Shuangsheng Zhang^1,5, Hanhu Liu¹, Jing Qiang^2,*, Hongze Gao^3,*, Diego Galar⁴, Jing Lin⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 373-394, 2019, DOI:10.32604/cmes.2019.03825

Abstract Coupling Bayes’ Theorem with a two-dimensional (2D) groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity (M ), release location ( X₀ , Y₀) and release time (T₀), based on monitoring well data. To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters, a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy. To demonstrate how the model works, an exemplar problem with an instantaneous release of a contaminant in… More >

Chen Ding¹, Guizhi Wang^1,*, Qi Liu²

Journal on Big Data, Vol.1, No.2, pp. 55-69, 2019, DOI:10.32604/jbd.2019.06110

Abstract Haze concentration prediction, especially PM2.5, has always been a significant focus of air quality research, which is necessary to start a deep study. Aimed at predicting the monthly average concentration of PM2.5 in Beijing, a novel method based on Monte Carlo model is conducted. In order to fully exploit the value of PM2.5 data, we take logarithmic processing of the original PM2.5 data and propose two different scales of the daily concentration and the daily chain development speed of PM2.5 respectively. The results show that these data are both approximately normal distribution. On the basis… More >

Jieping Liu¹, Lingxin Zhang^1,*, Haohao Zhang², Tao Liu¹

Structural Durability & Health Monitoring, Vol.13, No.2, pp. 123-142, 2019, DOI:10.32604/sdhm.2019.04486

Abstract As there is a lack of earthquake damage data for factory buildings with seismic fortifications in China, seismic vulnerability analysis was performed by numerical simulation in this paper. The earthquake-structure analysis model was developed with considering the influence of uncertainties of the ground motion and structural model parameters. The small-size sampling was conducted based on the Latin hypercube sampling and orthogonal design methods. Using nonlinear analysis, the seismic vulnerability curves and damage probability matrix with various seismic fortification intensities (SFI) were obtained. The seismic capacity of the factory building was then evaluated. The results showed… More >

Yongzheng Lin¹, Hong Liu^{1, ∗}, Zhenxiang Chen², Kun Zhang², Kun Ma²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 245-257, 2019, DOI:10.32604/cmc.2019.04322

Abstract Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive More >

Wenyu Qu¹, Zhiyang Li^2,*, Junfeng Wu², Yinan Wu³, Zhaobin Liu²

Computer Systems Science and Engineering, Vol.33, No.2, pp. 115-123, 2018, DOI:10.32604/csse.2018.33.115

Abstract Conventional image skeletonization techniques implicitly assume the pixel level connectivity. However, noise inside the object regions destroys the connectivity and exhibits sparseness in the image. We present a skeletonization algorithm designed for these kinds of sparse shapes. The skeletons are produced quickly by using three operations. First, initial skeleton nodes are selected by farthest point sampling with circles containing the maximum effective information. A skeleton graph of these nodes is imposed via inheriting the neighborhood of their associated pixels, followed by an edge collapse operation. Then a skeleton tting process based on feature-preserving Laplacian smoothing More >

MengYuan Chen^1,2

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 593-602, 2018, DOI:10.31209/2018.100000026

Abstract With the increasing number of feature points of a map, the dimension of systematic observation is added gradually, which leads to the deviation of the volume points from the desired trajectory and significant errors on the state estimation. An Iterative Squared-Root Cubature Kalman Filter (ISR-CKF) algorithm proposed is aimed at improving the SR-CKF algorithm on the simultaneous localization and mapping (SLAM). By introducing the method of iterative updating, the sample points are re-determined by the estimated value and the square root factor, which keeps the distortion small in the highly nonlinear environment and improves the… More >

Mena E. Tawfik^{1, 2}, Peter L. Bishay^{3, *}, Edward A. Sadek¹

CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 105-129, 2018, DOI:10.3970/cmes.2018.115.105

Abstract Monte Carlo Simulations (MCS), commonly used for reliability analysis, require a large amount of data points to obtain acceptable accuracy, even if the Subset Simulation with Importance Sampling (SS/IS) methods are used. The Second Order Reliability Method (SORM) has proved to be an excellent rapid tool in the stochastic analysis of laminated composite structures, when compared to the slower MCS techniques. However, SORM requires differentiating the performance function with respect to each of the random variables involved in the simulation. The most suitable approach to do this is to use a symbolic solver, which renders… More >

Zhifeng Wang¹, Diqun Yan^1,*, Rangding Wang¹, Li Xiang¹, Tingting Wu¹

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 247-259, 2018, DOI:10.3970/cmc.2018.02902

Abstract Speech resampling is a typical tempering behavior, which is often integrated into various speech forgeries, such as splicing, electronic disguising, quality faking and so on. By analyzing the principle of resampling, we found that, compared with natural speech, the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect. Based on our observation, a new resampling detection algorithm based on the inconsistency of band energy is proposed. First, according to the sampling ratio of the suspected speech, a band-pass Butterworth filter is More >

Liu M^1,2, Z-W Liang^*1,2, L-H Huang^1,2, M-M Wang^1,2, H-Y Yang^1,2

Phyton-International Journal of Experimental Botany, Vol.85, pp. 162-168, 2016, DOI:10.32604/phyton.2016.85.162

Abstract Saline-sodic stress is a major abiotic constraint responsible for rice (Oryza sativa L.) yield reductions in Northeast China. The rice root system is crucial for yield development, and it is usually recognized as the key for improving future crop productivity. However, most of the saline-sodic soils in these areas contain high levels of soluble Na₂CO₃ and NaHCO₃, which results in a high pH (>8.5), clay dispersion, soil swelling, and overall poor soil physical properties. Isolation, washing and measurement of the rice crown roots is highly time-demanding in this kind of soil. Our aim was to explore whether… More >

H. Rafieayan Zadeh¹, M. Mohammadi^1,2, E. Babolian¹

CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.6, pp. 375-396, 2015, DOI:10.3970/cmes.2015.108.375

Abstract A local reproducing kernel method based on spatial trial space spanned by the Newton basis functions in the native Hilbert space of the reproducing kernel is proposed. It is a truly meshless approach which uses the local sub clusters of domain nodes for approximation of the arbitrary field. It leads to a system of ordinary differential equations (ODEs) for the time-dependent partial differential equations (PDEs). An adaptive algorithm, so-called adaptive residual subsampling, is used to adjust nodes in order to remove oscillations which are caused by a sharp gradient. The method is applied for solving More >