Sistema de apoio à criminologia

Este trabalho consiste no desenvolvimento de um Sistema de Apoio à Criminologia – SAC, onde se pretende ajudar os detectives/analistas na prevenção proactiva da criminalidade e na gestão dos seus recursos materiais e humanos, bem como impulsionar estudos sobre a alta incidência de determinados tipos de crime numa dada região. Historicamente, a resolução de crimes tem sido uma prerrogativa da justiça penal e dos seus especialistas e, com o aumento da utilização de sistemas computacionais no sistema judicial para registar todos os dados que dizem respeito a ocorrências de crimes, dados de suspeitos e vítimas, registo criminal de indivíduos e outros dados que fluem dentro da organização, cresce a necessidade de transformar estes dados em informação proveitosa no combate à criminalidade. O SAC tira partido de técnicas de extracção de conhecimento de informação e aplica-as a um conjunto de dados de ocorrências de crimes numa dada região e espaço temporal, bem como a um conjunto de variáveis que influenciam a criminalidade, as quais foram estudadas e identificadas neste trabalho. Este trabalho é constituído por um modelo de extracção de conhecimento de informação e por uma aplicação que permite ao utilizador fornecer um conjunto de dados adequado, garantindo a máxima eficácia do modelo.

Análise de eficiência energética de transportes rodoviários

Projecto para obtenção do grau de Mestre em Engenharia Informática e de computadores

Towards the detection of deception in interactive multimedia environments

A classical application of biosignal analysis has been the psychophysiological detection of deception, also known as the polygraph test, which is currently a part of standard practices of law enforcement agencies and several other institutions worldwide. Although its validity is far from gathering consensus, the underlying psychophysiological principles are still an interesting add-on for more informal applications. In this paper we present an experimental off-the-person hardware setup, propose a set of feature extraction criteria and provide a comparison of two classification approaches, targeting the detection of deception in the context of a role-playing interactive multimedia environment. Our work is primarily targeted at recreational use in the context of a science exhibition, where the main goal is to present basic concepts related with knowledge discovery, biosignal analysis and psychophysiology in an educational way, using techniques that are simple enough to be understood by children of different ages. Nonetheless, this setting will also allow us to build a significant data corpus, annotated with ground-truth information, and collected with non-intrusive sensors, enabling more advanced research on the topic. Experimental results have shown interesting findings and provided useful guidelines for future work. Pattern Recognition

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Rede social académica

O processo de Bolonha apresenta directivas para a construção de um espaço europeu de ensino superior. A adopção destas directivas requer uma abordagem que favoreça, na prática, a mobilidade dos estudantes que têm dificuldades em compreenderem as oportunidades que lhes são oferecidas. Neste contexto, esta dissertação explora a hipótese de utilização de uma rede social para apoiar a mobilidade de estudantes no espaço europeu. No âmbito desta dissertação propõe-se um modelo de conhecimento para representar os membros de uma rede social vocacionada para apoiar cenários de mobilidade, designada por rede social académica. Este modelo foi obtido pela fusão da ontologia Academic Ontology to Support the Bologna Mobility Process com a ontologia Friend of a Friend Ontology. Para efeitos de avaliação experimental, foi criado um demonstrador numa rede social disponível publicamente na Internet que utiliza uma versão simplificada do modelo proposto. Os cenários usados nas experiências representam situações reais às quais foi aplicado um processo rudimentar de descoberta de conhecimento

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Universidades da terceira idade: duas décadas de intervenção em Portugal

Dissertação apresentada à Escola Superior de Educação de Lisboa para a obtenção do grau de mestre em Ciências da Educação - Especialidade em Educação Social e Intervenção Comunitária

Integrated didactics: an example of a curriculum model enhancing knowledge crossing

In this paper, we introduce an innovative course in the Portuguese Context, the Master's Course in “Integrated Didactics in Mother Tongue, Maths, Natural and Social Sciences”, taking place at the Lisbon School of Education and discussing in particular the results of the evaluation made by the students who attended the Curricular Unit - Integrated Didactics (CU-ID). This course was designed for in-service teachers of the first six years of schooling and intends to improve connections between different curriculum areas. In this paper, we start to present a few general ideas about curriculum development; to discuss the concept of integration; to present the principles and objectives of the course created as well as its structure; to describe the methodology used in the evaluation process of the above mentioned CU-ID. The results allow us to state that the students recognized, as positive features of the CU-ID, the presence in all sessions of two teachers simultaneously from different scientific areas, as well as invitations issued to specialists on the subject of integration and to other teachers that already promote forms of integration in schools. As negative features, students noted a lack of integrated purpose, applying simultaneously the four scientific areas of the course, and also indicated the need to be familiar with more models of integrated education. Consequently, the suggestions for improvement derived from these negative features. The students also considered that their evaluation process was correct, due to the fact that it was focused on the design of an integrated project for one of the school years already mentioned.