Grande panorama de Lisboa em azulejo: Novos contributos para a fixação da data, encomenda e autoria

O Grande panorama de Lisboa, obra maior da azulejaria nacional e hoje à guarda do Museu Nacional do Azulejo, pertenceu outrora a um palácio situado na freguesia de Santiago, propriedade da família Ferreira de Macedo no final do século XVII. A investigação apresentada procura esclarecer alguns aspectos relacionados com a execução do grandioso painel e com o perfil sócio-cultural do encomendador. À luz de novos elementos documentais, o artigo discute ainda a questão da autoria do painel, dada há muito ao pintor barroco Gabriel del Barco.

Um modelo Data Envelopment Analysis para avaliação da eficiência dos terminais de contentores do grupo TERTIR

O transporte marítimo tem vindo a adquirir uma considerável importância na economia mundial desde o século XV. O transporte marítimo é visto como um dos meios de transporte mais viáveis, que engloba um largo número de destinos no mundo e representa, para uma determinada distância a percorrer, o menor custo por tonelada. É, também, comparativamente com o transporte aéreo e rodoviário, o meio de transporte menos poluente, tornando-o, assim, uma alternativa “amiga do ambiente”. Em particular, o transporte via contentores tem vindo a ser cada vez mais utilizado devido às suas inúmeras vantagens. O contentor permite o transporte de qualquer tipo de mercadoria em boas condições de acondicionamento e permitiu otimizar as operações efetuadas através da redução de tempo de trabalho, custos e espaço. Ademais, com a globalização, a evolução do mercado, a construção de navios de maiores dimensões e a maior tecnologia investida no setor, a competição entre os portos alcançou níveis que exigem uma maior eficiência de toda a estrutura portuária. Neste contexto, a presente dissertação visa avaliar a eficiência dos terminais de contentores do grupo TERTIR, nomeadamente os de Lisboa, Leixões e Setúbal, utilizando o método Data Envelopment Analaysis (DEA). De um modo geral, o método DEA avalia a capacidade dos terminais em converter inputs em outputs. Mais especificamente os inputs selecionados nesta dissertação dizem respeito às infraestruturas e equipamentos dos terminais em estudo, e o output considera a carga movimentada por cada terminal, sendo neste caso representada pelo número de TEUs movimentados. O modelo proposto é aplicado a um conjunto de 30 terminais de contentores Europeus de 6 países diferentes, nomeadamente, Alemanha, Bélgica, Espanha, França, Holanda e Portugal. De um modo geral, os terminais TERTIR apresentam níveis de eficiência baixos quando comparados com outros terminais Europeus. Os resultados contribuem, também, para auxiliar o grupo TERTIR no debate de algumas questões atuais com as autoridades portuárias, nomeadamente no que se refere à descida dos tarifários praticados aos seus clientes e à enunciada construção do terminal de contentores do Barreiro.

The effect of music marketing: A consumer perspective

The purpose of this thesis is to get a consumer perspective regarding event marketing in music festivals. Event marketing is a tool used by marketers that evolved out of philanthropy and commercial sponsorship. Brands are more and more using music or other entertainment moments to create a strong relationship with their clients, and the target group at these events, the millennial generation. Brands use sponsoring and therefore event marketing for several reasons as: increase brand awareness; create brand image; re-position the brand/product in the minds of consumers; increase profit over a short period; and, achieve larger market share. Nonetheless, we wonder how is this tool seen by consumers? To understand this, a preliminary research with nine interviews was conducted to obtain basic ideas about event marketing. Afterwards the main research was developed, also using interviews, to get deeper insights. With this thesis, it is possible to conclude that some brands are able to create brand awareness on attendees through brand sponsorship. Moreover, entertainment activities in festivals are well seen by consumers, they like it and are able to describe it well, even though it is more about the activity itself than the brand promoting it. Furthermore, it was possible to understand that experiential marketing in a festival might have a positive effect on consumers as it might create a link between the event and the brand. Finally, we recommend some actions, for brands to develop in future music festivals.

Enunciados do tipo injuntivo em géneros de texto publicitários sobre o vinho.

A partir de um corpus de géneros de texto publicitários, rótulos e contrarrótulos de garrafa de vinho e anúncios sobre o vinho, neste trabalho, serão analisados os enunciados injuntivos em ocorrência para averiguar as relações que se estabelecem entre marcas comerciais e consumidores, o tipo de informação veiculada e as representações linguisticamente construídas destes sujeitos. Situando-se no âmbito da Teoria do Texto e combinando patamares de análise linguística com a dimensão social, esta investigação convoca ainda o Interacionismo Sociodiscursivo que defende uma perspetiva ontogenética da linguagem, consentânea com uma abordagem discursivo-textual da Linguística. A análise dos dados indica que os domínios sociais ou as atividades envolvidas, publicitária e de produção e de comercialização do vinho, preconizam imagens do consumidor ideal de vinho no que diz respeito à prova de vinho, a um comportamento socialmente adequado e sobre as boas propriedades do vinho.

The impact of in-store activations (communication) in the consumer's emotions

Consumer behavior: Sport Zone. The analysis of "The impact of in-store activations (communication) in the consumer's emotions" Several studies have been conducted on the consumer behavior. This study aims to analyze and understand which factors are important to consumers’ emotions when the purchase decision occurs, the brand awareness, brand loyalty and the campaigns/activations’ impact in the above factors. Two research surveys were conducted to realize this study, the first online and the other was an interview to the Agency Up Partner who conceived and put into practice this Fitness campaign. First of all, was the consumer’s survey, a survey with 100 answers, to understand which factors are taken into account when a campaign in-store is held, in which the atmosphere is mainly used to arouse consumer’s desire to purchase, and also emotions. Second, the interview with the agency was realized to find out on what they were based on when they delineate it, and if the raise of emotions was taken into account in the origin of it. Concluding, emotions have a significant impact on formation of consumer in-store behavior, satisfaction and loyalty. As we could assay through of how this Fitness campaign was carried out as well as the optimal feedback received by consumers, improved attention over in-store marketing activity strongly influences consumer behavior at the point of purchase. “Sport Zone: A new store concept where the love for sports is combined with functionality”

Exploring the consumer decision journey and online shoping experience through an emotional prespective

Traditional consumer decision-making models have long used quantitative research to address a link between emotional and rational behavior. However, little qualitative research has been conducted in the area of online shopping as an end-to-end experience. This study aims to provide a detailed phenomenological account of consumers’ online shopping experience and extend Mckinsey & Companys’s consumer decision journey model from an emotional perspective. Six semi-structured interviews and a focus group of nine people are analyzed using Interpretive Phenomenology Analysis and five superordinate themes emerged from the results: emotional experience, empathy and encouragement, in relation to brand preference, emotional encounters in relation to consumer satisfaction and emotional exchange and relationship with a company or brand. A model interrelating these themes is then introduced to visually represent the emotional essence of a large online purchase. This study promises to be applicable as a descriptive, and perhaps, better predictive report for understanding the complex consumer decision-making process as it relates to online consumer behavior. Future research topics are also identified.

A comparison analysis of the marketing strategy of Lufthansa and Emirates in Germany

The objective of this paper is to perform an analysis of the marketing strategy of Lufthansa and Emirates in Germany. Since both airlines use a similar approach to increase brand awareness an in-depth analysis is implemented in order to identify potential differences. Hereby, consumer insights about the perception and expectation travellers have in common will be analyzed and assessed with quantitative data. Both airlines are well positioned in terms of their marketing strategy, but when Emirates is strengthen its marketing campaign with that pace, the Gulf carrier will certainly make use of its economic strength and can become a frightening threat for the Lufthansa Group on long-haul destinations. Finally, recommendations for future marketing activities for both airlines will be given.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Modelos de negócios para a internet das coisas baseados em big data : Muzzley, um estudo de caso

A Internet das Coisas tal como o Big Data e a análise dos dados são dos temas mais discutidos ao querermos observar ou prever as tendências do mercado para as próximas décadas, como o volume económico, financeiro e social, pelo que será relevante perceber a importância destes temas na atualidade. Nesta dissertação será descrita a origem da Internet das Coisas, a sua definição (por vezes confundida com o termo Machine to Machine, redes interligadas de máquinas controladas e monitorizadas remotamente e que possibilitam a troca de dados (Bahga e Madisetti 2014)), o seu ecossistema que envolve a tecnologia, software, dispositivos, aplicações, a infra-estrutura envolvente, e ainda os aspetos relacionados com a segurança, privacidade e modelos de negócios da Internet das Coisas. Pretende-se igualmente explicar cada um dos “Vs” associados ao Big Data: Velocidade, Volume, Variedade e Veracidade, a importância da Business Inteligence e do Data Mining, destacando-se algumas técnicas utilizadas de modo a transformar o volume dos dados em conhecimento para as empresas. Um dos objetivos deste trabalho é a análise das áreas de IoT, modelos de negócio e as implicações do Big Data e da análise de dados como elementos chave para a dinamização do negócio de uma empresa nesta área. O mercado da Internet of Things tem vindo a ganhar dimensão, fruto da Internet e da tecnologia. Devido à importância destes dois recursos e á falta de estudos em Portugal neste campo, com esta dissertação, sustentada na metodologia do “Estudo do Caso”, pretende-se dar a conhecer a experiência portuguesa no mercado da Internet das Coisas. Visa-se assim perceber quais os mecanismos utilizados para trabalhar os dados, a metodologia, sua importância, que consequências trazem para o modelo de negócio e quais as decisões tomadas com base nesses mesmos dados. Este estudo tem ainda como objetivo incentivar empresas portuguesas que estejam neste mercado ou que nele pretendam aceder, a adoptarem estratégias, mecanismos e ferramentas concretas no que diz respeito ao Big Data e análise dos dados.

Saúde em Portugal : estudo das urgências hospitalares através do Data Mining

Qualquer assunto relacionado com a saúde é sempre um tema sensível, pela importância que tem junto da população, já que interage diretamente com o bem-estar das pessoas e, essencialmente, com a sensação de segurança que as estas pretendem ter na prestação dos cuidados básicos de saúde. Dados estatísticos mostram que a população está cada vez mais envelhecida, reforçando a importância da existência de bons centros hospitalares e de um bom Sistema Nacional de Saúde (SNS) (Plano Nacional de Saúde, 2010). Em Portugal, caso os pacientes necessitem de cuidados mais urgentes, podem recorrer ao Serviço de Urgências disponibilizado para toda a população através do SNS. No entanto, a gestão e planeamento deste serviço é complexa, dado este serviço ser frequentemente utilizado por pacientes que não necessitam de cuidados urgentes, levando a que os hospitais deixem de conseguir dar a resposta esperada, implicando a prestação por vezes um serviço de menor qualidade. Neste sentido, analisaram-se dados de um hospital do norte do país com o intuito de perceber o ponto de situação das urgências, de forma a encontrar padrões relevantes através da análise de clusters e de regras de associação. Começando pela análise de clusters, utilizaram-se apenas as variáveis que foram consideradas importantes para o problema, resultando da análise final 3 clusters. O primeiro cluster é constituído por elementos do sexo masculino de todas as idades, o segundo cluster por elementos do sexo masculino mais jovens e por elementos do sexo feminino até aos 60 anos e o terceiro cluster apenas por elementos do sexo feminino a partir dos 40 anos. No final verificaram-se muitas semelhanças entre os clusters 1 e 3, pois ambos continham os pacientes mais idosos, havendo um padrão comum no seu comportamento. No ano 2012 não houve registo de nenhuma epidemia, não havendo por isso nenhuma doença que se destacasse comparativamente às restantes. Concluiu-se também que na maior parte dos casos houve a necessidade de uma intervenção urgente (pulseira de cor Amarela), no entanto a maioria dos pacientes observados conseguiu regressar às suas habitações após as consultas nas Urgências Hospitalares, sem intervenções médicas adicionais. Relativamente às regras de associação, houve a necessidade de transformar e eliminar algumas variáveis que enviesassem o estudo. Após o processo da criação das regras de associação, percebeu-se que as regras eram muito similares entre si, apresentando uma maior confiança nas variáveis que apareceram em maior número (“Pacientes com pulseira de cor Amarela”, “distrito do Porto” ou “Alta Médica para a Residência”).

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.

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.

A data-driven analytics approach in the study of pneumonia’s fatalities

As huge amounts of data become available in organizations and society, specific data analytics skills and techniques are needed to explore this data and extract from it useful patterns, tendencies, models or other useful knowledge, which could be used to support the decision-making process, to define new strategies or to understand what is happening in a specific field. Only with a deep understanding of a phenomenon it is possible to fight it. In this paper, a data-driven analytics approach is used for the analysis of the increasing incidence of fatalities by pneumonia in the Portuguese population, characterizing the disease and its incidence in terms of fatalities, knowledge that can be used to define appropriate strategies that can aim to reduce this phenomenon, which has increased more than 65% in a decade.

A bayesian approach for NDT data fusion: The Saint Torcato Church case study

This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.