Proposta de um modelo de medição e análise da satisfação de clientes em empresas de software : caso prático do ambiente business-to-business

Os estudos da satisfação e lealdade do cliente em ambiente Business-to-Business têm emergido devido ao interesse práctico e académico. Recorreu-se a um caso práctico de uma empresa de software internacional, ESRI, a operar em Portugal com modelo de negócio B2B e comportamento de compra extensivo. Desenvolveu-se um modelo estrutural com 11 variáveis latentes: lealdade; satisfação; imagem; atmosfera; cooperação; adaptação; processos; tecnologia; orientação ao cliente; competências; colaboradores e comunicação. Foram analisadas 304 respostas ao questionário de satisfação e de seguida aplicou-se o modelo a seis grupos de clientes segmentados de acordo com a contribuição do cliente para as receitas e o comportamento no processo de decisão de compra. Recorreu-se a modelos SEM (Structural Equation Modelling) com estimação dos parâmetros através da metodologia PLS (partial Least Squares). Os resultados mostram nos seis segmentos, que os valores da empresa, a cooperação através da competência dos colaboradores e da orientação ao cliente e a tecnologia são factores mais importantes para a satisfação e lealdade dos clientes.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

HEP-Frame: A software engineered framework to aid the development and efficient multicore execution of scientific code

This work was supported by FCT (Fundação para a Ciência e Tecnologia) within Project Scope (UID/CEC/00319/2013), by LIP (Laboratório de Instrumentação e Física Experimental de Partículas) and by Project Search-ON2 (NORTE-07-0162- FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework, through the European Regional Development Fund.

Refinement and variability techniques in model transformation of software requirements

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Estudo e implementação de testes de software em desenvolvimento ágil

Dissertação de mestrado em Engenharia de Sistemas

Frameworks no desenvolvimento de software: o caso da Elevation da PRIMAVERA BSS

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Feature Nets: behavioural modelling of software product lines

Software product lines (SPL) are diverse systems that are developed using a dual engineering process: (a)family engineering defines the commonality and variability among all members of the SPL, and (b) application engineering derives specific products based on the common foundation combined with a variable selection of features. The number of derivable products in an SPL can thus be exponential in the number of features. This inherent complexity poses two main challenges when it comes to modelling: Firstly, the formalism used for modelling SPLs needs to be modular and scalable. Secondly, it should ensure that all products behave correctly by providing the ability to analyse and verify complex models efficiently. In this paper we propose to integrate an established modelling formalism (Petri nets) with the domain of software product line engineering. To this end we extend Petri nets to Feature Nets. While Petri nets provide a framework for formally modelling and verifying single software systems, Feature Nets offer the same sort of benefits for software product lines. We show how SPLs can be modelled in an incremental, modular fashion using Feature Nets, provide a Feature Nets variant that supports modelling dynamic SPLs, and propose an analysis method for SPL modelled as Feature Nets. By facilitating the construction of a single model that includes the various behaviours exhibited by the products in an SPL, we make a significant step towards efficient and practical quality assurance methods for software product lines.

From software extensions to product lines of dataflow programs

Abstract Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE-speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the ReFlO tool and present two non-trivial case studies as evidence of our work’s generality

Da utilização e análise de dados de Geofísica em contextos arqueológicos: o Castro de Sapelos (Boticas) e o Seminário Conciliar de São Pedro e São Paulo (Braga)

Dissertação de mestrado em Arqueologia

Glazing daylighting performance and Trombe wall thermal performance of a modular façade system in four different Portuguese cities

This paper reports on a new façade system that uses passive solutions in the search for energy efficiency. The differentials are the versatility and flexibility of the modules, which are important advantages of the system. The thermal performance of Trombe walls and glazings and the daylighting performance of glazing were the key aspects analyzed in the results. Computational simulations were accomplished for the thermal performance of different arrangements of the modules with DesignBuilder software. The glazing daylighting performance was studied by means of Ecotect and Desktop Radiance programs and compared with the transmittance curves of glazings. Occupancy profile and internal gains were fixed according to the Portuguese reality for both studies. The main characteristics considered in this research were the use of two double glazings, four different climates in Portugal and one and two Trombe walls in the façade. The results show an important reduction in the energy consumption with the use of Trombe walls and double self-cleaning glazing in the façade, which also presented better daylighting performance.

Subendocardial fibrosis in remote myocardium results from reduction of coronary driving pressure during acute infarction in rats

OBJECTIVE: To investigate the role of hemodynamic changes occurring during acute MI in subsequent fibrosis deposition within non-MI. METHODS: By using the rat model of MI, 3 groups of 7 rats each [sham, SMI (MI <30%), and LMI (MI >30%)] were compared. Systemic and left ventricular (LV) hemodynamics were recorded 10 minutes before and after coronary artery ligature. Collagen volume fraction (CVF) was calculated in picrosirius red-stained heart tissue sections 4 weeks later. RESULTS: Before surgery, all hemodynamic variables were comparable among groups. After surgery, LV end-diastolic pressure increased and coronary driving pressure decreased significantly in the LMI compared with the sham group. LV dP/dt max and dP/dt min of both the SMI and LMI groups were statistically different from those of the sham group. CVF within non-MI interventricular septum and right ventricle did not differ between each MI group and the sham group. Otherwise, subendocardial (SE) CVF was statistically greater in the LMI group. SE CVF correlated negatively with post-MI systemic blood pressure and coronary driving pressure, and positively with post-MI LV dP/dt min. Stepwise regression analysis identified post-MI coronary driving pressure as an independent predictor of SE CVF. CONCLUSION: LV remodeling in rats with MI is characterized by predominant SE collagen deposition in non-MI and results from a reduction in myocardial perfusion pressure occurring early on in the setting of MI.