Brownian motion with drift threshold model

In this thesis we implement estimating procedures in order to estimate threshold parameters for the continuous time threshold models driven by stochastic di®erential equations. The ¯rst procedure is based on the EM (expectation-maximization) algorithm applied to the threshold model built from the Brownian motion with drift process. The second procedure mimics one of the fundamental ideas in the estimation of the thresholds in time series context, that is, conditional least squares estimation. We implement this procedure not only for the threshold model built from the Brownian motion with drift process but also for more generic models as the ones built from the geometric Brownian motion or the Ornstein-Uhlenbeck process. Both procedures are implemented for simu- lated data and the least squares estimation procedure is also implemented for real data of daily prices from a set of international funds. The ¯rst fund is the PF-European Sus- tainable Equities-R fund from the Pictet Funds company and the second is the Parvest Europe Dynamic Growth fund from the BNP Paribas company. The data for both funds are daily prices from the year 2004. The last fund to be considered is the Converging Europe Bond fund from the Schroder company and the data are daily prices from the year 2005.

Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

On the relation between the fractional Brownian motion and the fractional derivatives

Physics Letters A, vol. 372; Issue 7

A fractional linear system view of the fractional brownian motion

Nonlinear Dynamics, Vol. 38

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Unsupervised classification of remote sensing images combining Self Organizing Maps and segmentation techniques

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

Cluster analysis and segmentation of Global M&A transactions

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

Ground truth determination for segmentation of tomographic volumes using interpolation

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Range of motion measurements based on depth camera for clinical rehabilitation

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

A framework for developing motion-based games

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Microscopy image segmentation by active contour models

In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Insurance segmentation as unfair discrimination: what to expect next in the wake of Test-Achats

Proceedings of the 16th Annual Conference organized by the Insurance Law Association of Serbia and German Foundation for International Legal Co-Operation (IRZ), entitled "Insurance law, governance and transparency: basics of the legal certainty" Palic Serbia, 17-19 April 2015.

Customer relationship management at Siemens Healthcare – a diagnosis and proposal for strategy and market segmentation

Towards a holistic perspective of CRM, this project aims to diagnose and propose a strategy and market segmentation for Siemens Healthcare. The main underlying principle is to apply a full customer-centric outlook taking own business properties into consideration while preserving Siemens Healthcare’s culture and vision. Mainly focused on market segmentation, this project goes beyond established boundaries by employing an unbiased perspective of CRM while challenging current strategy, goals, processes, tools, initiatives and KPIs. In order to promote a sustainable business excellence strategy, this project aspires to streamline CRM strategic importance and driving the company one step forward.

Finding new opportunities in the Lisbon market through Whitaker consumer lifestyle segmentation

A sample of 445 consumers resident in distinct Lisbon areas was analyzed through direct observations in order to discover each lifestyle’s current proportion, applying the Whitaker Lifestyle™ Method. The findings of the conducted hypothesis tests on the population proportion unveil that Neo-Traditional and Modern Whitaker lifestyles have the significantly highest proportion, while the overall presence of different lifestyles varies across neighborhoods. The research further demonstrates the validity of Whitaker observation techniques, media consumption differences among lifestyles and the importance of style and aesthetics while segmenting consumers by lifestyles. Finally, market opportunities are provided for firms operating in Lisbon.