956 resultados para matching
Resumo:
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.
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The focus of this Thesis was the study of the sensor domains of two heme-containing methyl-accepting chemotaxis proteins (MCP) from Geobacter sulfurreducens: GSU0582 and GSU0935. These domains contain one c-type heme, form swapped dimers with a PAS-like fold and are the first examples of a new class of heme sensors. NMR spectroscopy was used to assign the heme and polypeptide signals in both sensors, as a first step to probe conformational changes in the vicinity of the hemes. However, the presence of two conformations in solution impaired the confident assignment of the polypeptide signals. To understand how conformational changes and swapped dimerization mechanism can effectively modulate the function of the two sensor domains and their signal transduction process, the sensor domains folding and stability were studied by circular dichroism and UV-visible spectroscopy. The results showed differences in the thermodynamic stability of the sensors, with GSU0582 displaying higher structural stability. These studies also demonstrated that the heme moiety undergoes conformational changes matching those occurring at the global protein structure and that the content of intrinsically disordered segments within these proteins (25% for GSU0935; 13% for GSU0582) correlates with the stability differences observed. The thermodynamic and kinetic properties of the sensor domains were determined at different pH and ionic strength by visible spectroscopy and stopped-flow techniques. Despite the remarkably similar spectroscopic and structural features of the two sensor domains, the results showed that their properties are quite distinct. Sensor domain GSU0935 displayed more negative reduction potentials and smaller reduction rate constants, which were more affected by pH and ionic strength. The available structures were used to rationalize these differences. Overall, the results described in this Thesis indicate that the two G. sulfurreducens MCP sensor domains are designed to function in different working potential ranges, allowing this bacterium to trigger an adequate cellular response in distinct anoxic subsurface environments.
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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.
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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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Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).
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Brazil is an emerging country where community school is being promoted in order to respond to the still significant gap between the poor and the rich population. This paper attempts to analyze one community school. Although other social programs whose scopes are also to enhance education have been implemented, such as the "Bolsa Familia", the impact of community schools need attention as well. Indeed, community schools must be studied due to the relevant positive attributes they can provide. Moreover, by improving the quality of education, studies show an enhancement of a higher-skilled nation and a better qualified labour force for the future. To clearly demonstrate the impacts of these communities, the treatment effect will be measured by using a matching estimator.
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Objective: Quality of life was measured using the EQ-5D index for Portugal and a Self-Assessed Ranking of Health (SARH) to understand which patients suffer the most decrease in quality of life: diabetics or hypertensive. Method: Using the National Health Survey (NHS), two analyses were conducted on 5649 respondents. The EQ-5D index was calculated by matching questions in the NHS with its dimensions. The SARH was calculated based on a specific question in the NHS. Results: Differences between diseases do not occur using the EQ-5D index. Using the SARH, type 1 diabetics suffer the most while hypertensive suffers the least.
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A Work Project, presented as part of the requirements for the Award of a Double Degree in Economics from NOVA School of Business and Economics and Maastricht School of Business and Economics
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Are return migrants more productive than non-migrants? If so, is it a causal effect or simply self-selection? Existing literature has not reached a consensus on the role of return migration for origin countries. To answer these research questions, an empirical analysis was performed based on household data collected in Cape Verde. One of the most common identification problems in the migration literature is the presence of migrant self-selection. In order to disentangle potential selection bias, we use instrumental variable estimation using variation provided by unemployment rates in migrant destination countries, which is compared with OLS and Nearest Neighbor Matching (NNM) methods. The results using the instrumental variable approach provide evidence of labour income gains due to return migration, while OLS underestimates the coefficient of interest. This bias points towards negative self-selection of return migrants on unobserved characteristics, although the different estimates cannot be distinguished statistically. Interestingly, migration duration and occupational changes after migration do not seem to influence post-migration income. There is weak evidence that return migrants from the United States have higher income gains caused by migration than the ones who returned from Portugal.
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Hospital-acquired infections (HAIs) delay healing, prolong Hospital stay, and increase both Hospital costs and risk of death. This study aims to estimate the extra length of stay and mortality rate attributable to each of the following HAIs: wound infection (WI); bloodstream infection (BSI); urinary infections (UI); and Hospital-acquired pneumonia (HAP). The study population consisted of patients discharged in CHLC in 2014. Data was collected to identify demographic information, surgical operations, development of HAIs and its outputs. The study used regressions and a matched strategy to compare cases (infected) and controls (uninfected). The matching criteria were: age, sex, week and type of admission, number of admissions, major diagnostic category and type of discharge. When compared to matched controls, cases with HAI had a higher mortality rate and greater length of stay. WI related to hip or knee surgery, increased mortality rate by 27.27% and the length of stay by 74.97 days. WI due to colorectal surgery caused an extra mortality rate of 10.69% and an excess length of stay of 20.23 days. BSI increased Hospital stay by 28.80 days and mortality rate by 32.27%. UI caused an average additional length of stay of 19.66 days and risk of death of 12.85%. HAP resulted in an extra Hospital stay of 25.06 days and mortality rate of 24.71%. This study confirms the results of the previous literature that patients experiencing HAIs incur in an excess of mortality rates and Hospital stay, and, overall, it presents worse results comparing with other countries.
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PURPOSE: Enteral alimentation is the preferred modality of support in critical patients who have acceptable digestive function and are unable to eat orally, but the advantages of continuous versus intermittent administration are surrounded by controversy. With the purpose of identifying the benefits and complications of each technique, a prospective controlled study with matched subjects was conducted. PATIENTS AND METHODS: Twenty-eight consecutive candidates for enteral feeding were divided into 2 groups (n = 14 each) that were matched for diagnosis and APACHE II score. A commercial immune-stimulating polymeric diet was administered via nasogastric tube by electronic pump in the proportion of 25 kcal/kg/day, either as a 1-hour bolus every 3 hours (Group I), or continuously for 24 hours (Group II), over a 3-day period. Anthropometrics, biochemical measurements, recording of administered drugs and other therapies, thorax X-ray, measurement of abdominal circumference, monitoring of gastric residue, and clinical and nutritional assessments were performed at least once daily. The principal measured outcomes of this protocol were frequency of abdominal distention and pulmonary aspiration, and efficacy in supplying the desired amount of nutrients. RESULTS: Nearly half of the total population (46.4%) exhibited high gastric residues on at least 1 occasion, but only 1 confirmed episode of pulmonary aspiration occurred (3.6%). Both groups displayed a moderate number of complications, without differences. Food input during the first day was greater in Group II (approximately 20% difference), but by the third day, both groups displayed similarly small deficits in total furnished volume of about 10%, when compared with the prescribed diet. CONCLUSIONS: Both administration modalities permitted practical and effective administration of the diet with frequent registered abnormalities but few clinically significant problems. The two groups were similar in this regard, without statistical differences, probably because of meticulous technique, careful monitoring, strict patient matching, and conservative amounts of diet employed in both situations. Further studies with additional populations, diagnostic groups, and dietetic prescriptions should be performed in order to elucidate the differences between these commonly used feeding modalities.
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This dissertation consists of three essays on the labour market impact of firing and training costs. The modelling framework resorts to the search and matching literature. The first chapter introduces firing costs, both liner and non-linear, in a new Keynesian model, analysing business cycle effects for different wage rigidity degrees. The second chapter adds training costs in a model of a segmented labour market, accessing the interaction between these two features and the skill composition of the labour force. Finally, the third chapter analyses empirically some of the issues raised in the second chapter.
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Immersive environments (IE) are being increasingly used in order to perform psychophysical experiments. The versatility in terms of stimuli presentation and control and the less time-consuming procedures are their greatest strengths. However, to ensure that IE results can be generalized to real world scenarios we must first provide evidence that performance in IE is quantitatively indistinguishable from performance in real-world. Our goal was to perceptually validate distance perception for CAVE-like IEs. Participants performed a Frontal Matching Distance Task (Durgin & Li, 2011) in three different conditions: real-world scenario (RWS); photorealistic IE (IEPH) and non-photorealistic IE (IENPH). Underestimation of distance was found across all the conditions, with a significant difference between the three conditions (Wilks’ Lambda = .38, F(2,134)= 110.8, p<.01, significant pairwise differences with p<.01). We found a mean error of 2.3 meters for the RWS, 5 meters for the IEPH, and of 6 meters for the IENPH in a pooled data set of 5 participants. Results indicate that while having a photorealistic IE with perspective and stereoscopic depth cues might not be enough to elicit a real-world performance in distance judgment tasks, nevertheless this type of environment minimizes the discrepancy between simulation and real-world when compared with non-photorealistic IEs.
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In spite of all innovations in stent design, commonly used metallic stents present several problems such as corrosion, infection and restenosis, leading to health complications or even death of patients. In this context, the present paper reports a systematic investigation on designing and development of 100% fiber based stents, which can eliminate or minimize the problems with existing metallic stents. For this purpose, braided stents were produced by varying different materials, structural and process parameters such as mono-filament type and diameter, braiding angle and mandrel diameter. The influence of these design parameters on mechanical behavior as well as stent's porosity was thoroughly investigated, and suitable parameters were selected for developing a stentwith mechanical characteristics and porosity matching with the commercial stents. According to the experimental results, the best performance was achieved with a polyester stent designed with 0.27 mm monofilament diameter, braiding angle of 35° and mandrel diameter of 6 mm, providing similar properties to commercial Nitinol stents.
Resumo:
The currently available clinical imaging methods do not provide highly detailed information about location and severity of axonal injury or the expected recovery time of patients with traumatic brain injury [1]. High-Definition Fiber Tractography (HDFT) is a novel imaging modality that allows visualizing and quantifying, directly, the degree of axons damage, predicting functional deficits due to traumatic axonal injury and loss of cortical projections. This imaging modality is based on diffusion technology [2]. The inexistence of a phantom able to mimic properly the human brain hinders the possibility of testing, calibrating and validating these medical imaging techniques. Most research done in this area fails in key points, such as the size limit reproduced of the brain fibers and the quick and easy reproducibility of phantoms [3]. For that reason, it is necessary to develop similar structures matching the micron scale of axon tubes. Flexible textiles can play an important role since they allow producing controlled packing densities and crossing structures that match closely the human crossing patterns of the brain. To build a brain phantom, several parameters must be taken into account in what concerns to the materials selection, like hydrophobicity, density and fiber diameter, since these factors influence directly the values of fractional anisotropy. Fiber cross-section shape is other important parameter. Earlier studies showed that synthetic fibrous materials are a good choice for building a brain phantom [4]. The present work is integrated in a broader project that aims to develop a brain phantom made by fibrous materials to validate and calibrate HDFT. Due to the similarity between thousands of hollow multifilaments in a fibrous arrangement, like a yarn, and the axons, low twist polypropylene multifilament yarns were selected for this development. In this sense, extruded hollow filaments were analysed in scanning electron microscope to characterize their main dimensions and shape. In order to approximate the dimensional scale to human axons, five types of polypropylene yarns with different linear density (denier) were used, aiming to understand the effect of linear density on the filament inner and outer areas. Moreover, in order to achieve the required dimensions, the polypropylene filaments cross-section was diminished in a drawing stage of a filament extrusion line. Subsequently, tensile tests were performed to characterize the mechanical behaviour of hollow filaments and to evaluate the differences between stretched and non-stretched filaments. In general, an increase of the linear density causes the increase in the size of the filament cross section. With the increase of structure orientation of filaments, induced by stretching, breaking tenacity increases and elongation at break decreases. The production of hollow fibers, with the required characteristics, is one of the key steps to create a brain phantom that properly mimics the human brain that may be used for the validation and calibration of HDFT, an imaging approach that is expected to contribute significantly to the areas of brain related research.