On finite dynamic equations for fluid-saturated porous media

Summary The paper concerns the relations between two principally different approaches to the formulation of momentum balance equations in porous media theories, namely, the dynamic approach similar to Biot's theory and the modern approach as a result of mixture theories extended by the concept of volume fractions. In particular, it is shown that both approaches necessarily lead to the same type of momentum balance equations and furthermore contain, in a certain sense, within the geometrically linear case, the well-known classical equations of Biot's theory.     

Electromagnetic field diffusion, θ-functions,and image solutions

Contents We discuss some initial and boundary value problems of one-dimensional electromagnetic field diffusion. The solutions can be given by infinite series in two essentially different (however equivalent) forms, one being the usual Fourier-expansion and the other one being an infinite series of Gaussian exponentials or related functions (as for instance error-functions). The second form can be obtained by using infinitely many images to fulfill initial and boundary conditions. Finally the mathematical relations between the two equivalent types of solutions are discussed in terms of -functions and their transformation properties. The existence of the solutions in these two different forms is very interesting from a numerical point of view also.

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Die Diffusion elektromagnetischer Felder, -Funktionen und Spiegelungsmethoden

Übersicht Es werden einige Anfangs- und Randwertprobleme eindimensionaler elektromagnetischer Felddiffusion erörtert. Die Lösungen können in zwei wesentlich verschiedenen (jedoch gleichwertigen) Formen angegeben werden, erstens in Form üblicher Fourier-Reihen und zweitens in Form unendlicher Reihen von Gaußschen Exponentialfunktionen oder damit verwandter Funktionen (z.B. Fehlerfunktionen). Diese zweite Form der Lösungen läßt sich durch die Anwendung unendlich oft wiederholter Spiegelung zur Erfüllung der Rand- und Anfangsbedingung anschaulich interpretieren. Abschließend werden die beiden Lösungstypen mit Hilfe von -Funktionen und deren Transformationseigenschaften erläutert. Die Verfügbarkeit der Lösungen in beiden Formen ist auch numerisch sehr interessant.

     

An Automated Brain Image Analysis System for Brain Cancer using Shearlets

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification of MRI images into normal or low grade or high grade plays a vital role for the early diagnosis. The Non-Subsampled Shearlet Transform (NSST) that captures more visual information than conventional wavelet transforms is employed for feature extraction. As the feature space of NSST is very high, a statistical t-test is applied to select the dominant directional sub-bands at each level of NSST decomposition based on sub-band energies. A combination of features that includes Gray Level Co-occurrence Matrix (GLCM) based features, Histograms of Positive Shearlet Coefficients (HPSC), and Histograms of Negative Shearlet Coefficients (HNSC) are estimated. The combined feature set is utilized in the classification phase where a hybrid approach is designed with three classifiers; k-Nearest Neighbor (kNN), Naive Bayes (NB) and Support Vector Machine (SVM) classifiers. The output of individual trained classifiers for a testing input is hybridized to take a final decision. The quantitative results of ABIA system on Repository of Molecular Brain Neoplasia Data (REMBRANDT) database show the overall improved performance in comparison with a single classifier model with accuracy of 99% for normal/abnormal classification and 98% for low and high risk classification.     

Communication across Viewpoints

A case situation arising in a normal interaction among people is the baseline for discussing properties of the theory of viewpoints. In particular we consider how to ensure agreement on the meaning of certain utterances by agents who have different perspectives on the situation, while maintaning other knowledge as private. We argue that communication should be modeled as adding facts to the common knowledge of agents. We introduce the principle of 'referent sharing' in communications and argue that common knowledge resulting from communication should only use constants whose referent is manifest to the parties involved.     

Large deformation measurement by holographic interferometry

Summary The use of holographic interferometry for the measurement of large deformations is described. From the nature of holographic interferometry it is evident that large deformations exceed the wave length of the light source used by at least ten times of this size. To obtain holographically identifiable values of large deformations, a method of successive partial lighting is used. It shows how it is possible to keep all the advantages of the holographic method and use it even under conditions which apparently exceed its possibilities of application.     

Repeated auctions for robust task execution by a robot team

We present empirical results of an auction-based algorithm for dynamic allocation of tasks to robots. The results have been obtained both in simulation and using real robots. A distinctive feature of our algorithm is its robustness to uncertainties and to robot malfunctions that happen during task execution, when unexpected obstacles, loss of communication, and other delays may prevent a robot from completing its allocated tasks. Therefore tasks not yet achieved are resubmitted for bids every time a task has been completed. This provides an opportunity to improve the allocation of the remaining tasks, enabling the robots to recover from failures and reducing the overall time for task completion.     

Filling gaps in diameter measurements on standing tree boles in the urban forest of Thessaloniki,Greece

Missing data are omnipresent in forestry research, and this poses problems in the analysis of primary data. Many statistical problems have been viewed as missing data problems. To cope with incomplete data, several methods are currently being used. They are all based on assumptions some of which might not be valid in a particular case. The choice mostly depends on the objective of the study. Considerable mensuration research is motivated by the need for yield projections that can support forest management decisions. This paper is focused on a new approach for filling gaps in diameter measurements on standing tree boles. Dealing with this problem, an attempt was made to examine the applicability of artificial neural network models for missing data estimation and to use the estimated values in the subsequent analysis. The procedure that should be followed in the development of such models is outlined. The results show good performance of the examined ANN models compared to regression treatments for missing data and ANN models demonstrate their adequacy and potential for filling gaps in diameter measurements on standing tree boles. The ANN models applied in this study are sufficiently general and have great potential to be applicable for estimating the missing values of many variables in environmental applications.     

A numerical modelling for the extraction of decay regions from color images of monuments

An innovative application focused on the segmentation of decay zones from images of stone materials is presented. The adopted numerical approach to extract decay regions from the color images of monuments provides a tool that helps experts analyze degraded regions by contouring them. In this way even if the results of the proposed procedure depend on the evaluation of experts, the approach can be a contribution to improving the efficiency of the boundary detection process. The segmentation is a process that allows an image to be divided into disjoint zones so that partitioned zones contain homogeneous characteristics. The numerical method, used to segment color images, is based on the theory of interface evolution, which is described by the eikonal equation. We adopted the fast marching technique to solve the upwind finite difference approximation of the eikonal equation. The fast marching starts from a seed point in the region of interest and generates a front which evolves according to a specific speed function until the boundary of the region is identified. We describe the segmentation results obtained with two speed functions, attained by the image gradient computation and color information about the object of interest. Moreover, we present the extension of the working modality of the method by introducing the possibility to extract the regions not only in a local way but also in a global way on the entire image. In this case, in order to improve the segmentation efficiency the application of the fast marching technique starts with more seed points defined as seed regions. The study case concerns the impressive remains of the Roman Theatre in the city of Aosta (Italy). In the image segmentation process the color space L^∗a^∗b^∗$L^{\ast }{a}^{\ast }{b}^{\ast }$ is utilized.