Rosa María Aguilar

Cytological image analysis with a genetic fuzzy finite state machine

The objective of this research is to design a pattern recognition system based on a Fuzzy Finite State Machine (FFSM). We try to find an optimal FFSM with Genetic Algorithms (GA). In order to validate this system, the classifier has been applied to a real problem: distinction between normal and abnormal cells in cytological breast fine needle aspirate images and cytological peritoneal fluid images. The characteristic used in the discrimination between normal and abnormal cells is a texture measurement of the chromatin distribution in cellular nuclei. Furthermore, the effectiveness of this method as a pattern classifier is compared with other existing supervised and unsupervised methods and evaluated with Receiver Operating Curves (ROC) methodology.

Patient-centered simulation tool for aiding in hospital management

Abstract The study of a particular complex system by means of computer simulation is described in this paper. Hospitals are chosen as target systems where the proposed methodology is applied. In order to choose the right decisions, hospital managers need all the information about the functioning of the organization. This research project presents a simulation tool that allows virtual societies such as hospitals to be implemented. In this way, the study of emergent behaviors in these systems can be carried out. The methodology used to model the hospital is process oriented. This approach allows us to implement a patient-centered simulation tool.

Using KADS methodology in a simulation assisted knowledge based system: application to hospital management

Abstract This paper presents a knowledge-based system for aiding in the decision-making process that is carried out in hospital management. There are a number of reasons that have led us to choose a tool such as this one: the amount of information generated in a hospital, its great interrelation and the need of heuristic knowledge for its processing. The KBS has been designed following the KADS methodology. KADS has allowed us to obtain a structured representation of the knowledge, which makes easier both the construction and the debugging of the knowledge base. As a starting point, the decision-making task has been decomposed in four subtasks: monitoring; diagnosis; prediction of the possible solutions for the stated problem; and design of the solution. The prediction task can only be performed through a simulation program where the dynamics of the hospital is modeled. This allows the system to detect the consequences of the application of different possible solutions. The co-operation between simulation and artificial intelligence has proven to be an adequate technique for dealing with the decision-making tasks that are involved with the management of complex organizations.

Patient-Centered Simulation to Aid Decision-Making in Hospital Management:

Computer simulation has eased the study of complex systems. A hospital is a complex sys tem that is formed by a large number of units with strong interrelationships. Even though resources are limited, patients must be effi ciently treated. This paper presents simulation as a tool to aid hospital management. In the first phase we present an introduction to the problem and its motivation. The next step is the description of how the system functions. The choice of the simulation model and the approach in dealing with it are described. Finally, the implementation of the simulation tool is pre sented. This tool is used for supporting the deci sion-making processes in hospital management.

Verification and validation of an intelligent tutorial system

This paper presents the results of a verification and validation process for an intelligent system. The system being studied is an Intelligent Tutorial that employs fuzzy logic and multiagent systems. Software engineering techniques were used in the verification process, while the validation exploited both qualitative and quantitative techniques.

Cytological breast fine needle aspirate images analysis with a genetic fuzzy finite state machine

A system based on a fuzzy finite state machine (FFSM) has been developed for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. The system uses computer vision techniques to analyse cell nuclei in order to extract determinate features and to try to find, by means of genetic algorithms (GA), the ideal FFSM that is able to classify them. This application to breast cancer diagnosis uses the characteristics of individual cells to discriminate benign from malignant breast lumps. In our system, we try to find a texture measurement that can be included in the feature set in order to improve the classifier performance: a complexity measurement of the structural pattern is used to discriminate between benign and malign cells. With this measure and the technique described, we have observed that not only is the absolute complexity of the image relevant, but also the way in which the complexity is distributed at different scales.

Fuzzy and MultiAgent Instructional Planner for an Intelligent Tutorial System

This article presents some aspects in our research into the design of a Fuzzy and MultiAgent Instructional Planner belonging to an Intelligent Tutoring System (ITS), which has been designed as a tool for the reinforcement of the addition operation. The authors propose the combined use of both fuzzy and MultiAgent Systems. The fuzzy logic methodology is used to model the students knowledge and the teaching strategy. Furthermore, the MultiAgent System implemented determines the learning objectives so as to provide the student with an efficient learning process. The fuzzy and MultiAgent Systems comprising the instructional planner were verified with the collaboration of experts in mathematics and in other areas of knowledge. The results obtained by the primary school children who used the ITS are also presented.

Automatic analysis of signals with symbolic content

This paper presents a set of methods for helping in the analysis of signals with particular features that admit a symbolic description. The methodology is based on a general discrete model for a symbolic processing subsystem, which is fuzzyfied by means of a fuzzy inference system. In this framework a number of design problems have been approached. The curse of dimensionality problem and the specification of adequate membership functions are the main ones. In addition, other strategies, which make the design process simpler and more robust, are introduced. Their goals are automating the production of the rule base of the fuzzy system and composing complex systems from simpler subsystems under symbolic constrains. These techniques are applied to the analysis of wakefulness episodes in the sleep EEG. In order to solve the practical difficulty of finding remarkable situations from the outputs of the symbolic subsystems an unsupervised adaptive learning technique (FART network) has been applied.

Teacher strategies simulation by using fuzzy systems

Fuzzy system technologies are of emerging interest in the specification and implementation of complex systems. This article introduces fuzzy instructional planner, which models the tutor module in a intelligent tutorial system (ITS). The behaviour of this system is defined by strategies which adapt the learning process for individual students by applying appropriate pedagogical methodologies. For this reason, the purpose of a instructional planner is to mimic the behaviour of the teacher able to control learning process satisfactorily. The knowledge acquisition is based on the reasoning carried out by the teacher in a learning process. Usually, this information is obtained from human expert who supplied linguistic information. The capacity to use linguistic information is specific to fuzzy inference systems.

Java for parallel discrete event simulation: a survey

Since the early 1990s, when it was first released, Java has become one of the most widespread programming languages. Discrete Event Simulation (DES) and also Parallel Discrete Event Simulation (PDES) have attracted more and more projects which are Java–based. This paper presents a brief survey on the tools and facilities that make Java such an attractive option for parallel simulation developers. Nevertheless, several drawbacks and lacks of the language are also exposed.