Ditopic molecular architectures for the recognition of anionic species

Dissertation presented to obtain the Ph.D degree in Chemistry

Sistema de detecção de fogo e detecção e seguimento de objectos

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

A marketing plan for Oqtopus in the Spanish market

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Gesture based persuasive interfaces for public ambient displays

Dissertação de Mestrado em Engenharia Informática 2º Semestre, 2011/2012

Analysable software language translations

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Exploring profitability diversity through financial statement analysis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Avatars and the «Imitation Game» – can machines smile?

Considering Alan Turing’s challenge in «Computing Machinery and Intelligence» (1950) – can machines play the «imitation game»? – it is proposed that the requirements of the Turing test are already implicitly being used for checking the credibility of virtual characters and avatars. Like characters, Avatars aim to visually express emotions (the exterior signs of the existence of feeling) and its creators have to resort to emotion codes. Traditional arts have profusely contributed for this field and, together with the science of anatomy, shaped the grounds for current Facial Action Coding System (FACS) and their databases. However, FACS researchers have to improve their «instruction tables» so that the machines will be able, in a near future, to be programmed to carry out the operation of recognizing human expressions (face and body) and classify them adequately. For the moment, the reproductions have to resort to the copy of real life expressions, and the presente smile of avatars comes from mirroring their human users.

Tool for discovering sequential patterns in financial markets

The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

Use of multi-sensory marketing techniques and its influence on brand experience in retail and HORECA sector

Double degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA- School of Business and Economics and Warsaw School of Economics

As práticas comerciais desleais

The following study aims to examine a controversial and relatively unexplored subject within our system: the legal framework on unfair business-to-consumer commercial practices. Given the fact that this subject is based on the Directive 2005/29/EC, we considered to be appropriate to explore, firstly, the background and origin of such normative instrument. Nevertheless, we have centered our analysis on the interpretation of the set rules established by the Portuguese legal system (Law nr 57/2008, March 26th). For this dissertation, we have proposed a model of tripartite approach. Chapter V seeks to shed light on the general clause by analyzing a set of open concepts such as professional diligence, honest market practice, good faith or material distortion of the consumer’s economic behavior. In chapter VI, we will focus on two common types of unfair commercial practices: misleading and aggressive practices. Finally, due to the fact that chapter VII deals with the black list, we have illustrated the listed practices by giving real life examples. Taking into account the indefinite concepts used in the general prohibition and in the misleading and aggressive clauses, it is particularly difficult to demonstrate the unfairness of the professional’s behavior. In the light of this information, we have concluded that the regime fails on achieving its main goal: it does not protect proper and effectively the consumer’s interests.

Trust, alliance management capability and the alliance management function: A comparative analysis of Portuguese SMEs

Strategic alliances represent a key driver for internationalization and growth, being the purpose of this work project to better understand the intertwined relationship between trust and the existence of an alliance management position. Previous research supports the positive impact of such position in stock market returns. However, little attention has been given to the impact of such position on the level of trust in the collaborative arrangement, which is deemed to be a key driver for alliance success. A qualitative comparative case-study of three Portuguese SMEs is used to draw conclusions from the literature to real life business cases and it demonstrates the positive impact of an alliance management position on trust.

Escalation of conflict in FMCG industry: A negotiation case

This work project develops a case-study to be used in Negotiation courses, both in Masters programs and in executive education workshops. The case-study is based on a real-life negotiating situation in Belgium between Unilever, the second largest Fast Moving Consumer Goods (FMCG) company in the world, and Delhaize, one of the most important Belgium’s retailers, with a significant international presence. We also present an analysis of the negotiation based on relevant literature. First, a brief literature review is presented about how to deal with multiple-issue negotiations and how to deal with processes of escalation of conflict. These concepts are then applied to the analysis of the case-study.

Management consulting lab- Galp social media

This study consists of the reflection on a consultancy project developed by four students and one project manager from NOVA SBE. In attempting to assist Galp Energia structure the operationalization of an entry into Social Media, we were confronted with first-time challenges in real-life highly demanding workplace situations. The following considerations attempt to defuse the problem-solving mindset of the practical experience from the methodological development and learning experience extracted from the consulting line of work

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Predicting market movement with Artificial Neural Networks

This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.