Sistema de posicionamento baseado em redes de sensores sem fios

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Sinistralidade rodoviária e o marketing relacional: perspetivas de soluções mais eficazes no seu combate em Portugal

Dissertação de mestrado em Marketing e Estratégia

Plano estratégico de marketing de uma empresa de moda portuguesa: estudo de caso da marca Guimanos

Dissertação de mestrado em Design de Comunicação de Moda

Aplicação móvel android de apoio a gestão de empréstimos e reservas das bibliotecas da Universidade do Minho

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Pervasive business intelligence: a marketing intelligence framework proposal

Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

Divulgação de boas práticas como estratégia de marketing na construção

Dissertação de mestrado integrado em Engenharia Civil

Os social media como parte integrante da comunicação empresarial

Relatório de estágio de mestrado em Ciências da Comunicação (área de especialização Publicidade e Relações Públicas)

Simultaneous detection of cyclopiazonic acid and aflatoxin B1 by HPLC in methanol/water mobile phase

A simple procedure for the simultaneous detection of cyclopiazonic acid (CPA) and aflatoxin B1 from fungal extracts is presented, using a methanol and water mobile phase and fluorescence detection. This methodology has been tested with standard solutions of both mycotoxins CPA and Aflatoxin B1 and with methanolic extracts of Aspergillus section Flavi strains, previously characterized for their mycotoxin production profile. Previously available methodology required the use of two different chromatographic runs for these mycotoxins, with distinct columns and detectors (fluorescence detection with a post-column photochemical derivatization (PHRED) for aflatoxin B1 and UV detection for CPA). The proposed method detects both mycotoxins in a single run. Data from these assays will be presented and discussed.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.