928 resultados para Precise Positioning


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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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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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Dissertation presented to obtain the Ph.D degree in Biochemistry, Structural Biochemistry

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A thesis submitted for the Degree of Master in Medical microbiology

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We report the findings of abdominal ultrasound and magnetic resonance imaging observed in a patient with advanced schistosomiasis mansoni. A 25-year-old man with hepatosplenic schistosomiasis and variceal bleeding confirmed by upper endoscopy was submitted to abdominal ultrasound and magnetic resonance imaging. During surgery for portal hypertension, a liver biopsy was taken and the diagnosis of Symmers' fibrosis was confirmed. magnetic resonance imaging scans gave more precise information about the gallbladder, periportal thickening and abdominal venous system than did the ultrasound.

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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.

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(Poly)phenols are the most widely distributed secondary metabolites, in plants, and, therefore, are regular constituents of human food products. The regular ingestion of (poly)phenol-containing foods has been associated with a reduced risk of acquiring chronic diseases and many studies are currently trying to corroborate this theory. However, the precise contribution of (poly)phenols to disease prevention is still unknown.(...)

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This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

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Cell division is a highly dynamic process where sister chromatids remain associated with each other from the moment of DNA replication until the later stages of mitosis, giving rise to two daughter cells with equal genomes. The “molecular glue” that links sister DNA molecules is called cohesin, a tripartite ring-like protein complex composed of two Structural Maintenance of Chromosome proteins (Smc1 and Smc3) bridged by a kleisin subunit Rad21/Scc1, that together prevent precocious sister chromatid separation. Accumulating evidence has suggested that cohesion decay may be the cause of segregation errors that underlie certain human pathologies. However it remains to be determined how much cohesin loss abolishes functional sister chromatid cohesion. To answer these questions, we have developed different experimental conditions aiming to titrate the levels of cohesin on mitotic chromosomes in a precise manner. Using these tools, we will determine the minimal amount of cohesin needed to confer functional cohesion. The approaches described here take advantage of a system in Drosophila melanogaster where the Tobacco Etch Virus (TEV) protease can cleave the Rad21 subunit of cohesin leading to precocious sister chromatid separation. Firstly, we tried to express different levels of TEV protease to obtain partial loss of cohesion. However, this approach has failed to produce systematic different levels of sister chromatid separation. Most of the work was therefore focused on a second strategy, for which we established strains with different levels of cohesin sensitive/cohesin resistant to TEV protease. Strains containing different amounts of functional cohesin (TEV resistant) were tested by in vitro cleavage and by in vivo injections in embryos for their ability to promote sister chromatid cohesion. Our results reveal that removal of half of the cohesin complexes does not impair chromosome segregation, implying that chromosome cohesion is less sensitive to cohesin amounts than previously anticipated.

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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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The “CMS Safety Closing Sensors System” (SCSS, or CSS for brevity) is a remote monitoring system design to control safety clearance and tight mechanical movements of parts of the CMS detector, especially during CMS assembly phases. We present the different systems that makes SCSS: its sensor technologies, the readout system, the data acquisition and control software. We also report on calibration and installation details, which determine the resolution and limits of the system. We present as well our experience from the operation of the system and the analysis of the data collected since 2008. Special emphasis is given to study positioning reproducibility during detector assembly and understanding how the magnetic fields influence the detector structure.

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Currently, China has the biggest automobile industry in the world. China’s economic situation helped the automobile market, as the internal demand of passenger cars increased substantially in the last years. Chinese automobile industry’s astonishing expansion over the past years has attracted many foreign automobile groups. SEAT decided to enter the Chinese market, following its expansion strategy to enter new markets. The purpose of this study is to analyse and understand the strategic entry of SEAT in the Chinese market, hence the choice of an explanatory case study (Yin, 2003). This study extends this analysis by examining the chines automobile market, more specifically the demand, the market segmentation and the intensity of competition, reviewing the SEAT company history, their competitive positioning and resources. I conclude that, although the Chinese market has growing potential, SEAT has failed to achieve its initial objective. The company has not been able to create a brand awareness in the Chinese market, unlike other foreign brands that have managed to accomplish that. This occurred, mostly, because of the high prices in comparison to its competitors due to additional import cost, such as import duties, transportation and distribution.

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This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.

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This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.