Abstract
In the application of conventional audio compression algorithms to low bit rate audio coding one is faced with the unsatisfactory tradeoff between coarser quantization and audio bandwidth reduction. Frequency Extension has therefore emerged as an important tool for the satisfactory performance of low bit rate audio codecs. In this paper we describe one of a newer class of Frequency Extension techniques which are applied directly to the high frequency resolution representation of the signal (e.g., MDCT). This particular technique is based on a Fractal Self-Similarity Model (FSSM) for the short-term frequency representation of the signal. The FSSM model, which may include multiple dilation and translation terms, has been found to be effective for a wide variety of speech and music signals and provides a compact description for long term correlation that may exist in frequency domain. The high frequency resolution of MDCT aids in accurate parameter estimation for the model, which in turn has shown promise as a Frequency Extension tool that offers a detailed and natural sounding quality at low bit rates. Structure of the FSSM model, issues related to parameter estimation, and its application to audio coding for bit rates of 8-48 kbps is discussed. Audio demos are available at http://www.atc-labs.com/fssm.

Abstract
The paper describes a new methodology for mapping a neural network into a rule-based fuzzy inference system. This mapping makes explicit the knowledge implicitly captured by the neural network during the learning stage, by transforming it into a set of rules. The method is applied in transformer fault diagnosis using dissolved gas-in-oil analysis. Studies on transformer failure diagnosis are reported, illustrating the good results obtained and the knowledge discovery made possible.

Abstract
The sol-gel method was employed to obtain poly(oxyethylene) (POE)/siloxane hybrids (di-ureasils) doped with erbium triflate (Er(CF3SO3)(3)). The host hybrid matrix employed is composed of a siliceous framework to which short POE chains are covalently bonded through urea linkages (-NH(C(=O)NH-). Xerogels with infinity > n >= 5 (where n, salt composition, is the molar ratio of OCH2CH2 moieties per Er3+ ion) were analyzed. Samples with n >= 20 are amorphous. Those with n > 20 are thermally stable up to about 325 degrees C. In the di-ureasils proposed, the Er3+ ions are active at room temperature (RT). Concentration effects on the quenching of the 1.53 mm emission intensity (excited at 488 nm) are negligible.

Abstract
This paper presents a new method to the adaptive cancellation of acoustic feedbacks. The method uses high resolution frequency analysis and high-Q notch filters so as to accurately detect feedbacks and cancel them without disturbing noticeably the main audio spectrum. The method will be described, its implementation on a TMS320C6711 DSP platform for real time operation will be explained, and results for the adaptive cancellation of two simultaneous acoustic feedbacks will be presented.

Abstract
This paper provides a different approach for electricity price forecast from risk management point of view. Making use of neural networks, the methodology presented here has as main concern finding the maximum and the minimum System Marginal Price (SMP) for a specific programming period, with a certain confidence level. To train the neural network, probabilistic information from past years is used. This approach was developed with the objective of integrating a decision-support system that uses Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data are presented and discussed in detail. © 2005 ISAP.

Abstract
The process of resources systems selection takes an important part in Agile/Virtual Enterprises (A/V E) integration. However, the resources systems selection is a difficult matter to solve in A/VE because: it can be of exponential complexity resolution; it can be a multi criteria problem; and because there are different types of A/V Es with different requisites that have originated the creation of a specific resources selection model for each one of them. In our A/V E project we have made some progress in this matter and identified the principal gaps to be solved. This paper will show one of those gaps in the algorithms area to be applied to the problem. In attention to that gaps we address the necessity to develop new algorithms and with more information disposal, for its selection by the Broker. In this paper we propose a genetic algorithm to deal with a specific case of resources system selection problem when the space solution dimension is high.