QL-CONST1: an expert system for quality level prediction in concrete structures

Current trends in the fields of artifical intelligence and expert systems are moving towards the exciting possibility of reproducing and simulating human expertise and expert behaviour into a knowledge base, coupled with an appropriate, partially ‘intelligent’, computer code. This paper deals with the quality level prediction in concrete structures using the helpful assistance of an expert system, QL-CONST1, which is able to reason about this specific field of structural engineering. Evidence, hypotheses and factors related to this human knowledge field have been codified into a knowledge base. This knowledge base has been prepared in terms of probabilities of the presence of either hypotheses or evidence and the conditional presence of both. Human experts in the fields of structural engineering and the safety of structures gave their invaluable knowledge and assistance to the construction of the knowledge base. Some illustrative examples for, the validation of the expert system behaviour are included.

Comments and remarks over classic linear loop-gain method for oscillator design and analysis. New proposed method based on NDF/RRT

Abstract. This paper describes a new and original method for designing oscillators based on the Normalized Determinant Function (NDF) and Return Relations (RRT)- Firstly, a review of the loop-gain method will be performed. The loop-gain method pros, cons and some examples for exploring wrong solutions provided by this method will be shown. This method produces in some cases wrong solutions because some necessary conditions have not been fulfilled. The required necessary conditions to assure a right solution will be described. The necessity of using the NDF or the Transpose Return Relations (RRT), which are related with the True Loop-Gain, to test the additional conditions will be demonstrated. To conclude this paper, the steps for oscillator design and analysis, using the proposed NDF/RRj method, will be presented. The loop-gain wrong solutions will be compared with the NDF/RRj and the accuracy of this method to estimate the oscillation frequency and QL will be demonstrated. Some additional examples of plane reference oscillators (Z/Y/T), will be added and they will be analyzed with the new NDF/RRj proposed method, even these oscillators cannot be analyzed using the classic loop gain method.

Un sistema experto para la evaluación del nivel de calidad en estructuras de edificación

Las tendencias actuales dentro de la Inteligencia Artificial y los Sistemas Expertos se mueven hacia la excitante posibilidad de reproducir y simular el conocimiento y comportamiento humanos dentro de Bases de Conocimiento, acopladas con códigos computacionales parcialmente inteligentes. Así, este trabajo se ocupa de la predicción del nivel de calidad en estructuras mediante un sistema experto denominado QL-CONST1, capaz de "razonar" sobre este campo de la ingeniería estructural. La Base de Conocimientos ha sido desarrollada en términos probabilísticos de hipótesis y evidencias, con la invalorable ayuda de expertos humanos en ingeniería estructural. Se incluyen algunos ejemplos ilustrativos para validar el comportamiento del sistema experto.

kyrie2: query rewriting under extensional constraints in ELHIO

In this paper we study query answering and rewriting in ontologybased data access. Specifically, we present an algorithm for computing a perfect rewriting of unions of conjunctive queries posed over ontologies expressed in the description logic ELHIO, which covers the OWL 2 QL and OWL 2 EL profiles. The novelty of our algorithm is the use of a set of ABox dependencies, which are compiled into a so-called EBox, to limit the expansion of the rewriting. So far, EBoxes have only been used in query rewriting in the case of DL-Lite, which is less expressive than ELHIO. We have extensively evaluated our new query rewriting technique, and in this paper we discuss the tradeoff between the reduction of the size of the rewriting and the computational cost of our approach.