3 resultados para normalizer circuits

em Universidad de Alicante


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The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from one language to a new one. Provided sufficient annotated data, machine learning algorithms allow to minimize the costs of such knowledge transfer but, up to date, proved to be ineffective for some specific tasks. Among these, the recognition and normalization of temporal expressions still remains out of their reach. Focusing on this task, and still adhering to the rule-based framework, this paper presents a bunch of experiments on the automatic porting to Italian of a system originally developed for Spanish. Different automatic rule translation strategies are evaluated and discussed, providing a comprehensive overview of the challenge.

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This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system for the recognition and normalization of temporal expressions originally developed for Spanish. TERSEO was first extended to English through the automatic translation of the temporal expressions. Then, an improved porting process was applied to Italian, where the automatic translation of the temporal expressions from English and from Spanish was combined with the extraction of new expressions from an Italian annotated corpus. Experimental results demonstrate how, while still adhering to the rule-based paradigm, the development of automatic rule translation procedures allowed us to minimize the effort required for porting to new languages. Relying on such procedures, and without any manual effort or previous knowledge of the target language, TERSEO recognizes and normalizes temporal expressions in Italian with good results (72% precision and 83% recall for recognition).

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Teachers are deeply concerned on how to be more effective in our task of teaching. We must organize the contents of our specific area providing them with a logical configuration, for which we must know the mental structure of the students that we have in the classroom. We must shape this mental structure, in a progressive manner, so that they can assimilate the contents that we are trying to transfer, to make the learning as meaningful as possible. In the generative learning model, the links before the stimulus delivered by the teacher and the information stored in the mind of the learner requires an important effort by the student, who should build new conceptual meanings. That effort, which is extremely necessary for a good learning, sometimes is the missing ingredient so that the teaching-learning process can be properly assimilated. In electrical circuits, which we know are perfectly controlled and described by Ohm's law and Kirchhoff's two rules, there are two concepts that correspond to the following physical quantities: voltage and electrical resistance. These two concepts are integrated and linked when the concept of current is presented. This concept is not subordinated to the previous ones, it has the same degree of inclusiveness and gives rise to substantial relations between the three concepts, materializing it into a law: The Ohm, which allows us to relate and to calculate any of the three physical magnitudes, two of them known. The alternate current, in which both the voltage and the current are reversed dozens of times per second, plays an important role in many aspects of our modern life, because it is universally used. Its main feature is that its maximum voltage is easily modifiable through the use of transformers, which greatly facilitates its transfer with very few losses. In this paper, we present a conceptual map so that it is used as a new tool to analyze in a logical manner the underlying structure in the alternate current circuits, with the objective of providing the students from Sciences and Engineering majors with another option to try, amongst all, to achieve a significant learning of this important part of physics.