992 resultados para Variability Models
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Variability management is one of the major challenges in software product line adoption, since it needs to be efficiently managed at various levels of the software product line development process (e.g., requirement analysis, design, implementation, etc.). One of the main challenges within variability management is the handling and effective visualization of large-scale (industry-size) models, which in many projects, can reach the order of thousands, along with the dependency relationships that exist among them. These have raised many concerns regarding the scalability of current variability management tools and techniques and their lack of industrial adoption. To address the scalability issues, this work employed a combination of quantitative and qualitative research methods to identify the reasons behind the limited scalability of existing variability management tools and techniques. In addition to producing a comprehensive catalogue of existing tools, the outcome form this stage helped understand the major limitations of existing tools. Based on the findings, a novel approach was created for managing variability that employed two main principles for supporting scalability. First, the separation-of-concerns principle was employed by creating multiple views of variability models to alleviate information overload. Second, hyperbolic trees were used to visualise models (compared to Euclidian space trees traditionally used). The result was an approach that can represent models encompassing hundreds of variability points and complex relationships. These concepts were demonstrated by implementing them in an existing variability management tool and using it to model a real-life product line with over a thousand variability points. Finally, in order to assess the work, an evaluation framework was designed based on various established usability assessment best practices and standards. The framework was then used with several case studies to benchmark the performance of this work against other existing tools.
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The irrigation application is one of the most useful techniques in tropical environments, especially during dry seasons. In this study, CO2 efflux, temperature and soil moisture were studied in a field sampled with a grid having 48 points distributed in 35 x 25 m, under irrigation promoted by a sprinkler located at the center of the area, provoking different levels of water deposition, with maximum irrigation levels of 44.4 and 62.2 mm in points closer to the sprinkler. The results show that the emissions, temperature and moisture were strongly affected by the two irrigations events, having a total water level added of 106,6 mm for the points next to the sprinkler and zero for the most distant points from it. The maps of space variation of the variables, as well as the linear correlation between them, indicate that the emissions were positively related to the soil moisture and negative correlated to the soil temperature only after the irrigations events. The special variability models of soil CO2 emission changed from exponential to spherical after the irrigations events. Such results indicate that soil moisture is among possible controlling factors of the soil CO2 emission, because even with reductions in soil temperature provoked by the wetness, emissions increased strongly.
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Estudos regionais mais detalhados, utilizando modelos de paisagem e geoestatística, têm demonstrado que, em áreas consideradas homogêneas, sob uma única classe de solo, existe dependência espacial de atributos granulométricos. Visando a avaliar a variabilidade espacial de atributos granulométricos em Latossolo Vermelho eutroférrico, foram feitas amostragens do solo em intervalos regulares de 50 m, em forma de malha, totalizando 306 pontos de amostragem. Foram coletadas amostras nas profundidades de 0-0,2 m e 0,6-0,8 m para a determinação da argila, silte, areia total (AT), areia grossa (AG), areia média (AM), areia fina (AF) e areia muito fina (AMF). Os dados foram submetidos à análise estatística descritiva, geoestatística e interpolação por krigagem. Os valores do coeficiente de variação apresentaram-se baixos para argila, médios para silte, AT, AF, AM e AMF e altos para AG. Observou-se ocorrência de dependência espacial para todas as variáveis com grau moderado de dependência espacial, com os maiores alcances ocorrendo na profundidade de 0-0,2 m. Os latossolos, apesar de serem homogêneos, mesmo em áreas de mesma classe de solo e manejo, apresentaram variabilidade diferenciada para os atributos granulométricos.
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This paper proposes a systematic approach to management of variability modelsdriven and aspects using the mechanisms of approaches Aspect-Oriented Software Development (AOSD) and Model-Driven Development (MDD). The main goal of the approach, named CrossMDA-SPL, is to improve the management(gerência), modularization and isolation ou separation of the variability of the LPSs of architecture in a high level of abstraction (model) at the design and implementing phases of development Software Product Lines (SPLs), exploiting the synergy between AOSD and MDD. The CrossMDA-SPL approach defines some artifacts basis for advance the separation clear in between the mandatory (bounden) and optional features in the architecture of SPL. The artifacts are represented by two models named: (i) core model (base domain) - responsible for specify the common features the all members of the SPL, and (ii) variability model - responsible for represent the variables features of SPL. In addition, the CrossMDA-SPL approach is composed of: (i) guidelines for modeling and representation of variability, (ii) CrossMDA-SPL services and process, and (iii) models of the architecture of SPL or product instance of SPL. The guidelines use the advantages of AOSD and MDD to promote a better modularization of the variable features of the architecture of SPL during the creation of core and variability models of the approach. The services and sub-processes are responsible for combination automatically, through of process of transformation between the core and variability models, and the generation of new models that represent the implementation of the architecture of SPL or a instance model of SPL. Mechanisms for effective modularization of variability for architectures of SPL at model level. The concepts are described and measured with the execution of a case study of an SPL for management systems of transport electronic tickets
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Em uma paisagem natural, os solos apresentam uma ampla variação dos atributos químicos, tanto vertical como horizontal, resultante da interação dos diversos fatores de formação envolvidos. Este trabalho foi desenvolvido em Guariba-SP, com o objetivo de avaliar a variabilidade espacial do pH, cálcio (Ca), magnésio (Mg) e saturação por bases (V%) em um Latossolo Vermelho eutroférrico sob cultivo de cana-de-açúcar, utilizando-se métodos da estatística clássica, análise geoestatística e técnica de interpolação de dados, com a finalidade de observar padrões de ocorrência destes atributos na paisagem. No terço inferior da encosta, após análise detalhada da variação do gradiente do declive, caracterizaram-se dois compartimentos (I e II), sob os quais os solos foram amostrados nos pontos de cruzamento de uma malha, com intervalos regulares de 50m, perfazendo um total de 206 pontos, nas profundidades de 0,0-0,2m e 0,6-0,8m. Os maiores alcances foram observados na profundidade de 0,0-0,2m para todos os atributos estudados, com exceção do cálcio que apresentou comportamento inverso, refletindo os efeitos do maior grau de intemperismo e do manejo na variabilidade natural dos solos. Pequenas variações, nas formas do relevo, condicionam variabilidade diferenciada para os atributos químicos.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Thermal effects in uncontrolled factory environments are often the largest source of uncertainty in large volume dimensional metrology. As the standard temperature for metrology of 20°C cannot be achieved practically or economically in many manufacturing facilities, the characterisation and modelling of temperature offers a solution for improving the uncertainty of dimensional measurement and quantifying thermal variability in large assemblies. Technologies that currently exist for temperature measurement in the range of 0-50°C have been presented alongside discussion of these temperature measurement technologies' usefulness for monitoring temperatures in a manufacturing context. Particular aspects of production where the technology could play a role are highlighted as well as practical considerations for deployment. Contact sensors such as platinum resistance thermometers can produce accuracy closest to the desired accuracy given the most challenging measurement conditions calculated to be ∼0.02°C. Non-contact solutions would be most practical in the light controlled factory (LCF) and semi-invasive appear least useful but all technologies can play some role during the initial development of thermal variability models.
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Software product line modeling aims at capturing a set of software products in an economic yet meaningful way. We introduce a class of variability models that capture the sharing between the software artifacts forming the products of a software product line (SPL) in a hierarchical fashion, in terms of commonalities and orthogonalities. Such models are useful when analyzing and verifying all products of an SPL, since they provide a scheme for divide-and-conquer-style decomposition of the analysis or verification problem at hand. We define an abstract class of SPLs for which variability models can be constructed that are optimal w.r.t. the chosen representation of sharing. We show how the constructed models can be fed into a previously developed algorithmic technique for compositional verification of control-flow temporal safety properties, so that the properties to be verified are iteratively decomposed into simpler ones over orthogonal parts of the SPL, and are not re-verified over the shared parts. We provide tool support for our technique, and evaluate our tool on a small but realistic SPL of cash desks.
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Utilizing the framework of effective surface quasi-geostrophic (eSQG) theory, we explored the potential of reconstructing the 3D upper ocean circulation structures, including the balanced vertical velocity (w) field, from high-resolution sea surface height (SSH) data of the planned SWOT satellite mission. Specifically, we utilized the 1/30°, submesoscale-resolving, OFES model output and subjected it through the SWOT simulator that generates the along-swath SSH data with expected measurement errors. Focusing on the Kuroshio Extension region in the North Pacific where regional Rossby numbers range from 0.22 to 0.32, we found that the eSQG dynamics constitutes an effective framework for reconstructing the 3D upper ocean circulation field. Using the modeled SSH data as input, the eSQG-reconstructed relative vorticity (ζ) and w fields are found to reach a correlation of 0.7–0.9 and 0.6–0.7, respectively, in the 1,000m upper ocean when compared to the original model output. Degradation due to the SWOT sampling and measurement errors in the input SSH data for the ζ and w reconstructions is found to be moderate, 5–25% for the 3D ζ field and 15-35% for the 3D w field. There exists a tendency for this degradation ratio to decrease in regions where the regional eddy variability (or Rossby number) increases.
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A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.
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