991 resultados para value-mapping


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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.

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There have never been so many touch points between companies and consumers as there are today, which paradoxically makes it very challenging for companies to be able to retain and engage customers. Gamification is a strategy used by a large number of companies to increase customer engagement and customer lifetime value. This work aims at developing a gamification system for MyGon, a Portuguese startup working in the market of discounts and experiences. In addition to examining the literature concerning gamification, its elements and characteristics, recommendations were developed for addressing MyGon’s business goals of increasing conversion and customer engagement. The gamification mechanisms suggested include badges, missions, points, leaderboards and levels.

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Accessibility is nowadays an important issue for the development of cities. It is seen as a priority in order toguarantee equal access to fundamental rights, to improve the quality of life of citizens and to ensure that everyone, regardless of age, mobility or ability, have equal access to all the resources and benefits cities have to offer. Consequently, factors closely related to the accessibility have gained a higher relevance for identifying and assessing the location of urban facilities. The main goal of the paper is to present an accessibility evaluation model applied in Santarém, in Brazil, a city located midway between the larger cities of Belem and Manaus. The research instruments, sampling method and data analysis proposed for mapping urban accessibility are described. Daily activities were used to identify and group key destinations. The model was implemented within a geographic information system and integrates the individualâ s perspective through the definition of each key destination weight, reflecting their significance for daily activities in the urban area. Accessibility to key destinations was mapped over 24 districts of the city of Santarém. The results of this model application can support city administration decision-making for new investments in order to improve urban quality of life.

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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.

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Tese de Doutoramento em Psicologia - Especialidade em Psicologia Experimental e Ciências Cognitivas

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Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Dissertação de mestrado em Engenharia Industrial

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Proceedings da AUTEX 2015, Bucareste, Roménia.

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Dissertação de mestrado em Plant Molecular Biology, Biotechnology and Bioentrepreneurship

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Mushrooms contain a multitude of biomolecules with nutritional and/or biological activity. Among the bioactive molecules, phenolic compounds and tocopherols are the most responsible for their antioxidant activity. In the present work, Boletus edulis, Lentinus edodes and Xerocomus badius, three edible mushroom species originated from Poland, were analyzed for their chemical composition and antioxidant activity. Carbohydrates were the most abundant macronutrients, followed by proteins and ash. Fructose, mannitol and trehalose were the prevalent sugars, but glucose was only found in B. edulis. Polyunsaturated fatty acids predominated over mono and saturated fatty acids. Palmitic, oleic and linoleic acids were abundant in the three samples. α- and β- Tocopherols were quantified in all the samples, but γ-tocopherol was only identified in X. badius. Oxalic and fumaric acids were quantified in the three samples; quinic acid was only present in L. edodes, and malic and citric acids were only found in X. badius. p-Hydroxybenzoic, protocatechuic and cinnamic acids were quantified in all the species, while p-coumaric acid was only found in B. edulis. This species and X. badius revealed the highest antioxidant properties, being B. edulis more effective in radicals scavenging activity and reducing power, and X. badius in lipid peroxidation inhibition, which is related with the highest amounts in phenolic compounds and tocopherols, respectively.

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Dissertação de mestrado integrado em Engenharia Civil

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Tese de Doutoramento em Psicologia Básica