890 resultados para METRICS
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We present a class of three-dimensional integrable structures associated with the Darboux-Egoroff metric and classical Euler equations of free rotations of a rigid body. They are obtained as canonical structures of rational Landau-Ginzburg potentials and provide solutions to the Painleve VI equation.
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The quality and the power of human activities affect the external environment in different ways that can be measured and evaluated by means of several approaches and indicators. While the scientific community has been publishing several proposals for sustainable development indicators, there is still no consensus regarding the best approach to the use of these indicators and their reliability to measure sustainability. It is important, therefore, to question the effectiveness of sustainable development indicators in an effort to continue in the search for sustainability. This paper compares the results obtained with emergy accounting with five global Sustainability Metrics (SMs) proposed in the literature to verify if metrics are communicating coherent and similar information to guide decision makers towards sustainable development. Results obtained using emergy indices are discussed with the aid of emergy ternary diagrams. Metrics are confronted with emergy results, and the degree of variability among them is analyzed using a correlation matrix created for the Mercosur nations. The contrast of results clearly shows that metrics arrive at different interpretations about the sustainability of the nations studied, but also that some metrics may be grouped and used more prudently. Mercosur is presented as a case study to highlight and explain the discrepancies and similarities among Sustainability Metrics, and to expose the extent of emergy accounting. (C) 2010 Elsevier Ltd. All rights reserved.
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Many topics related to association mining have received attention in the research community, especially the ones focused on the discovery of interesting knowledge. A promising approach, related to this topic, is the application of clustering in the pre-processing step to aid the user to find the relevant associative patterns of the domain. In this paper, we propose nine metrics to support the evaluation of this kind of approach. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Some experiments were done in order to present how the metrics can be used and their usefulness. © 2013 Springer-Verlag GmbH.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Issues related to association mining have received attention, especially the ones aiming to discover and facilitate the search for interesting patterns. A promising approach, in this context, is the application of clustering in the pre-processing step. In this paper, eleven metrics are proposed to provide an assessment procedure in order to support the evaluation of this kind of approach. To propose the metrics, a subjective evaluation was done. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Besides, the metrics do the users think about aspects related to the problems and provide a flexible way to solve them. Some experiments were done in order to present how the metrics can be used and their usefulness.
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Methods of recording soil erosion using photographs exist but they are not commonly considered in scientific studies. Digital images may hold an expressive amount of information that can be extracted quickly in different manners. The investigation of several metrics that were initially developed for landscape ecology analysis constitutes one method. In this study we applied a method of landscape metrics to quantify the spatial configuration of surface micro-topography and erosion-related features, in order to generate a possible complementary tool for environmental management. In a 3.7 m wide and 9.7 m long soil box used during a rainfall simulation study, digital images were systematically acquired in four instances: (a) when the soil was dry; (b) after a short duration rain for initial wetting; (c) after the first erosive rain; and (d) after the 2nd erosive rain. Thirteen locations were established in the box and digital photos were taken at these locations with the camera positioned at the same orthogonal distance from the soil surface under the same ambient light intensity. Digital photos were converted into bimodal images and seven landscape metrics were analyzed: percentage of land, number of patches, density of patches, largest patch index, edge density, shape index, and fractal dimension. Digital images were an appropriate tool because they can generate data very quickly. The landscape metrics were sensitive to changes in soil surface micro-morphology especially after the 1st erosive rain event, indicating significant erosional feature development between the initial wetting and first erosive rainfall. The method is considered suitable for spatial patterns of soil micro-topography evolution from rainfall events that bear similarity to landscape scale pattern evolution from eco-hydrological processes. Although much more study is needed for calibrating the landscape metrics at the micro-scale, this study is a step forward in demonstrating the advantages of the method.
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Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.
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There is a wide range of telecommunications services that transmit voice, video and data through complex transmission networks and in some cases, the service has not an acceptable quality level for the end user. In this sense the study of methods for assessing video quality and voice have a very important role. This paper presents a classification scheme, based on different criteria, of the methods and metrics that are being studied in recent years. This paper presents how the video quality is affected by degradation in the transmission channel in two kinds of services: Digital TV (ISDB-TB) due the fading in the air interface and video streaming service on an IP network due packet loss. For Digital TV tests was set up a scenario where the digital TV transmitter is connected to an RF channel emulator, where are inserted different fading models and at the end, the videos are saved in a mobile device. The tests of streaming video were performed in an isolated scenario of IP network, which are scheduled several network conditions, resulting in different qualities of video reception. The video quality assessment is performed using objective assessment methods: PSNR, SSIM and VQM. The results show how the losses in the transmission channel affects the quality of end-user experience on both services studied.
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The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shed light on the relationship between semantic and structural parameters of complex networks. They also indicate that when combined with traditional techniques the complex network approach may be useful to enhance the discrimination of senses in large texts. Copyright (C) EPLA, 2012
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Estimators of home-range size require a large number of observations for estimation and sparse data typical of tropical studies often prohibit the use of such estimators. An alternative may be use of distance metrics as indexes of home range. However, tests of correlation between distance metrics and home-range estimators only exist for North American rodents. We evaluated the suitability of 3 distance metrics (mean distance between successive captures [SD], observed range length [ORL], and mean distance between all capture points [AD]) as indexes for home range for 2 Brazilian Atlantic forest rodents, Akodon montensis (montane grass mouse) and Delomys sublineatus (pallid Atlantic forest rat). Further, we investigated the robustness of distance metrics to low numbers of individuals and captures per individual. We observed a strong correlation between distance metrics and the home-range estimator. None of the metrics was influenced by the number of individuals. ORL presented a strong dependence on the number of captures per individual. Accuracy of SD and AD was not dependent on number of captures per individual, but precision of both metrics was low with numbers of captures below 10. We recommend the use of SD and AD instead of ORL and use of caution in interpretation of results based on trapping data with low captures per individual.
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[ES] La aparición de Google Scholar Metrics en abril de 2012 como nuevo sistema de evaluación bibliométrica de revistas científicas a partir del recuento de las citas bibliográficas que estas han recibido en Google Scholar, abre nuevas posibilidades para la medición del impacto de las revistas de humanidades. El objetivo de este trabajo es comprobar el alcance de este producto, a partir del análisis de la cobertura que muestra de las revistas españolas de Historia. Las búsquedas bibliográficas se efectuaron entre el 5 y 6 de diciembre de 2012. Se han identificado 69 revistas, cifra que representa tan solo un 24% de las revistas españolas de Historia. Los valores del índice h alcanzados por las revistas son minúsculos lo que hace que el ranking carezca de poder discriminatorio. Se propone un cambio en el diseño de Google Scholar Metrics para adaptarse a los patrones de producción y citación de la Historia, en particular, y las Humanidades, en general.
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The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.
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Purpose – The purpose of the present analysis is to show that HR systems are not always designed in ways that consider the well-being of employees. In particular, performance metric methods seem to be designed with organizational goals in mind while focusing less on what employees need and desire. Design/methodology/approach – A literature review and multiple case-study method was utilized. Findings – The analysis showed that performance metrics should be revaluated by executives and HR professionals if they seek to develop socially responsible organizational cultures which care about the well-being of employees. Originality/value – The paper exposes the fact that performance appraisal techniques can be rooted in methodologies that ignore or deemphasize the value of employee well-being. The analysis provides a context in which all HR practices can be questioned in relation to meeting the standards of a social justice agenda in the area of corporate social responsibility.