Discrete choice modelling incorporating attribute thresholds of perception

In this paper we formulate a discrete choice model that incorporates thresholds in the perception of attribute changes. The model considers multiple options and allows changes in several attributes. We postulate that if thresholds exist they could be random, differ between individuals, and even be a function of socio-economic characteristics and choice conditions. Our formulation allows estimation of the parameters of the threshold probability distribution starting from information about choices. The model is applied to synthetic data and also to real data from a stated preference survey. We found that where perception thresholds exist in the population, the use of models without them leads to errors in estimation and prediction. Clearly, the effect is more relevant when the typical size of change in the attribute value is comparable with the threshold, and when the contribution of this attribute in the utility function is substantial. Finally, we discuss the implications of the threshold model for estimation of the benefits of transport investments, and show that where thresholds exist, models that do not represent them can overestimate benefits substantially

Engaging women into STEM in Latin America: W-STEM project

[EN]Significant progress has been made during the last decades to achieve gender equality, but there is still much work to do. In particular, the gender gap is pronounced in the science, technology, engineering, and mathematics (STEM) fields at all levels of education and labour market. In those areas, the women participation remains low, although there are differences from country to country. In the Latin American context, there is a need for carrying out studies to collect quality data about the actual situation of women in STEM. Although some available data show a high proportion of women in Latin American university education, they are a minority in STEM programs. Moreover, this problem is particularly severe in Latin America because of the biases or cultural norms that influence female behaviour. In this context, the W-STEM project seeks to improve strategies and mechanisms for attracting, accessing, and guiding women in Latin America in STEM higher education programs. This work aims to describe the main results to prepare a set of attraction campaigns in secondary schools in the Latin American countries involved in the project (Chile, Colombia, Costa Rica, Ecuador, Mexico). In particular, a self-assessment tool about gender equality in higher education institutions in Latin America, an interview protocol for female role models, and a mobile application to show those role models

Buying a car and the street: Transport justice and urban space distribution

In dense cities, the smaller the consumption of land per inhabitant, the more disruptive the use of individual transport as a sustainable transport mode. The impact of private vehicles on transport justice in the spatial dimension is worse there. The unbalanced distribution of street space in dense cities implies considerable challenges for sustainable transport. This paper explores the relationships between mode share, street space distribution, and those spaces’ construction costs. Based on justice principles, the paper discusses a fair distribution of street space in Bogotá, where injustices are apparent. We find imbalances in the prioritization of space for specific street users, with an accent on space for private motorization despite a visible change in investment in other spaces for urban mobility in recent years. Findings provide empirical evidence for informing policy and decision-making related to public investment in urban space and its distribution in practice

Evolving training sets for improved transfer learning in brain computer interfaces

A new proof-of-concept method for optimising the performance of Brain Computer Interfaces (BCI) while minimising the quantity of required training data is introduced. This is achieved by using an evolutionary approach to rearrange the distribution of training instances, prior to the construction of an Ensemble Learning Generic Information (ELGI) model. The training data from a population was optimised to emphasise generality of the models derived from it, prior to a re-combination with participant-specific data via the ELGI approach, and training of classifiers. Evidence is given to support the adoption of this approach in the more difficult BCI conditions: smaller training sets, and those suffering from temporal drift. This paper serves as a case study to lay the groundwork for further exploration of this approach

Strengthening study habits through information and communication technologies

El propósito de la investigación correspondió a fortalecer el hábito a través del mejoramiento de la lectoescritura a partir de las Tecnologías de Información y Comunicación como herramienta estratégica. Desde los procesos investigativo derivados de la integración de la Investigación como Estrategia Pedagógica. Metodológicamente la investigación es de tipo cuantitativo- descriptivo. La unidad de análisis estuvo constituida por 60 estudiantes pertenecientes a los grados tercero y quinto, entre las edades de 7 a 12 años. Los resultados derivados dan cuenta de los procesos de mejoramiento y fortalecimiento de los hábitos de estudio en los estudiantes involucrados en el proceso investigativo a través del uso de las TIC. A través del proceso investigativo se puede concluir que como estrategia de enseñanza aprendizaje es positivo la implementación de las TIC a fin de mejorar los resultados obtenidos por los estudiantes en las pruebas locales y nacionalesThe purpose of the research was to strengthen the habit through the improvement of literacy based on Information and Communication Technologies as a strategic tool. From the research processes derived from the integration of Research as a Pedagogical Strategy. Methodologically, the research is quantitative-descriptive. The analysis unit consisted of 60 students belonging to the third and fifth grades, between the ages of 7 to 12 years. The derived results show the processes of improvement and strengthening of study habits in students involved in the research process through the use of ICT. Through the research process it can be concluded that the implementation of ICTs is positive as a teaching-learning strategy in order to improve the results obtained by students in local and national test

Understanding valuation of travel time changes: are preferences different under different stated choice design settings?

Stated choice (SC) experiments are the most popular method to estimate the value of travel time changes (VTTC) of a population. In the simplest VTTC experiment, the SC design variables are time changes and cost changes. The levels of these variables create a particular setting from which preferences are inferred. This paper tries to answer the question “do preferences vary with SC settings?”. For this, we investigate the role of the variables used in the SC experiment on the estimation of the set of VTTC (i.e. mean and covariates). Ideally, one would like to observe the same individuals completing different SC experiments. Since that option is not available, an alternative approach is to use a large dataset of responses, and split it according to different levels of the variable of interest. We refer to this as partial data analysis. The estimation of the same model on each sub-sample provides insights into potential effects of the variable of interest. This approach is applied in relation to three design variables on the data for the last national VTTC study in the UK, using state-of-the-art model specifications. The results show several ways in which the estimated set of VTTC can be affected by the levels of SC design variables. We conclude that model estimates (including the VTTC and covariates) are different in different settings. Hence by focussing the survey on specific settings, sample level results will be affected accordingly. Our findings have implications for appraisal and can inform the construction of future SC experiments

Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach

In recent years we have seen an explosion of research seeking to understand the role that rules and heuristics might play in improving the predictive capability of discrete choice models, as well as delivering willingness to pay estimates for specific attributes that may (and often do) differ significantly from estimates based on a model specification that assumes all attributes are relevant. This paper adds to that literature in one important way—it explicitly recognises the endogeneity issues raised by typical attribute non-attendance treatments and conditions attribute parameters on underlying unobserved attribute importance ratings. We develop a hybrid model system involving attribute processing and outcome choice models in which latent variables are introduced as explanatory variables in both parts of the model, explaining the answers to attribute processing questions and explaining heterogeneity in marginal sensitivities in the choice model. The resulting empirical model explains how lower latent attribute importance leads to a higher probability of indicating that an attribute was ignored or that it was ranked as less important, as well as increasing the probability of a reduced value for the associated marginal utility coefficient in the choice model. The model does so by treating the answers to information processing questions as dependent rather than explanatory variables, hence avoiding potential risk of endogeneity bias and measurement error

ASASSN-15lu is a Type Ia Supernova

We report spectroscopic classification of ASASSN-15lu (ATel #7698) in SDSS J132112.88+401556.7 (z=0.035037, via NED) through inspection of an optical spectrum (range 370-680 nm, resolution 0.8 nm), obtained with the 2.3-m Bok telescope (+ Boller & Chivens spectrograph) at Kitt Peak on 2015 June 24.2 UT