987 resultados para pre-image attack
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Research in Crowdfunding is an emerging priority within the field of Entrepreneurship. Hundreds of platforms provide nowadays multiple Crowdfunding schemes which are intended to make it easier for entrepreneurs and others to collect money from the crowd. However, only a few campaigns become successful as others don’t reach the pre-established funding goal. It is thus necessary to keep on understanding the dynamics of these platforms and the factors which justify success. The asymmetry of information has been shown to be a delicate issue as people perceive quality in different manners. As so, this research aims to understand which components of perceived quality mostly influence investments decisions. Mainly Entrepreneurship and Marketing theories were explored along the way. This is research follows a causal approach where nineteen hypotheses are tested. An experimental survey was conducted and data was collected from 127 people who were asked to evaluate one of the most important pieces of any Crowdfunding campaign – the pitch video – and consequently invest on the presented products.
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This case study deals with the reasons why the Portuguese Footwear Cluster evolved from a small industry focused on the Portuguese internal market into a high-tech industry capable of designing and producing some of the best and most expensive shoes in the world. It went from using the low labor costs of an under-developed economy to produce long series of shoes for pre-designated brands in Northern Europe to having the ability to produce some of the highest quality shoes in the world, in small orders, designed and delivered in record timing, while offering a service of excellence. In 1960, when Portugal became a founding member of EFTA, the footwear industry in Portugal was globally irrelevant, producing low quality shoes directed to the puny internal market and its African colonies. The new free trade zone with economies much more developed that itself, led to the transfer of the labor-intensive, low skilled manufacture from the UK and Scandinavian countries to Portugal. Mostly through joint ventures, the industry was able to mechanize itself so it could produce shoes in long series at low prices. It grew based on that model up until the 1990s, when the emergence of the Asian countries meant either a different strategy or extinction. Taking advantage of a clarified leadership of its trade association, it used the European funds made available to it during the 1990s, to modernize its factory floors, so it could become more nimble and flexible, expand its design capabilities and dramatically change its image abroad. The role of the trade association, APICCAPS, was instrumental throughout the process going well beyond what came to be expected of trade associations. It used its privileged position to provide understanding regarding the current situation and competitive landscape, alerting for changes ahead and at the same time providing a strategic vision on how to deal with the challenges. Moreover, it helped companies get the resources they needed by creating a research center in collaboration with a University, by creating a process that allowed companies to learn from each other via the show casing of projects sponsored by the association or by helping industrials traveling to locations where new customers could be found. The case study provides insight on how the trade association leadership, which has no formal authority over its members, was able to guide and motivate an industry through a consistent positive approach. That approach focused on the solutions, on the opportunities and on the success stories of companies in the cluster rather than on what was wrong or needed to be addressed. Based on this case, one could use the leadership role of the trade association to discuss and change leaders’ roles and styles in other sectors or even companies.
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Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.
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Dissertação de mestrado em Construção e Reabilitação Sustentável
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Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.
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Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.
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Relatório de estágio de mestrado em Educação Pré-Escolar
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Dissertação de mestrado integrado em Psicologia (área de especialização em Psicologia Clínica e da Saúde)
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An ion chromatography procedure, employing an IonPac AC15 concentrator column was used to investigate on line preconcentration for the simultaneous determination of inorganic anions and organic acids in river water. Twelve organic acids and nine inorganic anions were separated without any interference from other compounds and carry-over problems between samples. The injection loop was replaced by a Dionex AC15 concentrator column. The proposed procedure employed an auto-sampler that injected 1.5 ml of sample into a KOH mobile phase, generated by an Eluent Generator, at 1.5 mL min-1, which carried the sample to the chromatographic columns (one guard column, model AG-15, and one analytical column, model AS15, with 250 x 4mm i.d.). The gradient elution concentrations consisted of a 10.0 mmol l-1 KOH solution from 0 to 6.5 min, gradually increased to 45.0 mmol l-1 KOH at 21 min., and immediatelly returned and maintained at the initial concentrations until 24 min. of total run. The compounds were eluted and transported to an electro-conductivity detection cell that was attached to an electrochemical detector. The advantage of using concentrator column was the capability of performing routine simultaneous determinations for ions from 0.01 to 1.0 mg l-1 organic acids (acetate, propionic acid, formic acid, butyric acid, glycolic acid, pyruvate, tartaric acid, phthalic acid, methanesulfonic acid, valeric acid, maleic acid, oxalic acid, chlorate and citric acid) and 0.01 to 5.0 mg l-1 inorganic anions (fluoride, chloride, nitrite, nitrate, bromide, sulfate and phosphate), without extensive sample pretreatment and with an analysis time of only 24 minutes.
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Fibre reinforced thermoplastic pre impregnated materials produced continuously by diverse methods and processing conditions were used to produce composites using pultrusion. The processing windows used to produce these materials and composites profiles were optimized by using the Taguchi / DOE (Design of Experiments) methods. Composites were manufactured by pultrusion and compression moulding and subsequently submitted to mechanical testing and microscopy analysis. The obtained results were compared with the expected theoretical ones predicted from the Rule of Mixtures (ROM) and with those of similar engineering conventional available materials. The results obtained shown that produced composites have adequate properties for applications in common and structural engineering markets.
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Light and water are important factors that may limit the growth and development of higher plants. The aim of this study was to evaluate photosynthetic parameters and growth in seedlings of Bertholletia excelsa and Carapa guianensis in response to pre-acclimation to full sunlight and mild water stress. I used six independent pre-acclimation treatments (0, 90 (11h15-12h45), 180 (10h30-13h30), 360 (09h00-15h00), 540 (07h30-16h30) and 720 min (06h00-18h00)) varying the time of exposure to full sunlight (PFS) during 30 days, followed by whole-day outdoor exposure for 120 days. Before PFS, the plants were kept in a greenhouse at low light levels (0.8 mol m-2 day-1). The PFS of 0 min corresponded to plants constantly kept under greenhouse conditions. From the beginning to the end of the experiment, each PFS treatment was submitted to two water regimes: moderate water stress (MWS, pre-dawn leaf water potential (ΨL) of -500 to -700 kPa) and without water stress (WWS, ΨL of -300 kPa, soil kept at field capacity). Plants under MWS received only a fraction of the amount of water applied to the well-watered ones. At the end of the 120-day-period under outdoor conditions, I evaluated light saturated photosynthesis (Amax), stomatal conductance (g s), transpiration (E) and plant growth. Both Amax and g s were higher for all plants under the PFS treatment. Stem diameter growth rate and Amax were higher for C. guianensis subjected to MWS than in well-watered plants. The contrary was true for B. excelsa. The growth of seedlings was enhanced by exposure to full sunlight for 180 minutes in both species. However, plants of B. excelsa were sensitive to moderate water stress. The higher photosynthetic rates and faster growth of C. guianensis under full sun and moderate water stress make this species a promissory candidate to be tested in reforestation programs.
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Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.
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Identification of pre-participation risk factors for noncontact anterior cruciate ligament (ACL) injuries has been attracting a great deal of interest in the sports medicine and traumatology communities. Appropriate methods that enable predicting which patients could benefit from pre- ventive strategies are most welcome. This would enable athlete-specific training and conditioning or tailored equipment in order to develop appropriate strategies to reduce incidence of injury. In order to accomplish these goals, the ideal system should be able to assess both anatomic and functional features. Complementarily, the screening method must be cost-effective and suited for widespread application. Anatomic study protocol requiring only standard X rays could answer some of such demands. Dynamic MRI/CT evaluation and electronically assisted pivot-shift evaluation can be powerful tools providing complementary information. These upcoming insights, when validated and properly combined, envision changing pre-participation knee examination in the near future. Herein different methods (validated or under research) aiming to improve the capacity to identify persons/athletes with higher risk for ACL injury are overviewed.