Auxiliary mechanisms for telerobotics

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Estimation and hypothesis testing in mixed linear models

Dissertação apresentada para obtenção do Grau de Doutor em Matemática, Estatística, pela Universidade Nova de Lisboa, faculdade de Ciências e Tecnologia

Estimation of vegetation carbon stock in Portugal using land use/ land cover data

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Estimation of infection rate in epidemic models with multiple populations

Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações Especialização em Actuariado, Estatística e Investigação Operacional

Estimation Models for the adoption and use of information technology: internet-related technologies at firm level in the Portuguese and European context

Dissertação apresentada como requisito parcial para obtenção do grau de Doutor em Gestão de Informação

Credit risk stress testing: The Portuguese environment, macroeconomic scenarios and the estimation of losses for corporate sectors

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

Recursive neuro fuzzy techniques for online identification and control

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Parameter estimation in the presence of auxiliary information

Dissertação para obtenção do Grau de Doutora em Estatística e Gestão de Risco, Especialidade em Estatística

Hospital-acquired infections: a cost estimation for CLABSI in Portugal

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Evaluation of uv spectrophotometry for estimation of nitrite and nitrate in nitrified urine

Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.

A solution for estimates in software development projects

The Corporate world is becoming more and more competitive. This leads organisations to adapt to this reality, by adopting more efficient processes, which result in a decrease in cost as well as an increase of product quality. One of these processes consists in making proposals to clients, which necessarily include a cost estimation of the project. This estimation is the main focus of this project. In particular, one of the goals is to evaluate which estimation models fit the Altran Portugal software factory the most, the organization where the fieldwork of this thesis will be carried out. There is no broad agreement about which is the type of estimation model more suitable to be used in software projects. Concerning contexts where there is plenty of objective information available to be used as input to an estimation model, model-based methods usually yield better results than the expert judgment. However, what happens more frequently is not having this volume and quality of information, which has a negative impact in the model-based methods performance, favouring the usage of expert judgement. In practice, most organisations use expert judgment, making themselves dependent on the expert. A common problem found is that the performance of the expert’s estimation depends on his previous experience with identical projects. This means that when new types of projects arrive, the estimation will have an unpredictable accuracy. Moreover, different experts will make different estimates, based on their individual experience. As a result, the company will not directly attain a continuous growing knowledge about how the estimate should be carried. Estimation models depend on the input information collected from previous projects, the size of the project database and the resources available. Altran currently does not store the input information from previous projects in a systematic way. It has a small project database and a team of experts. Our work is targeted to companies that operate in similar contexts. We start by gathering information from the organisation in order to identify which estimation approaches can be applied considering the organization’s context. A gap analysis is used to understand what type of information the company would have to collect so that other approaches would become available. Based on our assessment, in our opinion, expert judgment is the most adequate approach for Altran Portugal, in the current context. We analysed past development and evolution projects from Altran Portugal and assessed their estimates. This resulted in the identification of common estimation deviations, errors, and patterns, which lead to the proposal of metrics to help estimators produce estimates leveraging past projects quantitative and qualitative information in a convenient way. This dissertation aims to contribute to more realistic estimates, by identifying shortcomings in the current estimation process and supporting the self-improvement of the process, by gathering as much relevant information as possible from each finished project.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].

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.