Methane is a major greenhouse gas and a precursor of tropospheric ozone, and most of its sources are linked to anthropogenic activities. The sources of methane are well known and its monitoring generally involves the use of expensive gas analyzers with high operating costs. Many studies have investigated the use of low-cost gas sensors as an alternative for measuring methane concentrations; however, it is still an area that needs further development to ensure reliable measurements. In this work a low-cost platform for measuring methane within a low concentration range was developed and used in two distinct environments to continuously assess and improve its performance. The methane sensor was the Figaro TGS2600, a metal oxide semiconductor (MOS) based on tin dioxide (SnO2). In a first stage, the monitoring platform was applied in a small ruminant barn after undergoing a multi-point calibration. In a second stage, the system was used in a wastewater treatment plant together with a multi-gas analyzer (Gasera One Pulse). The calibration of low-cost sensor was based on the relation of the readings of the two devices. Temperature and relative humidity were also measured to perform corrections to minimize the effects of these variables on the sensor signal and an active ventilation system was used to improve the performance of the sensor. The system proved to be able to measure low methane concentrations following reliable spatial and temporal patterns in both places. A very similar behavior between both measuring systems was also well noticeable at WWTP. In general, the low-cost system presented good performance under several environmental conditions, showing itself to be a good alternative, at least as a screening monitoring system.

Este relatório reflete a avaliação da empresa de Semi-condutores, a NVIDIA Corporation e está de acordo com o trabalho final de mestrado de Finanças do ISEG. Este relatório foi escrito com base nas recomendações do CFA Institute. A NVIDIA é uma empresa que está a enfrentar um momento bastante singular comparado com os seus competidores, com um crescimento anual de vendas de 40% e um aumento na avaliação das suas ações de 334,46% nos últimos dos anos. Não só a NVIDIA está a ter uma performance financeira interessante como se está a entrar em mercados emergentes como a autonomização automóvel e a criptomoeda, o que faz com que seja um caso de estudo bastante interessante. Também a fascinação em relação a tecnologia e em especifico, ao gaming, foram uma das razões pela qual esta empresa foi escolhida. Este relatório foi desenvolvido com base em informação pública disponível até 30 de Junho de 2018 e nenhuma informação posterior a esta data não foi considerada. O preço de ação de $303,67, foi obtido através do modelo de Fluxos de Caixa Descontados. O método de avaliação relativa foi tentado, porém dado à situação única da NVIDIA, não existe competidores que consideremos como peer's comparáveis em termos de múltiplos. Esta avaliação sugere uma recomendação de COMPRA, apesar do seu risco médio, dado que a NVDIA está consolidada no seu mercado principal, o gaming, porém existe alguma incerteza relativamente aos mercados da criptomoeda e autonomização automóvel.

O seguinte trabalho consiste em uma avaliação do valor das ações da Samsung Electronics Co., Ltd. para o ano 2020, os pressupostos adotados para a previsão dos próximos cinco anos (2020F-2024F) foram baseados no desempenho histórico dos últimos quatro anos (2016-2019). Este trabalho foi elaborado em conformidade com as recomendações do CFA Institute. Eu escolhi fazer este trabalho sobre a Samsung Electronics Co., Ltd. devido a magnitude e presença global da marca através dos seus produtos e serviços nas diversas indústrias e setores onde atua. Além disso, a minha empatia pessoal com a marca que sempre utilizei desde a minha juventude motivou e ajudou-me a tomar esta decisão. O principal método utilizado para a avaliação foi o método do Fluxo de Caixa Descontado, cujo resultado definiu o preço-alvo de €68 624. Também foram utilizados métodos relativos, do qual os resultados encontrados também reforço a recomendação da COMPRA. Apesar da presente situação de pandemia global onde existe algum grau de incerteza quanto ao final do vírus e das suas consequências, o início do uso de tecnologia 5G em diversos países irão valorizar a ação. No entanto, levando em consideração o grau de incerteza causado pelo COVID-19 e o preço alvo alcançado, emitimos uma recomendação de COMPRA com risco médio.

This dissertation addresses the potential 100% acquistion of Infineon Technologies AG by Mercedes-Benz Group AG. Mercedes-Benz Group AG, one of the most important car manufacturers in the world, seeks to pioneer the direction of technological leadership in the field of electromobility through the acquisition of Infineon Technologies AG, the largest European semiconductor manufacturer, as well as protect itself against semiconductor supply bottlenecks. In this dissertation, enforceability of the potential transaction, theoretical and practical sense, potential synergies, the joint enterprise value and the potential purchase price are examined and analysed. The analysis leads to the conclusion that, after reviewing the identified risks, a transaction should be carried out. The transaction will result in a combined company value of €256.0 billion with the total synergies, deducting transaction and integration costs amounting to €21.4 billion. The acquisition price of €54.5 billion is based on an assumed acquisition premium of 30% on the current share price (17/08/2023), which will incentivize Infineon’s investors to sell while simultaneously increasing shareholder value for Mercedes-Benz. The increase in shareholder value amounts to 12.3%. The transaction process should be collaborative and completed with a cash payment.

I completed my master’s end-of-study internship at STMicroelectronics as a Data Scientist. The company specializes in the design and manufacturing of semiconductors. I joined the Data Science and Analytics team, a young international team whose main objective is to address all data science issues to improve performance in terms of manufacturing and process quality. During this internship, I worked on two major computer vision projects. The first project involved developing an image classification algorithm to improve the quality of the automatic inspection process of flip chips on the A49 assembly line at the backend site in Malta. For this project, I also developed a Spotfire dashboard to provide engineers with a real-time monitoring tool. The second project was a research and development mission. The objective was to develop a Python library for automatic multi-label image classification. The idea was to provide a flexible tool for Data Scientists that would save considerable time. This internship allowed me to develop and strengthen my skills in data science, particularly in image analysis. I also learned about best practices for teamwork, communication, and collaboration. In this sense, this experience was extremely enriching.

We have used a pair of crossed coils to generate rotating RF fields for a muon spin resonance measurement by driving one of the two coils and adjusting the tuned frequencies and mutual coupling to give the required 90o phase shift. Fitting the measured impedance to an equivalent circuit model gives information on the rotating field.