572 resultados para Bing Crosby


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This article presents a new method for data collection in regional dialectology based on site-restricted web searches. The method measures the usage and determines the distribution of lexical variants across a region of interest using common web search engines, such as Google or Bing. The method involves estimating the proportions of the variants of a lexical alternation variable over a series of cities by counting the number of webpages that contain the variants on newspaper websites originating from these cities through site-restricted web searches. The method is evaluated by mapping the 26 variants of 10 lexical variables with known distributions in American English. In almost all cases, the maps based on site-restricted web searches align closely with traditional dialect maps based on data gathered through questionnaires, demonstrating the accuracy of this method for the observation of regional linguistic variation. However, unlike collecting dialect data using traditional methods, which is a relatively slow process, the use of site-restricted web searches allows for dialect data to be collected from across a region as large as the United States in a matter of days.

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This paper aims to reducing difference between sketches and photos by synthesizing sketches from photos, and vice versa, and then performing sketch-sketch/photo-photo recognition with subspace learning based methods. Pseudo-sketch/pseudo-photo patches are synthesized with embedded hidden Markov model. Because these patches are assembled by averaging their overlapping area in most of the local strategy based methods, which leads to blurring effect to the resulted pseudo-sketch/pseudo-photo, we integrate the patches with image quilting. Experiments are carried out to demonstrate that the proposed method is effective to produce pseudo-sketch/pseudo-photo with high quality and achieve promising recognition results. © 2009.

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Purpose: To investigate whether eyes with diabetic macular edema (DME) and central retinal thickness (CRT) >400 μm had better visual and anatomical outcomes compared to eyes with a CRT <400 μm when treated with intravitreal bevacizumab in a real-world setting. Patients and methods: Patients undergoing intravitreal bevacizumab therapy for DME were identified from the departmental database of a tertiary referral unit. Following the initial injection, a retreatment was performed for any persistent macular edema, unless there had been no previous response to repeated doses. Recorded parameters included visual acuity, CRT on optical coherence tomography (spectral domain optical coherence tomography [SD-OCT]), and SD-OCT characteristics. Comparisons were made between data at baseline and 12 months after the first injection, and differences were tested for statistical significance using the Student's t-test. Results: In all, 175 eyes of 142 patients were analyzed. Patients in group 2 (CRT >400 μm) had significantly more injections than group 1 (CRT <400 μm) (4.0 versus 3.3; P=0.003). Both groups had similar numbers of eyes with preexisting epiretinal membrane and/or vitreomacular traction at baseline. The reduction in CRT was significantly greater in group 2 when compared to group 1 (P<0.0001). In terms of visual gain between baseline and month 12, each gained significantly by a mean of 0.12 logarithm of the minimum angle of resolution units (P=0.0001), but there was no difference between groups 1 and 2 (P=0.99). Conclusion: These results do not support a 400 μm baseline CRT cut-off for treating DME with bevacizumab, in contrast to published data on ranibizumab. Our results also indicate that patients with a thicker CRT require more bevacizumab injections, making treatment less cost-effective for these patients. Our results could be used by practitioners to support the use of bevacizumab in DME without applying a CRT cut-off. © 2014 Mushtaq et al.

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In dimensional metrology, often the largest source of uncertainty of measurement is thermal variation. Dimensional measurements are currently scaled linearly, using ambient temperature measurements and coefficients of thermal expansion, to ideal metrology conditions at 20˚C. This scaling is particularly difficult to implement with confidence in large volumes as the temperature is unlikely to be uniform, resulting in thermal gradients. A number of well-established computational methods are used in the design phase of product development for the prediction of thermal and gravitational effects, which could be used to a greater extent in metrology. This paper outlines the theory of how physical measurements of dimension and temperature can be combined more comprehensively throughout the product lifecycle, from design through to the manufacturing phase. The Hybrid Metrology concept is also introduced: an approach to metrology, which promises to improve product and equipment integrity in future manufacturing environments. The Hybrid Metrology System combines various state of the art physical dimensional and temperature measurement techniques with established computational methods to better predict thermal and gravitational effects.

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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

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We demonstrate a unique temperature-dependent characteristic of the selectively liquid-crystal-filled photonic crystal fiber, which is realized by a selectively infiltrating liquid crystal into a single air hole located at the second ring near the core of the PCF. Three-resonance dips are observed in the transmission spectrum. Theoretical and experimental investigations reveal that the three-resonance dips all result from the coupling between the LP01 core mode and the rod modes, i.e., LP03 and LP51. Then, we find that the dip shift induced by temperature shows good agreements with the thermo-optic performance of the LC employed. Furthermore, the dips shift greatly with changes in temperature, providing a method to achieve temperature measurement in such a compact structure.

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A new topology of the high frequency alternating current (HFAC) inverter bridge arm is proposed which comprises a coupled inductor, a switching device and an active clamp circuit. Based on it, new single-phase and threephase inverters are proposed and their operating states are analysed along with the traditional H-bridge inverter. Multiphase and multi-level isolated inverters are also developed using the HFAC bridge arm. Furthermore, based on the proposed HFAC, a front-end DC-DC converter is also developed for photovoltaic systems to demonstrate the application of the proposed HFAC converter. Simulation and experimental results from prototype converters are carried out to validate the proposed topologies which can be utilised widely in high frequency power conversion applications such as induction heating and wireless power transfer.

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System efficiency and cost effectiveness are of critical importance for photovoltaic (PV) systems. This paper addresses the two issues by developing a novel three-port dc-dc converter for stand-alone PV systems, based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation, and multiple operating modes for domestic and aerospace applications. A theoretical analysis is conducted to analyze the operating modes followed by simulation and experimental work. This paper is focused on a comprehensive modulation strategy utilizing both PWM and phase-shifted control that satisfies the requirement of PV power systems to achieve MPPT and output voltage regulation. A 250-W converter was designed and prototyped to provide experimental verification in term of system integration and high conversion efficiency.

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This study describes an optimised modulation strategy based on switching state sequences for the hybrid-clamped multilevel converter. Two key control variables defined as 'phase shift angle' and 'switching state change' for a five-level hybrid-clamped inverter are proposed to improve all switches' operation, and by changing their values, different control methods can be obtained for modulation optimisation purposes. Two example methods can solve the voltage imbalance problem of the dc-link capacitors and furthermore avoid two switches' simultaneous switching transitions and improve the inverter's performance as compared with the traditional phase disposition pulse-width modulation strategy. A 6 kW prototype inverter is developed and a range of simulation and experiments are carried out for validation. It is found that simulation and experimental results are in a good agreement and the proposed modulation strategy is verified in terms of low-order harmonic reduction.

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This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

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Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.

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This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

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Heat sinks are widely used for cooling electronic devices and systems. Their thermal performance is usually determined by the material, shape, and size of the heat sink. With the assistance of computational fluid dynamics (CFD) and surrogate-based optimization, heat sinks can be designed and optimized to achieve a high level of performance. In this paper, the design and optimization of a plate-fin-type heat sink cooled by impingement jet is presented. The flow and thermal fields are simulated using the CFD simulation; the thermal resistance of the heat sink is then estimated. A Kriging surrogate model is developed to approximate the objective function (thermal resistance) as a function of design variables. Surrogate-based optimization is implemented by adaptively adding infill points based on an integrated strategy of the minimum value, the maximum mean square error approach, and the expected improvement approaches. The results show the influence of design variables on the thermal resistance and give the optimal heat sink with lowest thermal resistance for given jet impingement conditions.

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Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.