Categorical Missing Data Imputation Using Fuzzy Neural Networks with Numerical and Categorical Inputs

There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson’s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.

Newer optics efficiently mix, dim, and color-tune LED light

Low-cost, plastic-injected optics mix light from different color LED dies without a significant decrease in average brightness, simplifying luminaire design both optically and electronically. In solid-state lighting, high-flux and high-color rendering index (CRI) light engines may be achieved by arraying and mixing the light from different color dies or phosphors, or a combination of the two, in the LED package. However, these nonhomogeneous sources, when combined with luminaire optics, tend to produce patterns with undesirable artifacts such as spatial and angular nonuniformities and color separation.

Neighborhood mobility: A Long-Gone Pardigm? Approaching proximity and land use mix using data from home based surveys.

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. Policies trying to increase walking within urban mobility modal split usually highlight the importance of the functional patterns and the environmental quality of the urban space as major drivers of citizens modal choices. Functional characteristics would be mainly associated to an appropriate mix of land uses within neighbourhoods, whereas environmental quality would be associated to the characteristics of urban spaces. The purpose of this research is threefold: first, to identify relevant proxy indicators, which could characterize pedestrian-friendly land use mix and environmental quality. Second, to assess, for both traits, existing disparities among neighbourhoods in a major metropolitan area. And finally, to explore the association between both indicators and children mobility patterns: according to their built environment, which neighbourhoods have a greater proportion of children and, how is their mobility? Using data from the 2004 household mobility survey in the 128 neighbourhoods of the municipality of Madrid, this paper concludes that potentially favourable conditions at the neighbourhood level seem to have only a modest influence in,mobility patterns , in terms of both, selection of closer destinations and a higher share of walking within modal split. The citys policy choices, with intensive investment in road and public transport infrastructure may explain why short-distance mobility is not as important as it could have been expected in those neighbourhoods with more pedestrian-friendly conditions. The metropolitan transport system is providing mobility conditions, which make far-away destinations attractive to most citizens.

Combining Text and Graphics for Interactive Exploration of Behavior Datasets

Modern sensor technologies and simulators applied to large and complex dynamic systems (such as road traffic networks, sets of river channels, etc.) produce large amounts of behavior data that are difficult for users to interpret and analyze. Software tools that generate presentations combining text and graphics can help users understand this data. In this paper we describe the results of our research on automatic multimedia presentation generation (including text, graphics, maps, images, etc.) for interactive exploration of behavior datasets. We designed a novel user interface that combines automatically generated text and graphical resources. We describe the general knowledge-based design of our presentation generation tool. We also present applications that we developed to validate the method, and a comparison with related work.

Neighbourhood mobility: a longgone Paradigm? Approaching "proximity" and "land use mix" using data from home-based surveys

Policies trying to increase walking within urban mobility modal split usually highlight the importance of the functional patterns and the environmental quality of the urban space as major drivers of citizens modal choices. Functional characteristics would be mainly associated to an appropriate mix of land uses within neighbourhoods, whereas environmental quality would be associated to the characteristics of urban spaces. The purpose of this research is threefold: first, to identify relevant proxy indicators, which could characterize pedestrian-friendly land use mix and environmental quality. Second, to assess, for both traits, existing disparities among neighbourhoods in a major metropolitan area. And finally, to explore the association between both indicators and children mobility patterns: according to their built environment, which neighbourhoods have a greater proportion of children and, how is their mobility? Using data from the 2004 household mobility survey in the 128 neighbourhoods of the municipality of Madrid, this paper concludes that potentially favourable conditions at the neighbourhood level seem to have only a modest influence in,mobility patterns , in terms of both, selection of closer destinations and a higher share of walking within modal split. The city s policy choices, with intensive investment in road and public transport infrastructure may explain why short-distance mobility is not as important as it could have been expected in those neighbourhoods with more pedestrian-friendly conditions. The metropolitan transport system is providing mobility conditions, which make far-away destinations attractive to most citizens.

Identifying wind power ramp causes from multivariate datasets: a methodological proposal and its application to reanalysis data.

Forecasting abrupt variations in wind power generation (the so-called ramps) helps achieve large scale wind power integration. One of the main issues to be confronted when addressing wind power ramp forecasting is the way in which relevant information is identified from large datasets to optimally feed forecasting models. To this end, an innovative methodology oriented to systematically relate multivariate datasets to ramp events is presented. The methodology comprises two stages: the identification of relevant features in the data and the assessment of the dependence between these features and ramp occurrence. As a test case, the proposed methodology was employed to explore the relationships between atmospheric dynamics at the global/synoptic scales and ramp events experienced in two wind farms located in Spain. The achieved results suggested different connection degrees between these atmospheric scales and ramp occurrence. For one of the wind farms, it was found that ramp events could be partly explained from regional circulations and zonal pressure gradients. To perform a comprehensive analysis of ramp underlying causes, the proposed methodology could be applied to datasets related to other stages of the wind-topower conversion chain.