986 resultados para entropy measure-valued solutions


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Tin-containing fluoride solutions can reduce erosive tissue loss, but the effects of the reaction between tin and enamel are still not clear. During a 10-d period, enamel specimens were cyclically demineralized (0.05 M citric acid, pH 2.3, 6 x 5 min d(-1)) and remineralized (between the demineralization cycles and overnight). In the negative-control group, no further treatment was performed. Three groups were treated (2 x 2 min d(-1)) with tin-containing fluoride solutions (400, 1,400 or 2,100 ppm Sn2+, all 1,500 ppm F-, pH 4.5). Three additional groups were treated with test solutions twice daily, but without demineralization. Tissue loss was determined profilometrically. Energy-dispersive X-ray spectroscopy was used to measure the tin content on and within three layers (10 mum each) beneath the surface. In addition, scanning electron microscopy was conducted. All test preparations significantly reduced tissue loss. Deposition of tin on surfaces was higher without erosion than with erosion, but no incorporation of tin into enamel was found without demineralization. Under erosive conditions, both highly concentrated solutions led to the incorporation of tin up to a depth of 20 mum; the less-concentrated solution led to small amounts of tin in the outer 10 mum. The efficacy of tin-containing solutions seems to depend mainly on the incorporation of tin into enamel.

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A novel time integration scheme is presented for the numerical solution of the dynamics of discrete systems consisting of point masses and thermo-visco-elastic springs. Even considering fully coupled constitutive laws for the elements, the obtained solutions strictly preserve the two laws of thermo dynamics and the symmetries of the continuum evolution equations. Moreover, the unconditional control over the energy and the entropy growth have the effect of stabilizing the numerical solution, allowing the use of larger time steps than those suitable for comparable implicit algorithms. Proofs for these claims are provided in the article as well as numerical examples that illustrate the performance of the method.

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This paper studies feature subset selection in classification using a multiobjective estimation of distribution algorithm. We consider six functions, namely area under ROC curve, sensitivity, specificity, precision, F1 measure and Brier score, for evaluation of feature subsets and as the objectives of the problem. One of the characteristics of these objective functions is the existence of noise in their values that should be appropriately handled during optimization. Our proposed algorithm consists of two major techniques which are specially designed for the feature subset selection problem. The first one is a solution ranking method based on interval values to handle the noise in the objectives of this problem. The second one is a model estimation method for learning a joint probabilistic model of objectives and variables which is used to generate new solutions and advance through the search space. To simplify model estimation, l1 regularized regression is used to select a subset of problem variables before model learning. The proposed algorithm is compared with a well-known ranking method for interval-valued objectives and a standard multiobjective genetic algorithm. Particularly, the effects of the two new techniques are experimentally investigated. The experimental results show that the proposed algorithm is able to obtain comparable or better performance on the tested datasets.

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We introduce an easily computable topological measure which locates the effective crossover between segregation and integration in a modular network. Segregation corresponds to the degree of network modularity, while integration is expressed in terms of the algebraic connectivity of an associated hypergraph. The rigorous treatment of the simplified case of cliques of equal size that are gradually rewired until they become completely merged, allows us to show that this topological crossover can be made to coincide with a dynamical crossover from cluster to global synchronization of a system of coupled phase oscillators. The dynamical crossover is signaled by a peak in the product of the measures of intracluster and global synchronization, which we propose as a dynamical measure of complexity. This quantity is much easier to compute than the entropy (of the average frequencies of the oscillators), and displays a behavior which closely mimics that of the dynamical complexity index based on the latter. The proposed topological measure simultaneously provides information on the dynamical behavior, sheds light on the interplay between modularity and total integration, and shows how this affects the capability of the network to perform both local and distributed dynamical tasks.

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Introducing teaching about healthy solutions in buildings and BIM has been a challenge for the University of Alicante. Teaching attached to very tighten study plans conditioned the types of methods that could be used in the past. The worldwide situation of crisis that especially reached Spain and the bursting of the housing bubble generated a lack of employment that reached universities where careers related to construction, Architecture and Architectural Technologist, suffered a huge reduction in the number of students enrolled. In the case of the University of Alicante, students’ enrolment for Architectural Technology reached an 80% reduction. The necessity of a reaction against this situation made the teachers be innovative and use the new Bologna adapted study plans to develop new teaching experiences introducing new concepts: people wellbeing in buildings and BIM. Working with healthy solutions in buildings provided new approaches for building design and construction as an alternative to sustainability. For many years sustainability was the concept that applied to housing gave buildings an added value and the possibility of having viability in a very complex scenario. But after lots of experiences, the approved methodologies for obtaining sustainable housing were ambiguous and at the end, investors, designers, constructors and purchasers cannot find real and validated criteria for obtaining an effective sustainable house. It was the moment to work with new ideas and concepts and start facing buildings from the users’ point of view. At the same time the development of new tools, BIM, has opened a wide range of opportunities, innovative and suggestive, that allows simulation and evaluation of many building factors. This paper describes the research in teaching developed by the University of Alicante to adapt the current study plans, introducing work with healthy solutions in buildings and the use of BIM, with the aim of attracting students by improving their future employability. Pilot experiences have been carried out in different subjects based on the work with projects and case studies under an international frame with the cooperation of different European partner universities. The use of BIM tools, introduced in 2014, solved the problems that appeared in some subjects, mainly building construction, and helped with the evaluation of some healthy concepts that presented difficulties until this moment as knowledge acquired by the students was hard to be evaluated. The introduction of BIM tools: Vasari, FormIt, Revit and Light Control among others, allowed the study of precise healthy concepts and provided the students a real understand of how these different parameters can condition a healthy architectural space. The analysis of the results showed a clear acceptance by the students and gave teachers the possibility of opening new research lines. At the same time, working with BIM tools to obtain healthy solutions in building has been a good option to improve students’ employability as building market in Spain is increasing the number of specialists in BIM with a wider knowledge.

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The development of solutions that prevent dehydration or promote adequate re-hydration play a vital role in preventing fatigue during exercise, however, the methods commonly used to assess the hydration ability of such solutions are invasive and often assess the components of absorption separately. This paper describes using a non-invasive deuterium tracer technique that assesses gastric emptying and intestinal absorption simultaneously to evaluate the uptake of water during rest and exercise. The kinetics of absorption are further examined by mathematical modelling of the data generated. For the rest group, 0.05 g/kg of body weight of deuterium, contained in gelatine capsules, was ingested with ordinary tap water and saliva samples were collected every 5 min for one hour while the subject remained seated. The deuterium was administered as above for the exercise group but sample collection was during one hour of exercise on a treadmill at 55% of the subject's maximum heart rate. The enrichment data for each subject were mathematically modelled and the parameters obtained were compared across groups using an independent samples t-test. Compared with the rest condition, the exercise group showed delayed absorption of water as indicated by significant differences for the modelling parameters t(2), t(1/2), maximum absorption rate and solution absorption amount at t(1). Labelling with a deuterium tracer is a good measure of the relative rate ingested fluids are absorbed by the body. Mathematical modelling of the data generates rates of maximum absorption and allows calculation of the percentage of the solution that is absorbed at any given time during the testing period. Copyright (C) 2004 John Wiley Sons, Ltd.

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We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.

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This work formulates existence theorems for solutions to two-point boundary value problems on time scales. The methods used include maximum principles, a priori bounds and topological degree theory.

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This work presents closed form solutions for fully developed temperature distribution and entropy generation due to forced convection in microelectromechanical systems (MEMS) in the Slip-flow regime, for which the Knudsen number lies within the range 0.001

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A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

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A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

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Projects solutions reuse methodology is offered for software development. The main idea consists in connection of the system objective with the situation using the entities which describe the condition of the system in the process of the objective statement. Every situation is associated with one or several design solutions, which can be used at the development. Based on this connection the situation representing language has been created, it lets to express a problem situation using a natural language describe. The similarity measure has been built to compare situations, it is based on the similarity coefficients with adding the absent part weight.

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Mathematics Subject Classification: 45G10, 45M99, 47H09

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2000 Mathematics Subject Classification: 35L15, 35B40, 47F05.

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A dolgozatban a döntéselméletben fontos szerepet játszó páros összehasonlítás mátrix prioritásvektorának meghatározására új megközelítést alkalmazunk. Az A páros összehasonlítás mátrix és a prioritásvektor által definiált B konzisztens mátrix közötti eltérést a Kullback-Leibler relatív entrópia-függvény segítségével mérjük. Ezen eltérés minimalizálása teljesen kitöltött mátrix esetében konvex programozási feladathoz vezet, nem teljesen kitöltött mátrix esetében pedig egy fixpont problémához. Az eltérésfüggvényt minimalizáló prioritásvektor egyben azzal a tulajdonsággal is rendelkezik, hogy az A mátrix elemeinek összege és a B mátrix elemeinek összege közötti különbség éppen az eltérésfüggvény minimumának az n-szerese, ahol n a feladat mérete. Így az eltérésfüggvény minimumának értéke két szempontból is lehet alkalmas az A mátrix inkonzisztenciájának a mérésére. _____ In this paper we apply a new approach for determining a priority vector for the pairwise comparison matrix which plays an important role in Decision Theory. The divergence between the pairwise comparison matrix A and the consistent matrix B defined by the priority vector is measured with the help of the Kullback-Leibler relative entropy function. The minimization of this divergence leads to a convex program in case of a complete matrix, leads to a fixed-point problem in case of an incomplete matrix. The priority vector minimizing the divergence also has the property that the difference of the sums of elements of the matrix A and the matrix B is n times the minimum of the divergence function where n is the dimension of the problem. Thus we developed two reasons for considering the value of the minimum of the divergence as a measure of inconsistency of the matrix A.