65 resultados para Processing image


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

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This paper investigates the implications of individuals’ mistaken beliefs of their abilities on incentives in organizations using the principal-agent model of moral hazard. The paper shows that if effort is observable, then an agent’s mistaken beliefs about own ability are always favorable to the principal. However, if effort is unobservable, then an agent’s mistaken beliefs about own ability can be either favorable or unfavorable to the principal. The paper provides conditions under which an agent’s over estimation about own ability is favorable to the principal when effort is unobservable. Finally, the paper shows that workers’ mistaken beliefs about their coworkers’ abilities make interdependent incentive schemes more attractive to firms than individualistic incentive schemes.

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This paper analyzes the implications of worker overestimation of productivity for firms in which incentives take the form of tournaments. Each worker overestimates his productivity but is aware of the bias in his opponent’s self-assessment. The manager of the firm, on the other hand, correctly assesses workers’ productivities and self-beliefs when setting tournament prizes. The paper shows that, under a variety of circumstances, firms make higher profits when workers have positive self-image than if workers do not. By contrast, workers’ welfare declines due to their own misguided choices.

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Dissertação para obtenção do Grau de Doutora em Engenharia Química e Bioquímica

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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

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The EM3E Master is an Education Programme supported by the European Commission, the European Membrane Society (EMS), the European Membrane House (EMH), and a large international network of industrial companies, research centers and universities

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Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

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Breast cancer is the most common type of cancer among women all over the world. An important issue that is not commonly addressed in breast cancer imaging literature is the importance of imaging the underarm region—where up to 80% of breast cancer cells can metastasise to. The first axillary lymph nodes to receive drainage from the primary tumour in the breast are called Sentinel Node. If cancer cells are found in the Sentinel Node, there is an increased risk of metastatic breast cancer which makes this evaluation crucial to decide what follow-up exams and therapy to follow. However, non-invasive detection of cancer cells in the lymph nodes is often inconclusive, leading to the surgical removal of too many nodes which causes adverse side-effects for patients. Microwave Imaging is one of the most promising non-invasive imaging modalities for breast cancer early screening and monitoring. This novel study tests the feasibility of imaging the axilla region by means of the simulation of an Ultra-Wideband Microwave Imaging system. Simulations of such system are completed in several 2D underarm models that mimic the axilla. Initial imaging results are obtained by means of processing the simulated backscattered signals by eliminating artefacts caused by the skin and beamforming the processed signals in order to time-align all the signals recorded at each antenna. In this dissertation several image formation algorithms are implemented and compared by visual inspection of the resulting images and through a range of performance metrics, such as Signal-to-Clutter Ratio and FullWidth Half Maximum calculations. The results in this study showed that Microwave Imaging is a promising technique that might allow to identify the presence and location of metastasised cancer cells in axillary lymph nodes, enabling the non-invasive evaluation of breast cancer staging.

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The present work is devoted to study the pre-treatment of lignocellulosic biomass, especially wheat straw, by the application of the acidic ionic liquid (IL) such as 1-butyl-3-methylimidazolium hydrogen sulphate. The ability of this IL to hydrolysis and conversion of biomass was scrutinised. The pre-treatment with hydrogen sulphate-based IL allowed to obtain a liquor rich in hemicellulosic sugars, furans and organic acids, and a solid fraction mainly constituted by cellulose and lignin. Quantitative and qualitative analyses of the produced liquors were made by capillary electrophoresis and high-performance liquid chromatography. Pre-treatment conditions were set to produce xylose or furfural. Specific range of temperatures from 70 to 175 °C and residence times from 20.0 to 163.3 min were studied by fixing parameters such as biomass/IL ratio (10 % (w/w)) and water content (1.25 % (w/w)) in the pre-treatment process. Statistical modelling was applied to maximise the xylose and furfural concentrations. For the purpose of reaction condition comparison the severity factor for studied ionic liquid was proposed and applied in this work. Optimum conditions for xylose production were identified to be at 125 °C and 82.1 min, at which 16.7 % (w/w) xylose yield was attained. Furfural was preferably formed at higher pre-treatment temperatures and longer reaction time (161 °C and 104.5 min) reaching 30.7 % (w/w) maximum yield. The influence of water content on the optimum xylose formation was also studied. Pre-treatments with 5 and 10 % (w/w) water content were performed and an increase of 100 % and 140 % of xylose yield was observed, respectively, while the conversion into furfural maintained unchanged.

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Sign language is the form of communication used by Deaf people, which, in most cases have been learned since childhood. The problem arises when a non-Deaf tries to contact with a Deaf. For example, when non-Deaf parents try to communicate with their Deaf child. In most cases, this situation tends to happen when the parents did not have time to properly learn sign language. This dissertation proposes the teaching of sign language through the usage of serious games. Currently, similar solutions to this proposal do exist, however, those solutions are scarce and limited. For this reason, the proposed solution is composed of a natural user interface that is intended to create a new concept on this field. The validation of this work, consisted on the implementation of a serious game prototype, which can be used as a source for learning (Portuguese) sign language. On this validation, it was first implemented a module responsible for recognizing sign language. This first stage, allowed the increase of interaction and the construction of an algorithm capable of accurately recognizing sign language. On a second stage of the validation, the proposal was studied so that the pros and cons can be determined and considered on future works.

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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.

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Nowadays, authentication studies for paintings require a multidisciplinary approach, based on the contribution of visual features analysis but also on characterizations of materials and techniques. Moreover, it is important that the assessment of the authorship of a painting is supported by technical studies of a selected number of original artworks that cover the entire career of an artist. This dissertation is concerned about the work of modernist painter Amadeo de Souza-Cardoso. It is divided in three parts. In the first part, we propose a tool based on image processing that combines information obtained by brushstroke and materials analysis. The resulting tool provides qualitative and quantitative evaluation of the authorship of the paintings; the quantitative element is particularly relevant, as it could be crucial in solving authorship controversies, such as judicial disputes. The brushstroke analysis was performed by combining two algorithms for feature detection, namely Gabor filter and Scale Invariant Feature Transform. Thanks to this combination (and to the use of the Bag-of-Features model), the proposed method shows an accuracy higher than 90% in distinguishing between images of Amadeo’s paintings and images of artworks by other contemporary artists. For the molecular analysis, we implemented a semi-automatic system that uses hyperspectral imaging and elemental analysis. The system provides as output an image that depicts the mapping of the pigments present, together with the areas made using materials not coherent with Amadeo’s palette, if any. This visual output is a simple and effective way of assessing the results of the system. The tool proposed based on the combination of brushstroke and molecular information was tested in twelve paintings obtaining promising results. The second part of the thesis presents a systematic study of four selected paintings made by Amadeo in 1917. Although untitled, three of these paintings are commonly known as BRUT, Entrada and Coty; they are considered as his most successful and genuine works. The materials and techniques of these artworks have never been studied before. The paintings were studied with a multi-analytical approach using micro-Energy Dispersive X-ray Fluorescence spectroscopy, micro-Infrared and Raman Spectroscopy, micro-Spectrofluorimetry and Scanning Electron Microscopy. The characterization of Amadeo’s materials and techniques used on his last paintings, as well as the investigation of some of the conservation problems that affect these paintings, is essential to enrich the knowledge on this artist. Moreover, the study of the materials in the four paintings reveals commonalities between the paintings BRUT and Entrada. This observation is supported also by the analysis of the elements present in a photograph of a collage (conserved at the Art Library of the Calouste Gulbenkian Foundation), the only remaining evidence of a supposed maquete of these paintings. The final part of the thesis describes the application of the image processing tools developed in the first part of the thesis on a set of case studies; this experience demonstrates the potential of the tool to support painting analysis and authentication studies. The brushstroke analysis was used as additional analysis on the evaluation process of four paintings attributed to Amadeo, and the system based on hyperspectral analysis was applied on the painting dated 1917. The case studies therefore serve as a bridge between the first two parts of the dissertation.

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Viral vectors are playing an increasingly important role in the vaccine and gene therapy elds. The broad spectrum of potential applications, together with expanding medical markets, drives the e orts to improve the production processes for viral vaccines and viral vectors. Developing countries, in particular, are becoming the main vaccine market. It is thus critical to decrease the cost per dose, which is only achievable by improving the production process. In particular advances in the upstream processing have substantially increased bioreactor yields, shifting the bioprocess bottlenecks towards the downstream processing. The work presented in this thesis aimed to develop new processes for adenoviruses puri cation. The use of state-of-the-art technology combined with innovative continuous processes contributed to build robust and cost-e ective strategies for puri cation of complex biopharmaceuticals.(...)

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Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.

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We are constantly immersed in stimuli. Upon reaching our senses, stimuli are processed within various brain systems along various pathways into the brain, and eventually turned into a percept. However, there are percepts that do not result from responses to external source stimuli. A particular case of this situation is the auditory percept known as tinnitus. Tinnitus can be seen as a task-irrelevant auditory percept, commonly reported to interfere with normal daily tasks. This is known from reports made by tinnitus sufferers that refer to their phantom percept as distracting, and that it diverts their focus from the task-relevant stimuli.(...)