Multistage Stochastic Portfolio Optimisation in Deregulated Electricity Markets Using Linear Decision Rules

The deregulation of electricity markets increases the financial risk faced by retailers who procure electric energy on the spot market to meet their customers’ electricity demand. To hedge against this exposure, retailers often hold a portfolio of electricity derivative contracts. In this paper, we propose a multistage stochastic mean-variance optimisation model for the management of such a portfolio. To reduce computational complexity, we perform two approximations: stage-aggregation and linear decision rules (LDR). The LDR approach consists of restricting the set of decision rules to those affine in the history of the random parameters. When applied to mean-variance optimisation models, it leads to convex quadratic programs. Since their size grows typically only polynomially with the number of periods, they can be efficiently solved. Our numerical experiments illustrate the value of adaptivity inherent in the LDR method and its potential for enabling scalability to problems with many periods.OR in energy, electricity portfolio management, stochastic programming, risk management, linear decision rules

Estimation of Depth Maps from Monocular Images using Deep Neural Networks

Computer vision tasks have seen recent improvements thanks to the development of deep learning and high-end hardware. One of these tasks is depth perception, which involves extracting three-dimensional information from two-dimensional elements like images and constructing a depth map. This kind of information is useful in many domains such as autonomous vehicles or scene reconstruction for augmented and virtual reality. Hu-mans and some other animals achieve this by using binocular vision (vision from two images) and some algorithms have been developed to imitate this process. However, re-cent progress has enabled the advancement of other approaches that allow monocular vision algorithms to accomplish decent depth maps. In this thesis two monocular deep learning methods (Monodepth and DenseDepth) are explored and compared to each other (and with binocular and monocular approaches in general). This experiment is conducted by exposing the two methods to images that have not been seen during training and per-forming a qualitative analysis of their results in two different scenarios: indoors and out-doors. Both Monodepth and DenseDepth are able to produce depth maps, but DenseDepth results are more promising and reliable. Results show the importance of the training do-main, as the accuracy is affected by the choice of pre-trained models, as well as the col-lection and selection of data. It is still an open problem and seems unlikely that monocular depth perception could replace other sensors in critical systems like autonomous driving. However, it could still be a great complement or useful in other products or domains like photography.Doble Grado en Ingeniería Informática y Administración de Empresa

Gluon energy loss in the gauge-string duality

We estimate the stopping length of an energetic gluon in a thermal plasma of strongly coupled N=4 super-Yang-Mills theory by representing the gluon as a doubled string rising up out of the horizon.Comment: 33 pages, 8 figures. v2: minor improvement

Sistema de informação laboratorial para o COVID-19

COVID-19, a respiratory disease caused by SARS-CoV-2, first appeared in Wuhan, China, on 31 December 2019. It has since spread worldwide and developed into an ongoing pandemic. Currently, COVID-19 does not have a cure, and prevention is the only way to fight against it. During waves of higher infection cases, tracking the infected population becomes a difficult but crucial task. Only a COVID-19 test can diagnose a person, and RT-PCR tests are the most effective. PORTIC, the research centre for P.Porto, started using its laboratory for RT-PCR tests to diagnose COVID-19 for the P.Porto community and some health centres that belong to ARSN. During this process, the laboratory needs to manage all of the sample and testing information and report the test results. This information management became a burden, and the staff would lose most of the time with administrative tasks. This dissertation’s main objective is to develop a laboratory information system for PORTIC. This system must satisfy the elicited and specified requirements. For that purpose, multiple architectures were analysed, concluding that the clean architecture is the best option for this system. The system supports data importation from multiple external sources, report generation and exportation and the entire sample flow. Its development followed a scrum methodology where each requirement was validated through user acceptance tests at the end of each iteration. To evaluate the system’s success, the laboratory answered a questionnaire to determine the perceived usefulness and ease of use. This concluded that the system was successful since the questionnaire determined that it was extremely useful and easy to use. The developed system is an innovation on COVID-19 testing since there are no real options in the market, and different laboratories can reuse the system to tackle COVID-19 testing.A COVID-19, uma doença respiratória causada pelo SARS-CoV-2, apareceu pela primeira vez em Wuhan, China no dia 31 de dezembro de 2019. Desde então, esta doença espalhou-se por todo o mundo, devenvolvendo-se numa pandemia em curso. Atualmente, não existe cura para a COVID-19, sendo que a única maneira de resistir à doença é através da prevenção. Durante as ondas de grandes números de infeções, rastrear a população infetada transformase numa tarefa árdua mas fundamental. A única maneira de diagnósticar a doença é através de um teste de COVID-19, sendo que os testes de RT-PCR são os mais eficazes. O PORTIC, centro de pesquisa do P.Porto, começou a realizar testes de RT-PCR, no seu laboratório, para diagnosticar COVID-19 à comunidade do P.Porto e para alguns centros de saúde que pertencem à ARSN. Durante este processo, o laboratório precisa de gerir toda a informação sobre as amostras e os testes, assim como reportar os resultados dos testes. Esta gestão de informação tornou-se num incómodo e os funcionários passaram a perder a maior parte do seu tempo com tarefas administrativas. O objetivo principal desta dissertação é o desenvolvimento de um sistema de informação de laboratório para o PORTIC. Este sistema deverá cumprir os requisitos elicitados e especificados. Para esse propósito, foram analisadas diferentes arquiteturas, chegando-se à conclusão de que a clean architecture é a opção mais viável para este sistema. O sistema suporta importação de dados de múltiplas fontes externas, geração e exportação de relatórios e todo o fluxo de amostras. O desenvolvimento do sistema seguiu uma metodologia scrum onde cada requisito foi validado através de testes de aceitação do utilizador no final de cada iteração. Para avaliar o sucesso do sistema, o laboratório respondeu a um questionário para determinar a utilidade e facilidade de utilização percecionada. Isto concluiu que o sistema foi bem sucedido dado que o questionário determinou que foi extremamente útil e fácil de utilizar. O sistema desenvolvido é uma inovação em testes de COVID-19 pois não existem opções no mercado e outros laboratórios podem reutilizar o sistema para endereçar os testes de COVID-19

Security for constrained IoT devices

Tese de mestrado, Segurança Informática, Universidade de Lisboa, Faculdade de Ciências, 2020In the recent past the Internet of Things has been the target of a great evolution, both in terms of applicability and of use. Society increasingly wants to use and massify the IoT to obtain information and act in the environment, for example, to remotely control an irrigation system. The reduction in the cost of devices and the constant evolution of personal mobile devices has largely contributed to their spread. However, its implementation is carried out in adverse environments and outside the typical information systems. The devices are, as a rule, limited in terms of resources, both computation and memory. The applicability to the IoT of the security techniques already known to conventional systems has therefore to be adapted, because it does not take into account the characteristics of the resources of the devices and require additional load when exchanging messages between these system elements. In addition, the development of applications is difficult because there is not yet developed tools and standards as there are for the traditional HTTPS or TLS when considering conventional systems. In this work, we intend to present a prototype of a low-cost solution (compared to existing equivalent solutions) that uses a secure communication channel based on standard protocols. An application is also developed based on technologies more familiar to programmers, similar to traditional Web development. We took into account the ”Green By Web” project as a case study. We have concluded that it is possible to have a secure communication, using UDP/DTLS over the CoAP protocol. With this approach we optimized the number of exchanged messages between the client and the server to be up to 8 times less and their size to be up to 10%, comparing against applications that use TCP/TLS connections, such as web applications that use HTTPS. This allows the energy spent by the low-cost components to be lower and increases their battery lifetime