Corporate social responsible behaviour in the financial industry

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

How to increase profitability of Golf Industry in Lisbon?

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

Machine learning Gaussian short rate

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco

Potential for ORC application in the Portuguese manufacturing industry

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

Botnet cluster identification

Botnets are a group of computers infected with a specific sub-set of a malware family and controlled by one individual, called botmaster. This kind of networks are used not only, but also for virtual extorsion, spam campaigns and identity theft. They implement different types of evasion techniques that make it harder for one to group and detect botnet traffic. This thesis introduces one methodology, called CONDENSER, that outputs clusters through a self-organizing map and that identify domain names generated by an unknown pseudo-random seed that is known by the botnet herder(s). Aditionally DNS Crawler is proposed, this system saves historic DNS data for fast-flux and double fastflux detection, and is used to identify live C&Cs IPs used by real botnets. A program, called CHEWER, was developed to automate the calculation of the SVM parameters and features that better perform against the available domain names associated with DGAs. CONDENSER and DNS Crawler were developed with scalability in mind so the detection of fast-flux and double fast-flux networks become faster. We used a SVM for the DGA classififer, selecting a total of 11 attributes and achieving a Precision of 77,9% and a F-Measure of 83,2%. The feature selection method identified the 3 most significant attributes of the total set of attributes. For clustering, a Self-Organizing Map was used on a total of 81 attributes. The conclusions of this thesis were accepted in Botconf through a submited article. Botconf is known conferênce for research, mitigation and discovery of botnets tailled for the industry, where is presented current work and research. This conference is known for having security and anti-virus companies, law enforcement agencies and researchers.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Enhancement of an implemented rating model and impact on existing risk management processes: A hands-on approach from financial supplier risk management within the automotive industry

The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

Strategy of Logoplaste in Mozambique's flexible plastic packaging industry

Logoplaste is a specialist in operating in-house industrial sites for manufacturing rigid plastic packaging containers. In developing countries, especially in Africa, the low income of consumers does not allow a widespread adoption of products typically sold in rigid plastic containers. In these countries the flexible packages are usually adopted as they allow for better ratios of cost/litter of product, particularly in smaller packages. Should Logoplaste offer this type of technology in order to expand into developing countries?

Do social factors matter for innovation, and do they influence innovation in Aeronautics Industry?

Based on the report for the course on “Social Factors of Innovation” of the PhD Program on Technology Assessment, supervised by Prof. António Brandão Moniz, Monte de Caparica, University NOVA Lisbon, Faculty of Sciences and Technology, July 2013

Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.

A business model for an entertainment solution to the in-vehicle infotainment industry

The evolution of mobile technologies that make its presence something ubiquitous and the idea of internet connectivity in every device, often called as the Internet of Things, are pushing a disruption in other industry: the in-vehicle infotainment (IVI). Many companies are trying to enter this new industry that comprises information (weather, news, location services) and entertainment solutions in just one. For that purpose, company X developed a new entertainment solution and intends to bring it to market. This Work Project focuses on creating a business model and an entry mode for the company.

Hotel industry: An answer to the emerging trends on the global demand side of tourism

This dissertation studies essentially how Millennials are changing the hotel industry, in the sense that new trends are emerging with this generation and hotels need to respond accordingly, in order to survive within their competitive industry. Emphasis is also given to Asian travellers, as the enlargement of these countries’ middle class populations is predicted, therefore making Asian travellers a valuable target for the hotel industry. To successfully target this segment, hoteliers need also to consider the cultural differences and aspirations that come together with the Asian travellers, and appropriately adapt their offer to them. I will then redirect this study to the city of Lisbon, the Portuguese capital, to analyse if Lisbon’s four and five-star hotel managers are aware of the new market trends, and to understand how they are changing their hotels in order to make them more attractive to Millennials and Asian travellers. Using a sample of 12 hotels (four and five-stars ratings), I have concluded that, although there is a notable undergoing process of adaptation to these guests, there is a long way ahead in order for Lisbon’s hotels to entirely please and retain millennial guests.

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.

A business plan for a new mobile application to the consumer foodservice industry

The Portuguese consumer foodservice industry is experiencing a boost in technology adoption, driven by significant changes in consumer behavior and business dynamics, due to mobile increasing penetration. Accordingly, the present work project consists on developing a business plan for meeting an identified opportunity in the technological foodservice landscape. Therefore, this report is divided into three sections, each of which addressing different objectives: (A) External Environment, providing key external insights that support the opportunity; (B) Strategy Formulation, establishing a strategic direction; and (C) Action Plan, determining an implementation plan for starting the business