Distributed physical sensors network for the protection of critical infrastractures against physical attacks

The SCOUT project is based on the use of multiple innovative and low impact technologies for the protection of space control ground stations and the satellite links against physical and cyber-attacks, and for intelligent reconfiguration of the ground station network (including the ground node of the satellite link) in the case that one or more nodes fail. The SCOUT sub-system devoted to physical attacks protection, SENSNET, is presented. It is designed as a network of sensor networks that combines DAB and DVB-T based passive radar, noise radar, Ku-band radar, infrared cameras, and RFID technologies. The problem of data link architecture is addressed and the proposed solution described

Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms

To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has to be increased. Consequently, the training computational cost is unaffordable for very low objective function value estimations, and the use of Importance Sampling (IS) techniques becomes convenient. The study of three different objective functions is considered, which implies the proposal of estimators of the objective function using IS techniques: the Mean-Square error, the Cross Entropy error and the Misclassification error criteria. The values of these functions are estimated by IS techniques, and the results are used to train NNs by the application of Genetic Algorithms. Results for a binary detection in Gaussian noise are provided. These results show the evolution of the parameters during the training and the performances of the proposed detectors in terms of error probability and Receiver Operating Characteristics curves. At the end of the study, the obtained results justify the convenience of using IS in the training

Does indomethacin for closure of patent ductus arteriosus affect cerebral function?

Abstract Objective: To study whether indomethacin used in conventional dose for closure of patent ductus arteriosus affects cerebral function measured by Electroencephalograms (EEG) evaluated by quantitative measures. Study design: Seven premature neonates with haemodynamically significant persistent ductus arteriosus were recruited. EEG were recorded before, during and after an intravenous infusion of 0.2 mg/kg indomethacin over 10 min. The EEG was analysed by two methods with different degrees of complexity for the amount of low-activity periods (LAP, "suppressions") as an indicator of affection of cerebral function. Results: Neither of the two methods identified any change in the amount of LAPs in the EEG as compared to before the indomethacin infusion. Conclusion: Indomethacin in conventional dose for closure of patent ductus arteriosus does not affect cerebral function as evaluated by quantitative EEG

WOLA Filter Bank Design Requirements in Hearing Aids

This paper deals with the design of DFT-based filter banks for hearing aids, where spectral modifications are necessaries to compensate hearing loss. The WOLA (Weighted Over-Lap Add) filter bank is considered. It is an efficient implementation of the DFT filter bank to carry out short-time analysis, which is sometimes included as a core in digital signal processors for hearing aids. The relation between analysis and synthesis windows in order to obtain perfect reconstruction if spectral modifications are not necessary, are studied. Some length constraints of the filters impulse responses, and the number of bands of the filter bank are established, in order to avoid time domain aliasing

ON THE CODING GAIN OF DYNAMIC HUFFMAN CODING APPLIED TO A WAVELET-BASED PERCEPTUAL AUDIO CODER

This paper evaluates the coding gain of using a dynamic Huffman entropy coder in an audio coder that uses a wavelet-packet decomposition that is close to the subband decomposition made by the human ear. The subband audio signals are modeled as samples of a stationary random process with laplacian probability density function because experimental results indicate that the highest coding efficiency is obtained in that case. We have also studied how the entropy coding gain varies with the band index. The proposed adaptive Huffman coding method gives rise to an average coding gain of approximately 0.25 bits per sample compared to binary coding. A further coding gain can be achieved if timevarying filter banks are used. Experimental results tell us that using a suitable method to translate the psychoacoustic information to the wavelet domain, combined with our adaptive Huffman coding scheme, binary rates of about 64 kbps can be obtained for transparent coding of CD quality monophonic audio signals. 1