Most learning systems applied to problem solving have the goal of learning knowledge for solving problems more eeciently. However, very few systems have focused on the acquisition of planning operator descriptions. In this paper, we present a system that learns operator deenitions from the interaction with a completely unknown environment. In order to achieve better learning convergence, severa...

The aviation industry stands to benefit from the technological advances that have come to be known as soft computing. This paper describes how soft computing techniques are being used to improve a pilot’s situational awareness. Of particular interest is the ability of a computer to add value to the raw sensor data, autonomously monitoring the aircraft’s situation for possible anomalies in fligh...

Implementation rules for iterative decoders of concatenated codes with interleavers are proposed based on a study of the quantization effects on the performance. We consider both cases of a single soft-input soft-output (SISO) module performing sequentially all iterations and of a pipelined structure in which a dedicated hardware is in charge of each SISO operation. In the last case, we show th...

A detector system, called DUVEX, has been developed for the soft-x-ray and extreme ultraviolet domain. It consists in a YAG :Ce scintillator coupled to a photomultiplier module working under vacuum in counting mode. The design and the performances of this detector in terms of yield, absolute efficiency, response and noise are reported. Spectra in the soft x-ray range of different elements (W, A...

Often we need to work in scenarios where events happen over time and preferences are associated with event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems requires exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solv...

Most learning systems applied to problem solving have the goal of learning knowledge for solving problems more eeciently. However, very few systems have focused on the acquisition of planning operator descriptions. In this paper, we present a system that learns operator deenitions from the interaction with a completely unknown environment. In order to achieve better learning convergence, severa...

This paper describes a bilingual text-to-speech (TTS) system, Microsoft Mulan, which switches between Mandarin and English smoothly and which maintains the sentence level intonation even for mixed-lingual texts. Mulan is constructed on the basis of the Soft Prediction Only prosodic strategy and the Prosodic-Constraint Orient unit-selection strategy. The unitselection module of Mulan is shared a...

Often we need to work in scenarios where events happen over time and preferences are associated to event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems require exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solvabl...

‎In this work‎, ‎we introduce the concept of classical 2-absorbing secondary modules over a commutative ring as a generalization of secondary modules and investigate some basic properties of this class of modules‎. ‎Let $R$ be a commutative ring with‎ ‎identity‎. ‎We say that a non-zero submodule $N$ of an $R$-module $M$ is a‎ ‎emph{classical 2-absorbing secondary submodule} of $M$ ...

The newly-developed prosody module of our text-to-speech (TTS) system is described in the paper. We present two main works on it’s establishment and improvement. On the basis of potential factors influencing prosody parameters, inclusive of duration, pitch and intensity, the prosody model is built as groundwork of this module which is superior to the former rule-based one in generation of natur...