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Wang R.,Shandong Police College | Zhang D.,Shandong University | Liu C.,Shandong University
Chemosphere | Year: 2017

Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) are highly toxic to humans and the environment. Developing efficient methods to detect or remove these pollutants is particularly important and urgent. Boron nitride nanotubes (BNNTs) with low dimension and high surface-to-volume ratio might be one of promising materials for the adsorption of PCDD/Fs. Here we present a density functional theory (DFT) study on the interaction of the pristine and Ni doped (8,0) single-walled BNNTs with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most toxic congener among PCDD/F family. The calculated results show that the pristine BNNT intrinsically interacts with TCDD via physisorption with π-π stacking interaction, in contrast, the Ni-doped BNNT presents much higher reactivities toward TCDD. The impurity Ni atom plays a crucial role for capturing TCDD molecule. We also find that the Ni doping introduces the local electronic states within the band gap of the BNNT and induces magnetism in the doped systems. The present results are expected to provide useful guidance for the potential application of BNNTs as adsorption materials for detecting or removing dioxin pollutants. © 2016


Wei Y.-Q.,Shandong Police College | Liu D.,Shandong Normal University | Duan L.-S.,Shandong Normal University
Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012 | Year: 2012

For mining sequential patterns on massive data set, the distributed sequential pattern mining algorithm based on MapReduce programming model and PrefixSpan is proposed. Mining tasks are decomposed to many small tasks, the Map function is used to mine each Prefix-Projected sequential pattern, and the projected databases were constructed parallelly. It simplifies the search space and acquires a higher mining efficiency. Then the intermediate values are passed to a Reduce function which merges together all these values to produce a possibly smaller set of values. Both theoretical analyses and experimental results show MR-PrefixSpan reduces the time of scanning database. It solves the problem of mining massive data effectively, has considerable speedup and scaleup performances with an increasing number of processors on the Hadoop platform. © 2012 IEEE.


Pan W.,Shandong University | Qi Y.,Shandong University | Wang R.,Shandong Police College | Han Z.,Shandong Academy of Sciences | And 2 more authors.
Chemosphere | Year: 2013

The effective abatement of flue gas emissions, especially polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), is one of the challenging issues in the field of environmental science currently. Imidazolium-based dicyanamide ionic liquids (ILs) were proposed to have potential in controlling the emissions of PCDD/Fs. However, the relevant mechanism at the molecular level still remains unclear. To address this subject, we here present a combined molecular dynamics (MD) simulation and quantum chemical (QM) study on the adsorption of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most toxic congener among PCDD/F family, by 1-butyl-3-methylimidazolium dicyanamide IL, a representative imidazolium dicyanoamide ILs, which were demonstrated to possess high capture capability for PCDD/Fs. The MD simulation results show that TCDD molecules can be effectively adsorbed on the IL surface to form a dense layer, but cannot enter the interior of the IL. The results of QM calculations show that the adsorption of TCDDs on the IL surface occurs via intra-molecular hydrogen bond interactions. The calculated interaction energy of the anion with TCDD molecule is two times more than that of the cation, implying that the IL anion dominates the interaction with TCDD molecules, while the cation plays a secondary role. Based on the calculated results, we propose that imidazolium dicyanamide IL films/membranes may be better materials than the corresponding bulk for capturing TCDD. The present theoretical results may be helpful to designing the functional ILs which effectively capture and concentrate PCDD/F compounds. © 2013 Elsevier Ltd.


Liu H.H.,Shandong Police College
Applied Mechanics and Materials | Year: 2014

The triangular mesh subdivision to any planar field has been widely adopted in such applicable fields as configurable engineer, computer graphics, and scientific computation visualization and so on because of its well approach to the borderline. Thus, developing and researching on one certain effective and reliable triangular mesh subdivision algorithm has important theoretical and practical meanings. This paper firstly describes a refined algorithm about triangular mesh based on geometrical multi-grid method, and discusses its advantages and disadvantages. Secondly a new refined algorithm about triangular mesh subdivision is put forward by applying Fermat point and its properties as well as the minimum weight theory of triangular meshed subdivision. Finally, this paper proves that this refined algorithm can actually improve the efficiency of triangular mesh subdivision and generate grids' amount and quality. © (2014) Trans Tech Publications, Switzerland.


Pan W.-X.,Shandong University | Lai Y.-C.,Shandong University | Wang R.-X.,Shandong Police College | Zhang D.-J.,Shandong University | Zhan J.-H.,Shandong University
Journal of Raman Spectroscopy | Year: 2014

To better understand experimentally observed surface-enhanced Raman Scattering (SERS) of polychlorinated biphenyls (PCBs) adsorbed on nanoscaled silver substrates, a systematic theoretical study was performed by carrying out density functional theory and time-dependent density functional theory calculations. 2,2′,5,5′-tetrachlorobiphenyl (PCB52) was chosen as a model molecule of PCBs, and Agn (n = 2, 4, 6, and 10) clusters were used to mimic active sites of substrates. Calculated normal Raman spectra of PCB52-Agn (n = 2, 4, 6, and 10) complexes are analogical in profile to that of isolated PCB52 with only slightly enhanced intensity. In contrast, the corresponding SERS spectra calculated at adopted incident light are strongly enhanced, and the calculated enhancement factors are 104 ~ 10 5. Thus, the experimentally observed SERS phenomenon of PCBs supported on Ag substrates should correspond to the SERS spectra rather than the normal Raman spectra. The dominant enhancement in Raman intensities origins from the charge transfer resonance enhancement between the molecule and clusters. Copyright © 2014 John Wiley & Sons, Ltd.


Wang R.X.,Shandong Police College
Journal of molecular modeling | Year: 2014

To explore the novel application of boron nitride nanotubes (BNNTs), we investigated the interaction of pentachlorophenol (PCP) pollutant with the pristine and Fe doped (Fe-doped) (8, 0) single-walled BNNTs by performing density functional theory calculations. Compared with the weak physisorption on the pristine BNNT, PCP molecule presents strong chemisorption on the Fe-doped BNNT. The calculated data for the electronic properties indicate that doping Fe atom into the BNNT significantly improves the electronic transport property of BNNT, induces magnetism in the BNNT, and increases its adsorption sensitivity toward PCP molecule. It is suggested that doping BNNTs with Fe is an available strategy for improving the properties of BNNTs, and that Fe-doped BNNT would be a potential resource for adsorbing PCP pollutant in environments.


Sui Y.,Shandong Police College
Applied Mechanics and Materials | Year: 2014

Information security is a matter of concern in any sector and industry, and the vulnerability is the important factor which caused this issue. Therefore it is necessary to analyze and predict the occurrence of vulnerability. This paper used the datas of CNNVD vulnerability database and Apriori algorithm to analyze and predict the occurrence of software vulnerability. In the data preprocessing stage by changing the level of vulnerability rule we can dig out more concept association. In the evaluation stage of association rules by designing filters we can find the rules in line with the degree of user interest. Finally, this papper could demonstrate the effectiveness of of this method by experiments. © (2014) Trans Tech Publications, Switzerland.


Wang R.,Shandong Police College | Zhang D.,Shandong University | Liu C.,Shandong University
Computational Materials Science | Year: 2014

To explore a novel sensor to detect toxic pollutant in the atmosphere, we investigate reactivities of the germanium doped (Ge-doped) (8, 0) single-walled boron nitride nanotubes (BNNTs) towards carbon monoxide (CO) and nitric oxide (NO) by performing density functional theory (DFT) calculations. CO and NO are found to present strong chemisorption on the Ge-doped BNNT with substituted boron and nitrogen defect site. Calculated data for the electronic density of states and the electronic charge densities further indicate that the doping of Ge atom improves the electronic transport property of the BNNT, induces magnetism of the BNNT, and increases its adsorption sensitivity towards CO and NO. Doping BNNTs with Ge is expected to be an available strategy for improving the properties of BNNTs, and Ge-doped BNNT is expected to be a potential resource for detecting the presence of CO and NO. © 2013 Elsevier B.V. All rights reserved.


Liu H.H.,Shandong Police College
Advanced Materials Research | Year: 2014

Shanghai Expo, a global event, has enormous influence in a large scope in terms of space and contents. This thesis studies its influence in one aspect-the influence on economy. Based on cost-benefit theory, data fitting and the input-output table of the 2010 World Expo in Shanghai, the thesis has set up a complete mathematical model for quantitative assessment of costs and benefits to analyze the direct and indirect influence of the Expo on the economy of Shanghai. Through the cost-benefit assessment model, we can get the direct economic revenue of the Expo is RMB 1.691 billion Yuan. By data fitting analysis, because of the influence of the Expo, tourism income is 14.69 billion Yuan more than the natural growth and business volume of science and technology is 2.89 billion Yuan more than the natural growth. © (2014) Trans Tech Publications, Switzerland.


Wang H.,Shandong Police College | Wang H.,Shandong University | Li H.,Shandong University
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2015

When cleaning seed cotton, cleaning devices of different types had different cleaning efficiencies on different types of impurities. Therefore, the classification identification of seed cotton impurities had a guiding significance for adjusting the parameter of seed cotton cleaning equipment. A classification recognition algorithm of impurities in seed cotton based on local binary pattern and gray level co-occurrence matrix was proposed in this paper. First, the images were transformed to local binary pattern images, and so the gray value of each pixel was also converted to the local binary pattern value. Local binary pattern reflected the micro-structure of the center pixel and its 3×3 neighborhood, but it could not reflect a wider range of image structure. If the micro-structures of images were similar but macro-structures were different, the local binary pattern could not effectively distinguish the images. Gray level co-occurrence matrix was used to the statistics on the position of pixel pair. The pixel pairs had some relationship of gray values. The distances of pixel pairs could be controlled by the step length. In this paper, gray level co-occurrence matrix was used for local binary pattern image. It could describe the image structures of different scales by adjusting the step-length value. This paper calculated the characteristic values of seed cotton images and all kinds of impurities images with the step-length values from 1 to 8. The characteristics included contrast, angular second moment, correlation and inverse difference moment. The test results showed that these characteristics could distinguish seed cotton and every kind of impurity when the step-length value was equal to 3 or 4. The classifier of this algorithm used the support vector machine. In solving the small-sample, nonlinear and high-dimension problems, the support vector machine had more advantages than the traditional machine learning methods. The support vector machine was a typical two-class classifier. But classification recognition of seed cotton and impurities needed multi-class classifier. Several classifiers of support vector machine were combined into one multi-class classifier, and radial basis function was used as the kernel function of the classifier. This paper compared the standard local binary pattern algorithm (LBP), the standard gray level co-occurrence matrix algorithm (GLCM) and the algorithm designed in this paper (LBP-GLCM). The test results showed that the average recognition rate of the algorithm designed in this paper, which reached 94%, was higher than the LBP algorithm and the GLCM algorithm. Among different objects, the recognition rate of the boll shell and the cotton bush was 100%, the recognition rate of the leaf fragment was 92%, the recognition rate of the dust miscellaneous was 94%, the recognition rates of the deed cotton and barren cotton seed were 90% and 88%, respectively. The recognition rate could satisfy the demand of practical application. ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.

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