Alchimia: an inexplicable or mysterious transmutation, a seemingly magical process of transformation, creation, or combination

Alchimia V2 is an interactive installation that relies on a single spectator/interactor standing in front of a screen/webcam. It has been coded in Processing 3.0 and is calculation intensive, using the webcam to perform facial detection, while simultaneously processing pre-prepared images and sounds, thus creating a virtual space of constant audio-visual movement to deliberately interfere with real-time self-perception and self-recognition. Alchimia V2 questions and changes our relationship with our own representation through the (ever present) camera and screen by focusing on the spectator’s face, altering the expression, gender, assigning masks, making the facial traits diffuse, mixed, funny or scary, always mysterious, in a search for another "self", oblivious of the "selfie" pose and attitude, while allowing for self discovery and playfulness – or intimidation. Through the interaction the spectator/interactor is absorbed in the transmutation process, unaware of the fact that they also have become part of a performance: unique, unrepeatable, transformed.info:eu-repo/semantics/publishedVersio

Light programming language

The increase of computing power in the last decades allowed for the creation and establishment of many high level programming languages such as Java and Python. In these languages, control over the hardware is often neglected in favor of more convenient abstractions for the programmer that offer some important guarantees (such as memory safety). At the same time, older lower level languages, such as C, are still considered one of the few viable options for systems programming. This work proposes a new low level programming language called Light that makes use of meta-programming ideas, commonly present in higher level, interpreted languages, in a compiled one. Light is a lower level, statically typed language that focuses on simplicity, consistent syntax and understandability. It has minimal runtime, no garbage collection and is composed of a simple core with a meta-programming layer built on top. We will present the complete language design and its compiler implementation. The objective of this work is to provide a general purpose system language that uses meta-programming to complement the base language as a tool to the programmer for building software.O aumento em poder computacional nas últimas decadas permitiram a criação e estabelecimento de diversas linguagens de programação de alto nível como Java e Python. Nessas linguagens, controle sobre o hardware é constantemente esquecido em favor de abstrações mais convenientes para o programador que oferencem algumas garantias importantes (como segurança de memória). Ao mesmo tempo, antigas linguagens de baixo nível como C, ainda são consideradas uma das poucas alternativas para linguagens de sistema. Esse trabalho propõe uma nova linguagem de programação de baixo nível chamada Light que faz uso de conceitos de meta-programação, comumente presentes em linguagens interpretadas de alto nível, em uma linguagem compilada. Light é uma linguagem de baixo nível, estaticamente tipada com foco em simplicidade, consistência de sintaxe e compreensibilidade. Possui ambiente de execução mínimo, não possui coletor de lixo e é composta de um núcleo simples com uma camada de meta-programação construída por cima. Nós apresentaremos o projeto completo da linguagem e a implementação de seu compilador. O objetivo deste trabalho é oferecer uma linguagem de sistema de uso geral que utiliza-se de meta-programação para complementar a linguagem base como uma ferramenta para o programador construir software

Trade Liberalization in Brazil: When and How?

Brazil's economy is among those most closed to foreign trade. Debate on trade policy has returned to the political agenda, but domestic and international circumstances do not currently favor reform. This brief discusses the outlook for trade policy reform in Brazil during President Michel Temer's term and the challenges that will be faced by any succeeding government

The cinematic selfie: questioning the self through generative art

This article addresses and questions the magic-mirror phenomenon, popularised by current smartphone selfie and video capture apps. This phenomenon stimulates the illusion of control over the appearance of the face, either through applying semi-automatic soft filters to highlight the face area, to smooth the skin or correct the posture; or through the use of humorous add-ons or distortions, such as bunny ears or anime features, among others. However these results are short-lived, as their publication in social networks is either ephemeral – as a story – or timed to become invisible or irrelevant – in the timeline stream. Cumulatively they leave little margin (if at all) to stimulate a deeper reflection on the subject of (self) identity, and could thus be reduced to an expression of narcissism and consumption rather than a shared, transformative, meaningful practice. The two generative artworks described in this article, on the other hand, seek to guide the visitor beyond the visual magic-mirror through thought-provoking and reflective processes, where face-based audio-visual trance inducing cycles are used to hint at new identities and possibilities, challenging species, race, gender and age. These artworks seek to immerse the visitor, with narrowed awareness of external surroundings and stimuli, with a deepened focus in a synesthetic experience of flow, aiming at an altered perception of the self. If appearance can act as a tool to communicate one’s identity to others, this article ponders the possibility that such a synesthetic environment can be artivistically used to influence the perception of the self.info:eu-repo/semantics/publishedVersio

A governação da Internet

A GOVERNAÇÃO DA INTERNET pode ser defi - nida como o desenvolvimento e aplicação pelos governos, o sector privado e a sociedade civil, no âmbito das respectivas competências e atribuições, de princípios, normas, regras, processos decisionais e programas comuns, que regulam a evolução e utilização da Internet. Quando se fala da governação da Internet não se pode fi car alheio ao papel fundamental de um conjunto de organizações que, à escala nacional, europeia e mundial, têm trabalhado no sentido de lidar com as matérias e problemas que daí advém. Merecem-nos aqui especial destaque o ICANN, o IGF, o ITU, o ISOC, a Comissão Europeia e, a nível nacional, as entidades responsáveis pela gestão dos ccTLD

Consumer Behavior: A Literature Review of the Early Research on the COVID-19 Outbreak

The outbreak of COVID-19 has substantially altered trends and the research agenda in Consumer Behavior (CB). The main objectives of this article is analyze and classify the main contributions published the early research on CB on the COVID -19 pandemic , seeking to discover the perspective and the gaps and outline future avenues of research . With this article, we performed a systematic literature review based on articles published in Web of Science (WoS). We used a bibliometric approach based on Bibliographic Coupling of Documents complemented by a thematic analysis which allows us to provide a more holistic overview of the domain under study. Based on literature review six key thematic areas were identified in CB research of early stage of the pandemic: Environmental Factors, Social Media CB and Business Strategies, Personal and Psychological Characteristics , Purchase Process , and Panic buying . The conclusions present limitations inherent to systematic literature review articles, in particular the filters used to limit the search.info:eu-repo/semantics/publishedVersio

A novel causally consistent replication protocol with partial geo-replication

Distributed storage systems are a fundamental component of large-scale Internet services. To keep up with the increasing expectations of users regarding availability and latency, the design of data storage systems has evolved to achieve these properties, by exploiting techniques such as partial replication, geo-replication and weaker consistency models. While systems with these characteristics exist, they usually do not provide all these properties or do so in an inefficient manner, not taking full advantage of them. Additionally, weak consistency models, such as eventual consistency, put an excessively high burden on application programmers for writing correct applications, and hence, multiple systems have moved towards providing additional consistency guarantees such as implementing the causal (and causal+) consistency models. In this thesis we approach the existing challenges in designing a causally consistent replication protocol, with a focus on the use of geo and partial data replication. To this end, we present a novel replication protocol, capable of enriching an existing geo and partially replicated datastore with the causal+ consistency model. In addition, this thesis also presents a concrete implementation of the proposed protocol over the popular Cassandra datastore system. This implementation is complemented with experimental results obtained in a realistic scenario, in which we compare our proposal withmultiple configurations of the Cassandra datastore (without causal consistency guarantees) and with other existing alternatives. The results show that our proposed solution is able to achieve a balanced performance, with low data visibility delays and without significant performance penalties

Speciesism | Ageism | Racism

Speciesism | Ageism | Racism (SAR) is a generative cinematic artwork stemming from the millennia-old practice of mask making and laying claim to the fundamental richness of diversity. SAR generates sequences of masks from photos of people and animals without bias, imbued meaning or particular intent, leaving all interpretations and assumptions to the audience. SAR is aesthetically rooted in traditional folklore and the worldwide popular art of mask-making, in the concepts of “loop” and metric montage. Conceptually, SAR thrives in the intersectionality of postcolonial theory, feminist and anti-discrimination studies, as well as animal rights movements, policies and practices. By stripping away the ability to consistently identify species, age, race, gender or sexual orientation, the artwork allows for a disruptive aesthetic appreciation, which confronts the ideology and politics of group superiority. SAR delivers a participatory, hypnotic, rhythmic and generative audio-visual experience, charged with an anti-discriminatory message countering speciesism, ageism and racism. Speciesism | Ageism | Racism can be enjoyed in its on-line pre-calculated version at https://pedroveiga.com/sar-speciesism-ageism-racism/info:eu-repo/semantics/publishedVersio

Machine learning algorithm development of SPO2 sensor for improved robustness in wearables

Wearable devices application in the digital measurement of health has gained attention by researchers. These devices allow for data acquisition during real-life activities, resulting in higher data availability. They often include photoplethysmography (PPG) sensors, the sensor behind pulse oximetry. Pulse oximetry is a non-invasive method for continuous oxygen saturation (SpO2) measurements, a standard monitor for anesthesia procedures, an essential tool for managing patients undergoing pulmonary rehabilitation and an effective method for assessing sleep-disordered breathing. However, the current market focuses on heart rate measurements and lacks the robustness of clinical applications for SpO2 assessment. In addition, the most common obstacle in PPG measurements is the signal quality, especially in the form of motion artifacts. Thus, this work aims at increasing the clinical robustness in this devices by evaluating its quality and then extracting relevant metrics. Firstly, a data acquisition protocol was developed, focused on acquiring data during daily activities. This resulted in a dataset with different signal qualities, which was manually annotated to be used as the base for the Machine Learning models. A second protocol was also developed especially designed for the extraction of the SpO2 measurement. Several Machine Learning models were developed to evaluate the signal in three distinct qualities (corrupted, suboptimal, optimal) in real time. A Random Forest classifier achieved accuracies of 79% and 80% for the binary models capable of differentiating between usable and unusable signals, and accuracies of 74% and 80% when distinguishing between optimal and suboptimal signals, for the two utilized channels. The multi-class models achieved accuracies of 66% and 65% for the two utilized channels. Three clinically relevant metrics were also extracted from the PPG signal: heart rate, respiratory rate and SpO2. The heart rate and respiratory rate algorithms resulted in performances similar to the ones found in the literature and in other devices currently on the market. However, while promising, more data is needed to reach statistical significance for the SpO2 measurement.A monitorização do estado de saúde de pacientes em ambulatório utilizando dispositivos wearables tem vindo a ser cada vez mais investigada. Estes dispositivos permitem uma aquisição de dados durante o dia a dia, resultando num maior conjunto de dados. Frequentemente, estes dispositivos incluem fotopletismógrafos (PPG), o sensor por detrás da oximetria de pulso. A oximetria de pulso é um método não invasivo para a medição da saturação de oxigénio no sangue (SpO2) de forma contínua. É um equipamento padrão para procedimentos com anestesia, uma ferramenta essencial para monitorizar pacientes em reabilitação pulmonar e um método eficaz para avaliar respiração desordenada do sono. Ainda assim, o mercado atual foca-se principalmente em medições da frequência cardíaca e carece robustez para aplicações clínicas da medição de SpO2. Para além disso, o obstáculo mais comum em medições com PPG é a qualidade do sinal. Consequentemente, este trabalho procura melhorar a robustez clínica destes dispositivos analisando a qualidade do sinal e, posteriormente, extrair métricas relevantes. Primeiramente, foi desenvolvido um protocolo para aquisição de dados de atividades do dia a dia. Assim, foram adquiridos dados com diferentes qualidades, que foram avaliados manualmente de forma a servir de base para os vários modelos de Machine Learning. Também foi desenvolvido um segundo protocolo para a extração do valor de SpO2. Diferentes modelos de Machine Learning foram desenvolvidos para avaliar em tempo real a qualidade do sinal em três qualidades (corrompido, subótimo, ótimo) . Um classificador baseado em Random Forest atingiu exatidões de 79% e 80% em classificadores binários capazes de distinguir entre sinais úteis e inúteis, e exatidões de 74% e 80% a diferenciar entre um sinal subótimo e ótimo, para os dois canais usados. Os classificadores multi-classe atingiram exatidões de 66% e 65% para os dois canais usados. Três medidas clinicamente relevantes foram também extraídas do sinal de PPG: frequências cardíaca e respiratória, cujos algoritmos atingiram resultados semelhantes aos encontrados na literatura e em aparelhos no mercado, e SpO2 que, ainda que promissores, mais dados seriam necessários para os resultados serem estatisticamente significativo

The Everywhere Museum of Everything: the curatorship challenge, from cigital urban art to NFTs

This article focuses on the overproduction of aestheticised digital content, a testament to social, cultural or recreational experiences, paradoxically short-lived and forgotten. These public aestheticised digital records of social interactions, intellectual engagement or consumerist indulgence are uploaded onto social networks and represent not only a real and abundant ethnographic portrait of contemporaneity, which could be searchable by geography, demography or subject, but also acquire remarkable potential as raw material for creative and artistic research, remixing, digital archaeology or exhibition. From this point of view, their curation is justified. The Everywhere Museum of Everything is the designation given by the author to the augmented urban spaces, populated by these layers of original and remixed digital audio-visual information, interconnected by hashtags and geo-tags, which can be rendered visible through augmented reality tools, thus transforming any urban space into a digital gallery of their recent social, aesthetic or ethnographic history.info:eu-repo/semantics/publishedVersio