Multicriteria decision making: a case study in the automobile industry

Multi-criteria decision analysis (MCDA) has been one of the fastest-growing areas of operations research during the last decades. The academic attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods distinguish themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diversity poses challenges to the process of selecting the most suited method for a specific real-world decision problem. In this paper we present a case study in a real-world decision problem arising in the painting sector of an automobile plant. We tackle the problem by resorting to the well-known AHP method and to the MCDA method proposed by Pereira and Fontes (2012) (MMASSI). By relying on two, rather than one, MCDA methods we expect to improve the confidence and robustness of the obtained results. The contributions of this paper are twofold: first, we intend to investigate the contrasts and similarities of the results obtained by distinct MCDA approaches (AHP and MMASSI); secondly, we expect to enrich the literature of the field with a real-world MCDA case study on a complex decision making problem since there is a paucity of applied research work addressing real decision problems faced by organizations.

Hyperspectral signal subspace estimation

Given an hyperspectral image, the determination of the number of endmembers and the subspace where they live without any prior knowledge is crucial to the success of hyperspectral image analysis. This paper introduces a new minimum mean squared error based approach to infer the signal subspace in hyperspectral imagery. The method, termed hyperspectral signal identification by minimum error (HySime), is eigendecomposition based and it does not depend on any tuning parameters. It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

Mapping the quality of life experience in Alfama: a case study in Lisbon, Portugal.

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

Imagiologia Espetral - Análise Forense de Notas e Escrita Manual

A análise forense de documentos é uma das áreas das Ciências Forenses, responsável pela verificação da autenticidade dos documentos. Os documentos podem ser de diferentes tipos, sendo a moeda ou escrita manual as evidências forenses que mais frequentemente motivam a análise. A associação de novas tecnologias a este processo de análise permite uma melhor avaliação dessas evidências, tornando o processo mais célere. Esta tese baseia-se na análise forense de dois tipos de documentos - notas de euro e formulários preenchidos por escrita manual. Neste trabalho pretendeu-se desenvolver técnicas de processamento e análise de imagens de evidências dos tipos referidos com vista a extração de medidas que permitam aferir da autenticidade dos mesmos. A aquisição das imagens das notas foi realizada por imagiologia espetral, tendo-se definidas quatro modalidades de aquisição: luz visível transmitida, luz visível refletida, ultravioleta A e ultravioleta C. Para cada uma destas modalidades de aquisição, foram também definidos 2 protocolos: frente e verso. A aquisição das imagens dos documentos escritos manualmente efetuou-se através da digitalização dos mesmos com recurso a um digitalizador automático de um aparelho multifunções. Para as imagens das notas desenvolveram-se vários algoritmos de processamento e análise de imagem, específicos para este tipo de evidências. Esses algoritmos permitem a segmentação da região de interesse da imagem, a segmentação das sub-regiões que contém as marcas de segurança a avaliar bem como da extração de algumas características. Relativamente as imagens dos documentos escritos manualmente, foram também desenvolvidos algoritmos de segmentação que permitem obter todas as sub-regiões de interesse dos formulários, de forma a serem analisados os vários elementos. Neste tipo de evidências, desenvolveu-se ainda um algoritmo de análise para os elementos correspondentes à escrita de uma sequência numérica o qual permite a obtenção das imagens correspondentes aos caracteres individuais. O trabalho desenvolvido e os resultados obtidos permitiram a definição de protocolos de aquisição de imagens destes tipos de evidências. Os algoritmos automáticos de segmentação e análise desenvolvidos ao longo deste trabalho podem ser auxiliares preciosos no processo de análise da autenticidade dos documentos, o qual, ate então, é feito manualmente. Apresentam-se ainda os resultados dos estudos feitos às diversas evidências, nomeadamente as performances dos diversos algoritmos analisados, bem como algumas das adversidades encontradas durante o processo. Apresenta-se também uma discussão da metodologia adotada e dos resultados, bem como de propostas de continuação deste trabalho, nomeadamente, a extração de características e a implementação de classificadores capazes aferir da autenticidade dos documentos.

Structured Light System Calibration for Perception in Underwater Tanks

The process of visually exploring underwater environments is still a complex problem. Underwater vision systems require complementary means of sensor information to help overcome water disturbances. This work proposes the development of calibration methods for a structured light based system consisting on a camera and a laser with a line beam. Two different calibration procedures that require only two images from different viewpoints were developed and tested in dry and underwater environments. Results obtained show, an accurate calibration for the camera/projector pair with errors close to 1 mm even in the presence of a small stereos baseline.

Aquisição e Processamento de Imagens de Microscopia em Balística Forense

As novas tecnologias aplicadas ao processamento de imagem e reconhecimento de padrões têm sido alvo de um grande progresso nas últimas décadas. A sua aplicação é transversal a diversas áreas da ciência, nomeadamente a área da balística forense. O estudo de evidências (invólucros e projeteis) encontradas numa cena de crime, recorrendo a técnicas de processamento e análise de imagem, é pertinente pelo facto de, aquando do disparo, as armas de fogo imprimirem marcas únicas nos invólucros e projéteis deflagrados, permitindo relacionar evidências deflagradas pela mesma arma. A comparação manual de evidências encontradas numa cena de crime com evidências presentes numa base de dados, em termos de parâmetros visuais, constitui uma abordagem demorada. No âmbito deste trabalho pretendeu-se desenvolver técnicas automáticas de processamento e análise de imagens de evidências, obtidas através do microscópio ótico de comparação, tendo por base algoritmos computacionais. Estes foram desenvolvidos com recurso a pacotes de bibliotecas e a ferramentas open-source. Para a aquisição das imagens de evidências balísticas foram definidas quatro modalidades de aquisição: modalidade Planar, Multifocus, Microscan e Multiscan. As imagens obtidas foram aplicados algoritmos de processamento especialmente desenvolvidos para o efeito. A aplicação dos algoritmos de processamento permite a segmentação de imagem, a extração de características e o alinhamento de imagem. Este último tem como finalidade correlacionar as evidências e obter um valor quantitativo (métrica), indicando o quão similar essas evidências são. Com base no trabalho desenvolvido e nos resultados obtidos, foram definidos protocolos de aquisição de imagens de microscopia, que possibilitam a aquisição de imagens das regiões passiveis de serem estudadas, assim como algoritmos que permitem automatizar o posterior processo de alinhamento de imagens de evidências, constituindo uma vantagem em relação ao processo de comparação manual.

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

A SDK improvement towards gesture support

Human-Computer Interaction have been one of the main focus of the technological community, specially the Natural User Interfaces (NUI) field of research as, since the launch of the Kinect Sensor, the goal to achieve fully natural interfaces just got a lot closer to reality. Taking advantage of this conditions the following research work proposes to compute the hand skeleton in order to recognize Sign Language Shapes. The proposed solution uses the Kinect Sensor to achieve a good segmentation and image analysis algorithms to extend the skeleton from the extraction of high-level features. In order to recognize complex hand shapes the current research work proposes the redefinition of the hand contour making it immutable to translation, rotation and scaling operations, and a set of tools to achieve a good recognition. The validation of the proposed solution extended the Kinects Software Development Kit to allow the developer to access the new set of inferred points and created a template-matching based platform that uses the contour to define the hand shape, this prototype was tested in a set of predefined conditions and showed to have a good success ration and has proven to be eligible for real-time scenarios.

Past/present and future worries: na fMRI study

For the past decade, numerous imaging techniques gave rise to remarka-ble progresses in the understanding of brain’s structure and function. Amongst the wide variety of studies onto the field of neuroscience, neuropsychiatric re-searches with resource to neuroimaging have attracted increasing attention. The present study will focus on the identification of brain areas recruited while normative subjects read sentences related to past/present or future wor-ries. Our main aim was to accurately characterize these brain areas while providing them with a time-stamp that would hopefully help us understand the implications of past/present memories and future envisioning in worrying episodes. With that purpose, functional magnetic resonance imaging data was collected from ten healthy individuals. The obtained data was processed and statistically treated using the General Linear Model and both Fixed and Ran-dom Effects Analysis for group-level results. Thereafter, a Multi-Voxel Pattern Analysis with Searchlight Mapping was performed in order to find patterns of activation that allow differentiation between conditions. The obtained results indicate higher brain activation while reading sen-tences related to past/present worries when compared to future worry or neu-tral sentences. The main areas include frontal cortex, posterior parietal, occipital and temporal areas. Worrying, per se, was characterized by activation of the medial posterior parietal cortex, left posterior occipital lobe and left central temporal lobe. With the searchlight mapping approach we were able to further identify patterns of distinction between conditions, which were located in the parietal, limbic and frontal lobes.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Detection of purkinje images for automatic positioning of fixation target and interferometric measurements of anterior eye chamber

In cataract surgery, the eye’s natural lens is removed because it has gone opaque and doesn’t allow clear vision any longer. To maintain the eye’s optical power, a new artificial lens must be inserted. Called Intraocular Lens (IOL), it needs to be modelled in order to have the correct refractive power to substitute the natural lens. Calculating the refractive power of this substitution lens requires precise anterior eye chamber measurements. An interferometry equipment, the AC Master from Zeiss Meditec, AG, was in use for half a year to perform these measurements. A Low Coherence Interferometry (LCI) measurement beam is aligned with the eye’s optical axis, for precise measurements of anterior eye chamber distances. The eye follows a fixation target in order to make the visual axis align with the optical axis. Performance problems occurred, however, at this step. Therefore, there was a necessity to develop a new procedure that ensures better alignment between the eye’s visual and optical axes, allowing a more user friendly and versatile procedure, and eventually automatizing the whole process. With this instrument, the alignment between the eye’s optical and visual axes is detected when Purkinje reflections I and III are overlapped, as the eye follows a fixation target. In this project, image analysis is used to detect these Purkinje reflections’ positions, eventually automatically detecting when they overlap. Automatic detection of the third Purkinje reflection of an eye following a fixation target is possible with some restrictions. Each pair of detected third Purkinje reflections is used in automatically calculating an acceptable starting position for the fixation target, required for precise measurements of anterior eye chamber distances.

The influence of fibre orientation on the post-cracking tensile behaviour of steel fibre reinforced self-compacting concrete

Adding fibres to concrete provides several advantages, especially in terms of controlling the crack opening width and propagation after the cracking onset. However, distribution and orientation of the fibres toward the active crack plane are significantly important in order to maximize its benefits. Therefore, in this study, the effect of the fibre distribution and orientation on the post-cracking tensile behaviour of the steel fibre reinforced self-compacting concrete (SFRSCC) specimens is investigated. For this purpose, several cores were extracted from distinct locations of a panel and were subjected to indirect (splitting) and direct tensile tests. The local stress-crack opening relationship (σ-w) was obtained by modelling the splitting tensile test under the finite element framework and by performing an Inverse Analysis (IA) procedure. Afterwards the σ-w law obtained from IA is then compared with the one ascertained directly from the uniaxial tensile tests. Finally, the fibre distribution/orientation parameters were determined adopting an image analysis technique.

High performance fiber reinforced concrete for the shear reinforcement: experimental and numerical research

High performance fiber reinforced concrete (HPFRC) is developing rapidly to a modern structural material with unique rheological and mechanical characteristics. Despite applying several methodologies to achieve self15 compacting requirements, some doubts still remain regarding the most convenient strategy for developing a HPFRC. In the present study, an innovative mix design method is proposed for the development of high17 performance concrete reinforced with a relatively high dosage of steel fibers. The material properties of the developed concrete are assessed, and the concrete structural behavior is characterized under compressive, flexural and shear loading. This study better clarifies the significant contribution of fibers for shear resistance of concrete elements. This paper further discusses a FEM-based simulation, aiming to address the possibility of calibrating the constitutive model parameters related to fracture modes I and II.

The relationship between stem vessel parameters and the development of strata in the early stages of secondary forest succession in Amazonia

In order to compare the development of strata in the early stages of secondary forest succession with vessel parameters of the tree species, a forest inventory was carried out in 4-year (Q1: 48 m2), 11-year (Q2: 400 m2) and 20-year (Q3: 400 m2) forests and vessel parameters were investigated from stem cross sections of 18 species obtained in Q2. Thirty three species (21 families), 77 species (35 families), 39 species (20 families) were found in Ql, Q2, Q3, respectively. The percentage of dead individuals, dead stems and the percentage of individuals with multiple stems increased with time after clear cutting. Also, the total D2H of Q3 was 26.1 times that of Q1, and the development of strata started in Q2 and Q3. The image analysis of vessel size, area and number of vessels revealed that species which reach the forest canopy had a large D2H value, vessel diameter and area, while species which remain near the forest floor had smaller ones. Poecilanthe effusa (Huber) Ducke is an example of the latter case, with a large number of individuals and abundant sprouting of new stems from stumps, but with high mortality.

FISHji: new ImageJ macros for the quantification of fluorescence in epifluorescence images

Fluorescence in situ hybridization (FISH) is based on the use of fluorescent staining dyes, however, the signal intensity of the images obtained by microscopy is seldom quantified with accuracy by the researcher. The development of innovative digital image processing programs and tools has been trying to overcome this problem, however, the determination of fluorescent intensity in microscopy images still has issues due to the lack of precision in the results and the complexity of existing software. This work presents FISHji, a set of new ImageJ methods for automated quantification of fluorescence in images obtained by epifluorescence microscopy. To validate the methods, results obtained by FISHji were compared with results obtained by flow cytometry. The mean correlation between FISHji and flow cytometry was high and significant, showing that the imaging methods are able to accurately assess the signal intensity of fluorescence images. FISHji are available for non-commercial use at http://paginas.fe.up.pt/nazevedo/.