Catálogo de publicaciones - libros

Considered are controllable systems of (structured) objects ∈ , a non-empty set, to which time instants (time “points”) of a partial ordered time (, <) are assigned. Treated are topological concepts, a theory of controllable variables, ordering relations on (,<) induced by <, discrete and continuous processes (), relations of processes, a general theory of algorithms, neighborhoods of processes, process approximations, and controllable evolutionary processes. Care has been taken of causality and time dependencies of physical processes.

In this paper we describe the results of modelling an activity in WSN; we concentrate on effects of organising groups of sensors, on relationships between sensors and the effects on their autonomy. Consequently our work are concentrated on developing the formal methods and techniques necessary to model and evaluate situations in the network, processes of decisions making and implementing intelligent behavior while following the general outlines of the network activity. These requirements will entail investigating ways in which intelligent systems evaluate, interact and self-organise, both individually and cooperating with other aerial explorers or interacting with environmental stimulus.

Fuzzy logic breaks logic equivalence of statements such as (A∧B)∨(¬A∧B)∨(A∧ ¬B) and A∨B. It breaks the symmetry of use of such logically equivalent statements. There is a controversy about this property. It is called a paradox (Elkan’s paradox) and interpreted as a logical weakness of fuzzy logic. In the opposite view, it is not a paradox but a fundamental postulate of fuzzy logic and one of the sources of its success in applications. There is no explanatory model to resolve this controversy. This paper provides such a model using a vector/matrix logic of rational and irrational agents that covers scalar classical and fuzzy logics. It is shown that the classical logic models rational agents, while fuzzy logic can model irrational agents. Rational agents do not break logic equivalence in contrast with irrational agents. We resolve the paradox by showing that the classical and fuzzy logics have different domains of rational and irrational agents.

The objective of this paper is to study several approaches to forecasting the temporal evolution of meteorological synoptic maps that carry information in visual form but without objects. Window-based descriptors are used in order to accomplish continuity so the prediction task is possible. Linear and non-linear models are applied for the prediction task, the first one being based on a spatio-temporal autoregressive (STAR) model whereas the second one is based on artificial neural networks. The method and obtained results are discussed.

Groupware applications support group work and groups may perform geographically distributed with different roles and using different organizational structures. It is important that these applications do not provide only the needed infrastructure to support group work, but also grant some ways to change the group behaviour during a session. Therefore, this paper presents a conceptual model of the session management policies by means of an ontology, i.e. we model the form in which group work is organized. This ontology describes the concepts, the relations among them and the axioms that allow to specify and control the role changes that a user can play in a session and the changes in the rights/obligations of each role. In this model we have separated the mechanisms that consent to establishing a session (i.e. mechanisms to create the shared workspace) from the session management policies. Moreover, we can create templates of policies that can be employed to facilitate their reuse in runtime. In this way, we can affirm that this model smooths the dynamic group work.

This work provides both a new global authentication system for Mobile Ad-hoc NETworks and a study of its simulation with NS-2. The proposed scheme is constructed in a self-organizing manner, which implies the fulfillment of most requirements for this type of networks, such as adaptation to the changing topology of the network, public availability of broadcast communications and strength of access control.

The main goal of this project is to monitor and control remote sensors from one or more desalination plants. These plants can be found and distributed from each other miles away. All critical parameters must be controlled. In a desalination plant, the installed sensors are the key elements. These sensors feed the system providing the needed information so it could work properly. The plant state is defined by the sensors readings. From this state, we can identify possible anomalies in the normal behavior of the plant, which could cause the activation of different alarms. In order to accomplish these goals, a modular and flexible system has been developed not only for desalination plants but also for any other systems that require controlling remote sensors. The system allows direct access to this remote information through a variety of interfaces (web, SMS). The tier architectural design plays an important role in providing a basic characteristic: its adaptability to different environments. Therefore, adding or changing specific modules can be easily introduced into the modular structure of the system without interfering the core application modules. The application has been develop under Java technologies (J2EE) using Open Source Toolkits.

Traditional interpretation of early visual image processing in a retinal level has focused exclusively on spatial aspects of receptive fields (RFs). We have learned recently that RFs are spatiotemporal entities and this characterization is crucial in understanding and modelling circuits in early visual processing ([2]). We present a generalization of the layered computation concept to describe visual information processing in the joint space-time domain.

Automatic change detection is the important subject in dynamical systems. There are known techniques for linear and some techniques for nonlinear systems, but merely few of them concern deterministic chaos. This paper presents automatic change detection technique for dynamical systems with chaos based on three different approaches neural network model, fractional dimension and recurrence plot. Control charts are used as a tool for automatic change detection. We consider the dynamical system described by the univariate time series. We assume that change parameters are unknown and the change could be either slight or drastic. Methods are checked by using small data set and stream data.

In this paper we report the numeric implementation of previously proposed symbolic non-standard discretization methods for nonlinear dynamical control systems. We discuss the advantages and disadvantages of both symbolic and numeric implementations, and illustrate them through their applications to case studies.