Semantic relations extraction from unstructured information for domain ontologies enrichment

Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Poker learner: modelação de jogadores através de data mining

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Aplicação da linha de equilíbrio no planeamento e controlo da construção

Dissertação de mestrado integrado em Engenharia Civil

Desenvolvimento do pensamento computacional com recurso ao Scratch: uma experiência com alunos do 8ºano

Relatório de estágio de mestrado em Ensino de Informática

A Grid Supercomputing Enviroment for High Demand Computational Applications

Despite the huge increase in processor and interprocessor network performace, many computational problems remain unsolved due to lack of some critical resources such as floating point sustained performance, memory bandwidth, etc... Examples of these problems are found in areas of climate research, biology, astrophysics, high energy physics (montecarlo simulations) and artificial intelligence, among others. For some of these problems, computing resources of a single supercomputing facility can be 1 or 2 orders of magnitude apart from the resources needed to solve some them. Supercomputer centers have to face an increasing demand on processing performance, with the direct consequence of an increasing number of processors and systems, resulting in a more difficult administration of HPC resources and the need for more physical space, higher electrical power consumption and improved air conditioning, among other problems. Some of the previous problems can´t be easily solved, so grid computing, intended as a technology enabling the addition and consolidation of computing power, can help in solving large scale supercomputing problems. In this document, we describe how 2 supercomputing facilities in Spain joined their resources to solve a problem of this kind. The objectives of this experience were, among others, to demonstrate that such a cooperation can enable the solution of bigger dimension problems and to measure the efficiency that could be achieved. In this document we show some preliminary results of this experience and to what extend these objectives were achieved.

Indexació de continguts televisius: anàlisis de vídeo

Aquest és un projecte que tracta sobre la indexació automàtica de continguts televisius. És una tasca que guanyarà importància amb els imminents canvis que hi haurà en la televisió que coneixem. L'entrada de la nova televisió digital farà que hi hagi una interacció molt més fluida entre l'espectador i la cadena, a més de grans quantitats de canals, cada un amb programes de tipus totalment diferents. Tot això farà que tenir mètodes de cerca basats en els continguts d'aquests programes sigui del tot imprescindible. Així doncs, el nostre projecte està basat plenament en poder extreure alguns d'aquests descriptors que faran possible la categorització dels diferents programes televisius.

Indexació de continguts televisius: anàlisi de so

Aquest és un projecte sobre la indexació de continguts televisius; és a dir, el procés d’etiquetatge de programes televisius per facilitar cerques segons diferents paràmetres. El món de la televisió està immers en un procés d'evolució i canvis gràcies a l'entrada de la televisió digital. Aquesta nova forma d'entendre la televisió obrirà un gran ventall de possibilitats i permetrà la interacció entre usuaris i emissora. El primer pas de la gestió de continguts consisteix en la indexació dels programes segons el contingut. Aquest és el nostre objectiu. Indexar els continguts televisius de manera automàtica mitjançant la intelligència artificial.

Programación de un robot autónomo: diseño, construcción, programación e integración de un robot autónomo en el entorno Pyro

En aquest projecte, s'ha dissenyat, construït i programat un robot autònom, dotat de sistema de locomoció i sensors que li permeten navegar sense impactar en un entorn controlat. Per assolir aquests objectius s'ha dissenyat i programat una unitat de control que gestiona el hardware de baix volum de dades amb diferents modes d'operació, abstraient-lo en una única interfície. Posteriorment s'ha integrat aquest sistema en l'entorn de robòtica Pyro. Aquest entorn permet usar i adaptar, segons es necessiti, eines d'intel·ligència artificial ja desenvolupades.

Innovació tecnològica a la construcció subterrània

Report for the scientific sojourn carried out in the International Center for Numerical Methods in Engineering (CIMNE) –state agency – from February until November 2007. The work within the project Technology innovation in underground construction can be grouped into the following tasks: development of the software for modelling underground excavation based on the discrete element method - the numerical algorithms have been implemented in the computer programs and applied to simulation of excavation using roadheaders and TBM-s -; coupling of the discrete element method with the finite element method; development of the numerical model of rock cutting taking into account of wear of rock cutting tools -this work considers a very important factor influencing effectiveness of underground works -.

Human biology: cibernética y biología humana en el nuevo discurso expositivo de la década de 1970

En este trabajo se explica cuáles fueron las estrategias utilizadas y los resultados obtenidos en la primera exposición del nuevo esquema museográfico del Museo de Historia Natural de Londres, concebido por Roger Miles, Jefe del Departamento de Servicios Públicos de esa prestigiada institución. Esta iniciativa pretendía atraer a un mayor número de visitantes a partir de exposiciones basadas en modelos y módulos interactivos que relegaban a los objetos de las colecciones a un segundo plano. La exposición se tituló Human Biology y fue inaugurada el 24 de mayo de 1977. El tema de la exposición fue la biología humana, pero como se argumenta en este trabajo, Human Biology sirvió también como medio para legitimar el discurso modernizador de la biología humana, en tanto disciplina más rigurosa por las herramientas y técnicas más precisas que las utilizadas por la antropología física tradicional. Se buscaba también generar una audiencia para reforzar el campo interdisciplinario de la ciencia cognitiva y en particular la inteligencia artificial. El equipo de asesores científicos de la exposición contó entre sus miembros con personalidades que jugaron un papel protagónico en el desarrollo de esas disciplinas, y necesitaban demostrar su validez y utilidad ante los no especialistas y el público en general.

Data bases for the assessment of medical technologies: examples from Europe.

The assessment of medical technologies has to answer several questions ranging from safety and effectiveness to complex economical, social, and health policy issues. The type of data needed to carry out such evaluation depends on the specific questions to be answered, as well as on the stage of development of a technology. Basically two types of data may be distinguished: (a) general demographic, administrative, or financial data which has been collected not specifically for technology assessment; (b) the data collected with respect either to a specific technology or to a disease or medical problem. On the basis of a pilot inquiry in Europe and bibliographic research, the following categories of type (b) data bases have been identified: registries, clinical data bases, banks of factual and bibliographic knowledge, and expert systems. Examples of each category are discussed briefly. The following aims for further research and practical goals are proposed: criteria for the minimal data set required, improvement to the registries and clinical data banks, and development of an international clearinghouse to enhance information diffusion on both existing data bases and available reports on medical technology assessments.

Estudi de comportaments socials d'aixams robòtics amb aplicació a la neteja d'espais no estructurats

La intel·ligència d’eixams és una branca de la intel·ligència artificial que està agafant molta força en els últims temps, especialment en el camp de la robòtica. En aquest projecte estudiarem el comportament social sorgit de les interaccions entre un nombre determinat de robots autònoms en el camp de la neteja de grans superfícies. Un cop triat un escenari i un robot que s’ajustin als requeriments del projecte, realitzarem una sèrie de simulacions a partir de diferents polítiques de cerca que ens permetran avaluar el comportament dels robots per unes condicions inicials de distribució dels robots i zones a netejar. A partir dels resultats obtinguts serem capaços de determinar quina configuració genera millors resultats.