Ingeniería Informática

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An inference engine based on fuzzy logic for uncertain and imprecise expert reasoning
(2002-07) D'Aquila, Raimundo; Crespo Crespo, Cecilia; Mate, J. L.; Pazos, J.
"This paper addresses the development and computational implementation of an inference engine based on a full fuzzy logic, excluding only imprecise quantifiers, for handling uncertainty and imprecision in rule-based expert systems. The logical model exploits some connectives of Lukasiewicz’s infinite multi-valued logic and is mainly founded on the work of L.A. Zadeh and J.F. Baldwin. As it is oriented to expert systems, the inference engine was developed to be as knowledge domain independent as possible, while having satisfactory computational efficiency (...)."
Learning by knowledge sharing in autonomous intelligent systems
(2006) García Martínez, Ramón; Borrajo, Daniel; Maceri, Pablo; Britos, Paola Verónica
"Very few learning systems applied to problem solving have focused on learning operator definitions from the interaction with a completely unknown environment. In order to achieve better learning convergence, several agents that learn separately are allowed to interchange each learned set of planning operators. Learning is achieved by establishing plans, executing those plans in the environment, analyzing the results of the execution, and combining new evidence with prior evidence. Operators are generated incrementally by combining rote learning, induction, and a variant of reinforcement learning. The results show how allowing the communication among individual learning (and planning) agents provides a much better percentage of successful plans, plus an improved convergence rate than the individual agents alone."
Identification of velocity variations in a seismic cube using neural networks
(2006) Cersósimo, Darío Sergio; Ravazoli, Claudia; García Martínez, Ramón
"This research allow to infer that from seismic section and well data it is possible to determine velocity anomalies variations in layers with thicknesses below to the seismic resolution using neuronal networks."
Patterns in temporal series of meteorological variables using SOM & TDIDT
(2006) Cogliati, Marisa; Britos, Paola Verónica; García Martínez, Ramón
"The purpose of the present article is to investigate if there exist any such set of temporal stable patterns in temporal series of meteorological variables studying series of air temperature, wind speed and direction an atmospheric pressure in a period with meteorological conditions involving nocturnal inversion of air temperature in Allen, Rio Negro, Argentina. Our conjecture is that there exist independent stable temporal activities, the mixture of which give rise to the weather variables; and these stable activities could be extracted by Self Organized Maps plus Top Down Induction Decision Trees analysis of the data arising from the weather patterns, viewing them as temporal signals."
Detection of breast lesions in medical digital imaging using neural networks
(2006) Ferrero, Gustavo; Britos, Paola Verónica; García Martínez, Ramón
"The purpose of this article is to present an experimental application for the detection of possible breast lesions by means of neural networks in medical digital imaging. This application broadens the scope of research into the creation of different types of topologies with the aim of improving existing networks and creating new architectures which allow for improved detection."
Conceptualization maturity metrics for expert systems
(2006) Britos, Paola Verónica; García Martínez, Ramón; Hauge, Ødwin
“Metrics used on development of expert systems is not a well investigated problem area. This article suggests some metrics to be used to measure the maturity of the conceptualization process and the complexity of the decision process in the problem domain. We propose some further work to be done with these metrics. Applying those metrics makes new and interesting problems, concerning the structure of knowledge to surface.”
Prediction in health domain using Bayesian networks optimization based on induction learning techniques
(2006) Felgaer, Pablo; Britos, Paola Verónica; García Martínez, Ramón
"A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain."
Foundations and applications for secure triggers
(2006-02) Futoransky, Ariel; Kargieman, Emiliano; Sarraute, Carlos; Waissbein, Ariel
"Imagine there is certain content we want to maintain private until some particular event occurs, when we want to have it automatically disclosed. Suppose furthermore, that we want this done in a (possibly) malicious host. Say, the conﬁdential content is a piece of code belonging to a computer program that should remain ciphered and then “be triggered” (i.e., deciphered and executed) when the underlying system satisﬁes a preselected condition which must remain secret after code inspection. In this work we present diﬀerent solutions for problems of this sort, using diﬀerent “declassiﬁcation” criteria, based on a primitive we call secure triggers. We establish the notion of secure triggers in the universally-composable security framework of [Canetti 2001] and introduce several examples. Our examples demonstrate that a new sort of obfuscation is possible. Finally, we motivate its use with applications in realistic scenarios."
Piet: a GIS-OLAP implementation
(2007) Vaisman, Alejandro Ariel; Gómez, Leticia Irene; Kuijpers, Bart; Escribano, Ariel
"Data aggregation in Geographic Information Systems (GIS) is a desirable feature, although only marginally present in commercial systems, which also fail to provide integration between GIS and OLAP (On Line Analytical Processing). With this in mind, we have developed Piet, a system that makes use of a novel query processing technique: first, a process called sub-polygonization decomposes each thematic layer in a GIS, into open convex polygons; then, another process computes and stores in a database the overlay of those layers for later use by a query processor. We describe the implementation of Piet, and provide experimental evidence that overlay precomputation can outperform GIS systems that employ indexing schemes based on R-trees."
Requirements elicitation in data mining for business intelligence projects
(2008) Britos, Paola Verónica; Dieste, Oscar; García Martínez, Ramón
"There are data mining methodologies for business intelligence (DM-BI) projects that highlight the importance of planning an ordered, documented, consistent and traceable requirement’s elicitation throughout the entire project. However, the classical software engineering approach is not completely suitable for DM-BI projects because it neglects the requirements specification aspects of projects. This article focuses on identifying concepts for understand DM-BI project domain from DM-BI field experience, including how requirements can be educed by a proposed DM-BI project requirements elicitation process and how they can be documented by a template set."
Optimizing relationships information in repertory grids
(2008) Calot, Enrique; Britos, Paola Verónica; García Martínez, Ramón
"The Repertory Grid method is widely used in knowledge engineering to infer functional relationships between constructs given by an expert. The method is ignoring information that could be used to infer more precise dependencies. This paper proposes an improvement to take advantage on the information that is being ignored in the current method. Furthermore, this improvement fixes several other limitations attached to the original method, such as election in a discrete set of two values as a similarity pole or a contrast pole, the arbitrary measurement of distances, the unit-scale dependency and the normalization, among others. The idea is to use linear regression to estimate the correlation between constructs and use the fitness error as a distance measure."
Learning life cycle in autonomous intelligent systems
(2008) Ierache, Jorge; García Martínez, Ramón; De Giusti, Armando
"Autonomous Intelligent Systems (AIS) integrate planning, learning, and execution in a closed loop, showing an autonomous intelligent behavior. A Learning Life Cycle (LLC) Operators, Trained Base Operators and World Interaction Operators. The extension of the original architecture to support the new type of operators is presented."
Pedagogical protocols selection automatic assistance
(2008) Britos, Paola Verónica; Cataldi, Zulma; Sierra, Enrique; García Martínez, Ramón
"The preliminary results presented in this paper corresponds to a research project oriented to the search of the relationship between the predilection of students concerning learning style and the pedagogical protocols used by the human tutors (professors during the first courses of the Computer Engineering undergraduate Program) by using intelligent systems tools."
Work in progress: programming misunderstandings discovering process based on intelligent data mining tools
(2008) Britos, Paola Verónica; Jiménez Rey, Elizabeth; Rodríguez, Darío; García Martínez, Ramón
"We present research work in progress that focuses on data mining tools used for helping teachers to apply a three step knowledge discovering process to diagnose students’ misunderstandings (and their causes) related to their programming errors."
RE-SPaM: Using regular expressions for sequential pattern mining in trajectory databases
(2008) Gómez, Leticia Irene; Vaisman, Alejandro Ariel
"In sequential pattern mining, languages based on regular expressions (RE) were proposed to restrict frequent sequences to the ones that satisfy user-specified constraints. In these languages, REs are applied over items. We propose a much powerful language, based on regular expressions, denoted RE-SPaM, where the basic elements are constraints over the attributes of the items. Expressions in this language may include attributes, functions over attributes, and variables. We present the data model, sketch the syntax and semantics of RE-SPaM, a set of examples, and suggest how RE-SPaM can be used in the mining process."
Aggregation languages for moving object and places of interest
(2008) Gómez, Leticia Irene; Kuijpers, Bart; Vaisman, Alejandro Ariel
"We address aggregate queries over GIS data and moving object data, where non-spatial information is stored in a data warehouse. We propose a formal data model and query language to express complex aggregate queries. Next, we study the compression of trajectory data, produced by moving objects, using the notions of stops and moves. We show that stops and moves are expressible in our query language and we consider a fragment of this language, consisting of regular expressions to talk about temporally ordered sequences of stops and moves. This fragment can be used not only for querying, but also for expressing data mining and pattern matching tasks over trajectory data."
Complete calculi for structured specifications in fork algebra
(2010) López Pombo, Carlos Gustavo; Frías, Marcelo
"In previous articles we presented Argentum, a tool for reasoning across heterogeneous specifications based on the language of fork algebras. Argentum’s foundations were formalized in the framework of institutions. The formalization made simple to describe a methodology capable of producing a complete system desription from partial views, eventually written in different logical languages. Structured specifications were introduced by Sannella and Tarlecki and extensively studied by Borzyszkowski. The latter also presented conditions under which the calculus for structured specifications is complete. Using fork algebras as a “universal” institution capable of representing expressive logics (such as dynamic and temporal logics), requires using a fork language that includes a reflexive-transitive closure operator. The calculus thus obtained does not meet the conditions required by Borzyszkowski. In this article we present structure building operators (SBOs) over fork algebras, and provide a complete calculus for these operators."
A data model and query language for spatio-temporal decision support
(2010) Gómez, Leticia Irene; Kuijpers, Bart; Vaisman, Alejandro Ariel
"In recent years, applications aimed at exploring and analyzing spatial data have emerged, powered by the increasing need of software that integrates Geographic Information Systems(GIS) and On-Line Analytical Processing (OLAP). These applications have been called SOLAP (Spatial OLAP). In previous work, the authors have introduced Piet, a system based on a formal data model that integrates in a single framework GIS, OLAP (On-Line Analytical Processing), and Moving Object data. Real-world problems are inherently spatio-temporal. Thus, in this paper we present a data model that extends Piet, allowing tracking the history of spatial data in the GIS layers. We present a formal study of the two typical ways of intro ducing time into Piet: timestamping the thematic layers in the GIS, and timestamping the spatial objects in each layer. We denote these strategies snapshot-based and timestamp-based representations, respectively, following well-known terminology borrowed from temporal databases. We present and discuss the formal model for both alternatives. Based on the timestamp-based representation, we introduce a formal First-Order spatio-temporal query language, which we denote Lt, able to express spatio-temporal queries over GIS, OLAP, and trajectory data. Finally, we discuss implementation issues, the update operators that must be supported by the model, and sketch a temporal extension to Piet-QL, the SQL-like query language that supports Piet."
Discovering sensing capability in multi-agent systems
(2010) Parpaglione, María Cristina; Santos, Juan Miguel
"What should be the sensing capabilities of agents in a Multi-Agent System be to solve a problem efficiently, quickly and economicly? This question often appears when trying to solve a problem using Multi-Agent Systems. This paper introduces a method to find these sensing capabilities in order to solve a given problem. To achieve this, the sensing capability of an agent is modeled by a parametrized function and then Genetic Algorithms are used to find the parameters’ values. The individual behavior of the agents are found with Reinforcement Learning."
A simple linearization of the self-shrinking generator by means of cellular automata
(2010) Fúster-Sabater, Amparo; Pazo-Robles, María Eugenia; Caballero-Gil, Pino
"In this work, it is shown that the output sequence of a well-known cryptographic generator, the so-called self-shrinking generator, can be obtained from a simple linear model based on cellular automata. In fact, such a cellular model is a linear version of a nonlinear keystream generator currently used in stream ciphers. The linearization procedure is immediate and is based on the concatenation of a basic structure. The obtained cellular automata can be easily implemented with FPGA logic. Linearity and symmetry properties in such automata can be advantageously exploited for the analysis and/or cryptanalysis of this particular type of sequence generator."

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