Binary ant colony optimization applied to variable screening in the Mahalanobis–Taguchi System

This work presents the application of the Mahalanobis–Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.     

Application of SVM-RFE on EEG signals for detecting the most relevant scalp regions linked to affective valence processing

In this work, event related potentials (ERPs) induced by visual stimuli categorized with different value of affective valence are studied. EEG signals are recorded during visualization of selected pictures belonging to International Affective Picture System (IAPS). A Morlet wavelet filter is used to transform the EEG input space to a topography-time–frequency feature space. Support vector machine-recursive feature elimination (SVM-RFE) is applied for detecting scalp spectral dynamics of interest (SSDOIs) in this feature space, allowing to identify the most relevant time intervals, frequency bands and EEG channels. This feature selection method has proven to outperform the classical t-test in the discrimination of brain cortex regions involved in affective valence processing. Furthermore, the presented combination of feature extraction and selection techniques can be applied as an alternative in other different clinical applications.     

Cooperative controllers for highways based on human experience

The AUTOPIA program has been working on the development of intelligent autonomous vehicles for the last 10 years. Its latest advances have focused on the development of cooperative man?uvres based on communications involving several vehicles. However, so far, these man?uvres have been tested only on private tracks that emulate urban environments. The first experiments with autonomous vehicles on real highways, in the framework of the grand cooperative driving challenge (GCDC) where several vehicles had to cooperate in order to perform cooperative adaptive cruise control (CACC), are described. In this context, the main challenge was to translate, through fuzzy controllers, human driver experience to these scenarios. This communication describes the experiences deriving from this competition, specifically that concerning the controller and the system implemented in a Citröen C3.     

Latent variable based model predictive control: Ensuring validity of predictions

This paper presents a methodology to constrain the optimisation problem in LV-MPC so that validity of predictions can be ascertained. LV-MPC is a model-based predictive control methodology implemented in the space of the latent variables and is based on a linear predictor. Provided real processes are non-linear, there is model-process mismatch, and under tight control, the predictor can be used for extrapolation. Extrapolation leads to bad predictions which deteriorates control performance, hence the interest in validity of predictions. In the proposed approach first two validity indicators on predictions are defined. The novelty in the two indicators proposed is they neglect past data, and so validity of predictions is ascertained in terms of future moves which are actually the degrees of freedom in the optimisation. Second, the indicators are introduced in the optimisation as constraints. Provided the indicators are quadratic, recursive optimisation with linearised constraints is implemented. A MIMO example shows how ensuring validity of predictions neglecting past data can improve closed-loop performance, specially under tight control outside the identification region.     

Digital business reporting standards: mapping the battle in France

Government agencies use information technology extensively to collect business data for regulatory purposes. Data communication standards form part of the infrastructure with which businesses must conform to survive. We examine the development of, and emerging competition between, two open business reporting data standards adopted by government bodies in France; Electronic Data Interchange for Administration, Commerce and Transport (EDIFACT) (incumbent) and eXtensible Business Reporting Language (XBRL) (challenger). The research explores whether an incumbent may be displaced in a setting in which the contest is unresolved. Latour's translation map is applied to trace the enrollments and detours in the battle. We find that regulators play an important role as allies in the development of the standards. The antecedent networks in which the standards are located embed strong beliefs that become barriers to collaboration and fuel the battle. One of the key differentiating attitudes is whether speed is more important than legitimacy. The failure of collaboration encourages competition. The newness of XBRL's technology just as regulators need to respond to an economic crisis and its adoption by French regulators not using EDIFACT create an opportunity for the challenger to make significant network gains over the longer term. ANT also highlights the importance of the preservation of key components of EDIFACT in ebXML.     

Application of the Resources Model to the Supervision of an Automated Process

The present study was designed to ascertain how far flagging up potential errors can improve the automatic interpretation of technical documents. We used the resources model to analyze the supervised retro-conversion of architectural floor plans from the perspective of distributed cognition. Results showed that automated assistance helps users to correct errors spotted by the system and saves time. Surprisingly, they also showed that flagging up possible errors may make users less effective in identifying and correcting errors that go unnoticed by the system. Responses to a questionnaire probing the participants’ confidence in the system suggested that they were so trusting that they lowered their vigilance in those areas that had not been signaled by the system, leading to the identification of fewer errors there. Thus, although the participants’ confidence in the automated assistance system led to improved performances in those areas it highlighted, it also meant that areas to which the system did not draw attention were less thoroughly checked.     

Efficient implementation of the implicit error correction nVoD schema

Implicit Error Correction is a near Video-on-Demand (nVoD) schema that trades bandwidth utilization for initial playback delay while potentially allowing an infinite number of users. Additionally, it provides error protection without further bandwidth increase by exploiting the implicit redundancy of nVoD protocols, using linear combinations of the segments transmitted in a given time slot. This paper introduces a new implementation that outperforms the original schema by adding two new mechanisms: redundancy channels and feedback error correction.     

A differential inclusion approach for modeling and analysis of dynamical systems under uncertainty

In this paper we deal with the application of differential inclusions to modeling nonlinear dynamical systems under uncertainty in parameters. In this case, differential inclusions seem to be better suited to modeling practical situations under uncertainty and imprecision than formulations by means of fuzzy differential equations. We develop a practical algorithm to approximate the reachable sets of a class of nonlinear differential inclusion, which eludes the computational problems of a previous set-valued version of the Heun’s method. Our algorithm is based on a complete discretization (time and state space) of the differential inclusion and it suits hardware features, handling the memory used by the method in a controlled fashion during all iterations. As a case of study, we formulate a differential inclusion to model an epidemic outbreak of dengue fever under Cuban conditions. The model takes into account interaction of human and mosquito populations as well as vertical transmission in the mosquito population. It is studied from the theoretical point of view to apply the Practical Algorithm. Also, we estimate the temporal evolution of the different human and mosquito populations given by the model in the Dengue 3 epidemic in Havana 2001, through the computation of the reachable sets using the Practical Algorithm.