987 resultados para Distance Scale
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Mestrado em Engenharia Electrotécnica e de Computadores - Ramo de Sistemas Autónomos
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A fourteen year schistosomiasis control program in Peri-Peri (Capim Branco, MG) reduced prevalence from 43.5 to 4.4%; incidence from 19.0 to 2.9%, the geometric mean of the number of eggs from 281 to 87 and the level of the hepatoesplenic form cases from 5.9 to 0.0%. In 1991, three years after the interruption of the program, the prevalence had risen to 19.6%. The district consists of Barbosa (a rural area) and Peri-Peri itself (an urban area). In 1991, the prevalence in the two areas was 28.4% and 16.0% respectively. A multivariate analysis of risk factors for schistosomiasis indicated the domestic agricultural activity with population attributive risk (PAR) of 29.82%, the distance (< 10 m) from home to water source (PAR = 25.93%) and weekly fishing (PAR = 17.21%) as being responsible for infections in the rural area. The recommended control measures for this area are non-manual irrigation and removal of homes to more than ten meters from irrigation ditches. In the urban area, it was observed that swimming at weekly intervals (PAR = 20.71%), daily domestic agricultural activity (PAR = 4.07%) and the absence of drinking water in the home (PAR=4.29%) were responsible for infections. Thus, in the urban area the recommended control measures are the substitution of manual irrigation with an irrigation method that avoids contact with water, the creation of leisure options of the population and the provision of a domestic water supply. The authors call attention to the need for the efficacy of multivariate analysis of risk factors to be evaluated for schistosomiasis prior to its large scale use as a indicator of the control measures to be implemented.
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We examine the constraints on the two Higgs doublet model (2HDM) due to the stability of the scalar potential and absence of Landau poles at energy scales below the Planck scale. We employ the most general 2HDM that incorporates an approximately Standard Model (SM) Higgs boson with a flavor aligned Yukawa sector to eliminate potential tree-level Higgs-mediated flavor changing neutral currents. Using basis independent techniques, we exhibit robust regimes of the 2HDM parameter space with a 125 GeV SM-like Higgs boson that is stable and perturbative up to the Planck scale. Implications for the heavy scalar spectrum are exhibited.
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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. 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. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.
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RESUMO: A monitorização da actividade física diária nos doentes com Doença Pulmonar Obstrutiva Crónica (DPOC) tem sido alvo de grande interesse nos últimos tempos. No entanto, ainda nenhum estudo reuniu o conjunto de factores – grau de obstrução, hiperinsuflação pulmonar, alteração das trocas gasosas, dispneia, dessaturação de oxigénio, capacidade de exercício, ansiedade e depressão – que podem afectar a sua realização, nem os correlacionou com os dados obtidos com o pedómetro e que reflectem o que cada doente realmente faz no seu dia-adia. O presente estudo teve como objectivo principal identificar os factores que influenciam a actividade física na vida diária dos doentes com DPOC. Estudaram-se 55 doentes do sexo masculino com idade média de 67 anos e um FEV1 médio de 50,8% do previsto, com DPOC moderada a muito grave (estadios II a IV), de entre os utentes do Laboratório de Fisiopatologia Respiratória do Centro Hospitalar de Torres Vedras. Avaliaram-se os parâmetros da escala de dispneia modificada do Medical Research Council (MMRC), escala London Chest Activity of Daily Living (LCADL), escala de Ansiedade e Depressão Hospitalar (HADS), índice BODE, estudo funcional respiratório em repouso, teste de marcha de seis minutos e o número de passos por dia utilizando um pedómetro por um período de três dias. Observou-se que os doentes deram em média 4972 passos por dia e apresentaram uma cotação total média de 17,7 na LCADL, tendo existido diferenças estatisticamente significativas em função da gravidade da doença, sendo que os doentes mais graves são os que em média andam menos no seu dia-a-dia e apresentam maior limitação na realização das actividades de vida diária. O número de passos por dia apresentou correlações significativas com as variáveis idade, dispneia, depressão, hiperinsuflação monar, gravidade de obstrução (FEV1), trocas gasosas (DLCO), saturação arterial de oxigénio mínima e correlação mais forte com a distância percorrida no TM6m. Este estudo permitiu identificar que os factores determinantes da actividade física na vida diária de doentes com DPOC nos estadios II a IV, foram a dispneia e a distância percorrida no TM6m. Além disso, estes doentes constituem um grupo sedentário, particularmente a partir do estadio III, com níveis de actividade física diária baixos.-----------ABSTRACT There has been an increased interest in monitoring the daily physical activity in patients with Chronic Obstructive Pulmonary Disease (COPD). However, no specific study has been realized so far that has put the different factors which can affect the results obtained altogether, (such as the degree of obstruction, pulmonary hyperinflation, abnormal gas exchange, dyspnea, oxygen desaturation, exercise capacity, anxiety and depression) or correlated with data obtained from the pedometer, which reflect each patient actual activity in their daily life. This study aimed to identify the main factors that influence physical activity in daily life of patients with COPD. The scope of this study was 55 male patients with an average age of 67 years old and an average FEV1 of 50.8% predicted, with moderate to severe COPD (stages II to IV), among patients from the Respiratory Pathophysiology Laboratory of the Centro Hospitalar de Torres Vedras. Were evaluated the parameters of the modified Medical Research Council dyspnea scale (MMRC), London Chest Activity of Daily Living scale (LCADL), Hospital Anxiety and Depression scale (HADS), BODE index, pulmonary function test at rest, six minute walk test (6MWT) and the number of steps per day using a pedometer for a period of three days. It was observed that patients have walked an average of 4972 steps per day and had a total score of 17.7 at LCADL, and statistically significant differences were stated depending on the severity of the disease. Whereas patients with a more severe degree of the disease have walked least in their daily life and show greater restraint in carrying out activities of daily living. The number of steps per day showed significant correlations with age, dyspnea, depression, lung hyperinflation, severity of obstruction (FEV1), gas exchange (DLCO), minimum arterial oxygen saturation and stronger correlation with distance walked on 6MWT. This study shows that the crucial factors of physical activity in daily life of COPD patients at stages II to IV were dyspnea and distance on 6MWT. Moreover, these patients constitute a sedentary group, particularly from the stage III, with lower levels of daily physical activity.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy in Sanitary Engineering in the Faculty of Sciences and Technology of the New University of Lisbon
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The concept of HRM perceptions is a growing interest in the literature, as one of the antecedents of HRM outcomes. Regardless, not only the cognitive aspect of perception is interesting in this field (what you think) but also the affective perspective is of interest (how you feel about it). In this study we propose a scale for assessing satisfaction with the perceptions of the HRM practices. A 24 item Likert-type scale was developed considering literature review, to assess subjects’ satisfaction with Human Resources Practices in a healthcare setting. Talked reflections were held and a survey encompassing all workers from a Hospital was conducted later, with a sample of 922 subjects. Exploratory and Confirmatory Factor Analysis were performed; reliability was tested using Cronbach’s alpha. The scale presents good psychometric properties with alpha values that range from .71 to .91. Exploratory and Confirmatory Factor Analysis demonstrated that the scale presents a very good fit with CFI= 0.94, AGFI= 0.88, and RMSEA= 0.07. The present study represents a first approach in the usage of this scale and despite having a large sample, respondents originate from a single institution. This study presents a pertinent scale towards measuring a seldom explored construct of the worker-organization relationship. The scale is parsimonious and results are promising. There seems to be very little research on how subjects feel about the HRM practices. This construct, very much in line with more recent studies concerning worker perceptions can be especially interesting in the context of the worker-organization relationship.
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Purpose: This work aims at further developing and testing the psychometric properties of the Cultural Intelligence Scale (Ang & Van Dyne, 2006) in an Erasmus Mundus Students and Alumni Population, including reliability. Design Methodology: The study included 626 participants from 109 different countries that emcompasses 6 continents. Exploratory and Confirmatory Factor Analysis procedures were carried out in order to test the scale in a multicultural scale of Erasmus Mundus Students. Reliability was assessed using Cronbach Alpha. Results: The scale presents excellent psychometric properties with alpha values that range from .84 to .90. Exploratory and Confirmatory Factor Analyses demonstrated that the original model of the scale presents an exceptionally good fit. Limitations: The present study was conducted using a convenience sample and online questionnaires that limit its conclusions when we consider the globality of the Erasmus Mundus Students. Research/Practical Implications: This study presents evidence that Ang and Van Dyne’s scale is an adequate measure instrument to assess intercultural intelligence in a multicultural setting of students and alumni. Originality/Value: Multicultural samples and studies are becoming more and more present and relevant; the study of intercultural competences and habilities is becoming increasingly important, and in this task, solid psychometric instruments are of paramount importance. This study presents evidence that Ang and Van Dyne’s (2006) scale is a fairly recent and parsimonious instrument with excellent psychometric properties properties.
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This paper describes the development and testing of a robotic capsule for search and rescue operations at sea. This capsule is able to operate autonomously or remotely controlled, is transported and deployed by a larger USV into a determined disaster area and is used to carry a life raft and inflate it close to survivors in large-scale maritime disasters. The ultimate goal of this development is to endow search and rescue teams with tools that extend their operational capability in scenarios with adverse atmospheric or maritime conditions.
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Canadian Journal of Civil Engineering 36(10) 1605–16
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Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.