981 resultados para Hybrid feature selections


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We study the multicast stream authentication problem when an opponent can drop, reorder and inject data packets into the communication channel. In this context, bandwidth limitation and fast authentication are the core concerns. Therefore any authentication scheme is to reduce as much as possible the packet overhead and the time spent at the receiver to check the authenticity of collected elements. Recently, Tartary and Wang developed a provably secure protocol with small packet overhead and a reduced number of signature verifications to be performed at the receiver. In this paper, we propose an hybrid scheme based on Tartary and Wang’s approach and Merkle hash trees. Our construction will exhibit a smaller overhead and a much faster processing at the receiver making it even more suitable for multicast than the earlier approach. As Tartary and Wang’s protocol, our construction is provably secure and allows the total recovery of the data stream despite erasures and injections occurred during transmission.

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A hybrid nano-urchin structure consisting of spherical onion-like carbon and MnO2 nanosheets is synthesized by a facile and environmentally-friendly hydrothermal method. Lithium-ion batteries incorporating the hybrid nano-urchin anode exhibit reversible lithium storage with superior specific capacity, enhanced rate capability, stable cycling performance, and nearly 100% Coulombic efficiency. These results demonstrate the effectiveness of designing hybrid nano-architectures with uniform and isotropic structure, high loading of electrochemically-active materials, and good conductivity for the dramatic improvement of lithium storage.

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A novel platform consisting of a multilayered substrate, activated graphite-like carbon film, and dense forest of long, vertically-aligned multiwall carbon nanotubes grown by the chemical vapor deposition is designed, fabricated, and tested for covalent immobilization of enzymatic biocatalysts with the aim of protecting them from shear forces and microbial attacks present in bioreactors. The covalent bonding ensures enzyme retention in a flow, while the dense nanotube forest may serve as a protection of the enzymes from microbial attack without impeding the flow of reactants and products. This platform was demonstrated for the two reference enzymes, horseradish peroxidase and catalase, which were immobilized without degrading their biological activity. This combination of an activated carbon layer for an efficient immobilization of biocatalysts with a protective layer of inert carbon nanotubes could dramatically improve the efficiency and longevity of enzymatic bio-catalysis employed in a large variety of advanced biotechnological processes.

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Optically transparent, highly oriented nanocrystalline AlN(002) films have been synthesized using a hybrid plasma enhanced chemical vapor deposition and plasma-assisted radio frequency (rf) magnetron sputtering process in reactive Ar+ N2 and Ar+ N2 + H2 gas mixtures at a low Si(111)/glass substrate temperature of 350 °C. The process conditions, such as the sputtering pressure, rf power, substrate temperature, and N2 concentration were optimized to achieve the desired structural, compositional, and optical characteristics. X-ray diffractometry reveals the formation of highly c -oriented AlN films at a sputtering pressure of 0.8 Pa. Field emission scanning electron microscopy suggests the uniform distribution of AlN grains over large surface areas and also the existence of highly oriented in the (002) direction columnar structures of a typical length ∼100-500 nm with an aspect ratio of ∼7-15. X-ray photoelectron and energy dispersive x-ray spectroscopy suggest that films deposited at a rf power of 400 W feature a chemically pure and near stoichiometric AlN. The bonding states of the AlN films have been confirmed by Raman and Fourier transform infrared spectroscopy showing strong E2 (high) and E1 transverse optical phonon modes. Hydrogenated AlN films feature an excellent optical transmittance of ∼80% in the visible region of the spectrum, promising for advanced optical applications.

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Recently, a variety high-aspect-ratio nanostructures have been grown and profiled for various applications ranging from field emission transistors to gene/drug delivery devices. However, fabricating and processing arrays of these structures and determining how changing certain physical parameters affects the final outcome is quite challenging. We have developed several modules that can be used to simulate the processes of various physical vapour deposition systems from precursor interaction in the gas phase to gas-surface interactions and surface processes. In this paper, multi-scale hybrid numerical simulations are used to study how low-temperature non-equilibrium plasmas can be employed in the processing of high-aspect-ratio structures such that the resulting nanostructures have properties suitable for their eventual device application. We show that whilst using plasma techniques is beneficial in many nanofabrication processes, it is especially useful in making dense arrays of high-aspect-ratio nanostructures.

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Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.

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Although urbanization can promote social and economic development, it can also cause various problems. As the key decision makers of urbanization, local governments should be able to evaluate urbanization performance, summarize experiences, and find problems caused by urbanization. This paper introduces a hybrid Entropy–McKinsey Matrix method for evaluating sustainable urbanization. The McKinsey Matrix is commonly referred to as the GE Matrix. The values of a development index (DI) and coordination index (CI) are calculated by employing the Entropy method and are used as a basis for constructing a GE Matrix. The matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of the city of Jinan in China demonstrates the process of using the evaluation method. The case study reveals that the method is an effective tool in helping policy makers understand the performance of urban sustainability and therefore formulate suitable strategies for guiding urbanization toward better sustainability.

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Battery/supercapacitor hybrid energy storage systems have been gaining popularity in electric vehicles due to their excellent power and energy performances. Conventional designs of such systems require interfacing dc-dc converters. These additional dc-dc converters increase power loss, complexity, weight and cost. Therefore, this paper proposes a new direct integration scheme for battery/supercapacitor hybrid energy storage systems using a double ended inverter system. This unique approach eliminates the need for interfacing converters and thus it is free from aforementioned drawbacks. Furthermore, the proposed system offers seven operating modes to improve the effective use of available energy in a typical drive cycle of a hybrid electric vehicle. Simulation results are presented to verify the efficacy of the proposed system and control techniques.

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Battery-supercapacitor hybrid energy storage systems are becoming popular in the renewable energy sector due to their improved power and energy performances. These hybrid systems require separate dc-dc converters, or at least one dc-dc converter for the supercapacitor bank, to connect them to the dc-link of the grid interfacing inverter. These additional dc-dc converters increase power losses, complexity and cost. Therefore, possibility of their direct connection is investigated in this paper. The inverter system used in this study is formed by cascading two 3-level inverters, named as the “main inverter” and the “auxiliary inverter”, through a coupling transformer. In the test system the main inverter is connected with the rectified output of a wind generator while the auxiliary inverter is directly attached to a battery and a supercapacitor bank. The major issues with this approach are the dynamic changes in dc-link voltages and inevitable imbalances in the auxiliary inverter voltages, which results in unevenly distributed space vectors. A modified SVM technique is proposed to solve this issue. A PWM based time sharing method is proposed for power sharing between the battery and the supercapacitor. Simulation results are presented to verify the efficacy of the proposed modulation and control techniques.

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This project was a preliminary step towards the development of novel methods for early stage cancer diagnosis and treatment. Diagnostic imaging agents with high Raman signal enhancement were developed based on tailored assemblies of gold nanoparticles, which demonstrated potential for non-invasive detection from deep under the skin surface. Specifically designed polymers were employed to assemble gold nanoparticles into controlled morphologies including dimers, nanochains, nanoplates, globular and core-satellite nanostructures. Our findings suggest that the Raman enhancement is strongly dependent on assembly morphology and can be tuned to adapt to the requirements of the diagnostic agent.

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This paper presents a grid-side inverter based supercapacitor direct integration scheme for wind power systems. The inverter used in this study consists of a conventional two-level inverter and three H-bridge modules. Three supercapacitor banks are directly connected to the dc-links of H-bridge modules. This approach eliminates the need for interfacing dc-dc converters and thus considerably improves the overall efficiency. However, for the maximum utilization of super capacitors their voltages should be allowed to vary. As a result of this variable voltage space vectors of the hybrid inverter get distributed unevenly. To handle this issue, a modified PWM method and a space vector modulation method are proposed and they can generate undistorted current even in the presence of unevenly distributed space vectors. A supercapacitor voltage balancing method is also presented in this paper. Simulation results are presented to validate the efficacy of the proposed scheme, modulation methods and control techniques.

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A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

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(Figure Presented) Unusual conductivity effects: Suitably functionalized dendrimers (see picture) are capable of forming truly covalent three-dimensional networks with remarkably high conductivity on electrochemical doping. Depending on the charging level of the electroactive components used as building blocks for the dendrimer core and the perimeter, two separated regimes of electrical conductivity can be observed.

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This paper presents a novel dc-link voltage regulation technique for a hybrid inverter system formed by cascading two 3-level inverters. The two inverters are named as “bulk inverter” and “conditioning inverter”. For the hybrid system to act as a nine level inverter, conditioning inverter dc link voltage should be maintained at one third of the bulk inverter dc link voltage. Since the conditioning inverter is energized by two series connected capacitors, dc-link voltage regulation should be carried out by controlling the capacitor charging/discharging times. A detailed analysis of conditioning inverter capacitor charging/discharging process and a simplified general rule, derived from the analysis, are presented in this paper. Time domain simulations were carried out to demonstrate efficacy of the proposed method on regulating the conditioning inverter dc-link voltage under various operating conditions.

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As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.