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Xiaoqin Yin,Mingxia Wang 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.1
Pro-active head restraint is a new automotive safety device with both active safety and passive safety characteristics. It can make a pre-estimation of the occurrence possibility of rear-end collision. Thus, the whiplash injury can be effectively reduced or even prevented. One of the key elements in rear-end collision avoidance system is to establish an effective safety distance mathematical model. Based on the running state of front car, the related calculation models of safety distance are established by means of dynamical and kinematical analysis of vehicle braking process and following process. Taken randomness and dynamic characteristics of parameters into consideration, the fuzzy relations between these parameters should be validated by means of fuzzy theory. Thus, it may accord with the actual driving conditions. By using the MATLAB software, the study shows that safety distance model and the methods used to determine parameters are reasonable, and the false alarm can be effectively minimized.
Xiaoqin Wang,Guizhen Li,노경호 대한화학회 2017 Bulletin of the Korean Chemical Society Vol.38 No.2
A novel deep eutectic solvent (DES) and ionic liquid (IL)-modified graphene (G) and graphene oxide (GO) were synthesized and used as effective adsorbents for the preconcentration of three chlorophenols (CPs), 4-chlorophenol (4-CP), 2,4-dichlorophenol (2,4-DCP), and 2,4,6-trichlorophenol (2,4,6-TCP), in environmental water samples prior to high-performance liquid chromatography (HPLC). The new materials were characterized by scanning electron microscopy (S-4200) and Fourier-transform infrared spectrometry. The prepared functionalized GO@silica shows remarkable adsorption capacity toward CPs. When used as solid-phase extraction (SPE) sorbents, a superior recovery (88.49–89.70%) could be obtained compared to commercial sorbents, such as silica and aminosilica. Based on this, a method for the analysis of CPs in water samples was established by coupling SPE with HPLC. These results highlight the potential new role of DES and IL-modified GO in the preparation of analytical samples.
Study on the Analytical Method of High-speed Railway Noise Sound Field Simulation
Wang XiaoQin 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.8
On the basis of the traditional structure of noise barrier, this paper seeks aerodynamic load to reduce the variation of maximum surface configuration (porous structure). Using the numerical simulation method, this paper builds a three-dimensional numerical model of deloading type noise barriers and trains. The large fluid calculation software, Fluent, is adopted to conduct simulation calculation of the high-speed deloading noise barriers. This thesis, conducting researches and analysis of the high-speed railway noise barrier aerodynamic load characteristics on the surface, concludes the characteristics of loading surface pressure distribution, time-history features as well as the law of influence factors, which is applicable to deloading sound barrier and lays a theoretical foundation for deloading sound barrier designing.
Extraction of Quercetin from Ginkgo biloba by DESs-based Monolithic Cartridge with RP-HPLC
( Wang Xiaoqin ),( Li Guizhen ),노경호 한국공업화학회 2016 한국공업화학회 연구논문 초록집 Vol.2016 No.1
Deep eutectic solvents (DES) were synthesized with choline chloride (ChCl), template molecular monolithic (TMM) and non-DES monolithic (N-DES-M) without template, were prepared in an identical procedure. Fourier transform infrared spectrometer (FT-IR) and field emission scanning electron microscopy (FE-SEM) were used to characterize the obtained polymers. Rebinding experiment and solid-phase extraction (SPE) were used to prove the high selectivity adsorption properties of the polymers. The optimum extraction condition was found to be: ultrasonic time optimized (30 min), the volume fraction of ethanol and ratio of liquid to material (20 mL g-1). Under these conditions, the extraction yield of quercetin was 290.8 mg g-1. Purification of Ginkgo biloba extract was achieved by SPE process. The results showed DES-sbased monolithic cartridge had potential for promising functional adsorption material for the purification of bioactive compounds.
A Study on the Financial Management Model of Business Group in the Era of Big Data
Xiaoqin Wang ASCONS 2021 IJASC Vol.3 No.4
Background/Objectives: In the Internet age of information technology development, the development of big data promotes the deepening of economic globalization and the competing market, and the enterprise management changes. More and more business groups are starting to study effective financial management models. The purpose of this paper is to find effective financial management models suitable for business groups in the context of new trends in the economic environment. Methods/Statistical analysis: For this purpose, this paper takes the representative Huayao Company in China as a case to study. Findings: The results show that the financial centralized management model can adapt to the trend of the enterprise and reduce the risk of the enterprise. Improvements/Applications: This study provides a theoretical basis for the generalization of enterprise groups with centralized financial management.
Zhaoqin Wang,Xiaorong Wang,Xiaoqin Liu,Yusen Wang,Chengyu Li,Tiesong Lin,Peng He 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.9
Common 3-axis CNC milling machines are generally equipped with 2D tool radius compensation (2D-TRC), which can realize TRC function for the contours in three basic planes when flat end mills are used. The 2D-TRC function makes engineers to program according to the actual contour of a part, and avoids over-cut phenomenon. Unfortunately, the 2D-TRC is unsuitable for ball end mills (BEMs), especially in the situation of milling complex curves or surfaces. In this work, a new TRC named BEM-TRC is used for milling NURBS curve swept surfaces using BEMs based on 3-axis CNC milling machines. In BEM-TRC, the TRC of a BEM involves radial and axial compensation. The cutting point (CP), which is the tangent point between a BEM and a NURBS curve, is considered as a calculation basis point. After obtaining a CP on a NURBS curve using the equi-arc length bisection interpolation method, the cutter center point of a BEM is calculated through off setting the CP the radius ( r ) distance of the BEM along its normal vector. Then the cutter location point of the BEM can be obtained according to the cutter center point. The CNC finishing program corresponding to the cutter location point can be obtained using Matlab software. The simulation based on VERICUT and machining based on a 3-axis milling machine verifies the effectiveness of the BEM-TRC. The over-cut phenomenon is avoided successfully when the BEM-TRC is used.
Exponential inequalities and complete convergence for a LNQD sequence
Wang Xuejun,Hu Shuhe,Yang Wenzhi,Li Xiaoqin 한국통계학회 2010 Journal of the Korean Statistical Society Vol.39 No.4
Some exponential inequalities for a linearly negative quadrant dependent sequence are obtained. By using the exponential inequalities, we give the complete convergence and almost sure convergence for a linearly negative quadrant dependent sequence. In addition,the asymptotic behavior of the probabilities for the partial sums of a linearly negative quadrant dependent sequence is studied.
( Qiuhua Wang ),( Xiaoqin Ouyang ),( Jiacheng Zhan ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.7
With the rapid development of network, Intrusion Detection System(IDS) plays a more and more important role in network applications. Many data mining algorithms are used to build IDS. However, due to the advent of big data era, massive data are generated. When dealing with large-scale data sets, most data mining algorithms suffer from a high computational burden which makes IDS much less efficient. To build an efficient IDS over big data, we propose a classification algorithm based on data clustering and data reduction. In the training stage, the training data are divided into clusters with similar size by Mini Batch K-Means algorithm, meanwhile, the center of each cluster is used as its index. Then, we select representative instances for each cluster to perform the task of data reduction and use the clusters that consist of representative instances to build a K-Nearest Neighbor(KNN) detection model. In the detection stage, we sort clusters according to the distances between the test sample and cluster indexes, and obtain k nearest clusters where we find k nearest neighbors. Experimental results show that searching neighbors by cluster indexes reduces the computational complexity significantly, and classification with reduced data of representative instances not only improves the efficiency, but also maintains high accuracy.