Quadratic programming versus second order con programming in portfolio optimization

Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.

Implementação de um modelo de geometric semantic genetic programming para aplicação naval

Recaí sob a responsabilidade da Marinha Portuguesa a gestão da Zona Económica Exclusiva de Portugal, assegurando a sua segurança da mesma face a atividades criminosas. Para auxiliar a tarefa, é utilizado o sistema Oversee, utilizado para monitorizar a posição de todas as embarcações presentes na área afeta, permitindo a rápida intervenção da Marinha Portuguesa quando e onde necessário. No entanto, o sistema necessita de transmissões periódicas constantes originadas nas embarcações para operar corretamente – casos as transmissões sejam interrompidas, deliberada ou acidentalmente, o sistema deixa de conseguir localizar embarcações, dificultando a intervenção da Marinha. A fim de colmatar esta falha, é proposto adicionar ao sistema Oversee a capacidade de prever as posições futuras de uma embarcação com base no seu trajeto até à cessação das transmissões. Tendo em conta os grandes volumes de dados gerados pelo sistema (históricos de posições), a área de Inteligência Artificial apresenta uma possível solução para este problema. Atendendo às necessidades de resposta rápida do problema abordado, o algoritmo de Geometric Semantic Genetic Programming baseado em referências de Vanneschi et al. apresenta-se como uma possível solução, tendo já produzido bons resultados em problemas semelhantes. O presente trabalho de tese pretende integrar o algoritmo de Geometric Semantic Genetic Programming desenvolvido com o sistema Oversee, a fim de lhe conceder capacidades preditivas. Adicionalmente, será realizado um processo de análise de desempenho a fim de determinar qual a ideal parametrização do algoritmo. Pretende-se com esta tese fornecer à Marinha Portuguesa uma ferramenta capaz de auxiliar o controlo da Zona Económica Exclusiva Portuguesa, permitindo a correta intervenção da Marinha em casos onde o atual sistema não conseguiria determinar a correta posição da embarcação em questão.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Using a domain-specific language to enrich ETL schemas

Today it is easy to find a lot of tools to define data migration schemas among different types of information systems. Data migration processes use to be implemented on a very diverse range of applications, ranging from conventional operational systems to data warehousing platforms. The implementation of a data migration process often involves a serious planning, considering the development of conceptual migration schemas at early stages. Such schemas help architects and engineers to plan and discuss the most adequate way to migrate data between two different systems. In this paper we present and discuss a way for enriching data migration conceptual schemas in BPMN using a domain-specific language, demonstrating how to convert such enriched schemas to a first correspondent physical representation (a skeleton) in a conventional ETL implementation tool like Kettle.

Refinement and variability techniques in model transformation of software requirements

Tese de Doutoramento em Tecnologias e Sistemas de Informação

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

Cross-language influences on new second language vocabulary acquisition: the effect of learning method

Dissertação de mestrado integrado em Psicologia

Otimização com restrições de complementaridade: algoritmos e aplicações

Tese de Doutoramento em Engenharia Industrial e de Sistemas (PDEIS)

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Digital manipulatives as scaffolds for preschoolers’ language development

The study reported here aims at contributing to a deeper understanding of the educational possibilities offered by digital manipulatives in preschool contexts. It presents a study carried with a digital manipulative to enhance the development of lexical knowledge and language awareness, which are relevant language abilities for formal literacy learning. The study took place in a Portuguese preschool, with a class of 20 five-year-olds in collaboration with the teacher. The digital manipulative supported the construction of multiple fictional worlds, motivating children's verbal interactions, and the playing of words and sound games, thus contextualizing the learning of an extensive collection of vocabulary and language awareness abilities. The degree of engagement and involvement that the manipulative provided in supporting children’s imaginative play as well as the imitation, in their own play, of the playful pedagogical interventions that the teacher had designed, shows the importance of well- designed materials that support a child-centered learning model. As such, it sustains a discussion on the potential of digital manipulatives to enhance fundamental language development in the preschool years. Further, the study highlights the importance of multidisciplinary teams in the creation of innovative pedagogical materials.

The music of language: an ERP investigation of the effects of musical training on emotional prosody processing

Recent studies have demonstrated the positive effects of musical training on the perception of vocally expressed emotion. This study investigated the effects of musical training on event-related potential (ERP) correlates of emotional prosody processing. Fourteen musicians and fourteen control subjects listened to 228 sentences with neutral semantic content, differing in prosody (one third with neutral, one third with happy and one third with angry intonation), with intelligible semantic content (semantic content condition--SCC) and unintelligible semantic content (pure prosody condition--PPC). Reduced P50 amplitude was found in musicians. A difference between SCC and PPC conditions was found in P50 and N100 amplitude in non-musicians only, and in P200 amplitude in musicians only. Furthermore, musicians were more accurate in recognizing angry prosody in PPC sentences. These findings suggest that auditory expertise characterizing extensive musical training may impact different stages of vocal emotional processing.