869 resultados para text to scene conversion


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As one of the most popular deep learning models, convolution neural network (CNN) has achieved huge success in image information extraction. Traditionally CNN is trained by supervised learning method with labeled data and used as a classifier by adding a classification layer in the end. Its capability of extracting image features is largely limited due to the difficulty of setting up a large training dataset. In this paper, we propose a new unsupervised learning CNN model, which uses a so-called convolutional sparse auto-encoder (CSAE) algorithm pre-Train the CNN. Instead of using labeled natural images for CNN training, the CSAE algorithm can be used to train the CNN with unlabeled artificial images, which enables easy expansion of training data and unsupervised learning. The CSAE algorithm is especially designed for extracting complex features from specific objects such as Chinese characters. After the features of articficial images are extracted by the CSAE algorithm, the learned parameters are used to initialize the first CNN convolutional layer, and then the CNN model is fine-Trained by scene image patches with a linear classifier. The new CNN model is applied to Chinese scene text detection and is evaluated with a multilingual image dataset, which labels Chinese, English and numerals texts separately. More than 10% detection precision gain is observed over two CNN models.

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Franchising is an important form of organizational control. Possible benefits of franchising include its ability to reduce agency costs that increase with costly monitoring, and provide incentives for the use of local information by onsite managers. However, these benefits may come at a cost, as franchisees may reduce quality by choosing to free ride. While many studies have investigated the reasons for franchising, few studies have documented the impacts of franchising on unit level operating performance. Using time-series data from a number of lodging properties that were converted to franchisee control from company control, this study documents the performance impacts of franchising. The analysis reveals that conversion results in a modest decline in financial performance and an immediate sharp decline in quality.

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The goal of the thesis "Conversion of a Micro, Glow-Ignition, Two-Stroke Engine from Nitromethane-Methanol Blend Fuel to Military Jet Propellant (JP-8)" was to demonstrate the ability to operate a small engine on JP-8 and was completed in two phases. The first phase included choosing, developing a test stand for, and baseline testing a nitromethane-methanol-fueled engine. The chosen engine was an 11.5 cc, glow-ignition, two-stroke engine designed for remote-controlled helicopters. A micro engine test stand was developed to load and motor the engine. Instrumentation specific to the low flow rates and high speeds of the micro engine was developed and used to document engine behavior. The second phase included converting the engine to operate on JP-8, completing JP-8-fueled steady-state testing, and comparing the performance of the JP-8-fueled engine to the nitromethane-methanol-fueled engine. The conversion was accomplished through a novel crankcase heating method; by heating the crankcase for an extended period of time, a flammable fuel-air mixture was generated in the crankcase scavenged engine, which greatly improved starting times. To aid in starting and steady-state operation, yttrium-zirconia impregnated resin (i.e. ceramic coating) was applied to the combustion surfaces. This also improved the starting times of the JP-8-fueled engine and ultimately allowed for a 34-second starting time. Finally, the steady-state data from both the nitromethane-methanol and JP-8-fueled micro engine were compared. The JP-8-fueled engine showed signs of increased engine friction while having higher indicated fuel conversion efficiency and a higher overall system efficiency. The minimal ability of JP-8 to cool the engine via evaporative effects, however, created the necessity of increased cooling air flow. The conclusion reached was that JP-8-fueled micro engines could be viable in application, but not without additional research being conducted on combustion phenomenon and cooling requirements.

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The purpose of this thesis was to examine the choice patterns that lead to conversion from Catholicism to Protestantism and the role of Vodou after conversion. This study highlights disappointment with the church as the leading cause of conversion in Haiti. Other causes significant to the study were examined. In illness and healing lie the controversies of religious conversion in Haiti. The only way to cure Satanic Illness is by resorting to magic. However, conversion to Protestantism means rejection of Vodou and all of its practice. A secondary purpose is to determine the role of Vodou after conversion. A total of 100 participants between the ages of 18 to 44 were included in this study. Seven percent (7%) converted for economic reasons, 43% selected disappointment with the church, 17% community/environment encounter, 13% sickness/near death experience, 2% economic and disappointment, 7% community/environment encounter and disappointment with the church, 9% disappointment sickness and near death experience, 1% economic and sickness near death experience, 1% economic and community/environment encounter. Findings suggest that Vodou is deeply rooted in Haitian identity, though all Haitians may not practice Vodou; but there are characteristics in the Haitian society that suggest that Haitians are Vodouisant. For the conversion process to be successful in Haiti it has to deeply acknowledged Vodou, the religion practiced by the masses in Haiti.

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Extended spectrum β-lactamases or ESBLs, which are derived from non-ESBL precursors by point mutation of β-lactamase genes (bla), are spreading rapidly all over the world and have caused considerable problems in the treatment of infections caused by bacteria which harbour them. The mechanism of this resistance is not fully understood and a better understanding of these mechanisms might significantly impact on choosing proper diagnostic and treatment strategies. Previous work on SHV β-lactamase gene, blaSHV, has shown that only Klebsiella pneumoniae strains which contain plasmid-borne blaSHV are able to mutate to phenotypically ESBL-positive strains and there was also evidence of an increase in blaSHV copy number. Therefore, it was hypothesised that although specific point mutation is essential for acquisition of ESBL activity, it is not yet enough, and blaSHV copy number amplification is also essential for an ESBL-positive phenotype, with homologous recombination being the likely mechanism of blaSHV copy number expansion. In this study, we investigated the mutation rate of non-ESBL expressing K. pneumoniae isolates to an ESBL-positive status by using the MSS-maximum likelihood method. Our data showed that blaSHV mutation rate of a non-ESBL expressing isolate is lower than the mutation rate of the other single base changes on the chromosome, even with a plasmid-borne blaSHV gene. On the other hand, mutation rate from a low MIC ESBL-positive (≤ 8 µg/mL for cefotaxime) to high MIC ESBL-positive (≥16 µg/mL for cefotaxime) is very high. This is because only gene copy number increase is needed which is probably mediated by homologous recombination that typically takes place at a much higher frequencies than point mutations. Using a subinhibitory concentration of novobiocin, as a homologous recombination inhibitor, revealed that this is the case.

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Biomass represents an abundant and relatively low cost carbon resource that can be utilized to produce platform chemicals such as levulinic acid. Current processing technology limits the cost-effective production of levulinic acid in commercial quantities from biomass. The key to improving the yield and effi ciency of levulinic acid production from biomass lies in the ability to optimize and isolate the intermediate products at each step of the reaction pathway and reduce re-polymerization and side reactions. New technologies (including the use of microwave irradiation and ionic liquids) and the development of highly selective catalysts would provide the necessary step change for the optimization of key reactions. A processing environment that allows the use of biphasic systems and/or continuous extraction of products would increase reaction rates, yields and product quality. This review outlines the chemistry of levulinic acid synthesis and discusses current and potential technologies for producing levulinic acid from lignocellulosics.

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Methane gas has been identified as the most destructive greenhouse gas (Liu et al., 2004). It was reported that the global warming potential of methane per molecule relative to CO2 is approximately 23 on a 100-year timescale or 62 over a 20-year period (IPCC, 2001). Methane has high C-H bond energy of about 439 kJ/mol and other higher alkanes (or saturated hydrocarbons) also have a very strong C-C and C-H bonds, thus making their molecules to have no empty orbitals of low energy or filled orbitals of high energy that could readily participate in chemical reactions as is the case with unsaturated hydrocarbons such as olefins and alkynes (Crabtree, 1994; Labinger & Bercaw, 2002)...

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Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

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Managing large cohorts of undergraduate student nurses during off-campus clinical placement is complex and challenging. Clinical facilitators are required to support and assess nursing students during clinical placement. Therefore clear communication between university academic coordinators and clinical facilitators is essential for consistency and prompt management of emerging issues. Increasing work demands require both coordinators and facilitators to have an efficient and effective mode of communication. The aim of this study was to explore the use of Short Message Service (SMS) texts, sent between mobile phones, for communication between university Unit Coordinators and off-campus Clinical Facilitators. This study used an after-only design. During a two week clinical placement 46 clinical facilitators working with first and second year Bachelor of Nursing students from a large metropolitan Australian university were regularly sent SMS texts of relevant updates and reminders from the university coordinator. A 15 item questionnaire comprising x of 5 point likert scale and 3 open-ended questions was then used to survey the clinical facilitators. The response rate was 47.8% (n=22). Correlations were found between the approachability of the coordinator and facilitator perception of a) that the coordinator understood issues on clinical placement (r=0.785, p<0.001,), and b) being part of the teaching team (r=0.768, p<0.001). Analysis of responses to qualitative questions revealed three themes: connection, approachability and collaboration. Results indicate that SMS communication is convenient and appropriate in this setting. This quasi-experimental after-test study found regular SMS communication improves a sense of connection, approachability and collaboration.