A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Stochastic modeling as a means of automatic speech recognition.
Stochastic modeling as a means of automatic speech recognition.
Accurate on-line support vector regression
Neural Computation
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Maintenance management is a subject that, instead of reducing importance with the increase of equipment reliability, it increases its role in the companies and obliges the increase of the level of demand of professionals involved because of the new technical and environmental demands. Sometimes, scientific developments anticipate the company's needs while other times it is the company that challenges science. The maintenance area is an example that offers challenges to both science and companies in order to optimize the performance of equipment and facilities. However, if during the industrial era the maintenance had to respond to industry, nowadays, and in parallel with the increase of equipment performance, the maintenance has the obligation to aid in order to convert technology in becoming more environmentally friendly. It is because of this kind of challenge that the authors are developing new methodologies, almost antagonistic, because of the areas in development, namely diesel engines and wind generators, and as we will demonstrate, areas which are compatible and can contribute to a better environment. In the case of wind generators, the methodology aims to optimize the cycles of production and consequently, reduce the other kinds of energy production. On the other hand, the methodologies for maintenance of diesel engines are based on environmental indicators that can predict the "health state" taking into account restrictions including health human factors among others. The new methodologies will later be incorporated through new predictive maintenance modules in an integrated maintenance management system called SMIT (Terology Integrated Modular System). The SMIT system includes the main modules of a traditional system, as well as a fault diagnosis, a nonperiodic maintenance planning and a generic on-condition maintenance module, among other innovations. The new features will include, in the case of wind generators, on-line measures and the corresponding on-time treatment, using algorithms based on time-series forecasting and wireless technology to transmit the signals. In the case of diesel engines, the algorithms are based on Markov chains and hidden Markov chains, with an approach that is offering good results, which proves the validity of the methodology and the innovation itself. It is based on these developments and the new researches mentioned so far that this paper is built upon, and we believe will be a contribution to the maintenance management area.