A new approach for mapping of Biological Soil Crusts in semidesert areas with hyperspectral imagery

Biological Soil Crusts (BSCs), consisting of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, live within or immediately on top of the uppermost millimeters of soil, where they form a more or less firm aggregation of soil particles and organisms. They mainly occur in soils of arid and semi-arid regions, which cover more than 35% of the earth's land surface and are assumed to play a major role as primary producers, C- and N-sinks and soil stabilizers.

In order to establish a methodology for mapping of BSCs, their spectral characteristics with respect to different crust types were analyzed. The resulting reflectance spectra of different crust types had a shallow absorption feature centered around 680 nm in common, in which they differed from the spectra of bare soil.

In October 2004, hyperspectral CASI data with a spatial resolution of 1 m were recorded in conjunction with field spectroscopic measurements in the Succulent Karoo, South Africa. Available spectral indices for Biological Soil Crusts were tested on the image but did not produce satisfying classifications. Therefore, an alternative approach was established based on spectral field data, field observations and the hyperspectral dataset. The newly developed Continuum Removal Crust Identification Algorithm (CRCIA) is based on small and narrow spectral characteristics, that were extracted by continuum removal and subsequently expressed as a set of logical conditions. Using this method, 16.2% of the area which covers 12 km² of gently sloping hills with some granite outcrops were classified as BSCs. Validation of the classification resulted in a Kappa index of 0.831.

In a next step, the methodology will be tested with regard to scale-dependent effects and applied to images covering areas with additional types of BSCs and soil to develop a robust and generally applicable method.     

Thermal degradation of copolymers based on 2-substituted oxazolines and β-methylhydrogenitaconate

Summary The thermal stabilities of poly(-methylhydrogenitaconate-co-2-methyl-2-oxazoline) and poly(-methylhydrogenitaconate-co-2-ethyl-2-oxazoline) obtained by spontaneous copolymerization have been studied by programmed thermogravimetric analysis over the temperature range from 293 K to 773 K under a flow of nitrogen. Most of the copolymers do not show weight loss until 473 K and they degrade in one step. The kinetic parameters Ea, n and A were obtained following one method of thermogravimetric analysis. The reaction order for all copolymers was 1.0. The poly(-methylhydrogenitaconate-co-2-methyl-2-oxazoline)s were the most thermostable copolymers.     

Analysis of the influence of binder properties on the mechanical response of bituminous mixtures

Asphalt mixtures are composed by a mass of aggregates (more than 90% of their total weight), which are bonded by a bituminous binder. Despite the fact that the binder is not the main component of these materials (around 5% of their total weight), it exerts a high influence on their mechanical response. In this sense, the service life of asphalt pavements will directly depend on the type of binder used, and thus an adequate choice is crucial to construct more durable roads. Because of this fact, it is necessary to know the characteristics of the bitumen in order to reduce the impact of different distresses that appear on roads. For this purpose, this paper studies the influence of the binder properties in the appearance of the main distresses that affect asphalt pavements around the world (stripping, fatigue cracking and plastic deformations). Five bitumens with different properties have been analysed during this research using diverse binder (UCL, multiple stress creep and recovery test and dynamic shear rheometer time sweep) and mixture (water sensitivity, wheel tracking and UGR-FACT) tests. The results obtained show that the properties of the binder influence the long-term performance of bituminous mixtures. In this sense, it can be said that flexible binders which are able to recover plastic deformations could extend the service life of the pavements.     

Mechanical and thermal behaviour of an acrylic bone cement modified with a triblock copolymer

The basic formulation of an acrylic bone cement has been modified by the addition of a block copolymer, Nanostrength^® (NS), in order to augment the mechanical properties and particularly the fracture toughness of the bone cement. Two grades of NS at different levels of loading, between 1 and 10 wt.%, have been used. Mechanical tests were conducted to study the behaviour of the modified cements; specific tests measured the bend, compression and fracture toughness properties. The failure mode of the fracture test specimens was analysed using scanning electron microscopy (SEM). The effect of NS addition on the thermal properties was also determined, and the polymerisation reaction using differential scanning calorimetry. It was observed that the addition of NS produced an improvement in the fracture toughness and ductility of the cement, which could have a positive contribution by reducing the premature fracture of the cement mantle. The residual monomer content was reduced when the NS was added. However this also produced an increase in the maximum temperature and the heat delivered during the polymerisation of the cement.     

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets

When performing a classification task, we may find some data-sets with a different class distribution among their patterns. This problem is known as classification with imbalanced data-sets and it appears in many real application areas. For this reason, it has recently become a relevant topic in the area of Machine Learning.The aim of this work is to improve the behaviour of fuzzy rule based classification systems (FRBCSs) in the framework of imbalanced data-sets by means of a tuning step. Specifically, we adapt the 2-tuples based genetic tuning approach to classification problems showing the good synergy between this method and some FRBCSs.Our empirical results show that the 2-tuples based genetic tuning increases the performance of FRBCSs in all types of imbalanced data. Furthermore, when the initial Rule Base, built by a fuzzy rule learning methodology, obtains a good behaviour in terms of accuracy, we achieve a higher improvement in performance for the whole model when applying the genetic 2-tuples post-processing step. This enhancement is also obtained in the case of cooperation with a preprocessing stage, proving the necessity of rebalancing the training set before the learning phase when dealing with imbalanced data.     

Effect of physical vapor deposition metallic thin films on micro injection molded weld line mechanical properties

Micro injection molded polymeric parts coated with functional thin films/layers show off the promising applications in microsystems area. But the unfavorable and unavoidable defect of weld line in micro injection molding part leads to detrimental mechanical and surface properties. The possibility of the functional thin film for enhancing micro injection molded weld lines was investigated. Two typical coating materials (aluminum and titanium) with various film thicknesses (400, 600, 800 nm) were deposited on one side of the micro injection molded weld line tensile sample via physical vapor deposition (PVD) method. The coated micro weld line samples were characterized by tensile tests. The results show that PVD films of aluminum and titanium can reinforce the strength and stiffness of micro injection molded weld line, even at thin thickness levels. But when the film thickness is increasing, the weaker adhesion between metallic films and polymers decreased the PVD films’ enhancing performance for micro weld line mechanical properties due to the degradation of polymers related to longer time exposure under high temperature.     

Model Checking Games for the Quantitative μ-Calculus

We investigate quantitative extensions of modal logic and the modal μ-calculus, and study the question whether the tight connection between logic and games can be lifted from the qualitative logics to their quantitative counterparts. It turns out that, if the quantitative μ-calculus is defined in an appropriate way respecting the duality properties between the logical operators, then its model checking problem can indeed be characterised by a quantitative variant of parity games. However, these quantitative games have quite different properties than their classical counterparts, in particular they are, in general, not positionally determined. The correspondence between the logic and the games goes both ways: the value of a formula on a quantitative transition system coincides with the value of the associated quantitative game, and conversely, the values of quantitative parity games are definable in the quantitative μ-calculus.     

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Nowadays, the patients and physicians use the health-related websites as an important information source and, therefore, it is critical the quality evaluation of health- related websites. The quality assessment of health-related websites becomes especially relevant because their use imply the existence of a wide range of threats which can affect people’s health. Additionally, website quality evaluation can also contribute to maximize the exploitation of invested resources by organizations in the development of user-perceived quality websites. But there is not yet a clear and unambiguous definition of the concept of website quality and the debate about quality evaluation on the Web remains open. In this paper, we present a qualitative and user-oriented methodology for assessing quality of health-related websites based on a 2-tuple fuzzy linguistic approach. To identify the quality criteria set, a qualitative research has been carried out using the focus groups technique. The measurement method generates linguistic quality assessments considering the visitors’ judgements with respect to those quality criteria. The combination of the linguistic judgements is implemented without a loss of information by applying a 2-tuple linguistic weighted average operator. This methodology means an improvement on quality evaluation of health websites through the commitment to put users first.     

Error Analysis for hp-FEM Semi-Lagrangian Second Order BDF Method for Convection-Dominated Diffusion Problems

We present in this paper an analysis of a semi-Lagrangian second order Backward Difference Formula combined with hp-finite element method to calculate the numerical solution of convection diffusion equations in ℝ². Using mesh dependent norms, we prove that the a priori error estimate has two components: one corresponds to the approximation of the exact solution along the characteristic curves, which is O(Dt²+h^m+1(1+\frac\mathopen|logh|Dt))O(\Delta t^{2}+h^{m+1}(1+\frac{\mathopen{|}\log h|}{\Delta t})); and the second, which is O(Dt^p+|| [(u)\vec]-[(u)\vec]_h||_L^￥)O(\Delta t^{p}+\| \vec{u}-\vec{u}_{h}\|_{L^{\infty}}), represents the error committed in the calculation of the characteristic curves. Here, m is the degree of the polynomials in the finite element space, [(u)\vec]\vec{u} is the velocity vector, [(u)\vec]_h\vec{u}_{h} is the finite element approximation of [(u)\vec]\vec{u} and p denotes the order of the method employed to calculate the characteristics curves. Numerical examples support the validity of our estimates.