996 resultados para Statistical maps.


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The Reeb graph of a scalar function represents the evolution of the topology of its level sets. In this video, we describe a near-optimal output-sensitive algorithm for computing the Reeb graph of scalar functions defined over manifolds. Key to the simplicity and efficiency of the algorithm is an alternate definition of the Reeb graph that considers equivalence classes of level sets instead of individual level sets. The algorithm works in two steps. The first step locates all critical points of the function in the domain. Arcs in the Reeb graph are computed in the second step using a simple search procedure that works on a small subset of the domain that corresponds to a pair of critical points. The algorithm is also able to handle non-manifold domains.

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We present an interactive map-based technique for designing single-input-single-output compliant mechanisms that meet the requirements of practical applications. Our map juxtaposes user-specifications with the attributes of real compliant mechanisms stored in a database so that not only the practical feasibility of the specifications can be discerned quickly but also modifications can be done interactively to the existing compliant mechanisms. The practical utility of the method presented here exceeds that of shape and size optimizations because it accounts for manufacturing considerations, stress limits, and material selection. The premise for the method is the spring-leverage (SL) model, which characterizes the kinematic and elastostatic behavior of compliant mechanisms with only three SL constants. The user-specifications are met interactively using the beam-based 2D models of compliant mechanisms by changing their attributes such as: (i) overall size in two planar orthogonal directions, separately and together, (ii) uniform resizing of the in-plane widths of all the beam elements, (iii) uniform resizing of the out-of-plane thick-nesses of the beam elements, and (iv) the material. We present a design software program with a graphical user interface for interactive design. A case-study that describes the design procedure in detail is also presented while additional case-studies are posted on a website. DOI:10.1115/1.4001877].

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Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

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In this paper, we propose a novel and efficient algorithm for modelling sub-65 nm clock interconnect-networks in the presence of process variation. We develop a method for delay analysis of interconnects considering the impact of Gaussian metal process variations. The resistance and capacitance of a distributed RC line are expressed as correlated Gaussian random variables which are then used to compute the standard deviation of delay Probability Distribution Function (PDF) at all nodes in the interconnect network. Main objective is to find delay PDF at a cheaper cost. Convergence of this approach is in probability distribution but not in mean of delay. We validate our approach against SPICE based Monte Carlo simulations while the current method entails significantly lower computational cost.

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Landscape is shaped by natural environment and increasingly by human activity. In landscape ecology, the concept of landscape can be defined as a kilometre-scale mosaic formed by different land-use types. In Helsinki Metropolitan Region, the landscape change caused by urbanization has accelerated after the 1950s. Prior to that, the landscape of the region was mainly only shaped by agriculture. The goal of this study was in addition to describing the landscape change to discuss the factors impacting the landscape change and evaluate thelandscape ecological impacts of the change. Three study areas at different distances from Helsinki city centre were chosen in order to look at the landscape change. Study areas were Malmi, Espoo and Mäntsälä regions representing different parts of the urban-to-rural gradient in 1955, 1975, 1990 and 2009. Land-use of the maps was then digitized into five classes: agricultural lands, semi-natural grasslands, built areas, waters and others using GIS methods. First, landscape change was studied using landscape ecological indices. Indices used were PLAND i.e. the proportions of the different land-use types in the landscape; MPS, SHEI and SHDI which describe fragmentation and heterogeneity of the landscape; and MSI and ED which are measures of patch shape. Second, landscape change was studied statistically in relation to topography, soil and urban structure of the study areas. Indicators used concerning urban structure were number of residents, car ownership and travel-related zones of urban form which indicate the degree of urban sprawl within the study areas. For the statistical analyses, each of the 9.25 x 9.25 km sized study areas was further divided into grids with resolution of 0.25 x 0.25 kilometres. Third, the changes in the green structure of the study areas were evaluated. The landscape change reflected by the proportions of the land-use types was the most notable in Malmi area where a large amount of agricultural land was developed from 1955 to 2009. The proportion of semi-natural grasslands also showed an interesting pattern in relation to urbanization. When urbanization started, a great number of agricultural lands were abandoned and turned into semi-natural grasslands but as the urbanization accelerated, the number of semi-natural grasslands started to decline because of urban densification. Landscape fragmentation and heterogeneity were the most widespread in Espoo study area which is not only because of the great differences in relative heights within the region but also its location in the rural-urban fringe. According to the results, urbanization induced agricultural lands to be more regular in shape both spatially and temporally whereas for built areas and semi-natural grasslands the impact of urbanization was reverse. Changes in landscape were the most insignificant in the most rural study area Mäntsälä. In Mäntsälä, built area per resident showed the greatest values indicating a widespread urban sprawl. The values were the smallest in highly urbanized Malmi study area. Unlike other study areas, in Mäntsälä the proportion of developing land in the ecologically disadvantageous cardependent zone was on the increase. On the other hand, the green structure of the Mäntsälä study area was the most advantageous whereas Malmi study area showed the most ecologically disadvantageous structure. Considering all the landscape ecological criteria used, the landscape structure of Espoo study area proved to be the best not least because of the great heterogeneity of its landscape. Thus the study confirmed the previous results according to which landscape heterogeneity is the most significant in areas exposed to a moderate human impact.

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The presence/absence data of twenty-seven forest insect taxa (e.g. Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, S Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models varied between species, possibly because some species may be associated with the characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocoetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

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The hot deformation behaviors of β brass in the temperature range of 550°C to 800°C and α-β brass in the temperature range of 450°C to 800°C have been characterized in the strain rate range of 0.001 to 100 s−1 using processing maps developed on the basis of the Dynamic Materials Model. The map for β brass revealed a domain of superplasticity in the entire temperature range and at strain rates lower than 1 s−1, with a maximum efficiency of power dissipation of about 68 pct. The temperature variation of the efficiency of power dissipation in the domain is similar to that of the diffusion coefficient for zinc in β brass, confirming that the diffusion-accommodated flow controls the superplasticity. The material undergoes microstructural instability in the form of adiabatic shear bands and strain markings at temperatures lower than 700°C and at strain rates higher than 10 s−1. The map for α-β brass revealed a wide domain for processing in the temperature range of 550°C to 800°C and at strain rates lower than 1 s−1, with a maximum efficiency of 54 pct occurring at about 750°C and 0.001 s−1. In the domain, the α phase undergoes dynamic recrystallization and controls the hot deformation of the alloy, while the β phase deforms superplastically. At strain rates greater than 1 s−1, α-β brass exhibits microstructural instabilities manifested as flow rotations at lower temperatures and localized shear bands at higher temperatures.

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Modern sample surveys started to spread after statistician at the U.S. Bureau of the Census in the 1940s had developed a sampling design for the Current Population Survey (CPS). A significant factor was also that digital computers became available for statisticians. In the beginning of 1950s, the theory was documented in textbooks on survey sampling. This thesis is about the development of the statistical inference for sample surveys. For the first time the idea of statistical inference was enunciated by a French scientist, P. S. Laplace. In 1781, he published a plan for a partial investigation in which he determined the sample size needed to reach the desired accuracy in estimation. The plan was based on Laplace s Principle of Inverse Probability and on his derivation of the Central Limit Theorem. They were published in a memoir in 1774 which is one of the origins of statistical inference. Laplace s inference model was based on Bernoulli trials and binominal probabilities. He assumed that populations were changing constantly. It was depicted by assuming a priori distributions for parameters. Laplace s inference model dominated statistical thinking for a century. Sample selection in Laplace s investigations was purposive. In 1894 in the International Statistical Institute meeting, Norwegian Anders Kiaer presented the idea of the Representative Method to draw samples. Its idea was that the sample would be a miniature of the population. It is still prevailing. The virtues of random sampling were known but practical problems of sample selection and data collection hindered its use. Arhtur Bowley realized the potentials of Kiaer s method and in the beginning of the 20th century carried out several surveys in the UK. He also developed the theory of statistical inference for finite populations. It was based on Laplace s inference model. R. A. Fisher contributions in the 1920 s constitute a watershed in the statistical science He revolutionized the theory of statistics. In addition, he introduced a new statistical inference model which is still the prevailing paradigm. The essential idea is to draw repeatedly samples from the same population and the assumption that population parameters are constants. Fisher s theory did not include a priori probabilities. Jerzy Neyman adopted Fisher s inference model and applied it to finite populations with the difference that Neyman s inference model does not include any assumptions of the distributions of the study variables. Applying Fisher s fiducial argument he developed the theory for confidence intervals. Neyman s last contribution to survey sampling presented a theory for double sampling. This gave the central idea for statisticians at the U.S. Census Bureau to develop the complex survey design for the CPS. Important criterion was to have a method in which the costs of data collection were acceptable, and which provided approximately equal interviewer workloads, besides sufficient accuracy in estimation.

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The influence of stacking fault energy (SFE) on the mechanism of dynamic recrystallization (DRX) during hot deformation of FCC metals is examined in the light of results from the power dissipation maps. The DRX domain for high SFE metals like Al and Ni occurred at homologous temperature below 0·7 and strain rates of 0·001 s−1 while for low SFE metals like Cu and Pb the corresponding values are higher than 0·8 and 100 s−1. The peak efficiencies of power dissipation are 50% and below 40% respectively. A simple model which considers the rate of interface formation (nucleation) involving dislocation generation and simultaneous recovery and the rate of interface migration (growth) occurring with the reduction in interface energy as the driving force, has been proposed to account for the effect of SFE on DRX. The calculations reveal that in high SFE metals, interface migration controls DRX while the interface formation is the controlling factor in low SFE metals. In the latter case, the occurrence of flow softening and oscillations could be accounted for by this model.

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A systematic structure analysis of the correlation functions of statistical quantum optics is carried out. From a suitably defined auxiliary two‐point function we are able to identify the excited modes in the wave field. The relative simplicity of the higher order correlation functions emerge as a byproduct and the conditions under which these are made pure are derived. These results depend in a crucial manner on the notion of coherence indices and of unimodular coherence indices. A new class of approximate expressions for the density operator of a statistical wave field is worked out based on discrete characteristic sets. These are even more economical than the diagonal coherent state representations. An appreciation of the subtleties of quantum theory obtains. Certain implications for the physics of light beams are cited.

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The absorption produced by the audience in concert halls is considered a random variable. Beranek's proposal [L. L. Beranek, Music, Acoustics and Architecture (Wiley, New York, 1962), p. 543] that audience absorption is proportional to the area they occupy and not to their number is subjected to a statistical hypothesis test. A two variable linear regression model of the absorption with audience area and residual area as regressor variables is postulated for concert halls without added absorptive materials. Since Beranek's contention amounts to the statement that audience absorption is independent of the seating density, the test of the hypothesis lies in categorizing halls by seating density and examining for significant differences among slopes of regression planes of the different categories. Such a test shows that Beranek's hypothesis can be accepted. It is also shown that the audience area is a better predictor of the absorption than the audience number. The absorption coefficients and their 95% confidence limits are given for the audience and residual areas. A critique of the regression model is presented.

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The effect of zirconium on the hot working characteristics of alpha and alpha-beta brass was studied in the temperature range of 500 to 850-degrees-C and the strain rate range of 0.001 to 100 s-1. On the basis of the flow stress data, processing maps showing the variation of the efficiency of power dissipation (given by [2m/(m+1)] where m is the strain rate sensitivity) with temperature and strain rate were obtained. The addition of zirconium to alpha brass decreased the maximum efficiency of power dissipation from 53 to 39%, increased the strain rate for dynamic recrystallization (DRX) from 0.001 to 0.1 s-1 and improved the hot workability. Alpha-beta brasses with and without zirconium exhibit a domain in the temperature range from 550 to 750-degrees-C and at strain rates lower than 1 s-1 with a maximum efficiency of power dissipation of nearly 50 % occurring in the temperature range of 700 to 750-degrees-C and a strain rate of 0.001 s-1. In the domain, the alpha phase undergoes DRX and controls the hot deformation of the alloy whereas the beta phase deforms superplastically. The addition of zirconium to alpha-beta brass has not affected the processing maps as it gets partitioned to the beta phase and does not alter the constitutive behavior of the alpha phase

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The constitutive behaviour of agr — nickel silver in the temperature range 700–950 °C and strain rate range 0.001–100 s–1 was characterized with the help of a processing map generated on the basis of the principles of the ldquodynamic materials modelrdquo of Prasadet al Using the flow stress data, processing maps showing the variation of the efficiency of power dissipation (given by 2m/(m+1) wherem is the strain-rate sensitivity) with temperature and strain rate were obtained, agr-nickel silver exhibits a single domain at temperatures greater than 750 °C and at strain rates lower than 1s–1, with a maximum efficiency of 38% occurring at about 950 °C and at a strain rate of 0.1 s–1. In the domain the material undergoes dynamic recrystallization (DRX). On the basis of a model, it is shown that the DRX is controlled by the rate of interface formation (nucleation) which depends on the diffusion-controlled process of thermal recovery by climb. At high strain rates (10 and 100s–1) the material undergoes microstructural instabilities, the manifestations of which are in the form of adiabatic shear bands and strain markings.