992 resultados para Applying technology


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Augmented Reality (AR) is currently gaining popularity in multiple different fields. However, the technology for AR still requires development in both hardware and software when considering industrial use. In order to create immersive AR applications, more accurate pose estimation techniques to define virtual camera location are required. The algorithms for pose estimation often require a lot of processing power, which makes robust pose estimation a difficult task when using mobile devices or designated AR tools. The difficulties are even larger in outdoor scenarios where the environment can vary a lot and is often unprepared for AR. This thesis aims to research different possibilities for creating AR applications for outdoor environments. Both hardware and software solutions are considered, but the focus is more on software. The majority of the thesis focuses on different visual pose estimation and tracking techniques for natural features. During the thesis, multiple different solutions were tested for outdoor AR. One commercial AR SDK was tested, and three different custom software solutions were developed for an Android tablet. The custom software solutions were an algorithm for combining data from magnetometer and a gyroscope, a natural feature tracker and a tracker based on panorama images. The tracker based on panorama images was implemented based on an existing scientific publication, and the presented tracker was further developed by integrating it to Unity 3D and adding a possibility for augmenting content. This thesis concludes that AR is very close to becoming a usable tool for professional use. The commercial solutions currently available are not yet ready for creating tools for professional use, but especially for different visualization tasks some custom solutions are capable of achieving a required robustness. The panorama tracker implemented in this thesis seems like a promising tool for robust pose estimation in unprepared outdoor environments.

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Several studies have shown that UV-C irradiation promotes the bioactive compounds and antioxidants of fresh fruits and vegetables. The aim of this study was to apply UV irradiation in lemon pomace dried powder for enhancing its phenolic content and antioxidant properties, thus more bioactive compounds should be available for extraction and utilization. Lemon pomace dried powder was placed above the UV lamp and treated with dosages of 4, 19, 80 and 185 kJ m-2, while untreated powder was used as a control. UV-C irradiation significantly affected the total phenolic content, total flavonoid content, proanthocyanidins and antioxidant capacity measured by CUPRAC and FRAP of the lemon pomace dried powder, while it did not affect the vitamin C content. UV-C irradiation of 19 kJ m-2 resulted in 19% higher total phenolic content than the control, while UV-C irradiation of 180 kJ m-2 resulted in 28% higher total flavonoid content than the control. The antioxidant capacity was reduced when UV-C irradiation more than 4 kJ m-2 was applied. The results of this study indicate that UV-C treatment has the potential to increase the extraction of bioactive compounds of lemon dried pomace at relatively high dosages.

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Part 3: Product-Service Systems

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Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

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To assess quality of care of women with severe maternal morbidity and to identify associated factors. This is a national multicenter cross-sectional study performing surveillance for severe maternal morbidity, using the World Health Organization criteria. The expected number of maternal deaths was calculated with the maternal severity index (MSI) based on the severity of complication, and the standardized mortality ratio (SMR) for each center was estimated. Analyses on the adequacy of care were performed. 17 hospitals were classified as providing adequate and 10 as nonadequate care. Besides almost twofold increase in maternal mortality ratio, the main factors associated with nonadequate performance were geographic difficulty in accessing health services (P < 0.001), delays related to quality of medical care (P = 0.012), absence of blood derivatives (P = 0.013), difficulties of communication between health services (P = 0.004), and any delay during the whole process (P = 0.039). This is an example of how evaluation of the performance of health services is possible, using a benchmarking tool specific to Obstetrics. In this study the MSI was a useful tool for identifying differences in maternal mortality ratios and factors associated with nonadequate performance of care.

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Standardized olfactory tests are now available to quantitatively assess disorders of olfaction. A Brazilian-Portuguese version of the University of Pennsylvania Smell Identification Test (UPSIT) is currently being developed specifically for the Brazilian population. The most recent Brazilian-Portuguese version of the UPSIT (UPSIT-Br2) was administered to 88 Brazilian subjects who had no history of neurological or otorhinolaryngological disease. UPSIT-Br2 scores decreased with age, were lower in men than in women, and were lower in subjects with lower income. The degree to which the poorer performance of subjects with lower socio-economic status reflects lack of familiarity with test items is not known. Although this version of the UPSIT provides a sensitive and useful test of smell function for the Brazilian population, a revision of some test items is needed to achieve comparable norms to those found using the North American UPSIT in the United States.

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Tool wear is a very important subject affecting the economics of machining, especially in tapping, since it is one of the last operations to be performed within most operation sequences. In the present study, some aspects of tapping such as the mechanisms and types of wear were investigated in taps working at conventional and high-speed cutting (HSC). Additionally, different types of coatings and cooling /lubrication conditions were used. The tapping operation (M8 x 1.25) was performed in through holes with two cutting speeds (30 and 60 m/min) in grey cast iron GG25. Lubrication conditions tested were dry and with minimal quantity of lubricant. Tap materials were manufactured by powder metallurgy and coated with (TiAl)N and with TiCN. A go-non-go gauge criterion was used to assess tool life. The wear and surface aspects of the tools and workpiece were evaluated by scanning electron microscopy and energy dissipation spectroscopy. Torque signals were also measured during the tests. The main wear mechanism observed was adhesion, although some abrasion and diffusion may also have occurred, and the main type of wear was flank wear. The adhesion of workpiece material on the tool was the main and decisive factor ending tool life. Tool coatings proved to be an efficient way to minimize adhesion. Torque signals followed the same pattern as the flank wear and no significant change was observed when the cutting speed was increased.

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The relationship between companies is an important issue in the management of supply chains. Several aspects relating to the flow and exchange of information along the chain are considered as having a decisive influence on the success of this relationship. The main objective of this work was to structured and test models that link aspects of this nature with performance and the purchaser-supplier relationship in the supply chain. Aspects relevant to communication and the use do IT in relationships between companies were investigated. The importance of performance in this relationship was also investigated. The research were based on empirical data obtained by means of structural equation modeling. The results show that some aspects contribute in a significant way to the success of this relationship while others that, a priori, are considered important make no contribution.

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This is a study of a monochromatic planar perturbation impinging upon a canonical acoustic hole. We show that acoustic hole scattering shares key features with black hole scattering. The interference of wave fronts passing in opposite senses around the hole creates regular oscillations in the scattered intensity. We examine this effect by applying a partial wave method to compute the differential scattering cross section for a range of incident wavelengths. We demonstrate the existence of a scattering peak in the backward direction, known as the glory. We show that the glory created by the canonical acoustic hole is approximately 170 times less intense than the glory created by the Schwarzschild black hole, for equivalent horizon-to-wavelength ratios. We hope that direct experimental observations of such effects may be possible in the near future.

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Studies concerning the accumulating capacity of native epiphytic bromeliads are of utmost relevance, due to the continuous incorporation of chemical elements provided by these organisms in the ecosystems. Bromeliad species from diverse So Paulo State conservation units, Brazil, were sampled for young, mature and old leaves using a sustainable sampling method. By applying INAA, the accumulation of ten chemical elements, i.e. Br, Ca, Co, Fe, K, Na, Rb, Sc, Sr and Zn, was investigated in different leaf vegetative stages. The bromeliads showed divergent chemical element distribution patterns, demonstrating a real complexity in the accumulation and translocation mechanisms utilized by these plants.

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For environmental quality assessment, INAA has been applied for determining chemical elements in small (200 mg) and large (200 g) samples of leaves from 200 trees. By applying the Ingamells` constant, the expected percent standard deviation was estimated in 0.9-2.2% for 200 mg samples. Otherwise, for composite samples (200 g), expected standard deviation varied from 0.5 to 10% in spite of analytical uncertainties ranging from 2 to 30%. Results thereby suggested the expression of the degree of representativeness as a source of uncertainty, contributing for increasing of the reliability of environmental studies mainly in the case of composite samples.

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In 2003-2004, several food items were purchased from large commercial outlets in Coimbra, Portugal. Such items included meats (chicken, pork, beef), eggs, rice, beans and vegetables (tomato, carrot, potato, cabbage, broccoli, lettuce). Elemental analysis was carried out through INAA at the Technological and Nuclear Institute (ITN, Portugal), the Nuclear Energy Centre for Agriculture (CENA, Brazil), and the Nuclear Engineering Teaching Lab of the University of Texas at Austin (NETL, USA). At the latter two, INAA was also associated to Compton suppression. It can be concluded that by applying Compton suppression (1) the detection limits for arsenic, copper and potassium improved; (2) the counting-statistics error for molybdenum diminished; and (3) the long-lived zinc had its 1115-keV photopeak better defined. In general, the improvement sought by introducing Compton suppression in foodstuff analysis was not significant. Lettuce, cabbage and chicken (liver, stomach, heart) are the richest diets in terms of human nutrients.

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A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

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Many authors point out that the front-end of new product development (NPD) is a critical success factor in the NPD process and that numerous companies face difficulties in carrying it out appropriately. Therefore, it is important to develop new theories and proposals that support the effective implementation of this earliest phase of NPD. This paper presents a new method to support the development of front-end activities based on integrating technology roadmapping (TRM) and project portfolio management (PPM). This new method, called the ITP Method, was implemented at a small Brazilian high-tech company in the nanotechnology industry to explore the integration proposal. The case study demonstrated that the ITP Method provides a systematic procedure for the fuzzy front-end and integrates innovation perspectives into a single roadmap, which allows for a better alignment of business efforts and communication of product innovation goals. Furthermore, the results indicated that the method may also improve quality, functional integration and strategy alignment. (C) 2010 Elsevier Inc. All rights reserved.

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This article presents an extensive investigation carried out in two technology-based companies of the So Carlos technological pole in Brazil. Based on this multiple case study and literature review, a method, entitled hereafter IVPM2, applying agile project management (APM) principles was developed. After the method implementation, a qualitative evaluation was carried out by a document analysis and questionnaire application. This article shows that the application of this method at the companies under investigation evidenced the benefits of using simple, iterative, visual, and agile techniques to plan and control innovative product projects combined with traditional project management best practices, such as standardization.