285 resultados para Computationally efficient


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Biomaterials play a fundamental role in disease management and the improvement of health care. In recent years, there has been a significant growth in the diversity, function, and number of biomaterials used worldwide. Yet, attachment of pathogenic microorganisms onto biomaterial surfaces remains a significant challenge that substantially undermines their clinical applicability, limiting the advancement of these systems. The emergence and escalating pervasiveness of antibiotic-resistant bacterial strains makes the management of biomaterial-associated nosocomial infections increasingly difficult. The conventional post-operative treatment of implant-caused infections using systemic antibiotics is often marginally effective, further accelerating the extent of antimicrobial resistance. Methods by which the initial stages of bacterial attachment and biofilm formation can be restricted or prevented are therefore sought. The surface modification of biomaterials has the potential to alleviate pathogenic biofouling, therefore preventing the need for conventional antibiotics to be applied.

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- Provided a practical variable-stepsize implementation of the exponential Euler method (EEM). - Introduced a new second-order variant of the scheme that enables the local error to be estimated at the cost of a single additional function evaluation. - New EEM implementation outperformed sophisticated implementations of the backward differentiation formulae (BDF) of order 2 and was competitive with BDF of order 5 for moderate to high tolerances.

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This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

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The National Energy Efficient Building Project (NEEBP) Phase One report, published in December 2014, investigated “process issues and systemic failures” in the administration of the energy performance requirements in the National Construction Code. It found that most stakeholders believed that under-compliance with these requirements is widespread across Australia, with similar issues being reported in all states and territories. The report found that many different factors were contributing to this outcome and, as a result, many recommendations were offered that together would be expected to remedy the systemic issues reported. To follow up on this Phase 1 report, three additional projects were commissioned as part of Phase 2 of the overall NEEBP project. This Report deals with the development and piloting of an Electronic Building Passport (EBP) tool – a project undertaken jointly by pitt&sherry and a team at the Queensland University of Technology (QUT) led by Dr Wendy Miller. The other Phase 2 projects cover audits of Class 1 buildings and issues relating to building alterations and additions. The passport concept aims to provide all stakeholders with (controlled) access to the key documentation and information that they need to verify the energy performance of buildings. This trial project deals with residential buildings but in principle could apply to any building type. Nine councils were recruited to help develop and test a pilot electronic building passport tool. The participation of these councils – across all states – enabled an assessment of the extent to which these councils are currently utilising documentation; to track the compliance of residential buildings with the energy performance requirements in the National Construction Code (NCC). Overall we found that none of the participating councils are currently compiling all of the energy performance-related documentation that would demonstrate code compliance. The key reasons for this include: a major lack of clarity on precisely what documentation should be collected; cost and budget pressures; low public/stakeholder demand for the documentation; and a pragmatic judgement that non-compliance with any regulated documentation requirements represents a relatively low risk for them. Some councils reported producing documentation, such as certificates of final completion, only on demand, for example. Only three of the nine council participants reported regularly conducting compliance assessments or audits utilising this documentation and/or inspections. Overall we formed the view that documentation and information tracking processes operating within the building standards and compliance system are not working to assure compliance with the Code’s energy performance requirements. In other words the Code, and its implementation under state and territory regulatory processes, is falling short as a ‘quality assurance’ system for consumers. As a result it is likely that the new housing stock is under-performing relative to policy expectations, consuming unnecessary amounts of energy, imposing unnecessarily high energy bills on occupants, and generating unnecessary greenhouse gas emissions. At the same time, Councils noted that the demand for documentation relating to building energy performance was low. All the participant councils in the EBP pilot agreed that documentation and information processes need to work more effectively if the potential regulatory and market drivers towards energy efficient homes are to be harnessed. These findings are fully consistent with the Phase 1 NEEBP report. It was also agreed that an EBP system could potentially play an important role in improving documentation and information processes. However, only one of the participant councils indicated that they might adopt such a system on a voluntary basis. The majority felt that such a system would only be taken up if it were: - A nationally agreed system, imposed as a mandatory requirement under state or national regulation; - Capable of being used by multiple parties including councils, private certifiers, building regulators, builders and energy assessors in particular; and - Fully integrated into their existing document management systems, or at least seamlessly compatible rather than a separate, unlinked tool. Further, we note that the value of an EBP in capturing statistical information relating to the energy performance of buildings would be much greater if an EBP were adopted on a nationally consistent basis. Councils were clear that a key impediment to the take up of an EBP system is that they are facing very considerable budget and staffing challenges. They report that they are often unable to meet all community demands from the resources available to them. Therefore they are unlikely to provide resources to support the roll out of an EBP system on a voluntary basis. Overall, we conclude from this pilot that the public good would be well served if the Australian, state and territory governments continued to develop and implement an Electronic Building Passport system in a cost-efficient and effective manner. This development should occur with detailed input from building regulators, the Australian Building Codes Board (ABCB), councils and private certifiers in the first instance. This report provides a suite of recommendations (Section 7.2) designed to advance the development and guide the implementation of a national EBP system.

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"This chapter discusses laminar and turbulent natural convection in rectangular cavities. Natural convection in rectangular two-dimensional cavities has become a standard problem in numerical heat transfer because of its relevance in understanding a number of problems in engineering. Current research identified a number of difficulties with regard to the numerical methods and the turbulence modeling for this class of flows. Obtaining numerical predictions at high Rayleigh numbers proved computationally expensive such that results beyond Ra ∼ 1014 are rarely reported. The chapter discusses a study in which it was found that turbulent computations in square cavities can't be extended beyond Ra ∼ O (1012) despite having developed a code that proved very efficient for the high Ra laminar regime. As the Rayleigh number increased, thin boundary layers began to form next to the vertical walls, and the central region became progressively more stagnant and highly stratified. Results obtained for the high Ra laminar regime were in good agreement with existing studies. Turbulence computations, although of a preliminary nature, indicated that a second moment closure model was capable of predicting the experimentally observed flow features."--Publisher Summary

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Multi-agent systems implicate a high degree of concurrency at both the Inter- and Intra-Agent levels. Scalable, fault tolerant, Agent Grooming Environment (SAGE), the second generation, FIPA compliant MAS requires a built in mechanism to achieve both the Inter- and Intra-Agent concurrency. This paper dilates upon an attempt to provide a reliable, efficient and light-weight solution to provide intra-agent concurrency with-in the internal agent architecture of SAGE. It addresses the issues related to using the JAVA threading model to provide this level of concurrency to the agent and provides an alternative approach that is based on an eventdriven, concurrent and user-scalable multi-tasking model for the agent's internal model. The findings of this paper show that our proposed approach is suitable for providing an efficient and lightweight concurrent task model for SA GE and considerably outweighs the performance of multithreaded tasking model based on JAVA in terms of throughput and efficiency. This has been illustrated using the practical implementation and evaluation of both models. © 2004 IEEE.

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The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.

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The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

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The choice of ethanol (C2H5OH) as carbon source in the Chemical Vapor Deposition (CVD) of graphene on copper foils can be considered as an attractive alternative among the commonly used hydrocarbons, such as methane (CH4) [1]. Ethanol, a safe, low cost and easy handling liquid precursor, offers fast and efficient growth kinetics with the synthesis of fullyformed graphene films in just few seconds [2]. In previous studies of graphene growth from ethanol, various research groups explored temperature ranges lower than 1000 °C, usually reported for methane-assisted CVD. In particular, the 650–850 °C and 900 °C ranges were investigated, respectively for 5 and 30 min growth time [3, 4]. Recently, our group reported the growth of highly-crystalline, few-layer graphene by ethanol-CVD in hydrogen flow (1– 100 sccm) at high temperatures (1000–1070 °C) using growth times typical of CH4-assisted synthesis (10–30 min) [5]. Furthermore, a synthesis time between 20 and 60 s in the same conditions was explored too. In such fast growth we demonstrated that fully-formed graphene films can be grown by exposing copper foils to a low partial pressure of ethanol (up to 2 Pa) in just 20 s [6] and we proposed that the rapid growth is related to an increase of the Cu catalyst efficiency due weak oxidizing nature of ethanol. Thus, the employment of such liquid precursor, in small concentrations, together with a reduced time of growth and very low pressure leads to highly efficient graphene synthesis. By this way, the complete coverage of a copper catalyst surface with high spatial uniformity can be obtained in a considerably lower time than when using methane.

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Free charge generation in donor-acceptor (D-A) based organic photovoltaic diodes (OPV) progresses through formation of charge-transfer (CT) and charge-separated (CS) states and excitation decay to the triplet level is considered as a terminal loss. On the other hand a direct excitation decay to the triplet state is beneficial for multiexciton harvesting in singlet fission photovoltaics (SF-PV) and the formation of CT-state is considered as a limiting factor for multiple triplet harvesting. These two extremes when present in a D-A system are expected to provide important insights into the mechanism of free charge generation and spin-character of bimolecular recombination in OPVs. Herein, we present the complete cycle of events linked to spin conversion in the model OPV system of rubrene/C60. By tracking the spectral evolution of photocurrent generation at short-circuit and close to open-circuit conditions we are able to capture spectral changes to photocurrent that reveal the triplet character of CT-state. Furthermore, we unveil an energy up-conversion effect that sets in as a consequence of triplet population build-up where triplet-triplet annihilation (TTA) process effectively regenerates the singlet excitation. This detailed balance is shown to enable a rare event of photon emission just above the open-circuit voltage (VOC) in OPVs.

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Thermally stable mesoporous TiO2/SiO2 hybrid films with pore size of 50 nm have been synthesized by adopting the polymeric micelle-assembly method. A triblock copolymer, poly(styrene-b-2-vinyl pyridine-b-ethylene oxide), which serves as a template for the mesopores, was utilized to form polymeric micelles. The effective interaction of titanium tetraisopropoxide (TTIP) and tetraethyl orthosilicate (TEOS) with the polymeric micelles enabled us to fabricate stable mesoporous films. By changing the molar ratio of TEOS and TTIP, several mesoporous TiO2/SiO2 hybrid films with different compositions can be synthesized. The presence of amorphous SiO2 phase effectively retards the growth of anatase TiO2 crystal in the pore walls and retains the original mesoporous structure, even at higher temperature (650 °C). These TiO2/SiO2 hybrid films are of very high quality, without any cracks or voids. The addition of SiO2 phase to mesoporous TiO2 films not only adsorbs more organic dyes, but also significantly enhances the photocatalytic activity compared to mesoporous pure TiO2 film without SiO2 phase.

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One-dimensional (1D) TiO2 nanostructures are very desirable for providing fascinating properties and features, such as high electron mobility, quantum confinement effects, and high specific surface area. Herein, 1D mesoporous TiO2 nanofibres were prepared using the electrospinning method to verify their potential for use as the photoelectrode of dye-sensitized solar cells (DSSCs). The 1D mesoporous nanofibres, 300 nm in diameter and 10-20 μm in length, were aggregated from anatase nanoparticles 20-30 nm in size. The employment of these novel 1D mesoporous nanofibres significantly improved dye loading and light scattering of the DSSC photoanode, and resulted in conversion cell efficiency of 8.14%, corresponding to an ∼35% enhancement over the Degussa P25 reference photoanode.

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Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

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Reducing carbon dioxide (CO2) to hydrocarbon fuel with solar energy is significant for high-density solar energy storage and carbon balance. In this work, single palladium/platinum (Pd/Pt) atoms supported on graphitic carbon nitride (g-C3N4), i.e. Pd/g-C3N4 and Pt/g-C3N4, acting as photocatalysts for CO2 reduction were investigated by density function theory (DFT) calcu-lations for the first time. During CO2 reduction, the individual metal atoms function as the active sites, while g-C3N4 provides the source of hydrogen (H*) from hydrogen evolution reaction. The complete, as-designed photocatalysts exhibit excellent activity in CO2 reduction. HCOOH is the preferred product of CO2 reduction on the Pd/g-C3N4 catalyst with a rate-determining barrier of 0.66 eV, while the Pt/g-C3N4 catalyst prefers to reduce CO2 to CH4 with a rate-determining barrier of 1.16 eV. In addition, depositing atom catalysts on g-C3N4 significantly enhances the visible light absorption, rendering them ideal for visible light reduction of CO2. Our findings open a new avenue of CO2 reduction for renewable energy supply.

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The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.