Modeling Movement of Tourists : Tools and Application in São Miguel Island, Portugal

Tourism contributes to the development of many regions. Different factors affect the movement of tourists within a destination. Those factors are related to the tourist characteristics, like the time budgets, preferences or destination knowledge, and to the destination features, like the attraction characteristics or accessibility level. Tourist decisions aren’t always done in a rational way. Emotions add further complexity to the human decision process. The use of footpaths can play an important role in the satisfaction of tourists, helping them discover the territory and giving them access to different types of attractions. The existence of a mathematical model that integrates the main factors related to the movement of independent tourists within a destination, in a dynamic way, will make possible the creation of an adaptable software tool. This tool will meet the specific needs of tourists, allowing the use of the network in an optimal way by the different tourist profiles, and the needs of the regional government and business, permitting better decisions and the offer of relevant tourism products. This article identifies the main tourists’ mobility criteria in the São Miguel island territory, Azores, Portugal, recognizes the necessary modelling process and identifies the basis for the construction of the mathematical model that explains the movement of tourists within the destination.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.

Signal Subspace Identification in Hyperspectral Linear Mixtures

Chpater in Book Proceedings with Peer Review Second Iberian Conference, IbPRIA 2005, Estoril, Portugal, June 7-9, 2005, Proceedings, Part II

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Biomechanical modeling and simulation of the spider crab (maja brachydactyla)

Uma linha de pesquisa e desenvolvimento na área da robótica, que tem recebido atenção crescente nos últimos anos, é o desenvolvimento de robôs biologicamente inspirados. A ideia é adquirir conhecimento de seres biológicos, cuja evolução ocorreu ao longo de milhões de anos, e aproveitar o conhecimento assim adquirido para implementar a locomoção pelos mesmos métodos (ou pelo menos usar a inspiração biológica) nas máquinas que se constroem. Acredita-se que desta forma é possível desenvolver máquinas com capacidades semelhantes às dos seres biológicos em termos de capacidade e eficiência energética de locomoção. Uma forma de compreender melhor o funcionamento destes sistemas, sem a necessidade de desenvolver protótipos dispendiosos e com longos tempos de desenvolvimento é usar modelos de simulação. Com base nestas ideias, o objectivo deste trabalho passa por efectuar um estudo da biomecânica da santola (Maja brachydactyla), uma espécie de caranguejo comestível pertencente à família Majidae de artrópodes decápodes, usando a biblioteca de ferramentas SimMechanics da aplicação Matlab / Simulink. Esta tese descreve a anatomia e locomoção da santola, a sua modelação biomecânica e a simulação do seu movimento no ambiente Matlab / SimMechanics e SolidWorks.

Efeito fisiológico da cafeína em estudos neurológicos com base na ponderação em susceptibilidade ferromagnética (SWI)

Introdução – O presente estudo avaliou o efeito da cafeína no valor da razão contraste ruído (CNR) em imagens SWI. Objetivos – Avaliar o efeito da cafeína qualitativamente e quantificado pelo cálculo do valor CNR em imagens de magnitude e MIP para as estruturas: veia cerebral interna, seio sagital superior, tórcula e artéria cerebral média. Metodologia – A população do estudo incluiu 24 voluntários saudáveis que estiveram pelo menos 24h privados da ingestão de cafeína. Adquiriram-se imagens SWI antes e após a ingestão de 100ml de café. Os voluntários foram subdivididos em quatro grupos de seis indivíduos/grupo e avaliados separadamente após decorrido um intervalo de tempo diferente para cada grupo (15, 25, 30 ou 45min pós-cafeína). Utilizou-se um scanner Siemens Avanto 1,5 T com bobine standard de crânio e os parâmetros: T2* GRE 3D de alta resolução no plano axial, TR=49; TE=40; FA=15; FOV=187x230; matriz=221x320. O processamento de imagem foi efetuado no software OsiriX® e a análise estatística no GraphPadPrism®. Resultados e Discussão – As alterações de sinal e diferenças de contraste predominaram nas estruturas venosas e não foram significantes na substância branca, LCR e artéria cerebral média. Os valores CNR pré-cafeína diferiram significativamente do pós-cafeína nas imagens de magnitude e MIP na veia cerebral interna e nas imagens de magnitude do seio sagital superior e da tórcula (p<0,0001). Não se verificaram diferenças significativas entre os grupos avaliados nos diferentes tempos pós-cafeína. Conclusões – Especulamos que a cafeína possa vir a ser usada como agente de contraste nas imagens SWI barato, eficaz e de fácil administração.

Three-dimensional modeling of tongue during speech using MRI data

The tongue is the most important and dynamic articulator for speech formation, because of its anatomic aspects (particularly, the large volume of this muscular organ comparatively to the surrounding organs of the vocal tract) and also due to the wide range of movements and flexibility that are involved. In speech communication research, a variety of techniques have been used for measuring the three-dimensional vocal tract shapes. More recently, magnetic resonance imaging (MRI) becomes common; mainly, because this technique allows the collection of a set of static and dynamic images that can represent the entire vocal tract along any orientation. Over the years, different anatomical organs of the vocal tract have been modelled; namely, 2D and 3D tongue models, using parametric or statistical modelling procedures. Our aims are to present and describe some 3D reconstructed models from MRI data, for one subject uttering sustained articulations of some typical Portuguese sounds. Thus, we present a 3D database of the tongue obtained by stack combinations with the subject articulating Portuguese vowels. This 3D knowledge of the speech organs could be very important; especially, for clinical purposes (for example, for the assessment of articulatory impairments followed by tongue surgery in speech rehabilitation), and also for a better understanding of acoustic theory in speech formation.

Magnetic resonance imaging of the vocal tract: techniques and applications

Magnetic resonance (MR) imaging has been used to analyse and evaluate the vocal tract shape through different techniques and with promising results in several fields. Our purpose is to demonstrate the relevance of MR and image processing for the vocal tract study. The extraction of contours of the air cavities allowed the set - up of a number of 3D reconstruction image stacks by means of the combination of orthogonally oriented sets of slices for e ach articulatory gesture, as a new approach to solve the expected spatial under sampling of the imaging process. In result these models give improved information for the visualization of morphologic and anatomical aspects and are useful for partial measure ments of the vocal tract shape in different situations. Potential use can be found in Medical and therapeutic applications as well as in acoustic articulatory speech modelling.

The influence of the blood pressure on the venous cerebral flow measured by magnetic susceptibility (SWI) technique

Susceptibility Weighted Image (SWI) is a Magnetic Resonance Imaging (MRI) technique that combines high spatial resolution and sensitivity to provide magnetic susceptibility differences between tissues. It is extremely sensitive to venous blood due to its iron content of deoxyhemoglobin. The aim of this study was to evaluate, through the SWI technique, the differences in cerebral venous vasculature according to the variation of blood pressure values. 20 subjects divided in two groups (10 hypertensive and 10 normotensive patients) underwent a MRI system with a Siemens® scanner model Avanto of 1.5T using a synergy head coil (4 channels). The obtained sequences were T1w, T2w-FLAIR, T2* and SWI. The value of Contrast-to-Noise Ratio (CNR) was assessed in MinIP (Minimum Intensity Projection) and Magnitude images, through drawing free hand ROIs in venous structures: Superior Sagittal Sinus (SSS) Internal Cerebral Vein (ICV) and Sinus Confluence (SC). The obtained values were presented in descriptive statistics-quartiles and extremes diagrams. The results were compared between groups. CNR shown higher values for normotensive group in MinIP (108.89 ± 6.907) to ICV; (238.73 ± 18.556) to SC and (239.384 ± 52.303) to SSS. These values are bigger than images from Hypertensive group about 46 a.u. in average. Comparing the results of Magnitude and MinIP images, there were obtained lower CNR values for the hypertensive group. There were differences in the CNR values between both groups, being these values more expressive in the large vessels-SSS and SC. The SWI is a potential technique to evaluate and characterize the blood pressure variation in the studied vessels adding a physiological perspective to MRI and giving a new approach to the radiological vascular studies.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Image quality and dose analysis for a PA chest X-ray: comparison between AEC mode acquisition and manual mode using the 10 kVp ‘rule’

Purpose - To compare the image quality and effective dose applying the 10 kVp rule with manual mode acquisition and AEC mode in PA chest X-ray. Method - 68 images (with and without lesions) were acquired using an anthropomorphic chest phantom using a Wolverson Arcoma X-ray unit. These images were compared against a reference image using the 2 alternative forced choice (2AFC) method. The effective dose (E) was calculated using PCXMC software using the exposure parameters and the DAP. The exposure index (lgM provided by Agfa systems) was recorded. Results - Exposure time decreases more when applying the 10 kVp rule with manual mode (50%–28%) when compared with automatic mode (36%–23%). Statistical differences for E between several ionization chambers' combinations for AEC mode were found (p = 0.002). E is lower when using only the right AEC ionization chamber. Considering the image quality there are no statistical differences (p = 0.348) between the different ionization chambers' combinations for AEC mode for images with no lesions. Considering lgM values, it was demonstrated that they were higher when the AEC mode was used compared to the manual mode. It was also observed that lgM values obtained with AEC mode increased as kVp value went up. The image quality scores did not demonstrate statistical significant differences (p = 0.343) for the images with lesions comparing manual with AEC mode. Conclusion - In general the E is lower when manual mode is used. By using the right AEC ionising chamber under the lung the E will be the lowest in comparison to other ionising chambers. The use of the 10 kVp rule did not affect the visibility of the lesions or image quality.

Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

Guest editorial: OPTIMAX 2013

In 2012 we were awarded an Erasmus Intensive Programme grant to facilitate OPTIMAX 2013, a three week duration residential summer school held within the UK during August 2013. The summer school helped to further develop student radiographer skills in optimising x-radiation dose and image quality. With a major emphasis on visual techniques to determine image quality, lesion visibility, lesion detection performance and physical measures of image quality (eg signal to noise ratio (SNR)) we conducted controlled laboratory experiments on phantoms using Computed Radiography, CT and Full Field Digital Mammography. Mathematical modelling was used for radiation dose estimation. Sixty seven people from 5 European countries participated. This included 49 PhD, MSc and BSc students. Discipline areas included radiography, physics, biomedical science and nuclear medicine.