Knowledge base specification to automate the fluid critical point of fluids

In this paper an analytical procedure implemented to structure the knowledge required by an expert system applied for controlling a chemical process is described. The analytical approach is based on L ifecycle of Systems and on Task Model approaches. It was validated with an experimental procedure related to the determination of the critical point of pure fluids (CO₂, N₂O, SF₆) and mixtures of low concentration (CO₂-limonene). For the implementation of the control system an expert system shell (CHRONOS?) was used.     

A stereophonic acoustic signal extraction scheme for noisy and reverberant environments

In this contribution, a novel two-channel acoustic front-end for robust automatic speech recognition in adverse acoustic environments with nonstationary interference and reverberation is proposed. From a MISO system perspective, a statistically optimum source signal extraction scheme based on the multichannel Wiener filter (MWF) is discussed for application in noisy and underdetermined scenarios. For free-field and diffuse noise conditions, this optimum scheme reduces to a Delay & Sum beamformer followed by a single-channel Wiener postfilter. Scenarios with multiple simultaneously interfering sources and background noise are usually modeled by a diffuse noise field. However, in reality, the free-field assumption is very weak because of the reverberant nature of acoustic environments. Therefore, we propose to estimate this simplified MWF solution in each frequency bin separately to cope with reverberation. We show that this approach can very efficiently be realized by the combination of a blocking matrix based on semi-blind source separation (‘directional BSS’), which provides a continuously updated reference of all undesired noise and interference components separated from the desired source and its reflections, and a single-channel Wiener postfilter. Moreover, it is shown, how the obtained reference signal of all undesired components can efficiently be used to realize the Wiener postfilter, and at the same time, generalizes well-known postfilter realizations. The proposed front-end and its integration into an automatic speech recognition (ASR) system are analyzed and evaluated in noisy living-room-like environments according to the PASCAL CHiME challenge. A comparison to a simplified front-end based on a free-field assumption shows that the introduced system substantially improves the speech quality and the recognition performance under the considered adverse conditions.     

Automotive observers based on multibody models and the extended Kalman filter

This work is part of a project aimed to develop automotive real-time observers based on detailed nonlinear multibody models and the extended Kalman filter (EKF). In previous works, a four-bar mechanism was studied to get insight into the problem. Regarding the formulation of the equations of motion, it was concluded that the state-space reduction method known as matrix-R is the most suitable one for this application. Regarding the sensors, it was shown that better stability, accuracy and efficiency are obtained as the sensored magnitude is a lower derivative and when it is a generalized coordinate of the problem. In the present work, the automotive problem has been addressed, through the selection of a Volkswagen Passat as a case-study. A model of the car containing fifteen degrees of freedom has been developed. The observer algorithm that combines the equations of motion and the integrator has been reformulated so that duplication of the problem size is avoided, in order to improve efficiency. A maneuver of acceleration from rest and double lane change has been defined, and tests have been run for the “prototype,” the “model” and the “observer,” all the three computational, with the model having 100 kg more than the prototype. Results have shown that good convergence is obtained for position level sensors, but the computational cost is high, still far from real-time performance.     

The Old-Age Healthy Dependency Ratio in Europe

The aim of this study is to answer the question of whether improvements in the health of the elderly in European countries could compensate for population ageing on the supply side of the labour market. We propose a state-of-health-specific (additive) decomposition of the old-age dependency ratio into an old-age healthy dependency ratio and an old-age unhealthy dependency ratio in order to participate in a discussion of the significance of changes in population health to compensate for the ageing of the labour force. Applying the proposed indicators to the Eurostat's population projection for the years 2010-2050, and assuming there will be equal improvements in life expectancy and healthy life expectancy at birth, we discuss various scenarios concerning future of the European labour force. While improvements in population health are anticipated during the years 2010-2050, the growth in the number of elderly people in Europe may be expected to lead to a rise in both healthy and unhealthy dependency ratios. The healthy dependency ratio is, however, projected to make up the greater part of the old-age dependency ratio. In the European countries in 2006, the value of the old-age dependency ratio was 25. But in the year 2050, with a positive migration balance over the years 2010-2050, there would be 18 elderly people in poor health plus 34 in good health per 100 people in the current working age range of 15-64. In the scenarios developed in this study, we demonstrate that improvements in health and progress in preventing disability will not, by themselves, compensate for the ageing of the workforce. However, coupled with a positive migration balance, at the level and with the age structure assumed in the Eurostat's population projections, these developments could ease the effect of population ageing on the supply side of the European labour market.     

Information technology investment announcements and market value in transition economies: Evidence from Warsaw Stock Exchange

This study examines stock market reactions to announcements of information technology investments in Poland, an emerging market and transition economy. Based on 66 announcements by companies traded at the Warsaw Stock Exchange in the period 2002–2009, our study confirms some previously published results from studies conducted primarily in highly developed markets, but also shows that specific characteristics of announcements play a more important role than has been commonly assumed. Our results indicate that investors in Poland react more positively if systems are acquired from global rather than local vendors. Announcements about completed projects are more positively received than announcements about planned or in-progress projects. Furthermore, announcements in Polish, targeted at existing shareholders, are more likely to be received positively than similar announcements released in English, targeting global investors.     

Error Analysis for a Hybridizable Discontinuous Galerkin Method for the Helmholtz Equation

Finite element methods for acoustic wave propagation problems at higher frequency result in very large matrices due to the need to resolve the wave. This problem is made worse by discontinuous Galerkin methods that typically have more degrees of freedom than similar conforming methods. However hybridizable discontinuous Galerkin methods offer an attractive alternative because degrees of freedom in each triangle can be cheaply removed from the global computation and the method reduces to solving only for degrees of freedom on the skeleton of the mesh. In this paper we derive new error estimates for a hybridizable discontinuous Galerkin scheme applied to the Helmholtz equation. We also provide extensive numerical results that probe the optimality of these results. An interesting observation is that, after eliminating the internal element degrees of freedom, the condition number of the condensed hybridized system is seen to be almost independent of the wave number.     

Robust anti-sliding control of autonomous vehicles in presence of lateral disturbances

Path following control problem of autonomous vehicles is investigated, concerning both unmeasurable sliding effects and lateral disturbances which lead to some difficulties in designing autonomous control under complex environment. To deal with the sliding effects, sideslip angles are modeled and reconstructed by estimating the tire cornering stiffness, which plays important role in analyzing the sliding effects. To this end, a Luenberger-type observer is designed, which is able to identify the tire cornering stiffness adaptively even in presence of time-varying lateral disturbances. Furthermore, to guarantee high-precision guidance, a sliding mode controller is designed based on chained system theory, and this controller is shown to be robust to both the lateral disturbances and the inaccuracy of the sliding reconstruction. Simulations illustrate that the proposed methods can reconstruct the sliding angles and provide high-accuracy anti-sliding control even in presence of the time-varying lateral disturbances.     

Case Based Imprecision Estimates for Bayes Classifiers with the Bayesian Bootstrap

This article outlines a Bayesian bootstrap method for case based imprecision estimates in Bayes classification. We argue that this approach is an important complement to methods such as k-fold cross validation that are based on overall error rates. It is shown how case based imprecision estimates may be used to improve Bayes classifiers under asymmetrical loss functions. In addition, other approaches to making use of case based imprecision estimates are discussed and illustrated on two real world data sets. Contrary to the common assumption, Bayesian bootstrap simulations indicate that the uncertainty associated with the output of a Bayes classifier is often far from normally distributed.