SOS rule formats for convex and abstract probabilistic bisimulations

Probabilistic transition system specifications (PTSSs) in the $nt \mu f\theta / nt\mu x\theta$ format provide structural operational semantics for Segala-type systems that exhibit both probabilistic and nondeterministic behavior and guarantee that bisimilarity is a congruence for all operator defined in such format. Starting from the $nt \mu f\theta / nt\mu x\theta$ format, we obtain restricted formats that guarantee that three coarser bisimulation equivalences are congruences. We focus on (i) Segala's variant of bisimulation that considers combined transitions, which we call here "convex bisimulation"; (ii) the bisimulation equivalence resulting from considering Park & Milner's bisimulation on the usual stripped probabilistic transition system (translated into a labelled transition system), which we call here "probability obliterated bisimulation"; and (iii) a "probability abstracted bisimulation", which, like bisimulation, preserves the structure of the distributions but instead, it ignores the probability values. In addition, we compare these bisimulation equivalences and provide a logic characterization for each of them.Comment: In Proceedings EXPRESS/SOS 2015, arXiv:1508.0634

Geometric quantization, complex structures and the coherent state transform

It is shown that the heat operator in the Hall coherent state transform for a compact Lie group $K$ is related with a Hermitian connection associated to a natural one-parameter family of complex structures on $T^*K$. The unitary parallel transport of this connection establishes the equivalence of (geometric) quantizations of $T^*K$ for different choices of complex structures within the given family. In particular, these results establish a link between coherent state transforms for Lie groups and results of Hitchin and Axelrod, Della Pietra and Witten.Comment: to appear in Journal of Functional Analysi

On the BKS pairing for Kahler quantizations of the cotangent bundle of a Lie group

A natural one-parameter family of K\"ahler quantizations of the cotangent bundle $T^*K$ of a compact Lie group $K$, taking into account the half-form correction, was studied in \cite{FMMN}. In the present paper, it is shown that the associated Blattner-Kostant-Sternberg (BKS) pairing map is unitary and coincides with the parallel transport of the quantum connection introduced in our previous work, from the point of view of \cite{AdPW}. The BKS pairing map is a composition of (unitary) coherent state transforms of $K$, introduced in \cite{Ha1}. Continuity of the Hermitian structure on the quantum bundle, in the limit when one of the K\"ahler polarizations degenerates to the vertical real polarization, leads to the unitarity of the corresponding BKS pairing map. This is in agreement with the unitarity up to scaling (with respect to a rescaled inner product) of this pairing map, established by Hall.Comment: final version, to appear in Journ. Funct. Ana

Can we seduce customers to buy private label products by using irrelevant attributes?

Private Label brands (often referred to as low-cost options) are the strategy retailers found to offer quality products at affordable prices, allowing families to fulfil their needs and better manage their monthly disposable income. However, these brands tend to suffer from lack of identity, poor perception of quality and scepticism, which often disappear after people start consuming the products. This dissertation aims to test to which extent the presence of Irrelevant Attributes effectively contributes to reducing perceived quality deficits through the creation or enhancement of brands’ personality traits. By strengthening their identities, brands can turn consumers’ identification with the brand easier, which positively impacts their perceived value, expected hedonic experience, purchase intentions and willingness-to-pay. Although some authors claim that the presence of Irrelevant Attributes is understood by consumers as a mechanism that brands use to compensate for the underperforming attributes (as found in National brands), Private Labels may benefit from using this tool to outperform in competitive markets like Food Retail or FMCG, where players are fierce and fight incessantly. This research’s results reveal that the presence of Irrelevant Attributes allows brands to enhance their personality and differentiate themselves from its competitors. Nevertheless, they also show that perceived value and purchase intentions do not increase significantly, unlike the willingness to pay, which increases when Irrelevant Attributes are present. The presence of Irrelevant Attributes in National brands tends to weaken them, which reinforces their importance to Private Label brands as a point of differentiation.As marcas próprias têm permitido aos retalhistas oferecer produtos de qualidade a preços acessíveis, que permitem uma melhor gestão do rendimento mensal disponível e a satisfação das necessidades das famílias. Contudo, estas marcas sofrem de falta de identidade, baixa perceção de qualidade e de ceticismo criado pelos consumidores, tendencialmente suprimido após consumir o produto. As marcas próprias tendem, por isso, a ser vistas como uma opção low-cost. Esta dissertação pretende testar se a presença de Atributos Irrelevantes contribui de forma eficaz para a redução do défice de qualidade percebido através da criação de uma personalidade, o que, facilitando a identificação do consumidor com a marca, impactaria positivamente o valor percebido, as expetativas, as intenções de compra e o valor que o consumidor está disposto a despender. Apesar de alguns autores afirmarem que a presença de Atributos Irrelevantes é vista pelos consumidores como um mecanismo a que as marcas recorrem para compensar pela performance deficitária de outros atributos (o que se verificou para as marcas de fabricante), as marcas próprias podem recorrer à utilização desta ferramenta para se diferenciarem em mercados competitivos. Este estudo revela que a presença de Atributos Irrelevantes permite às marcas enaltecer a sua personalidade e diferenciar-se da concorrência. Contudo, os resultados mostram que o valor percebido e as intenções de compra não aumentam significativamente, ao contrário do preço a pagar. A presença de Atributos Irrelevantes em marcas de fabricante tende a prejudicá-las, reforçando a importância dos mesmos para as marcas próprias enquanto ponto de diferenciação

Equity research: An analysis on Farfetch´s IPO

The personal luxury goods market has been growing over the past 20 years, presenting an annual growth rate of 6%, being that in 2017 it registered a value over 300 billion of dollars. The regions of America and Europe are the main geographical market segments, representing 65% of the personal luxury goods market, even though the Asian region has shown a big growth over the last years, due to its economic development. The online segment has been increasing, driven by the strong and fast technological development, being that this segment represents 9% of the market and it registered a growth rate of 24% in 2017. The fast growth observed in the online segment is also due to the generational shift that is occurring over the last years, since the consumers of the generations Y and Z are increasing. Therefore, Farfetch is taking advantage of the opportunities that the market provides, to its development and growth, and it became a listed company on the North American stock exchange NASDAQ. This project aims to valuate the company upon its listing on the stock market, where it will be valued the price per share through different valuation model, and the values obtained will be compared between them and with Farfetch’s IPO price. Taking into consideration the results, it was concluded that the IPO price of 20 dollars per share, falls short from the values obtained through the DCF models, so it is suggested to buy the shares of the IPO.O mercado da moda de luxo tem vindo a crescer nos últimos 20 anos, apresentando uma taxa de crescimento anual de 6%, sendo que em 2017 registou um valor superior a 300 mil milhões de dólares. Os continentes americano e europeu são, do ponto de vista geográfico, os principais mercados, representado 65%, ainda que o mercado asiático tenha demonstrado um forte crescimento nos últimos anos, devido ao seu desenvolvimento económico. Em relação aos canais de distribuição, o segmento online do mercado da moda, tem vindo a crescer, impulsionado pelo forte e rápido desenvolvimento tecnológico, sendo que representa 9% do valor total e registou um crescimento anual de 24% de 2016 para 2017. O forte crescimento deste segmento deve-se à mudança geracional que se tem vindo a assistir nos últimos anos, sendo que têm vindo a crescer o número de consumidores da geração Y e Z. Assim sendo, a Farfetch vai aproveitando as oportunidades que este mercado proporciona, para o seu desenvolvimento e crescimento, tendo-se tornado uma empresa cotada na bolsa norte americana NASDAQ. Este projeto visa a avaliação da empresa aquando da sua entrada em bolsa, onde irá ser avaliado o preço por ação através de diferentes modelos e os valores obtidos serão comparados entre eles e com o preço da OPI da Farfetch. Considerando os resultados obtidos, concluiu-se que o valor da OPI de 20 dólares por ação, fica aquém dos valores obtidos pelos modelos de DCF, sendo assim é recomendado a compra das ações ao preço da OPI

Performance Evaluation of Low Complexity Massive MIMO Techniques for SC-FDE Schemes

Massive-MIMO technology has emerged as a means to achieve 5G's ambitious goals; mainly to obtain higher capacities and excellent performances without requiring the use of more spectrum. In this thesis, focused on the uplink direction, we make a study of performance of low complexity equalization techniques as well as we also approach the impact of the non-linear elements located on the receivers of a system of this type. For that purpose, we consider a multi-user uplink scenario through the Single Carrier with Frequency Domain Equalization (SC-FDE) scheme. This seems to be the most appropriate due to the low energy consumption that it implies, as well as being less favorable to the detrimental effects of high envelope fluctuations, that is, by have a low Peak to Average Power Ratio (PAPR) comparing to other similar modulations, such as the Orthogonal Frequency Division Multiplexing (OFDM). Due to the greater number of antennas and consequent implementation complexity, the equalization processes for Massive- MIMO schemes are aspects that should be simplified, that is, they should avoid the inversion of matrices, contrary to common 4G, with the Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) techniques. To this end, we use low-complexity techniques, such as the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC). Since these algorithms are not sufficiently capable of removing the entire Inter-Symbol Interference (ISI) and Inter-User Interference (IUI), we combine them with iterative techniques, namely with the Iterative Block with Decision Feedback Equalizer (IB-DFE) to completely remove the residual ISI and IUI. We also take into account the hardware used in the receivers, since the effects of non-linear distortion can impact negatively the performance of the system. It is expected a strong performance degradation associated to the high quantization noise levels when implementing low-resolution Analog to Digital Converters (ADCs). However, despite these elements with these configurations become harmful to the performance of the majority of the systems, they are considered a desirable solution for Massive-MIMO scenarios, because they make their implementation cheaper and more energy efficient. In this way, we made a study of the impact in the performance by the low-resolution ADCs. In this thesis we suggest that it is possible to bypass these negative effects by implementing a number of receiving antennas far superior to the number of transmitting antennas

Malware Analysis with Machine Learning

Tese de mestrado, Segurança Informática, Universidade de Lisboa, Faculdade de Ciências, 2022Malware attacks have been one of the most serious cyber risks in recent years. Almost every week, the number of vulnerability reports is increasing in the security communities. One of the key causes for the exponential growth is the fact that malware authors started introducing mutations to avoid detection. This means that malicious files from the same malware family, with the same malicious behaviour, are constantly modified or obfuscated using a variety of technics to make them appear to be different. Characteristics retrieved from raw binary files or disassembled code are used in existing machine learning-based malware categorization algorithms. The variety of such attributes has made it difficult to develop generic malware categorization methods that operate well in a variety of operating scenarios. To be effective in evaluating and categorizing such enormous volumes of data, it is necessary to divide them into groups and identify their respective families based on their behaviour. Malicious software is converted to a greyscale image representation, due to the possibility to capture subtle changes while keeping the global structure helps to detect variations. Motivated by the Machine Learning results achieved in the ImageNet challenge, this dissertation proposes an agnostic deep learning solution, for efficiently classifying malware into families based on a collection of discriminant patterns retrieved from its visualization as images. In this thesis, we present Malwizard, an adaptable Python solution suited for companies or end users, that allows them to automatically obtain a fast malware analysis. The solution was implemented as an Outlook add-in and an API service for the SOAR platforms, as emails are the first vector for this type of attack, with companies being the most attractive targets. The Microsoft Classification Challenge dataset was used in the evaluation of the noble approach. Therefore, its image representation was ciphered and generated the correspondent ciphered image to evaluate if the same patterns could be identified using traditional machine learning techniques. Thus, allowing the privacy concerns to be addressed, maintaining the data analysed by neural networks secure to unauthorized parties. Experimental comparison demonstrates the noble approach performed close to the best analysed model on a plain text dataset, completing the task in one-third of the time. Regarding the encrypted dataset, classical techniques need to be adapted in order to be efficient

Distribuição de conteúdos over-the-top multimédia em redes sem fios

mestrado em Engenharia Eletrónica e TelecomunicaçõesHoje em dia a Internet é considerada um bem essencial devido ao facto de haver uma constante necessidade de comunicar, mas também de aceder e partilhar conteúdos. Com a crescente utilização da Internet, aliada ao aumento da largura de banda fornecida pelos operadores de telecomunicações, criaram-se assim excelentes condições para o aumento dos serviços multimédia Over-The-Top (OTT), demonstrado pelo o sucesso apresentado pelos os serviços Netflix e Youtube. O serviço OTT engloba a entrega de vídeo e áudio através da Internet sem um controlo direto dos operadores de telecomunicações, apresentando uma proposta atractiva de baixo custo e lucrativa. Embora a entrega OTT seja cativante, esta padece de algumas limitações. Para que a proposta se mantenha em crescimento e com elevados padrões de Qualidade-de-Experiência (QoE) para os consumidores, é necessário investir na arquitetura da rede de distribuição de conteúdos, para que esta seja capaz de se adaptar aos diversos tipos de conteúdo e obter um modelo otimizado com um uso cauteloso dos recursos, tendo como objectivo fornecer serviços OTT com uma boa qualidade para o utilizador, de uma forma eficiente e escalável indo de encontro aos requisitos impostos pelas redes móveis atuais e futuras. Esta dissertação foca-se na distribuição de conteúdos em redes sem fios, através de um modelo de cache distribuída entre os diferentes pontos de acesso, aumentando assim o tamanho da cache e diminuindo o tráfego necessário para os servidores ou caches da camada de agregação acima. Assim, permite-se uma maior escalabilidade e aumento da largura de banda disponível para os servidores de camada de agregação acima. Testou-se o modelo de cache distribuída em três cenários: o consumidor está em casa em que se considera que tem um acesso fixo, o consumidor tem um comportamento móvel entre vários pontos de acesso na rua, e o consumidor está dentro de um comboio em alta velocidade. Testaram-se várias soluções como Redis2, Cachelot e Memcached para servir de cache, bem como se avaliaram vários proxies para ir de encontro ás características necessárias. Mais ainda, na distribuição de conteúdos testaram-se dois algoritmos, nomeadamente o Consistent e o Rendezvouz Hashing. Ainda nesta dissertação utilizou-se uma proposta já existente baseada na previsão de conteúdos (prefetching ), que consiste em colocar o conteúdo nas caches antes de este ser requerido pelos consumidores. No final, verificou-se que o modelo distribuído com a integração com prefecthing melhorou a qualidade de experiência dos consumidores, bem como reduziu a carga nos servidores de camada de agregação acima.Nowadays, the Internet is considered an essential good, due to the fact that there is a need to communicate, but also to access and share information. With the increasing use of the Internet, allied with the increased bandwidth provided by telecommunication operators, it has created conditions for the increase of Over-the-Top (OTT) Multimedia Services, demonstrated by the huge success of Net ix and Youtube. The OTT service encompasses the delivery of video and audio through the Internet without direct control of telecommunication operators, presenting an attractive low-cost and pro table proposal. Although the OTT delivery is captivating, it has some limitations. In order to increase the number of clients and keep the high Quality of Experience (QoE) standards, an enhanced architecture for content distribution network is needed. Thus, the enhanced architecture needs to provide a good quality for the user, in an e cient and scalable way, supporting the requirements imposed by future mobile networks. This dissertation aims to approach the content distribution in wireless networks, through a distributed cache model among the several access points, thus increasing the cache size and decreasing the load on the upstream servers. The proposed architecture was tested in three di erent scenarios: the consumer is at home and it is considered that it has a xed access, the consumer is mobile between several access points in the street, the consumer is in a high speed train. Several solutions were evaluated, such as Redis2, Cachelot and Memcached to serve as caches, along with the evaluation of several proxies server in order to ful ll the required features. Also, it was tested two distributed algorithms, namely the Consistent and Rendezvous Hashing. Moreover, in this dissertation it was integrated a prefetching mechanism, which consists of inserting the content in caches before being requested by the consumers. At the end, it was veri ed that the distributed model with prefetching improved the consumers QoE as well as it reduced the load on the upstream servers