Catálogo de publicaciones - libros

Mobility patterns in large cities has changed in the last decades making traditional fix-line public transportation no longer efficient to tackle the increasing complexity. Demand-responsive transportation leverages as an alternative where routes, departure times, vehicles and even operators, can be matched to the identified demand, allowing a more user-oriented and cost effective approach to service provision. In this context, the design of a multiagent system is presented following the agent-oriented software engineering methodology (AOSE) PASSI.

In this paper we propose the use of a social robot as a majordomo interface between users and Smart Environments. We focus, in particular, on the need for the robot to plan its behaviour by taking into account factors that are relevant in public environments in which the robot has a “social” role. In this context, once the situation has been recognized, the robot uses a probabilistic model to trigger social attitudes towards the user that influence, as a consequence, the activation of its high-level goals. According to the most probable goals, the behaviour plan is computed by applying a utility-based approach that allows selecting the most convenient actions in that situation.

In addition to the Database Comprehension Problem, where diagrammatic conceptual data models are too large for a modeller or domain expert to comprehend or manage, an Ontology Comprehension Problem is emerging. Formal ontologies are, however, more amenable to automated abstractions to improve understandability. Three ways of abstraction are defined with 11 abstraction functions that use foundational ontology categories. Usability of the abstraction functions is enhanced by associating the functions with a basic framework of levels and abstraction hierarchy, thereby facilitating querying and visualizing ontologies.

This paper proposes an approach based on the Ontology and transformation-based error-driven learning (TBL) to recognize Chinese proper nouns. Firstly, our approach redefines the label set and tags Chinese words according to the usage of proper nouns and their context, and then it extracts Characteristic Information (CI) of the proper noun from the text and merges them based on the Ontology. Secondly, it tags the training corpus following the new definition of Multi-dimension Attribute Points (MAP), and then extracts rules using the TBL approach. Finally, it recognizes proper nouns by utilizing the rule set and Ontology. The experimental results in our open test show that the precision is 92.5% and the recall is 86.3%.

This paper describes a similarity measure for images to be used in image-based localization for autonomous robots with low computational resources. We propose a novel signature to be extracted from the image and to be stored in memory. The proposed signature allows, at the same time, memory saving and fast similarity calculation. The signature is based on the calculation of the 2D Haar Wavelet Transform of the gray-level image. We present experiments showing the effectiveness of the proposed image similarity measure. The used images were collected using the AIBOs ERS-7 of the RoboCup Team Araibo of the University of Tokyo on a RoboCup field, however, the proposed image similarity measure does not use any information on the structure of the environment and do not exploit the peculiar features of the RoboCup environment.

In this paper we are reporting about an ongoing project LT4eL (Language Technolohy for eLearning) aiming at improving the effectiveness of retrieval and accessibility of learning objects within a learning management system. We elaborate the process of building the domain ontology and present the multilingual support offered to the application.

In this paper, a hybrid genetic algorithm (HGA) has been developed to solve the constraint-based school timetabling problem (CB-STTP). HGA has a new operator called repair operator, in addition to standard crossover and mutation operators. A timetabling tool has been developed for HGA to solve CB-STTP. The timetabling tool has been tested extensively using real-word data obtained the Technical and Vocational High Schools in Turkey. Experimental results have presented that performance of HGA is better than performance of standard GA.