A quest for the right word enhancing reflexivity and technology in terminology training

INTED2010, the 4th International Technology, Education and Development Conference was held in Valencia (Spain), on March 8, 9 and 10, 2010.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Comparative study of the topical effectiveness of the andiroba oil (Carapa guianensis) and DEET 50% as repellent for Aedes sp

DEET (N,N-diethyl-3-methylbenzamide) is nowadays the most effective mosquito repellent available, however, its use can present some topical and systemic side effects. Some botanical compositions, as Andiroba (Carapa guianensis), have been proved repellent properties at low cost and toxicity. An experimental study was driven involving four volunteers submitting their forearms covered with Andiroba oil at 100%, DEET 50%, refined soy oil, Andiroba oil 15% and in the absence of products, directly to healthy females of Aedes sp. The times of first and third bites were checked. The results showed that the median of the first bite without any product was 17.5s and the third bite, 40.0s. In the soy oil, the bites happened in 60.0s and 101.5s, in the presence of Andiroba oil 100%, in 56.0s and 142.5s and in Andiroba oil 15%, in 63.0s and 97.5s. The volunteers using DEET 50% had not received bites after 3600s in most of the experiments (p < 0.001 Wilcoxon). Pure Andiroba oil compared to the soy oil, forearm without product and Andiroba oil 15%, showed discreet superiority (p < 0.001 Wilcoxon). Our conclusion is that this study demonstrated that the pure Andiroba oil presents discreet repellent effect against bite of Aedes sp., being significantly inferior to DEET 50%.

Sustainability Improvement of a composite materials’ industry through recycling and re-engineering process approaches

Recent Advances in Mechanics and Materials in Design

Um Bongo and sport: How can a brand communicate through its mascots

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

How CSR claims in advertising affect children’s preferences and purchase intentions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Use of multi-sensory marketing techniques and its influence on brand experience in retail and HORECA sector

Double degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA- School of Business and Economics and Warsaw School of Economics

The influence of sports events endorsement on children’s perceptions of healthy food products and brands

Field lab in marketing: Children consumer behaviour

A case study of product usability of a pelvic device used by children with neuromotor impairments

On assistive technology targeted for people with activity limitations and participation, usability issues becomes an essential tool to ensure that the product has the appropriate ergonomics characteristics, in other words, ensure that it fits the specific user´s needs. The aim of this study was to analyze the usability of an adaptive seating device for children with neuromotor impairments, by using kinematic indicators of the reaching movement. The study sample consisted of 13 children with associated neurologic conditions. The tests were developed by using a wooden bench height adjustable, integrated with the adaptive seating device under study, and a system to capture three-dimensional image, called Qualisys Track Manager. The following reaching kinematics variables were measured: maximum reaching velocity, movement duration, index of curvature, and unit movements. It was found that the use of the adaptive seating device had a positive impact on upper limb function in children with neuromotor impairments. It was also noticed an improvement in the reaching movement kinematics, which was statistical significant for the index of curvature and unit movements. As main conclusions, it is possible to point out some positive effects that the product under study seems to have on users' movements, such as the improved movement quality of the upper limb, which could mean a better postural adjustments and higher trunk postural control. By identifying new measures of usability in terms of effectiveness and efficiency for the analyzeddevice, the results obtained may serve also as performance indicators, providing new data that may help to improve the product and eventually modifying it, in order to turn it more compatible with the needs of the considered target population.

Firm innovation and co-location in Portugal

This paper investigates the geographical distribution and concentration of firms’ innovation persistence and innovation type (product and process) based on three waves of the Portuguese Community Innovation Survey data covering the period 1998–2006. The main findings are: 1) both innovation persistence and innovation type are asymmetrically distributed across Portuguese regions, 2) the degree of correlation between geographical location and innovative output varies with the innovation type, and 3) the correlation between geographical unit and innovation increases when the spatial unit of analysis is narrower. The results suggest that the firms’ choices of geographical location have a long-lasting effect, engendering no equal probabilities of being persistently innovative.

Semigroup operators and applications

Dissertação de mestrado em Matemática

Contribution to an efficient transmission of information to the textile fashion consumer and the influence in sustainable attitudes

The concepts involved in sustainable textile fashion, demanding good knowledge about raw materials, processes, end use properties and circuits amongst others, are able to determine the way the textile product is designed and the behavior of the consumer, regarding life style and buying decisions. The textile product`s life integrates raw materials, their processing, distribution, use by the consumer and destination of the product after useful lifetime, this is, his complete life cycle. It is very important to recognize the power of the consumer to influence parameters related to sustainability, namely when he decides how, when and why he buys and afterwards by the attitudes taken during and after use. The conscious act of consumption involves ethical, ecological and technical knowledge in which the concern is overall lifecycle of the fashion product and not exclusively aesthetic and symbolic values strongly related with its ephemeral nature. The present work proposes the classification of textile products by means of an innovative label aiming to establish a rating related to the Life of Fashion Products, by using parameters considered with especial impact in lifecycle, as textile fibers, processing conditions, generated wastes, commercialization circuits, durability and cleaning procedures. This label for sustainable fashion products aims to assist the stakeholders with informed attitudes and correct decisions in order to promote the objectives of sustainable fashion near designers, consumers and industrial experts.

Financial development, labor and market regulations and growth

This paper investigates the importance that market regulation and financial imperfections have on firm growth. We analyse institutions af- fecting labor market as Employment Protection Laws (EP) and Product Market Regulation (PM). We show that together with the beneficial effects of financial development, a firm will get less financing, and thus investless, in a weak financial market (finance effect), the strictness of product and labor market regulations also affect firm growth (labor effect). In particular, we show that the stricter the rules the more detrimental the influence on growth in sectoral value added for a large number of countries. We also show that the labor effect overcomes the positive finance effect.

A study of the endocervical columnar cells II - effects of physiological changes and of oathological lesions of the uterus on the specific numerical composition of the endocervical epithelium

In the second part of this paper we nalysed the correlation between the clinical pathological alterations and the sum of the types of columnar cells of 300 histological sections of cervix. Fifty histological sections of normal cervix of sexually mature women were selected and considered as normal in pattern. The specific counts of the columnar cells which line the endocervical mucosa and those of the glands of 50 normal cervices were compared with other similar counts made in 50 histological sections of cervices of old women and emphasized the differences. Comparisons were made also between 50 normal cervices and 50 sections of cervices with chronic inflammation, 50 cervices with epidermoid metaplasia and 50 cervices with myoma of the corpus. Counts were made from 50 cervices of patients who on the occasion of the surgical operation were in the proliferative phase of the menstrual cycle; these were compared with the counts of 50 cervices of uteri in the luteal phase. Finally, the numerical frequency of the following data encountered in the 300 cervices was recorded: 1. aspects of the ectocervical epithelium; 2. number of Nabothian cysts; 3. number of cervical glands; 5. number of deliveries and 6. aspect of the material within the cervical canal.

Evaluation of the xenodiagnosis of chronic Chagas patients infected ten years or over in an area where transmission has been interrupted - Iguatama and Pains, west Minas Gerais State, Brazil

To evaluate the results of xenodiagnosis in chronic Chagas patients infected for ten years or over in an area where transmission has been stemmed as well as the performance of these tests applied one or more times to determine the presence of the paraiste in serum-positive patients for Trypanosoma cruzi infection, 570 xenodiagnosis were performed in 246 patients by exoposing each pacient to 40 Triatoma infestans nymphs of 3 rd/4th stage once, twice or three times, at 30 days intervals. The 570 xenodiagnosis showed overall positive results in 50.7% with a peak 78% in patients under 20 years of age, and 60.5% in those over 60. Of the l58 patients who underwent three xenodiagnosis, 51 (32.3%) had three positive tests, 48 (30.3%) had all negative results, and the remainder had alternating positve and negative findings. There was no difference in number of positive results between the 1st, 2nd and 2rd tests; however, the 1st and 2nd trials added up to 53.2% and the sum total of all three trials was 57.7%.