991 resultados para Capture Efficiency
Resumo:
This note examines the productive efficiency of 62 starting guards during the 2011/12 National Basketball Association (NBA) season. This period coincides with the phenomenal and largely unanticipated performance of New York Knicks’ starting point guard Jeremy Lin and the attendant public and media hype known as Linsanity. We employ a data envelopment analysis (DEA) approach that includes allowance for an undesirable output, here turnovers per game, with the desirable outputs of points, rebounds, assists, steals and blocks per game and an input of minutes per game. The results indicate that depending upon the specification, between 29% and 42% of NBA guards are fully efficient, including Jeremy Lin, with a mean inefficiency of 3.7% and 19.2%. However, while Jeremy Lin is technically efficient, he seldom serves as a benchmark for inefficient players, at least when compared with established players such as Chris Paul and Dwayne Wade. This suggests the uniqueness of Jeremy Lin's productive solution and may explain why his unique style of play, encompassing individual brilliance, unselfish play and team leadership, is of such broad public appeal.
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Water and ammonium retention by sandy soils may be low and result in leaching of applied fertiliser. To increase water and nutrient retention, zeolite is sometimes applied as a soil ameliorant for high value land uses including turf and horticulture. We have used a new modified kaolin material (MesoLite) as a soil amendment to test the efficiency of NH4+ retention and compared the results with natural zeolite. MesoLite is made by caustic reaction of kaolin at temperature between 80-95°C; although it has a moderate surface area, its cation exchange capacity is very high;(SA=13m2/g,CEC=500meq/100g). A 13cm tall sand column filled with ~450g of sandy soil homogeneously mixed with 1, 2, 4, and 8g of MesoLite or natural zeolite per 1kg of soil was prepared. After saturation with local bore water, concentrated ammonium sulfate solution was injected at the base. Then, bore water was passed from bottom to top through the column at amounts up to 6 pore volumes and at a constant flow rate of 10ml/min using a peristaltic pump. Concentrations of leached NH4+ were determined using an AutoAnalyser. The concentration of NH4+ leached from the column with 0.4% MesoLite was greatly (90%) reduced relative to unamended soil. Under these conditions NH4+ retention by the soil-MesoLite mixture was 11.5 times more efficient than the equivalent soil-natural zeolite mixture. Glasshouse experiments conducted in a separate study show that NH4+ adsorbed by MesoLite is available to plants.
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Bunker fuels used in the aviation and maritime sectors are responsible for nearly 10% of global greenhouse gas emissions.1 According to a scientific survey: ‘[s]hipping is estimated to have emitted 1,046 million tonnes of CO2 in 2007, which corresponds to 3.3% of the global emissions during 2007. International shipping is estimated to have emitted 870 million tonnes, or about 2.7% of the global emissions of CO2 in 2007’. The study also predicted that ‘by 2050, in the absence of policies, ship emissions may grow by 150% to 250% (compared to the emissions in 2007) as a result of the growth in shipping.’
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Increasing concerns about the atmospheric CO2 concentration and its impact on the environment are motivating researchers to discover new materials and technologies for efficient CO2 capture and conversion. Here, we report a study of the adsorption of CO2, CH4, and H2 on boron nitride (BN) nanosheets and nanotubes (NTs) with different charge states. The results show that the process of CO2 capture/release can be simply controlled by switching on/off the charges carried by BN nanomaterials. CO2 molecules form weak interactions with uncharged BN nanomaterials and are weakly adsorbed. When extra electrons are introduced to these nanomaterials (i.e., when they are negatively charged), CO2 molecules become tightly bound and strongly adsorbed. Once the electrons are removed, CO2 molecules spontaneously desorb from BN absorbents. In addition, these negatively charged BN nanosorbents show high selectivity for separating CO2 from its mixtures with CH4 and/or H2. Our study demonstrates that BN nanomaterials are excellent absorbents for controllable, highly selective, and reversible capture and release of CO2. In addition, the charge density applied in this study is of the order of 1013 cm–2 of BN nanomaterials and can be easily realized experimentally.
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First principle calculations for a hexagonal (graphene-like) boron nitride (g-BN) monolayer sheet in the presence of a boron-atom vacancy show promising properties for capture and activation of carbon dioxide. CO2 is found to decompose to produce an oxygen molecule via an intermediate chemisorption state on the defect g-BN sheet. The three stationary states and two transition states in the reaction pathway are confirmed by minimum energy pathway search and frequency analysis. The values computed for the two energy barriers involved in this catalytic reaction after enthalpy correction indicate that the catalytic reaction should proceed readily at room temperature.
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Concern about the increasing atmospheric CO2 concentration and its impact on the environment has led to increasing attention directed toward finding advanced materials and technologies suited for efficient CO2 capture, storage and purification of clean-burning natural gas. In this letter, we have performed comprehensive theoretical investigation of CO2, N2, CH4 and H2 adsorption on B2CNTs. Our study shows that CO2 molecules can form strong interactions with B2CNTs with different charge states. However, N2, CH4 and H2 can only form very weak interactions with B2CNTs. Therefore, the study demonstrates B2CNTs could sever as promising materials for CO2 capture and gas separation.
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Recent literature has emphasized the pivotal role of knowledge integration in Enterprise Systems (ES) success. This research-in-progress paper, building upon Knowledge Based Theory of the firm (KBT), examines the efficiency of knowledge integration in the context of ES implementation and identifies the factors contributing to its enhancement. The proposed model in this paper suggests that the efficiency of knowledge integration in an ES implementation process depends upon the level of common knowledge and the level of coordination in the ES adopting organization. It further suggests that the level of common knowledge can be enhanced by proper training, improving ES users’intrinsic and extrinsic motivations and business process modeling and the level of coordination can be improved by articulating a clear unified organizational goal for the ES adoption in the organization, forming a competent ES team, enhancing interdepartmental communication and the cross-functionality in the organization structure.
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This video article articulates two exercises that have been developed to respond to the need for preparedness in the growing field of Performance Capture. The first is called Walking Through (Delbridge 2013), where the actor navigates a series of objects that exist in screen space through a developed sense of the existing physical particularities of the studio and an interaction with a screen (or feedback loop). The second exercise is called The Donut (Delbridge 2013), where the performer continues to navigate screen space but this time does so through the literal stepping through of a Torus in the virtual – again with nothing but the studio infrastructure and the screen as a guide. Notions of Motion Captured performance infer the existence of an interface that combines performer with system, separating (or intervening in) the space between performance and the screen. It is precisely the effect and provided opportunity of the intermediary device on the practice, craft and preparedness of the actor as they navigate the connection between 3D screen space and the physical properties of the studio that is examined here. Defining the scope of current practice for the contemporary actor is a key construct of this challenge, with the most appropriate definition revolving around the provision of a required mixture of performance and content for live, mediated, framed and variously captured formats. One of these particular formats is Performance Capture. The exercises presented here are two from a series, developed over a three year study that contribute to our understanding of the potential for a training regimen to be developed for the rigors of Performance Capture.
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Motion capture continues to be adopted across a range of creative fields including, animation, games, visual effects, dance, live theatre and the visual arts. This panel will discuss and showcase the use of motion capture across these creative fields and consider the future of virtual production in the creative industries.
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Electrospun scaffolds manufactured using conventional electrospinning configurations have an intrinsic thickness limitation, due to a charge build-up at the collector. To overcome this limitation, an electrostatic lens has been developed that, at the same relative rate of deposition, focuses the polymer jet onto a smaller area of the collector, resulting in the fabrication of thick scaffolds within a shorter period of time. We also observed that a longer deposition time (up to 13 h, without the intervention of the operator) could be achieved when the electrostatic lens was utilised, compared to 9–10 h with a conventional processing set-up and also showed that fibre fusion was less likely to occur in the modified method. This had a significant impact on the mechanical properties, as the scaffolds obtained with the conventional process had a higher elastic modulus and ultimate stress and strain at short times. However, as the thickness of the scaffolds produced by the conventional electrospinning process increased, a 3-fold decrease in the mechanical properties was observed. This was in contrast to the modified method, which showed a continual increase in mechanical properties, with the properties of the scaffold finally having similar mechanical properties to the scaffolds obtained via the conventional process at longer times. This “focusing” device thus enabled the fabrication of thicker 3-dimensional electrospun scaffolds (of thicknesses up to 3.5 mm), representing an important step towards the production of scaffolds for tissue engineering large defect sites in a multitude of tissues.
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The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manner. In this paper, we address the lack of a systematic exploration of the fundamental relations that can be used to capture the behavior of concurrent systems, i.e., co-occurrence, conflict, causality, and concurrency. Besides the definition of the spectrum of behavioral relations, which we refer to as the 4C spectrum, we also show that our relations give rise to implication lattices. We further provide operationalizations of the proposed relations, starting by proposing techniques for computing relations in unlabeled systems, which are then lifted to become applicable in the context of labeled systems, i.e., systems in which state transitions have semantic annotations. Finally, we report on experimental results on efficiency of the proposed computations.
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This paper presents two efficiency models for the regenerative dynamometer to be built at the University of Queensland. The models incorporate an accurate accounting of the losses associated with the regenerative dynamometer and the battery modelling technique used. In addition to the models the cycle and instantaneous efficiencies were defined for a regenerative system that requires a desired torque output. The simulation of the models allowed the instantaneous and cycle efficiencies to be examined. The results show the intended dynamometer machine has significant efficiency draw backs but incorporating field winding control, the efficiency can be improved.
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The measurement of losses in high efficiency / high power converters is difficult. Measuring the losses directly from the difference between the input and output power results in large errors. Calorimetric methods are usually used to bypass this issue but introduce different problems, such as, long measurement times, limited power loss measurement range and/or large set up cost. In this paper the total losses of a converter are measured directly and switching losses are exacted. The measurements can be taken with only three multimeters and a current probe and a standard bench power supply. After acquiring two or three power loss versus output current sweeps, a series of curve fitting processes are applied and the switching losses extracted.
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The auxiliary load DC-DC converters of the Sunshark solar car have never been examined. An analysis of the current design reveals it is complicated, and inefficient. Some simple measures to greatly improve the efficiency are present which will achieve an overall worthwhile power saving. Two switch-mode power supply DC-DC converter designs are presented. One is a constant current supply for the LED brake and turn indicators, which allows them to be powered directly from the main DC bus, and switched only as necessary. The second is a low power flyback converter, which employs synchronous rectification among other techniques to achieve good efficiency and regulation over a large range of output powers. Practical results from both converters, and an indication of the overall improvement in system efficiency will be offered.
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This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.