945 resultados para Point density analysis


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We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

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In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.

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This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation) has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (INUNGAMA) has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use.

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A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

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A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

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In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

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One of the most relevant properties of composite materials to be considered is stiffness. Fiberglass has been used traditionally as a fibrous reinforcing element when stiff materials are required. However, natural fibers are been exploited as replacements for synthetic fibers to satisfy environmental concerns. Among the different natural fibers, wood fibers show the combination of relatively high aspect ratio, good specific stiffness and strength, low density, low cost, and less variability than other natural fibers of such those from annual crops. In this work, composites from polypropylene and stone groundwood fibers from softwood were prepared and mechanically characterized under tensile loads. The Young’s moduli of the ensuing composites were analyzed and their micromechanics aspects evaluated. The reinforcing effect of stone groundwood fibers was compared to that of conventional reinforcement such fiberglass. The Halpin-Tsai model with the modification proposed by Tsai-Pagano accounted fairly for the behavior of PP composites reinforced with stone groundwood fibers. It was also demonstrated that the aspect ratio of the reinforcement plays a role in the Young’s modulus of injection molded specimens

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Emission trading with greenhouse gases and green certificates are part if the climate policy the main target of which is reduce greenhouse gas emissions. The carbon dioxide and fine particle emissions of energy production in Helsinki Metropolitan area are calculated in this study. The analysis is made mainly by district heating point of view and the changes of the district heating network are assessed. Carbon dioxide emissions would be a bit higher, if the district heating network is expanded, but then the fine particle emissions would be much lower. Carbon dioxide emissions are roughly 10 % higher, if the district heating network is expanded at same rate as it has in past five years in the year 2030. The expansion of district heating network would decrease the fine particle emissions about 40 %. The cost of the expansion is allocated to be reduction cost of the fine particle emissions, which is considerably higher than the traditional reduction methods costs. The possible new nuclear plant would reduce the emissions considerably and the costs of the nuclear plant would be relatively low comparing the other energy production methods.

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This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

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Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

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In this paper, we present the Melodic Analysis of Speech method (MAS) that enables us to carry out complete and objective descriptions of a language's intonation, from a phonetic (melodic) point of view as well as from a phonological point of view. It is based on the acoustic-perceptive method by Cantero (2002), which has already been used in research on prosody in different languages. In this case, we present the results of its application in Spanish and Catalan.

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A simple cloud point extraction procedure is presented for the preconcentration of copper in various samples. After complexation by 4-hydroxy-2-mercapto-6-propylpyrimidine (PTU), copper ions are quantitatively extracted into the phase rich in Triton X-114 after centrifugation. Methanol acidified with 0.5 mol L-1 HNO3 was added to the surfactant-rich phase prior to its analysis by flame atomic absorption spectrometry (FAAS). Analytical parameters including concentrations for PTU, Triton X-114 and HNO3, bath temperature, centrifugation rate and time were optimized. The influences of the matrix ions on the recoveries of copper ions were investigated. The detection limits (3SDb/m, n=4) of 1.6 ng mL-1 along with enrichment factors of 30 for Cu were achieved. The proposed procedure was applied to the analysis of environmental samples.

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A photometric procedure was developed for determination of aflatoxin B1 in peanuts by TLC-CCD technique. The quantification and detection limit were 1.2 μg kg-1 and 0.4 ng per spot, respectively, with mean recovery of 98%. The CCD camera is sufficiently sensitive to detect small changes in spots fluorescence intensity and the results for performance confirmed the efficiency of the method. Another important property of CCD detector is its linearity for a wide range of luminous stimulus determined by analysis of five-point calibration curves using the intensity of AFB1 fluorescence versus AFB1 concentration (0.8 to 4.8 ng per spot). The method was applied to the analysis of thirty nine peanut samples and aflatoxin B1 levels ranged from 16 to 115 μg kg-1. The TLC-CCD and the photometric procedure developed in this study demonstrated to be a simple and efficient tool for quantitative analyses of AFB1 in peanut samples.

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A new cloud point extraction (CPE) method was developed for the separation and preconcentration of copper (II) prior to spectrophotometric analysis. For this purpose, 1-(2,4-dimethylphenyl) azonapthalen-2-ol (Sudan II) was used as a chelating agent and the solution pH was adjusted to 10.0 with borate buffer. Polyethylene glycol tert-octylphenyl ether (Triton X-114) was used as an extracting agent in the presence of sodium dodecylsulphate (SDS). After phase separation, based on the cloud point of the mixture, the surfactant-rich phase was diluted with acetone, and the enriched analyte was spectrophotometrically determined at 537 nm. The variables affecting CPE efficiency were optimized. The calibration curve was linear within the range 0.285-20 µg L-1 with a detection limit of 0.085 µg L-1. The method was successfully applied to the quantification of copper in different beverage samples.

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Appearance of trust in regional, co-operative networks In our times, the value of social networks has been widely acknowledged. One can say that it is important for private persons to get networked, whilst it is even a must for companies and organizations in business life. This doctor's thesis examines three co-operative regional networks. Networks are located in Western Uusimaa (Länsi-Uusimaa) region in southernmost Finland, and they had both public organizations and private companies as participants (later called ‘players’). Initially, all of them were co-financed from public funds, and two of them are still operational while writing this. The main target of these networks has been to act as learning networks. The learning network stands for an ensemble of research and development units and workplaces constituting a common forum for learning. The main focus in this study has been on qualitative and structural characteristics of the networks, and how they are relating with intrinsic trust. In addition to the development of trust, it has been studied, at what level organizational learning within the networks takes place, and lastly, what kind of factors facilitate the development of social capital. The theoretical framework for the study is built on analysing trust and social capital. It is a 'mission impossible' to find single definitions for such major concepts. In this study, from the research questions' point of view it has been more relevant to concentrate on the aspects of networking and the relationships between the participating organizations. The total view in this study is very network-centric, and therefore those theories which have similar point of view have been prioritized. Such is the theory about structural holes by Ronald S. Burt (1992). It has been widely applied; especially his views on constraints affecting players in networks. The purpose of this study has not been to create new theories or to analyse and compare thoroughly the existing theoretical trends. Instead, the existing theories have provided the study with conceptual tools, which have been utilized for supporting the empirical results. The aim has been to create an explanatory case study consisting relevant discussion on the relationship between the network characteristics and the appearance of trust. The conceptual categorization for confidence vs. trust created by Niklas Luhmann (1979) is another important theoretical building block. In most cases, co-operation in networks is initiated by people already trusting in each other and willing to work together. However, personal trust is not sufficient in the long run to sustain the co-operation within the network: more abstract systemic trust described by Luhmann must also emerge. In the networks with different structures and at different development phases, these forms of trust appear at different levels. In this study, Luhmann’s systemic trust as a term has been replaced by the concept of 'trust in network as a system'. Structural characteristics of a network (density, centrality, structural holes etc.) have been selected to explain the creation of social capital and trust. The ability to adapt new information is essential for the development of social capital. Qualitative analysis for development phase has been used, and the Learning Network Maturity Test by Leenamaija Otala (2000) and her work have been applied. Thus, the qualitative characteristics and the structural characteristics of the networks are utilized together, when the creation of social capital and appearance of trust are assessed. Social Network Analysis, questionnaires and interviews have been the research methods. Quantitative and qualitative data have been combined. There is a similarity in viewpoints to research data with Extensive Case Study method, in which different cases are searched by exploring various cases and comparing certain common features between them and generic models. Development of trust, social capital and organizational learning has been explained in the study by comparing the networks in hand. Being a case study, it doesn't have targets to provide with general results and findings like conventional surveys. However, in this work phenomena and mechanisms related to them are interpreted from the empirical data. Key finding of this study is that the networks with high structural equality and clear target setting enable building trust to the network as a system. When systemic trust is present, e.g. changes in personnel involved in the co-operation won't hinder the network from remaining operational. On the other hand, if the players are not well motivated to co-operate, if the network is extremely centralized structurally, or if the network has players holding very much more beneficial position compared to the others, systemic trust won't develop: trust tends to remain at the personal level, and is directed to some players only. Such networks won't generate results and benefits to its players, and most probably they won’t live very long. In other words, learning networks cannot solely be based on willingness to learn, but also on willingness to co-operate.