Profiling Attitudes for Personalized Information Provision

PAROS is a generic system under design whose goal is to offer personalization, recommendation, and other adaptation services to information providing systems. In its heart lies a rich user model able to capture several diverse aspects of user behavior, interests, preferences, and other attitudes. The user model is instantiated with profiles of users, which are obtained by analyzing and appropriately interpreting potentially arbitrary pieces of user-relevant information coming from diverse sources. These profiles are maintained by the system, updated incrementally as additional data on users becomes available, and used by a variety of information systems to adapt the functionality to the users’ characteristics

Second order ancillary: A differential view from continuity

Second order approximate ancillaries have evolved as the primary ingredient for recent likelihood development in statistical inference. This uses quantile functions rather than the equivalent distribution functions, and the intrinsic ancillary contour is given explicitly as the plug-in estimate of the vector quantile function. The derivation uses a Taylor expansion of the full quantile function, and the linear term gives a tangent to the observed ancillary contour. For the scalar parameter case, there is a vector field that integrates to give the ancillary contours, but for the vector case, there are multiple vector fields and the Frobenius conditions for mutual consistency may not hold. We demonstrate, however, that the conditions hold in a restricted way and that this verifies the second order ancillary contours in moderate deviations. The methodology can generate an appropriate exact ancillary when such exists or an approximate ancillary for the numerical or Monte Carlo calculation of $p$-values and confidence quantiles. Examples are given, including nonlinear regression and several enigmatic examples from the literature.Comment: Published in at http://dx.doi.org/10.3150/10-BEJ248 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

MDA-based ATL transformation to generate MVC 2 web models

Development and maintenance of Web application is still a complex and error-prone process. We need integrated techniques and tool support for automated generation of Web systems and a ready prescription for easy maintenance. The MDA approach proposes an architecture taking into account the development and maintenance of large and complex software. In this paper, we apply MDA approach for generating PSM from UML design to MVC 2Web implementation. That is why we have developed two meta-models handling UML class diagrams and MVC 2 Web applications, then we have to set up transformation rules. These last are expressed in ATL language. To specify the transformation rules (especially CRUD methods) we used a UML profiles. To clearly illustrate the result generated by this transformation, we converted the XMI file generated in an EMF (Eclipse Modeling Framework) model.Comment: International Journal of Computer Science & Information Technology-201

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

A statistical model of the population of first-order olfactory receptor neurons (ORNs) is proposed and analysed. It describes the relationship between stimulus intensity (odour concentration) and coding variables such as rate and latency of the population of several thousand sex-pheromone sensitive ORNs in male moths. Although these neurons likely express the same olfactory receptor, they exhibit, at any concentration, a relatively large heterogeneity of responses in both peak firing frequency and latency of the first action potential fired after stimulus onset. The stochastic model is defined by a multivariate distribution of six model parameters that describe the dependence of the peak firing rate and the latency on the stimulus dose. These six parameters and their mutual linear correlations were estimated from experiments in single ORNs and included in the multidimensional model distribution. The model is utilized to reconstruct the peak firing rate and latency of the message sent to the brain by the whole ORN population at different stimulus intensities and to establish their main qualitative and quantitative properties. Finally, these properties are shown to be in agreement with those found previously in a vertebrate ORN population

Representation of industrial products in the early stages of design: Drawing and artistic expression in industrial design

Comunicació presentada a ICERI 2018 11th annual International Conference of Education, Research and Innovation (Seville, Spain. 12-14 November, 2018)Hand drawing is a basic tool for industrial designers, as it allows them to represent and communicate concepts in an agile way during the initial design phase. Although we can find subjects related to drawing in the first years of all university degrees in industrial design, the way to implement the necessary activities is not always the most appropriate, and it may happen that, despite having practiced sketching, at the end of the course the students do not have the necessary skills to communicate their ideas effectively or adequately represent the reality that surrounds them. This paper proposes twelve groups of activities designed to help industrial design students acquire skills related to hand drawing. The activities were implemented during the second course of the Degree in Industrial Design and Product Development Engineering at Universitat Jaume I, improving those implemented during the last course. The paper analyzes and discusses the positive results of the innovations introduced, which improved the mean grade of the course by 4.48% with respect to the grade obtained the previous year

Transductive Learning with String Kernels for Cross-Domain Text Classification

For many text classification tasks, there is a major problem posed by the lack of labeled data in a target domain. Although classifiers for a target domain can be trained on labeled text data from a related source domain, the accuracy of such classifiers is usually lower in the cross-domain setting. Recently, string kernels have obtained state-of-the-art results in various text classification tasks such as native language identification or automatic essay scoring. Moreover, classifiers based on string kernels have been found to be robust to the distribution gap between different domains. In this paper, we formally describe an algorithm composed of two simple yet effective transductive learning approaches to further improve the results of string kernels in cross-domain settings. By adapting string kernels to the test set without using the ground-truth test labels, we report significantly better accuracy rates in cross-domain English polarity classification.Comment: Accepted at ICONIP 2018. arXiv admin note: substantial text overlap with arXiv:1808.0840

Negative Energies and a Constantly Accelerating Flat Universe

It has been shown that in the context of General Relativity (GR) enriched with a new set of discrete symmetry reversal conjugate metrics, negative energy states can be rehabilitated while avoiding the well-known instability issues. We review here some cosmological implications of the model and confront them with the supernovae and CMB data. The predicted flat universe constantly accelerated expansion phase is found to be in rather good agreement with the most recent cosmological data