80 research outputs found

    Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

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    Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described

    A Hybrid Model Based on Wavelet Decomposition-Reconstruction in Track Irregularity State Forecasting

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    Wavelet is able to adapt to the requirements of time-frequency signal analysis automatically and can focus on any details of the signal and then decompose the function into the representation of a series of simple basis functions. It is of theoretical and practical significance. Therefore, this paper does subdivision on track irregularity time series based on the idea of wavelet decomposition-reconstruction and tries to find the best fitting forecast model of detail signal and approximate signal obtained through track irregularity time series wavelet decomposition, respectively. On this ideology, piecewise gray-ARMA recursive based on wavelet decomposition and reconstruction (PG-ARMARWDR) and piecewise ANN-ARMA recursive based on wavelet decomposition and reconstruction (PANN-ARMARWDR) models are proposed. Comparison and analysis of two models have shown that both these models can achieve higher accuracy

    Efficient Processing of Continuous Skyline

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    The analyzing and processing of multisource real-time transportation data stream lay a foundation for the smart transportation's sensibility, interconnection, integration, and real-time decision making. Strong computing ability and valid mass data management mode provided by the cloud computing, is feasible for handling Skyline continuous query in the mass distributed uncertain transportation data stream. In this paper, we gave architecture of layered smart transportation about data processing, and we formalized the description about continuous query over smart transportation data Skyline. Besides, we proposed mMR-SUDS algorithm (Skyline query algorithm of uncertain transportation stream data based on micro-batchinMap Reduce) based on sliding window division and architecture

    First-principles study of electronic structures and optical properties of Cu, Ag, and Au-doped anatase TiO2

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    We perform first-principles calculations to investigate the band structure, density of states, optical absorption, and the imaginary part of dielectric function of Cu, Ag, and Au-doped anatase TiO2 in 72 atoms systems. The electronic structure results show that the Cu incorporation can lead to the enhancement of d states near the uppermost of valence band, while the Ag and Au doping cause some new electronic states in band gap of TiO2. Meanwhile, it is found that the visible optical absorptions of Cu, Ag, and Au-doped TiO2, are observed by analyzing the results of optical properties,.which locate in the region of 400-1000 nm. The absorption band edges of Cu, Ag, and Au-doped TiO2 shift to the long wavelength region compared with the pure TiO2. Furthermore, according to the calculated results, we propose the optical transition mechanisms of Cu, Ag, and Au-doped TiO2, respectively. Our results show that the visible light response of TiO2 can be modulated by substitutional doping of Cu, Ag, and Au.Comment: 12 pages, 6 figures, 43 reference

    Hierarchical Sulfur‐Based Cathode Materials with Long Cycle Life for Rechargeable Lithium Batteries

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    Composite materials of porous pyrolyzed polyacrylonitrile–sulfur@graphene nanosheet (pPAN–S@GNS) are fabricated through a bottom‐up strategy. Microspherical particles are formed by spray drying of a mixed aqueous colloid of PAN nanoparticles and graphene nanosheets, followed by a simple heat treatment with elemental sulfur. The pPAN–S primary nanoparticles are wrapped homogeneously and loosely within a three‐dimensional network of graphene nanosheets (GNS). The hierarchical pPAN–S@GNS composite shows a high reversible capacity of 1449.3 mAh g −1 sulfur or 681.2 mAh g −1 composite in the second cycle; after 300 cycles at a 0.2 C charge/discharge rate the capacity retention is 88.8 % of its initial reversible value. Additionally, the coulombic efficiency (CE) during cycling is near 100 %, apart from in the first cycle, in which CE is 81.1 %. A remarkable capacity of near 700 mAh g −1 sulfur is obtained, even at a high discharge rate of 10 C. The superior performance of pPAN–S@GNS is ascribed to the spherical secondary GNS structure that creates an electronically conductive 3D framework and also reinforces structural stability. The Peter PAN of Composites : Composite materials of porous pyrolyzed polyacrylonitrile–sulfur@graphene nanosheet (pPAN–S@GNS) are prepared through a bottom‐up strategy. The superior rate capability and excellent cycling stability of pPAN–S@GNS is ascribed to the special spherical structure possessing an electronically conductive and rigid hierarchical framework.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102635/1/cssc_201300742_sm_miscellaneous_information.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/102635/2/563_ftp.pd

    Localized geographic routing to a mobile sink with guaranteed delivery in sensor networks

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    International audienceWe propose a novel localized Integrated Location Service and Routing (ILSR) scheme, based on the geographic routing protocol GFG, for data communications from sensors to a mobile sink in wireless sensor networks. The objective is to enable each sensor to maintain a slow-varying routing next hop to the sink rather than the precise knowledge of quick-varying sink position. In ILSR, sink updates location to neighboring sensors after or before a link breaks and whenever a link creation is observed. Location update relies on flooding, restricted within necessary area, where sensors experience (next hop) change in GFG routing to the sink. Dedicated location update message is additionally routed to selected nodes for prevention of routing failure. Considering both unpredictable and predictable (controllable) sink mobility, we present two versions. We prove that both of them guarantee delivery in a connected network modeled as unit disk graph. ILSR is the first localized protocol that has this property. We further propose to reduce message cost, without jeopardizing this property, by dynamically controlling the level of location update. A few add-on techniques are as well suggested to enhance the algorithm performance. We compare ILSR with an existing competing algorithm through simulation. It is observed that ILSR generates routes close to shortest paths at dramatically lower (90% lower) message cost

    A Study on the Organizational Architecture and Standard System of the Data Sharing Network of Earth System Science in China

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    The aim of this paper is to discuss the organizational architecture and standard system for sharing research data at the national level. The Data Sharing Network of Earth System Science (DSNESS) is one of the nine pilot projects of the Scientific Data Sharing Project in China that has become a long-term operational research data-sharing platform in the National Science and Technology Infrastructure (NSTI) of China. First, a data sharing union mechanism was designed with the core principle being, “data come from research and will be reused in research”. Second, a data sharing organizational architecture was constructed that consists of three sections: data resource architecture, data management architecture, and data services architecture. A physical data sharing network was constructed that includes one general center and 15 distributed sub-centers based on the architecture. Third, a series of data sharing standards and specifications were designed and implemented in the DSNESS. The reference model of the DSNESS standard system includes three levels of standards: directive standards, general standards, and application standards. In total, 21 high level standards and specifications were developed and implemented in the DSNESS. Several core standards and specifications, such as the extensible metadata standard, data quality control specifications, and so on, were analyzed in detail. Finally, the data service effect was summarized in three aspects: dataset services, standard and specification services, and international cooperation services. This research shows that the organizational architecture and standard system is a very important soft environment for research data sharing. The practices of DSNESS will provide useful experiences for multi-disciplinary data sharing in Earth science and will help to eliminate the data gap between the rich and poor at the national level
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