• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.58-78
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• 2016

Compressed sensing (CS) possesses the potential benefits for spectrum sensing of wideband signal in cognitive radio. The sparsity of signal in frequency domain denotes the number of occupied channels for spectrum sensing. This paper presents a scheme of adaptively adjusting the number of compressed measurements to reduce the unnecessary computational complexity when priori information about the sparsity of signal cannot be acquired. Firstly, a method of sparsity estimation is introduced because the sparsity of signal is not available in some cognitive radio environments, and the relationship between the amount of used data and estimation accuracy is discussed. Then the SNR of the compressed signal is derived in the closed form. Based on the SNR of the compressed signal and estimated sparsity, an adaptive algorithm of adjusting the number of compressed measurements is proposed. Finally, some simulations are performed, and the results illustrate that the simulations agree with theoretical analysis, which prove the effectiveness of the proposed adaptive adjusting of compressed measurements.

• Computers and Concrete
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• v.18 no.5
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• pp.1019-1039
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• 2016

In this paper, a parallel algorithm of nonlinear dynamic analysis of three-dimensional (3D) reinforced concrete (RC) frame structures based on the platform of graphics processing unit (GPU) is proposed. Time integration is performed using Newmark method for nonlinear implicit dynamic analysis and parallelization strategies are presented. Correspondingly, a parallel Preconditioned Conjugate Gradients (PCG) solver on GPU is introduced for repeating solution of the equilibrium equations for each time step. The RC frames were simulated using fiber beam model to capture nonlinear behaviors of concrete and reinforcing bars. The parallel finite element program is developed utilizing Compute Unified Device Architecture (CUDA). The accuracy of the GPU-based parallel program including single precision and double precision was verified in comparison with ABAQUS. The numerical results demonstrated that the proposed algorithm can take full advantage of the parallel architecture of the GPU, and achieve the goal of speeding up the computation compared with CPU.

• Computers and Concrete
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• v.19 no.1
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• pp.87-98
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• 2017

In recent year, the coat layer drops and the rebar rust of bridge parapets, which caused the structural performance degradation. In order to achieve the comprehensive rehabilitation, ultra high performance cementitious composites is proposed to existing RC parapet rehabilitation. The influence factors of UHPCC rehabilitation includes two parts, i.e., internal factors related with material, such as UHPCC layer thickness, corrosion ratio of rebars, fiber volume fraction, and external factors related with the load, such as impact speeds, impact angles, vehicle mass. The influence of the factors was analyzed in this paper based on the nonlinear finite element. The analysis results of the maximum dynamic deformation and the peak impact load of parapets revealed the influence of the internal factors and the external factors on anti-collision performance and degree degradation. This research may provide a reference for the comprehensive multifunctional rehabilitation of existing bridge parapets.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.125-140
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• 2011

This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2873-2877
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• 2012

Objective: To determine STAT3, P-STAT3, and VEGF-C expression levels in small cell lung cancers (SCLCs), and discuss their role and clinical significance in SCLC development. Method: Immunohistochemical methods were applied to 128 cases of SCLC and 40 cases of adjacent normal tissue. Results: The expression levels of STAT3, P-STAT3, and VEGF-C were higher in SCLC than in normal tissue (P<0.05). Pairwise comparisons showed positive correlations with lymph node metastasis, clinical stage, and tumor size (P<0.05). The expression levels were also related with the overall survival rates. Conclusion: STAT3 and VEGF-C play important roles in the development of SCLC, and might be expected to become new targets for SCLC treatment.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.99-103
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• 2007

Translation equivalence is very important for bilingual lexicography, machine translation system and cross-lingual information retrieval. Extraction of equivalences from bilingual sentence pairs belongs to data mining problem. In this paper, discriminative learning methods are employed to filter translation equivalences. Discriminative features including translation literality, phrase alignment probability, and phrase length ratio are used to evaluate equivalences. 1000 equivalences randomly selected are filtered and then evaluated. Experimental results indicate that its precision is 87.8% and recall is 89.8% for support vector machine.

• Journal of Magnetics
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• v.19 no.4
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• pp.385-392
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• 2014

Uncertainties in loads, materials and manufacturing quality must be considered during electromagnetic devices design. This paper presents an effective methodology for robust optimization design based on the variance decomposition in order to keep higher accuracy of the robustness prediction. Sobol' theory is employed to estimate the response variance under some specific tolerance in design variables. Then, an optimal design is obtained by adding a criterion of response variance upon typical optimization problems as a constraint of the optimization. The main contribution of this paper is that the proposed method applies the variance decomposition to obtain a more accurate variance of the response, as well save the computational cost. The performance and robustness of the proposed algorithms are investigated through a numerical experiment with both an analytic function and the TEAM 22 problem.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.9-15
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• 2013

This paper presents a uniform analytical model by energy method and Fourier series expansion to analyze detent force in uneven magnetic field for permanent magnet linear synchronous motor (PMLSM). The model reveals that detent force in long-primary type is mainly influenced by non-ideal distribution of permanent magnet magnetic motive force, while nounified air-gap permeance makes a great impact on detent force of short-primary type. Hence, magnetic field similarity of motor design techniques referring rotary counterpart are adopted. For long-primary type novel method of splitting edge magnets is proposed to reduce end effects force, and optimal widths of edge tooth in short-primary type also verify the effectiveness of magnetic field similarity. The experimental results validate finite element analysis results.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.200-207
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• 2007

The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

• Journal of Power Electronics
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• v.12 no.3
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• pp.439-447
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• 2012

In this paper, an input-series auxiliary power supply scheme is proposed, which is suitable for high input voltage and multiple-output applications. The power supply scheme is based on a two-transistor forward topology, all of the series modules have a common duty ratio, all the switches are turned on and off simultaneously, and the whole circuit has a single power transformer. It does not require an additional controller but still achieves efficient input voltage sharing (IVS) for each series module through its inherent transformer-integration strategy. The IVS process of this power supply scheme is analyzed in detail and the design considerations for the related parameters are given. Finally, a 100W multiple-output auxiliary power supply prototype is built, and the experimental results verify the feasibility of the proposed scheme and the validity of the theoretical analysis.