvement over previous approaches. A case study is also presented that validates the results.     

Excimer laser processing of inkjet-printed and sputter-deposited transparent conducting SnO2:Sb for flexible electronics

The feasibility of low-temperature fabrication of transparent electrode elements from thin films of antimony-doped tin oxide (SnO₂:Sb, ATO) has been investigated via inkjet printing, rf magnetron sputtering and post-deposition excimer laser processing. Laser processing of thin films on both glass and plastic substrates was performed using a Lambda Physik 305i excimer laser, with fluences in the range 20-100 mJ cm^− 2 reducing sheet resistance from as-deposited values by up to 3 orders of magnitude. This is consistent with TEM analysis of the films that shows a densification of the upper 200 nm of laser-processed regions.     

Dynamic provisioning of low-speed unicast/multicast traffic demands in mesh-based WDM optical networks

This paper addresses the problem of dynamically provisioning both low-speed unicast and multicast connection requests in mesh-based wavelength division multiplexing (WDM) optical networks. Several routing/provisioning schemes to dynamically provision both unicast and multicast connection requests are presented. In addition, a constraint-based grooming strategy is devised to utilize the overall network resources as efficiently as possible. Based on this strategy, several different sequential multicast grooming heuristics are first presented. Then, we devise a hybrid grooming approach and combine it with sequential approaches to achieve a grooming scheme that is biased toward serving multicast traffic demands in comparison with all other sequential grooming approaches. To achieve our objective, we decompose the problem into four subproblems: 1) routing problem; 2) light-tree-based logical-topology-design problem; 3) provisioning problem; and 4) traffic-grooming problem. The simulation results of the proposed schemes are compared with each other and with those of conventional nongrooming approaches. To the best of our knowledge, this is the first detailed paper to address and examine the problem of grooming dynamic multicast traffic demands.