Towards the implementation of a preference-and uncertain-aware solver using answer set programming

Logic programs with possibilistic ordered disjunction (or LPPODs) are a recently defined logic-programming framework based on logic programs with ordered disjunction and possibilistic logic. The framework inherits the properties of such formalisms and merging them, it supports a reasoning which is nonmonotonic, preference-and uncertain-aware. The LPPODs syntax allows to specify 1) preferences in a qualitative way, and 2) necessity values about the certainty of program clauses. As a result at semantic level, preferences and necessity values can be used to specify an order among program solutions. This class of program therefore fits well in the representation of decision problems where a best option has to be chosen taking into account both preferences and necessity measures about information. In this paper we study the computation and the complexity of the LPPODs semantics and we describe the algorithm for its implementation following on Answer Set Programming approach. We describe some decision scenarios where the solver can be used to choose the best solutions by checking whether an outcome is possibilistically preferred over another considering preferences and uncertainty at the same time.Postprint (published version

Consecuencias legales derivadas de un accidente laboral

Traballo fin de grao (UDC.DER). Dereito. Curso 2014/201

Self-Referencing Fiber-Optic Intensity Sensors Using Ring Resonators and Fiber Bragg Gratings

An improved ring resonator self-referencing technique in a new reflection configuration for remote fiber-optic intensity sensors is demonstrated using fiber Bragg gratings. Sensor sensitivity doubles and a single fiber lead is used. The sensor is interrogated at two subcarrier frequencies having a high rejection of interference from laser source intensity fluctuations and loss in the fiber lead. We experimentally demonstrate the efficiency of the new reflection configuration, the usefulness of the theoretical model proposed, and discuss design parameters for optimum insertion lossesThis work was supported in part by CICYT (TIC2003-03783 and TEC2006-13273-C03-03-MIC), in part by UC3M (FAVICOBIS), in part by CAM (FACTOTEM-CM:S-0505/ESP/000417), and in part by COST 299.Publicad

Air traffic flow management regulations: big data analytics

Air traffic in Europe is constantly increasing. Due to this, Air Traffic Management is getting more complex and all stakeholders get affected by that. Among these, air traffic controllers are the ones that suffer the biggest impact in terms of overload of work. Every day, a set of regulations occurs in the regions controlled by these operators, which provokes delays on ground and rerouting in mid-air. All of these variations directly affect the entire ATM network and translates into big expenses for passengers and airlines. With this project, the aim is to predict these daily contingencies by using big data analysis models, so that costs associated are reduced. Most of the information needed to run the analysis has been very complicated to extract, process and correlate because the data sources are not open to researchers. Therefore, the number of instances available for the prediction is very low (only 18 months of data). Nevertheless, while working with this limitation, a Naive Bayes classifier has been chosen as the analytical algorithm. In terms of results, the work done does not reveal a high predictive capability due to the amount of data acquired and the simplicity of the temporal variables. This suggests that, in future researches, it could be convenient to intake broader historical data (more years). Moreover, more complex predictive models could be implemented if variables coming from the weather or the number of flights are used.Ingeniería Aeroespacial (Plan 2010

CMOS circuit implementations for neuron models

The mathematical neuron basic cells used as basic cells in popular neural network architectures and algorithms are discussed. The most popular neuron models (without training) used in neural network architectures and algorithms (NNA) are considered, focusing on hardware implementation of neuron models used in NAA, and in emulation of biological systems. Mathematical descriptions and block diagram representations are utilized in an independent approach. Nonoscillatory and oscillatory models are discusse

CWDM self-referencing sensor network based on ring resonators in reflective configuration

A new scalable self-referencing sensor network with low insertion losses implemented in Coarse Wavelength Division Multiplexing (CWDM) technology is reported. It allows obtaining remote self-referenced measurements with a full-duplex fibre downlead up to 35 km long, with no need for optical amplification. Fibre Bragg gratings (FBG) are used in order to achieve a reflective configuration, thus increasing the sensitivity of the optical transducers. Low-cost off-the-shelf devices in CWDM technology can be used to implement and scale the network. Ring resonator (RR) based incoherent interferometers at the measuring points are used as selfreferencing technique. A theoretical analysis of power budget of the topology is reported, with a comparison between the proposed network and a conventional star topology. Finally, the new configuration has been experimentally demonstrated.This work has been supported by CICYT:TIC2003-03783, UC3M:FAVICOBIS and CAM:FACTOTEM-CM (S-0505/ESP/000417).Publicad

Dynamics of a Ø4 kink in the presence of strong potential fluctuations, dissipation, and boundaries

We have carried out a number of simulations to study the dynamical behavior of kinks in the ifJ4 model in the presence of strong fluctuations of its double-well potential. Our work widens the computational and analytical knowledge of this system in four directions. First, we describe in detail a numerical procedure that can be easily generalized to other stochastic, soliton-bearing equations. We demonstrate that it exhibits consistency features never found in previous research on nonlinear stochastic partial differential equations. Second, we fix the range of validity of theoretical approaches based on secular perturbative expansions. We show how this range depends on a combination of noise strength and duration. Third, we numerically study the model beyond the applicability of analytical methods. We compute the main characteristics of kink dynamics in this regime and discuss their stability under this random perturbation. Finally, we introduce dissipation and boundaries in the dynamically disordered model. We establish that the essential consequence of friction action is to soften the noise effects, while boundaries give rise to a critical velocity below which kinks cannot enter the noisy zone.We are thankful for partial financial support from the Direccion General de Investigacion Cientifica y Tecnica (DGICyT) through Project No. TIC 73/89. A.S. was supported by the program ((Formacion de Personal Investigador" of the Ministerio de Educación y Ciencia of Spain.Publicad

Mismatch distance term compensation in centroid configurations with nonzero-area devices

This paper presents an analytical approach to distance term compensation in mismatch models of integrated devices. Firstly, the conditions that minimize parameter mismatch are examined under the assumption of zero-area devices. The analytical developments are illustrated using centroid configurations. Then, deviations from the previous approach due to the nonzero device areas are studied and evaluated