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  • Articles  (35)
  • 2015-2019  (35)
  • 1995-1999
  • 1970-1974
  • 2015  (35)
  • Technology  (35)
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  • Articles  (35)
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  • 2015-2019  (35)
  • 1995-1999
  • 1970-1974
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  • 1
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    Identifying Critical Loads of Frame Structures with Equilibrium Equations in Rate Form (2015)
    Hindawi
    Details
    Publication Date: 2015-08-24
    Description: Frame structures are widely used in engineering practice. They are likely to lose their stability before damage. As an indicator of load-carrying capability, the first critical load plays a crucial role in the design of such structures. In this paper, a new method of identifying this critical load is presented, based on the governing equations in rate form. With the presented method, a great deal of well-developed numerical methods for ordinary differential equations can be used. As accurate structural tangent stiffness matrices are essential to stability analysis, the method to obtain them systematically is discussed. To improve the computational efficiency of nonlinear stability analysis in large-scale frame structures, the corotational substructure elements are formulated as well to reduce the dimension of the governing equations. Four examples are studied to illustrate the validity and efficiency of the presented method.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 2
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    Backtracking-Based Simultaneous Orthogonal Matching Pursuit for Sparse Unmixing of Hyperspectral Data (2015)
    Hindawi
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    Publication Date: 2015-05-15
    Description: Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed signatures of a hyperspectral image can be expressed in the form of linear combination of only a few spectral signatures (endmembers) in an available spectral library. Simultaneous orthogonal matching pursuit (SOMP) algorithm is a typical simultaneous greedy algorithm for sparse unmixing, which involves finding the optimal subset of signatures for the observed data from a spectral library. But the numbers of endmembers selected by SOMP are still larger than the actual number, and the nonexisting endmembers will have a negative effect on the estimation of the abundances corresponding to the actual endmembers. This paper presents a variant of SOMP, termed backtracking-based SOMP (BSOMP), for sparse unmixing of hyperspectral data. As an extension of SOMP, BSOMP incorporates a backtracking technique to detect the previous chosen endmembers’ reliability and then deletes the unreliable endmembers. Through this modification, BSOMP can select the true endmembers more accurately than SOMP. Experimental results on both simulated and real data demonstrate the effectiveness of the proposed algorithm.
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  • 3
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    Bioagriculture Outlier Elimination Based on 3D View of - Variance and Leverage Measurement (2015)
    Hindawi
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    Publication Date: 2015-04-16
    Description: Aiming at effective outlier elimination in the biological near-infrared spectral and achieving high accuracy predictive modeling, this paper proposes a novel outlier elimination method based on variance and leverage analysis. Firstly, the characters of near-infrared spectral are summarized; then residual sample -variance, leverage, and residual sample -variance are concatenated as a divergence measurement. We further compared the proposed method with variance, Mahalanobis distance, and Hotelling statistical analysis; the experiment results demonstrate that the proposed methods have competitive outlier elimination and better performance in time complexity and accuracy. The proposed method can also be adopted for other outlier elimination tasks.
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  • 4
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    Salient Region Detection via Feature Combination and Discriminative Classifier (2015)
    Hindawi
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    Publication Date: 2015-12-29
    Description: We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.
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  • 5
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    Decomposition and Decoupling Analysis of Energy-Related Carbon Emissions from China Manufacturing (2015)
    Hindawi
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    Publication Date: 2015-10-13
    Description: The energy-related carbon emissions of China’s manufacturing increased rapidly, from 36988.97 × 104 tC in 1996 to 74923.45 × 104 tC in 2012. To explore the factors to the change of the energy-related carbon emissions from manufacturing sector and the decoupling relationship between energy-related carbon emissions and economic growth, the empirical research was carried out based on the LMDI method and Tapio decoupling model. We found that the production scale contributed the most to the increase of the total carbon emissions, while the energy intensity was the most inhibiting factor. And the effects of the intrastructure and fuel mix on the change of carbon emissions were relatively weak. At a disaggregative level within manufacturing sector, EI subsector had a greater impact on the change of the total carbon emissions, with much more potentiality of energy conservation and emission reduction. Weak decoupling of manufacturing sector carbon emissions from GDP could be observed in the manufacturing sector and EI subsector, while strong decoupling state appeared in NEI subsector. Several advices were put forward, such as adjusting the fuel structure and optimizing the intrastructure and continuing to improve the energy intensity to realize the manufacturing sustainable development in low carbon pattern.
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  • 6
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    Modeling and Coordinated Control Strategy of Large Scale Grid-Connected Wind/Photovoltaic/Energy Storage Hybrid Energy Conversion System (2015)
    Hindawi
    Details
    Publication Date: 2015-01-23
    Description: An AC-linked large scale wind/photovoltaic (PV)/energy storage (ES) hybrid energy conversion system for grid-connected application was proposed in this paper. Wind energy conversion system (WECS) and PV generation system are the primary power sources of the hybrid system. The ES system, including battery and fuel cell (FC), is used as a backup and a power regulation unit to ensure continuous power supply and to take care of the intermittent nature of wind and photovoltaic resources. Static synchronous compensator (STATCOM) is employed to support the AC-linked bus voltage and improve low voltage ride through (LVRT) capability of the proposed system. An overall power coordinated control strategy is designed to manage real-power and reactive-power flows among the different energy sources, the storage unit, and the STATCOM system in the hybrid system. A simulation case study carried out on Western System Coordinating Council (WSCC) 3-machine 9-bus test system for the large scale hybrid energy conversion system has been developed using the DIgSILENT/Power Factory software platform. The hybrid system performance under different scenarios has been verified by simulation studies using practical load demand profiles and real weather data.
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  • 7
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    A Novel Dynamic Model for Predicting Pressure Wave Velocity in Four-Phase Fluid Flowing along the Drilling Annulus (2015)
    Hindawi
    Details
    Publication Date: 2015-01-16
    Description: A dynamic pressure wave velocity model is presented based on momentum equation, mass-balance equation, equation of state, and small perturbation theory. Simultaneously, the drift model was used to analyze the flow characteristics of oil, gas, water, and drilling fluid multiphase flow. In addition, the dynamic model considers the gas dissolution, virtual mass force, drag force, and relative motion of the interphase as well. Finite difference and Newton-Raphson iterative are introduced to the numerical simulation of the dynamic model. The calculation results indicate that the wave velocity is more sensitive to the increase of gas influx rate than the increase of oil/water influx rate. Wave velocity decreases significantly with the increase of gas influx. Influenced by the pressure drop of four-phase fluid flowing along the annulus, wave velocity tends to increase with respect to well depth, contrary to the gradual reduction of gas void fraction at different depths with the increase of backpressure (BP). Analysis also found that the growth of angular frequency will lead to an increase of wave velocity at low range. Comparison with the calculation results without considering virtual mass force demonstrates that the calculated wave velocity is relatively bigger by using the presented model.
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  • 8
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    Topologically Ordered Feature Extraction Based on Sparse Group Restricted Boltzmann Machines (2015)
    Hindawi
    Details
    Publication Date: 2015-09-28
    Description: How to extract topologically ordered features efficiently from high-dimensional data is an important problem of unsupervised feature learning domains for deep learning. To address this problem, we propose a new type of regularization for Restricted Boltzmann Machines (RBMs). Adding two extra terms in the log-likelihood function to penalize the group weights and topologically ordered factors, this type of regularization extracts topologically ordered features based on sparse group Restricted Boltzmann Machines (SGRBMs). Therefore, it encourages an RBM to learn a much smoother probability distribution because its formulations turn out to be a combination of the group weight-decay and topologically ordered factor regularizations. We apply this proposed regularization scheme to image datasets of natural images and Flying Apsara images in the Dunhuang Grotto Murals at four different historical periods. The experimental results demonstrate that the combination of these two extra terms in the log-likelihood function helps to extract more discriminative features with much sparser and more aggregative hidden activation probabilities.
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  • 9
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    Three-Dimensional Numerical Analysis of the Tunnel for Polyaxial State of Stress (2015)
    Hindawi
    Details
    Publication Date: 2015-09-28
    Description: The aim of this study is to have a comprehensive understanding of the mechanical behavior of rock masses around excavation under different value of intermediate principal stress. Numerical simulation was performed to investigate the influence of intermediate principal stress using a new polyaxial strength criterion which takes polyaxial state of stress into account. In order to equivalently substitute polyaxial failure criterion with Mohr-Coulomb failure criterion, a mathematical relationship was established between these two failure criteria. The influence of intermediate principal stress had been analyzed when Mohr-Coulomb strength criterion and polyaxial strength criterion were applied in the numerical simulation, respectively. Results indicate that intermediate principal stress has great influence on the mechanical behavior of rock masses; rock strength enhanced by intermediate principal stress is significant based on polyaxial strength criterion; the results of numerical simulation under Mohr-Coulomb failure criterion show that it does not exert a significant influence on rock strength. Results also indicate that when intermediate principal stress is relatively small, polyaxial strength criterion is not applicable.
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  • 10
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    EIV-Based Interference Alignment Scheme with CSI Uncertainties (2015)
    Hindawi
    Details
    Publication Date: 2015-10-05
    Description: A novel interference alignment (IA) scheme based on the errors-in-variables (EIV) mathematic model has been proposed to overcome the channel state information (CSI) estimation error for the MIMO interference channels. By solving an equivalently unconstrained optimization problem, the proposed IA scheme employing a weighted total least squares (WTLS) algorithm can obtain the solution to a constrained optimization problem for transmit precoding (TPC) matrices and minimizes the distortion caused by imperfect CSI according to the EIV model. It is shown that the design of TPC matrices can be realized through an efficient iterative algorithm. The convergence of the proposed scheme is presented as well. Simulation results show that the proposed IA scheme is robust over MIMO interference channels with imperfect CSI, which yields significantly better sum rate performance than the existing IA schemes such as distributed iterative IA, maximum signal-to-interference-plus-noise ratio (Max SINR), and minimum mean square error (MMSE) schemes.
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