We describe a method to automatically discover translation collocations from a bilingual corpus and how these improve a machine translation system. The process of inference of collocations is iterative: An alignment i...
详细信息
ISBN:
(纸本)9781586034528
We describe a method to automatically discover translation collocations from a bilingual corpus and how these improve a machine translation system. The process of inference of collocations is iterative: An alignment is used to derive an initial set of collocations, these are used in turn to improve the alignment and this new alignment is used to generate new collocations. This process is repeated until no more collocations are found. The final alignment and the set of collocations are used to train a translation model. We use a model that is based on finite state transducers and word clusters and has been modified to work with collocations in addition to single words. We present experiments in which we show that automatic collocations improve translation quality without prior linguistic information.
Many processes, even being of a continuous nature, involve in its operation signals or rules different from the classical continuous variables represented by real variables and modelled by DAE. In practice they includ...
详细信息
Many processes, even being of a continuous nature, involve in its operation signals or rules different from the classical continuous variables represented by real variables and modelled by DAE. In practice they includ...
详细信息
Many processes, even being of a continuous nature, involve in its operation signals or rules different from the classical continuous variables represented by real variables and modelled by DAE. In practice they include on/off valves or other binary actuators, are subjected to logical operational rules, or are mixed with sequential operations. As a result, classical control does not fit very well with the overall operation of the plant. In this paper we consider the problem of hybrid control from a predictive control perspective, showing in a practical non trivial example with changing process structure, how the problem can be stated and solved.
Recent proliferation of sensor networks in various application areas has promoted real-time behavioral monitoring of various physical systems. The opportunity to use sensor generated data dynamically for improving spe...
详细信息
Recent proliferation of sensor networks in various application areas has promoted real-time behavioral monitoring of various physical systems. The opportunity to use sensor generated data dynamically for improving speed, accuracy, and general performance of predictive behavior modeling simulation is of paramount importance. The present paper identifies enabling modeling methods and computational strategies that are critical for achieving real-time or near real-time simulation response of very large and complex systems. It also discusses our choices of these technologies in the context of sample multidisciplinary computational mechanics applications and describes two examples to demonstrate the feasibility of integrating real-time data with real-time simulation.
To reduce speech recognition error rate we can use better statistical language models. These models can be improved by grouping words into word equivalence classes. Clustering algorithms can be used to automatically d...
详细信息
To reduce speech recognition error rate we can use better statistical language models. These models can be improved by grouping words into word equivalence classes. Clustering algorithms can be used to automatically do this word grouping. We present an incremental clustering algorithm and two iterative clustering algorithms. Also, we compare them with previous algorithms. The experimental results show that the two iterative algorithms perform as well as previous ones. It should be pointed out that one of them, that uses the leaving one out technique, has the ability to automatically determine the optimum number of classes. These iterative algorithms are used by the incremental one. On the other hand, the proposed incremental algorithm achieves the best results of the compared algorithms, its behavior is the most regular with the variation of the number of classes and can automatically determine the optimum number of classes.
Deformable models have been intensively studied in image analysis through the last decade, and are used for detection and recognition of flexible or rigid templates under diverse viewing conditions. Genetic algorithm ...
详细信息
Deformable models have been intensively studied in image analysis through the last decade, and are used for detection and recognition of flexible or rigid templates under diverse viewing conditions. Genetic algorithm (GA) based deformable models are used for generic visual landmark detection and interpretation. The developed system allows topologic localization and navigation using natural and artificial landmarks, exploiting deformable models' ability for handling landmark perspective variations. The resulting perception module has been integrated successfully in a complex navigation system. Various experimental results in real environments are presented on this paper, showing the effectiveness and capacity of the landmark detection and reading system.
High resolution requirements for airport surface traffic monitoring with lightweight, small, all-weather sensors call for the use of a network of millimetre-wave radars to perform the surveillance function in the surf...
详细信息
High resolution requirements for airport surface traffic monitoring with lightweight, small, all-weather sensors call for the use of a network of millimetre-wave radars to perform the surveillance function in the surface movement control and guidance system. In this paper a W-band radar employed as the basic sensor is described. Some results of recent and present field trials are reported.
作者:
Rogelio MazaedaCéar de PradaISPJAE
Cuba at present with the Dpt. Systems Engineering and Automatic Control Faculty of Sciences University of Valladolid c/ Real de Burgos s/n 47011 Valladolid Spain. tlf. +34 983 423162 Fax +34 983 423161 Dpt. Systems Engineering and Automatic Control
Faculty of Sciences University of Valladolid c/ Real de Burgos s/n 47011 Valladolid Spain. tlf. +34 983 423164 Fax +34 983 423161.
Iterative Feedback Tuning (IFT) is a tuning method that adjust on-line the parameters in the controller so that a performance criterion is minimised. The IFT method uses only experimental data obtained from the closed...
详细信息
Iterative Feedback Tuning (IFT) is a tuning method that adjust on-line the parameters in the controller so that a performance criterion is minimised. The IFT method uses only experimental data obtained from the closed loop system without assuming knowledge of the plant or perturbations models. In this paper the application of IFT to the tuning of a PID controller of a pilot plant is reported. The impact on the achieved system performance due to time weighting of the control error is particularly addressed.
An integrated advanced control and supervision system in operation in a sugar factory is presented. The system works on top of a commercial distributed computer control system, and combines artificial intelligence tec...
详细信息
An integrated advanced control and supervision system in operation in a sugar factory is presented. The system works on top of a commercial distributed computer control system, and combines artificial intelligence techniques for fault detection and diagnosis with advanced predictive controllers and models for other tasks.
In this paper the problem of assuring nominal stability in constrained predictive control is addressed for the case when, due to disturbances, inadequate constraints, etc., the reference cannot be reached within the p...
详细信息
In this paper the problem of assuring nominal stability in constrained predictive control is addressed for the case when, due to disturbances, inadequate constraints, etc., the reference cannot be reached within the prediction horizon. The proposed algorithm is formulated in the delta domain, but the idea can be extended to other kind of models. It combines the cancellation of modes at the end of the prediction horizon with a minimization of the distance to the controller reference. In this way, it assures stability even with open loop unstable processes while, at the same time, avoids the feasibility problems.
暂无评论