Rely-guarantee protocols for safe interference over shared memory

Mutable state can be useful in certain algorithms, to structure programs, or for efficiency purposes. However, when shared mutable state is used in non-local or nonobvious ways, the interactions that can occur via aliases to that shared memory can be a source of program errors. Undisciplined uses of shared state may unsafely interfere with local reasoning as other aliases may interleave their changes to the shared state in unexpected ways. We propose a novel technique, rely-guarantee protocols, that structures the interactions between aliases and ensures that only safe interference is possible. We present a linear type system outfitted with our novel sharing mechanism that enables controlled interference over shared mutable resources. Each alias is assigned separate, local roles encoded in a protocol abstraction that constrains how an alias can legally use that shared state. By following the spirit of rely-guarantee reasoning, our rely-guarantee protocols ensure that only safe interference can occur but still allow many interesting uses of shared state, such as going beyond invariant and monotonic usages. This thesis describes the three core mechanisms that enable our type-based technique to work: 1) we show how a protocol models an alias’s perspective on how the shared state evolves and constrains that alias’s interactions with the shared state; 2) we show how protocols can be used while enforcing the agreed interference contract; and finally, 3) we show how to check that all local protocols to some shared state can be safely composed to ensure globally safe interference over that shared memory. The interference caused by shared state is rooted at how the uses of di↵erent aliases to that state may be interleaved (perhaps even in non-deterministic ways) at run-time. Therefore, our technique is mostly agnostic as to whether this interference was the result of alias interleaving caused by sequential or concurrent semantics. We show implementations of our technique in both settings, and highlight their di↵erences. Because sharing is “first-class” (and not tied to a module), we show a polymorphic procedure that enables abstract compositions of protocols. Thus, protocols can be specialized or extended without requiring specific knowledge of the interference produce by other protocols to that state. We show that protocol composition can ensure safety even when considering abstracted protocols. We show that this core composition mechanism is sound, decidable (without the need for manual intervention), and provide an algorithm implementation.

Urban change monitoring using GIS and remote sensing tools in Kathmandu valley (Nepal)

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Leadership paradoxes in Angolan organizations: Emic paradoxes, etic paradoxes, and paradox work

The study departs from two assumptions. First, it considers that organizations and their leadership are inherently paradoxical and that, in that sense, dealing with paradox is a necessary component of the leadership process. Second, it explores whether the paradoxes of leadership may manifest differently in different contexts. We explore the emergence of paradox in the leadership of Angolan organizations. Angola is an economy transitioning from a centrally-planned to a market mode, and this makes it a rich site for understanding the specificities of paradoxical processes in an under-researched, “rest of the world”, context. The findings of our inductive study led to the emergence of four interrelated paradoxes and highlight the importance of paradoxical work as a management requirement.

The brushstroke and materials of Amadeo de Souza-Cardoso combined in an authentication tool

Nowadays, authentication studies for paintings require a multidisciplinary approach, based on the contribution of visual features analysis but also on characterizations of materials and techniques. Moreover, it is important that the assessment of the authorship of a painting is supported by technical studies of a selected number of original artworks that cover the entire career of an artist. This dissertation is concerned about the work of modernist painter Amadeo de Souza-Cardoso. It is divided in three parts. In the first part, we propose a tool based on image processing that combines information obtained by brushstroke and materials analysis. The resulting tool provides qualitative and quantitative evaluation of the authorship of the paintings; the quantitative element is particularly relevant, as it could be crucial in solving authorship controversies, such as judicial disputes. The brushstroke analysis was performed by combining two algorithms for feature detection, namely Gabor filter and Scale Invariant Feature Transform. Thanks to this combination (and to the use of the Bag-of-Features model), the proposed method shows an accuracy higher than 90% in distinguishing between images of Amadeo’s paintings and images of artworks by other contemporary artists. For the molecular analysis, we implemented a semi-automatic system that uses hyperspectral imaging and elemental analysis. The system provides as output an image that depicts the mapping of the pigments present, together with the areas made using materials not coherent with Amadeo’s palette, if any. This visual output is a simple and effective way of assessing the results of the system. The tool proposed based on the combination of brushstroke and molecular information was tested in twelve paintings obtaining promising results. The second part of the thesis presents a systematic study of four selected paintings made by Amadeo in 1917. Although untitled, three of these paintings are commonly known as BRUT, Entrada and Coty; they are considered as his most successful and genuine works. The materials and techniques of these artworks have never been studied before. The paintings were studied with a multi-analytical approach using micro-Energy Dispersive X-ray Fluorescence spectroscopy, micro-Infrared and Raman Spectroscopy, micro-Spectrofluorimetry and Scanning Electron Microscopy. The characterization of Amadeo’s materials and techniques used on his last paintings, as well as the investigation of some of the conservation problems that affect these paintings, is essential to enrich the knowledge on this artist. Moreover, the study of the materials in the four paintings reveals commonalities between the paintings BRUT and Entrada. This observation is supported also by the analysis of the elements present in a photograph of a collage (conserved at the Art Library of the Calouste Gulbenkian Foundation), the only remaining evidence of a supposed maquete of these paintings. The final part of the thesis describes the application of the image processing tools developed in the first part of the thesis on a set of case studies; this experience demonstrates the potential of the tool to support painting analysis and authentication studies. The brushstroke analysis was used as additional analysis on the evaluation process of four paintings attributed to Amadeo, and the system based on hyperspectral analysis was applied on the painting dated 1917. The case studies therefore serve as a bridge between the first two parts of the dissertation.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Extraction automatique d´associations lexicales à partir de corpora

The automatic acquisition of lexical associations from corpora is a crucial issue for Natural Language Processing. A lexical association is a recurrent combination of words that co-occur together more often than expected by chance in a given domain. In fact, lexical associations define linguistic phenomena such as idiomes, collocations or compound words. Due to the fact that the sense of a lexical association is not compositionnal, their identification is fundamental for the realization of analysis and synthesis that take into account all the subtilities of the language. In this report, we introduce a new statistically-based architecture that extracts from naturally occurring texts contiguous and non contiguous. For that purpose, three new concepts have been defined : the positional N-gram models, the Mutual Expectation and the GenLocalMaxs algorithm. Thus, the initial text is fisrtly transformed in a set of positionnal N-grams i.e ordered vectors of simple lexical units. Then, an association measure, the Mutual Expectation, evaluates the degree of cohesion of each positional N-grams based on the identification of local maximum values of Mutual Expectation. Great efforts have also been carried out to evaluate our metodology. For that purpose, we have proposed the normalisation of five well-known association measures and shown that both the Mutual Expectation and the GenLocalMaxs algorithm evidence significant improvements comparing to existent metodologies.

Algorithms for time series clustering applied to biomedical signals

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

EDP InovCity: Electricity feedback with smart meters through tv

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

EDP inovcity: Electricity feedback with smart meters through TV

In this work project I propose an innovative service – Electricity Feedback with Smart Meters through TV – to be considered as an additional test in the residential electricity use feedback trials currently being conducted in EDP’s InovCity project. My proposal is based on relevant past and current research studies, both Portuguese and international, which explain and support the proposed operationalization and characteristics of this new service. Furthermore, a careful analysis about the segmentation framing, the best market entry strategy and the consequences of adopting a joint venture with cable TV operators, is also provided. Finally, I present a SWOT analysis and highlight critical issues affecting the effectiveness of feedback which require further research.

Prevalência do excesso de peso em idade pré-escolar no concelho da Murtosa: um estudo transversal

RESUMO - A prevalência de obesidade infantil em Portugal é das mais elevadas da Europa. No concelho da Murtosa (Aveiro), para estimar a prevalência de excesso de peso e obesidade entre os 3 e os 6 anos e determinar os factores que lhe estão associados, desenvolveu-se, durante o ano de 2008, um estudo transversal que consistiu na avaliação estatoponderal das crianças frequentadoras dos estabelecimentos de ensino pré-escolar do concelho e aplicação de um questionário aos pais sobre antecedentes e perinatais, hábitos alimentares, actividades da criança e características da família. Através de um modelo de regressão logística multivariada identificaram-se as variáveis associadas ao excesso de peso/obesidade. Participaram no estudo 258 crianças, estimando-se uma prevalência de excesso de peso de 15,5 % (IC 95 % : 11,6 % a 20,4 %) e de obesidade de 6,2 % (IC 95 % : 3,9 % a 9,8 % ). Observou-se uma maior prevalência de excesso de peso nos meninos (19,5 %) e de obesidade nas meninas (10,4 %). O excesso de peso materno e o hábito de comer a ver televisão aumentaram o risco de excesso de peso/obesidade (OR: 10,548; OR: 13,815); o maior número de horas de sono diário, o maior número de refeições diárias e o aumento ponderal materno durante a gravidez (OR: 0,490; OR: 0,366; OR: 0,804) associaram-se a um menor risco de excesso de peso/obesidade. Justifica-se o desenvolvimento de programas de prevenção primária e secundária da obesidade infantil dirigidos aos factores de risco modificáveis identificados, sugerindo-se a necessidade de uma abordagem familiar e da avaliação sistemática deste tipo de intervenções.

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.

Characterization of the clients retention in the tlecommunications companies

The ability of a company to be able to do a precisely churn prediction, so it can act on it, is paramount. For this reason, Deloitte addressed me the challenge of characterizing the client’s retention in the telecom companies. To do so, it was created a comprehensive tool that enables Deloitte to evaluate the churn management maturity level of a telecom operator and highlight its strengths and weaknesses. The development of this matrix was based on a depth churn research, a market research based on 40 interviews and 2 focus group and the valuable feedback from Deloitte consultants.