Rosa Ayala

A Model Transformation Approach for Automatic Composition of COTS User Interfaces in Web-Based Information Systems

Globalization of the information and the Knowledge Society requires the modernization of Web-based Information Systems (WIS) into evolutive and adaptable user interfaces. Today, WIS user interfaces are built following traditional development paradigms. This article is inspired on a Model-Driven Development (MDD) perspective to produce runtime automatic composition of user interfaces from model and metamodel representations of widgets-type COTS interface components architectures and model transformation.

Contextual and Hierarchical Classification of Satellite Images Based on Cellular Automata

Satellite image classification is an important technique used in remote sensing for the computerized analysis and pattern recognition of satellite data, which facilitates the automated interpretation of a large amount of information. Today, there exist many types of classification algorithms, such as parallelepiped and minimum distance classifiers, but it is still necessary to improve their performance in terms of accuracy rate. On the other hand, over the last few decades, cellular automata have been used in remote sensing to implement processes related to simulations. Although there is little previous research of cellular automata related to satellite image classification, they offer many advantages that can improve the results of classical classification algorithms. This paper discusses the development of a new classification algorithm based on cellular automata which not only improves the classification accuracy rate in satellite images by using contextual techniques but also offers a hierarchical classification of pixels divided into levels of membership degree to each class and includes a spatial edge detection method of classes in the satellite image.

Modelling an Environmental Knowledge-Representation System

Environmental Management Systems(EMS) are social-technical systems with a variety of final users and actors that cooperate with each other and interact with the system for decision-making, problems resolution, etc. The modelling of these systems using formal methods provides mechanisms and tools that guarantee the users a correct deployment and use of it. In this paper we showing environmental knowledge modelling accomplished in the SOLERES project, a spatio-temporal information system for environmental management, a cooperative system based on multi-agent architectures and intelligent agents. The system modelling uses UML for knowledge representation, and Model-Driven Engineering(MDE) perspective --based on the OMG classical Model-driven Architecture(MDA)-- to create OWL/XML ontology automatically.

Characterization of Texture in Images by Using a Cellular Automata Approach

Spatial patterns in an image that shows a visual perception of roughness or softness of the surface is known as the texture of the image. Most of the analysis and description of texture found in the literature is based on statistical or structural properties of this attribute [2]. The field of cellular automata (CA), which has been developed mainly to model the dynamical behavior of systems, is based on the behavior or arrangements of pixel values and their neighborhood which, according to some rules behaves in different manners [2, 8]. In this paper, within the frame of structural approach, a novel method based on the properties of linear cellular automata is proposed to characterize different sort of textures. To this purpose, it is assumed that a binary version of the image under study was generated by a cellular automata technique. By using this model a number of textural primitives are found which allows the production of a characterizing image. In order to verify the feasibility of the proposed method, texture images generated by CA techniques as well as natural images has been used.

Classification of Satellite Images Using the Cellular Automata Approach

Nowadays, remote sensing allows us the acquisition of information using techniques that do not require be in contact with the object or area being observed. This science can be used in many environmental applications, helping to solve and improve the social problems derived from them. Examples of re- motely sensed applications are in soil quality, water resources, environmental management and protection or meteorology, among others. The classification algorithms are one of the most important techniques used in remote sensing that help developers to interpret the information contained in the satellite images. At present, there are several classification processes, i.e., maximum likelihood, paralelepiped or minimum distance classifier, among others. In this paper, we investigate a new Classification Algorithm based on Cellular Automata (ACA): a technique usually used by researchers on Complex Systems. This kind of clas- sifier will be validated and experimented in the SOLERES framework.

SOLERES-HCI: Modelling a Human-Computer Interaction Framework for Open EMS

Organizations and administrations working on environmental information for specific behaviors of soil or planning management of natural resources need to have innovator systems of quality information in order to guarantee the success of theirs daily activities. Experts managing the system consider that not only it is important to have reliable and updated information in order to help to make the most suitable decisions. Due to the variety of final users that cooperate and interact with the decision making system (for instance, politicians, technicians, administrators, etc.) it is also important to have real-time query systems that facilitate the human-human and human-computer interaction and coordination not only with user interfaces that adapt to the users’ profiles habits, but also with intelligent software agents. In this work we advance some ideas about the HCI framework of the SOLERES project, an Environmental Management System (EMS) that fixes, defines and experiences solutions to problems previously described.

Open-Environmental Ontology Modeling

Current open information systems need formal semantic definitions to describe and handle information which is dealt within different interaction environments such as human-to-human, human-to-computer, and computer-to-computer interactions. This paper provides a semantic definition of the knowledge used by environmental management information systems. We describe an ontological model in UML class diagrams and present a formalization of the ontology in first-oder logic and encoded in description logic. A model transformation approach is also used to map the UML class diagram elements into web ontology language. A running example is presented to explain the ontological knowledge modeling of EMIS SOLERES cartography and satellite information.

Cellular automata applied in remote sensing to implement contextual Pseudo-fuzzy classification

Nowadays, remote sensing is used in many environmental applications, helping to solve and improve the social problems derived from them. Examples of remotely sensed applications include soil quality studies, water resources searching, environmental protection or meteorology simulations. The classification algorithms are one of the most important techniques used in remote sensing that help developers to interpret the information contained in the satellite images. At present, there are several classification processes, i.e., maximum likelihood, paralelepiped or minimum distance classifier. In this paper we investigate a new satellite image classification Algorithm based on Cellular Automata (ACA), a technique usually used by researchers on complex systems. There are not previous works related to satellite image classification with cellular automata. This new kind of satellite image classifier, that improves the results obtained by classical algorithms in several aspects, has been validated and experimented in the SOLERES framework.

Semantic Matching of Components at Run-Time in Distributed Environments

Software factories are a key element in Component-Based Software Engineering due to the common space provided for software reuse through repositories of components. These repositories can be developed by third parties in order to be inspected and used by different organizations, and they can also be distributed in different locations. Therefore, there is a need for a trading service that manages all available components. In this paper, we describe a matching process based on syntactic and semantic information of software components. This matching operation is part of a trading service which is in charge of generating configurations of components from architectural definitions. With this aim, the proposed matching allows us to evaluate and score the possible configurations, thus guiding a search process to build the architectural solution which best fulfills an input definition.

OntoTrader: An Ontological Web Trading Agent Approach for Environmental Information Retrieval

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a “Query-Searching/Recovering-Response” information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated.