How aspiring filmmakers cope with unexpected events on set

Making the transition between plans and unexpected occurrences is something organizations are used to doing every day. However, not much is known about how actors cope with unanticipated events and how they accommodate them within predefined schedules. In this study, we draw on an inductive analysis of aspiring filmmakers’ film sets to elaborate on how they plan their shooting activities every day, only to adjust them when unforeseen complications arise. We discover that film crews anchor their expectations for the day based on a planned shooting schedule, yet they incorporate a built-in assumption that it will inevitably be disrupted. We argue that they resort to triage processes and “troubleshooting protocols” that help decipher incoming problems. Familiar problems are solved by making use of experience obtained from past situations, whereas unprecedented problems are solved through a tacit protocol used as a tool to quickly devise an appropriate game plan. This study contributes to the literature on sense-making and provides valuable information about the unexplored world of filmmaking.

Terra Nativa. A relação eco-humana na vida e na obra de Ferreira de Castro

A presente investigação teve o apoio financeiro da FCT, através de uma Bolsa de Doutoramento.

The global shopper & brands communication at airports

This project aims to illuminate two perspectives on travel retail. On the one hand, it describes the main character of the shopping scenario at airports, namely the Global Shopper. It covers the entire profile of the referred character, the main nationalities that represent him and the current shopping trends of the passenger. Also estimates of the booming nationalities and the future purchasing trends are accurately presented. On the other hand, the travel retail market is analyzed from the airport brands’ perspective. It is described what is currently done in terms of brands communication in the top ten airports around the world and the expected future market retail trends. To accurately explore the Global Shopper behavior and purchasing preferences, a market research was conducted with a sample of 128 respondents, male and female, from different nationalities, age groups, occupation and education backgrounds. The essay tests hypothesis regarding the relevance of several variables in the purchasing process of the Global Shopper in order to understand the most pleasant way to approach consumers in travel retail. The main variables studied concern the reasons to shop at airports, to whom the passenger shops, the preferred category and brand of purchase, feelings while shopping abroad, impulsive buying behavior, brand loyalty, the use of mobile devices in the shopping process, brands communication at airports, pre-ordering online and the attitude towards self-service stores. Some findings were in accordance with expectations, while others were a surprise and may produce valuable recommendations for future travel retail practices. 4 The main relevant results concern two areas, namely pre-ordering online and self-service stores. Results showed a certain stress about not having enough time to choose between the various offerings in travel retail, as well as difficulty in dealing with crowed stores. However, pre-ordering online was not common, which would be an initiative that could solve the discomfort at airport’s stores. Moreover, self-service would promote efficiency in stores allowing passengers to save time if they already know how to go through the shopping process by themselves. Another possible recommendation concerns differentiating the strategy in travel retail for the two genders. Some differences were found in the categories bought by male and female, as well as to how brands should shape their approach concerning the demands of each gender.

Characterization of the clients retention in the tlecommunications companies

The ability of a company to be able to do a precisely churn prediction, so it can act on it, is paramount. For this reason, Deloitte addressed me the challenge of characterizing the client’s retention in the telecom companies. To do so, it was created a comprehensive tool that enables Deloitte to evaluate the churn management maturity level of a telecom operator and highlight its strengths and weaknesses. The development of this matrix was based on a depth churn research, a market research based on 40 interviews and 2 focus group and the valuable feedback from Deloitte consultants.

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.

Inventário e valorização do património arqueológico do concelho da Chamusca : da época Romana à época Moderna

O presente relatório resulta do estágio efetuado na Câmara Municipal da Chamusca. O mesmo teve como objetivo a realização de um inventário do património arqueológico do concelho da Chamusca, centrado nos períodos da época Romana à Moderna, elaborando conjuntamente uma observação sobre o respetivo povoamento do território. O inventário realizado compilou toda a informação identificada nas fontes bibliográficas nos documentos da época já publicados e nas informações orais que se foram recolhendo. Posteriormente, procedeu-se à confirmação dos dados no terreno, através de uma prospeção dirigida aos sítios nos quais havia indícios de ocorrências patrimoniais. O desenvolvimento deste projeto e deste tipo de investigação possibilitou a identificação/relocalização de um número muito significativo de sítios e potenciais sítios arqueológicos, num total de 136 sítios. O seu inventário foi sistematizado e permitiu, assim, a compilação do conhecimento do património arqueológico deste município, contribuindo diretamente para a sua salvaguarda, preservação e valorização junto da comunidade. A autarquia passou agora a ter um instrumento essencial para a definição das políticas de salvaguarda do património, bem como para a definição das estratégias de desenvolvimento do seu território.

A practical approach to execute and test a lean startup

This paper practically applies the “Lean Startup Approach” by identifying, analyzing and executing a newly developed web-based business idea. Hypotheses were designed and tested with the construction of a minimum viable product – i.e. a landing page. In-depth interviews allowed deciding either to pivot or persevere the initial launch strategy. Overall, the aim was to collect as much valuable response as possible from customers and ultimately decide for a superior strategy while devoting the smallest amount of time and money.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

À descoberta do mundo pelo jogo dos sentidos

Relatório de estágio de mestrado em Educação Pré-Escolar

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

A aprendizagem baseada na resolução de problemas na aprendizagem da Geologia: uma intervenção centrada no tópico "Ocupação antrópica e problemas de ordenamento"

Dissertação de mestrado em Ensino de Biologia e Geologia no 3º Ciclo do Ensino Básico e no Ensino Secundário

O lúdico como estratégia de consolidação e revisão de conhecimentos na aula de Língua Estrangeira

Relatório de estágio de mestrado em Ensino do Português no 3º Ciclo do Ensino Básico e no Ensino Secundário e de Espanhol nos Ensinos Básico e Secundário

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.

[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.