As relações entre a Matemática e a Astronomia no século XVI: tradução e comentários da obra Ouranographia de Adriaan van Roomen

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reducing the gap between mobile and intelligent software agents

This paper presents an approach to integrate an artificial intelligence (AI) technique, concretely rule-based processing, into mobile agents. In particular, it focuses on the aspects of designing and implementing an appropriate inference engine of small size to reduce migration costs. The main goal is combine two lines of agent research, First, the engineering oriented approach on mobile agent architectures, and, second, the AI related approach on inference engines driven by rules expressed in a restricted subset of first-order predicate logic (FOPL). In addition to size reduction, the main functions of this type of engine were isolated, generalized and implemented as dynamic components, making possible not only their migration with the agent, but also their dynamic migration and loading on demand. A set of classes for representing and exchanging knowledge between rule-based systems was also proposed.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

Mapeamento Mobile Art: propostas poéticas em telefones celulares : de 2001 a 2010

Pós-graduação em Artes - IA

MiLoc-Sys Mobile: gestão em locação

Companies that invest in current technologies maintain themselves updated, improve their business rules and anticipate themselves against rivals providing a better service to their customers. This project aims to develop an ERP - Enterprise Resource Planning module for Android which complements an existing manager system and, that attends the needs of a rental equipment business for civil building, i.e., it improves the communication channel company-client and betters the identification and control of products. During the developing of this project, it was necessary to study the company business rules, analyze the requirements and the appropriate technologies. This project was organized in two parts, contemplating e ach of these needs. It were implemented specific modules for generate budgets and pre-orders in the first part and, the use of radiofrequency tags in the second one. Thus, it was possible to assign mobility to company business rules so that a better rental service can be provided and the equipments can be better managed