Catálogo de publicaciones - libros

With the continued advances in wireless communications and geo-positioning, an infrastructure is emerging that enables location-based services which rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. The main interest of these services is to efficiently store and query the positions of moving objects. To achieve this goal, index structures are required. In this paper we propose a new index structure for moving objects in networks: NCO-Tree. It efficiently supports the Segment-Based tracking approaches and its optimization. We give the structure description, insertion and search algorithms, then evaluate it with experiment.

This paper studies the direction relations between two spatial objects and presents the reasoning model of spatial direction relation based on Voronoi diagram. The algorithm of the reasoning is described detailedly and an example is analyzed. This paper also discusses the six typical circumstances about spatial direction relation based on Voronoi diagram. These include the direction relations of point-point, point-line, point-region, line-line, line-region and region-region. At last, the advantages and disadvantages about the model are summarized.

This paper describes annotation of face images in keywords based on latent semantic indexing, and experimental results in FIARS. Two latent semantic spaces are constructed from visual and symbolic features. These features are corresponding to lengths of some places of a face and keywords. One latent semantic space is constructed from visual features, the other space is constructed from both features. The former space is used for retrieving similar face images, and the latter for seeking keywords to a given face image. Moreover, the two types of visual futures are utilized. One is specified in terms of the lengths of face parts, and the other in terms of points on the outlines of a face and its parts. As an experiment, recall and precision ratios of assigned keywords are measured using the two types of the visual features.

is an enhanced C++ persistent programming language and compliant with the standard. provides which enables any persistent objects to be extended by obtaining any type and by losing any unnecessary types. Furthermore, provides which enables any persistent objects to be accessed through a virtual type derivable from other base/virtual types. However, it does not allow the type which a virtual type is derived from to be a repeating one. To overcome this constraint, this paper proposes which allows a virtual type to be derived from a repeating one and shows a method of implementing it in .

When we look for locations, we use the names of geographical objects (e.g., landmarks, rivers, lakes). However, we often memorize the locations by using relations among landmarks like remarkable buildings. For this reason, we focus on spatial relations among geographical objects, and we define spatial relations based on the geographical proximity. In this paper, we manipulate two types of geographical proximities: a vertical proximity and a horizontal proximity. The vertical proximity shows two geographical objects are overlapping, and the horizontal proximity shows two geographical objects are adjacent. In order to represent these proximities, we introduce two spatial relations: “overlapping” and “neighboring”. “Overlapping” represents the vertical proximity, and “neighboring” represents the horizontal proximity. Furthermore, we propose a spatial relational graph which is generated by connecting geographical objects with these two spatial relations. In addition, we search maps by inclusive relations among spatial relational graphs, and implement the prototype system to find out locations by using a map.

This paper addresses a geographic information management to model various kinds of geographic objects with respect to the space and time features. In this model, an event represents the geographic situation in which geographic objects change, and represented as a set of geographic objects which are concerned to the event. It is possible to easily divide an event into sub-events along space and time criteria. Using this model, our geographic information system can provide users with a capability to manipulate an event from various viewpoints.

This paper discusses the evolution of the INCA demonstrator through a number of re-implementations that have investigated the applicability of various aspects of multi-agent technology to the management of Community Care. The latest experiences are described, making full use of the latest developments in semantic agents to provide a richer, more rigorous and highly scalable implementation than the previous demonstrators. This is presented in the context of a simulated real-world environment, based on knowledge of the actual operational environment within which the fully deployed agents would be expected to work. In particular the grouping of different communities of agents so that scalable solutions can be fully implemented and rigorously tested. So for example the agents that one would normally expect within a single household, including the home unit and the associated sensors, alarms etc. are treated as one group, and a care provider and the associated carers also. Not only does this reduce the communications overhead but also leads to simplifications in implementation as each class of agent only needs to be implemented once and individual instances are characterized by initial configurations and their interactions with their peers.

The problem of controlling the level of unconsciousness measured by the Bispectral Index of the EEG (BIS) of patients under anaesthesia, is considered. It is assumed that the manipulated variable is the infusion rate of the hypnotic drug propofol, while the drug remifentanil is also administered for analgesia. Since these two drugs interact, the administration rate of remifentanil is considered as an accessible disturbance. In order to tackle the high uncertain present on the system, the predictive adaptive controller MUSMAR is used. The performance of the controller is illustrated by means of simulation with 45 patient individual adjusted models, which incorporate the effect of the drugs interaction on BIS. This controller structure proved to be robust to the remifentanil disturbance, different reference values and noise. A reduction of propofol consumption was also observed when comparing to the real clinical dose used for a similar BIS trend.

In previous papers we introduced , a multi-agent system that helps doctors to follow the automatic application of clinical guidelines to patients. In this paper we show how aggregation operators, based on fuzzy logic, may be integrated in this system in order to personalize some of its tasks. These operators take into account the patient preferences when several medical services propose different conditions under which a specific medical test can be performed. The paper describes how different proposals can be rated and ranked, and discusses the influence of two parameters (the set of linguistic preference values and the rating policy) on the results of the aggregation procedure.

In recent years, the interest in extracting useful knowledge from gene expression data has experimented an enormous increase with the development of microarray technique. Biclustering is a recent technique that aims at extracting a subset of genes that show a similar behaviour for a subset conditions. It is important, therefore, to measure the quality of a bicluster, and a way to do that would be checking if each data submatrix follows a specific trend, represented by a pattern. In this work, we present an evolutionary algorithm for finding significant shifting patterns which depict the general behaviour within each bicluster. The empirical results we have obtained confirm the quality of our proposal, obtaining very accurate solutions for the biclusters used.