Exploring the Effect of Overload on the Discontinuous Intention of SNS: The Moderating Effect of Gender

Yu Xiang Xia,Seong Wook Chae 한국데이터전략학회 2021 Journal of information technology applications & m Vol.28 No.5

With the proliferation of smartphones and 5G networks, mobile social network service (SNS) has become an indispensable part of people’s daily lives. However, with the use of SNS, fatigue and withdrawal behavior gradually emerged. Based on The Transactional Theory of Stress and Coping (TTSC), we explored the mechanism of SNS overload on users’ discontinuous intention under the framework of "stressor-strain-outcome". And we also investigated the moderating effects of gender in this process. We hope that through our research, we can help SNS users to reduce unnecessary fatigue, and provide better suggestions for platform designers to adjust product design to improve user experience.

Local Binary Haar Feathers Kadane and Multi-Threshold AdaBoost for Facial Classification and Recognition

Yu Xiang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.10

A face recognition algorithm based on local binary Haar feathers which represented as Kadane optimizing multi-threshold AdaBoost was proposed according to the problems of texture shape feature representation and classification algorithm accuracy in the process of facial classifying detection and recognition, First, improve the traditional expression by using image Local binary pattern of Haar features , improve image model of texture and shape feature expression ability ; Secondly, for single threshold weak learning algorithm we can not make full use of local binary Haar feature information, resulting in a lower classification accuracy problem proposed Kadane optimizing multi-threshold AdaBoost classifier, to achieve local binary Haar feature representation of facial high accuracy recognition; Finally, through the experiments show, efficient face recognition rate can reach more than 90% by the algorithm,which is superior to the selected comparison algorithm.

Unbalance Control Strategy of Boost Type Three-Phase to Single-Phase Matrix Converters Based on Lyapunov Function

Yu-xiang Xu,Hongjuan Ge,Hai Guo 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.1

This paper analyzes the input side performance of a conventional three-phase to single-phase matrix converter (3-1MC). It alsopresents the input-side waveform quality under this topology. The suppression of low-frequency input current harmonics isstudied using the 3-1MC plus capacitance compensation unit. The constraint between the modulation function of the output andcompensation sides is analyzed, and the relations among the voltage utilization ratio and the output compensation capacitance,filter capacitors and other system parameters are deduced. For a 3-1MC without large-capacity energy storage, the systemperformance is susceptible to input voltage imbalance. This paper decouples the inner current of the 3-1MC using a Lyapunovfunction in the input positive and negative sequence bi-coordinate axes. Meanwhile, the outer loop adopts a voltage-weightedsynthesis of the output and compensation sides as a cascade of control objects. Experiments show that this strategy suppressesthe low-frequency input current harmonics caused by input voltage imbalance, and ensures that the system maintains good staticand dynamic performances under input-unbalanced conditions. At the same time, the parameter selection and debugging methodsare simple.

Bayesian Prediction Model Based on Attribute Weighting and Kernel Density Estimations

Xiang, Zhong-Liang,Yu, Xiang-Ru,Kang, Dae-Ki Hindawi Limited 2015 Mathematical problems in engineering Vol.2015 No.-

<P>Although naïve Bayes learner has been proven to show reasonable performance in machine learning, it often suffers from a few problems with handling real world data. First problem is conditional independence; the second problem is the usage of frequency estimator. Therefore, we have proposed methods to solve these two problems revolving around naïve Bayes algorithms. By using an attribute weighting method, we have been able to handle conditional independence assumption issue, whereas, for the case of the frequency estimators, we have found a way to weaken the negative effects through our proposed smooth kernel method. In this paper, we have proposed a compact Bayes model, in which a smooth kernel augments weights on likelihood estimation. We have also chosen an attribute weighting method which employs mutual information metric to cooperate with the framework. Experiments have been conducted on UCI benchmark datasets and the accuracy of our proposed learner has been compared with that of standard naïve Bayes. The experimental results have demonstrated the effectiveness and efficiency of our proposed learning algorithm.</P>

The Image Sparse Denoising of Redundant Dictionary Based on Filtering Guidance

Yu Xiang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9

This paper conducts a research on information loss of local feature existing in the image denoising process and puts forward the method of image sparse denoising of redundant dictionary based on filtering guidance. This method utilizes bias noise (additional noise and image errors after denoised image and the corresponding additional noise deviation) for image sparse expression, and extracts the feature information of bias noise to improve the effectiveness of de-noising. In the first place, based on filtering guidance, the method carries out aftertreatment to bias noise still existing after denoise the image. And then, the method, in the basis of this bias noise, designs a new dictionary training method, and obtains redundant dictionary for image processing through self-adaption. Finally, the method extracts featured texture from bias noise image based on the dictionary mentioned above. And it takes advantage of filtering guidance in combination with featured texture extracting information and denoising image to realize image restoration. According to emulated data, the performance of proposed algorithm should be better than the selected comparing algorithm and be equipped with a better visual recovery effect.

Predictive Factors Determining Neoadjuvant Chemotherapy Outcomes in Breast Cancer - a Single Center Experience

Yu, Yang,Xiang, Hua,He, Xiang-Ming,Yang, Hong-Jian,Zong, Xiang-Yun Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.4

From January 1, 2008 to March 31, 2010, 101 patients with stage II-III breast cancer were enrolled in this study and subjected to an anthracycline-based neoadjuvant chemotherapy regimen with or without docetaxel. Surgery was performed after 2-6 cycles of chemotherapy, and the clinical response was determined by pathological and histochemical assessments. The clinical response rate, as indicated by complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD), were 6.9, 52.5, 36.6, and 4.0%, respectively. A multivariable correlation analysis indicated that the overall clinical response rate correlated with the number of metastatic lymph nodes, number of chemotherapy cycles, and vessel invasion status. Importantly, the CR rate was only associated with the number of chemotherapy cycles. Nonparametric tests failed to detect a correlation between HER2 or Topo $II{\alpha}$ status and clinical response to neoadjuvant chemotherapy in these patients. When they were stratified by HER2 or HR status, for HER2-positive patients the CR rate was associated with vessel invasion and Topo $II{\alpha}$ status. Based on our findings, we propose that HR, HER-2 and Topo $II{\alpha}$ are not putative predictive biomarkers of chemotherapy outcome for breast cancer patients. Topo $II{\alpha}$ expression level was only inversely correlated with CR rate among HR-positive patients. Importantly, the achievement of CR was largely related to the number of chemotherapy cycles.

A Stability Study of the Longest Steel Truss Deck Cable-stayed Bridge during Construction

Xiang-min Yu,De-wei Chen,Zhi-zhou Bai 대한토목학회 2019 KSCE Journal of Civil Engineering Vol.23 No.4

For long-span cable-stayed bridges, the stability performance during construction is vital from the point view of structural safety. This paper presents an extensive study of stability performance during construction for the world longest steel truss deck cable-stayed bridge-Yachihe Bridge. Based on the finite element analysis, the Linear Elastic Stability (LES), Nonlinear Elastic Stability (NLES) and Nonlinear Inelastic Stability (NLIES) of the bridge have been investigated to identify the effects of geometry nonlinearity and material nonlinearity on the structural stability performance. In addition, the influences of temperature variations and static lateral winds on stability performance are also focused. The results show that: 1) Under design ambient temperature, the corresponding design of steel truss deck yields the minimum stability coefficients of LES, NLES and NLIES by 5.72, 4.64 and 2.96, respectively, corresponding to the completion of superimposed dead loads; 2) both the geometry nonlinearity and material nonlinearity have been identified to make negative effects on the stability performance and the material nonlinearity will reduce the structural stabilitycoefficient largely; 3) during construction, the rise and drop in temperature will increase and decrease the stability coefficients, respectively. NLIES is the most sensitive one to variations of temperature; and 4) the lateral static winds slightly reduce the stability coefficients of LES, NLES and NLIES.

New Method for Analysis of Sliding Cable Structures in Bridge Engineering

Xiang-min Yu,De-wei Chen,Zhi-zhou Bai 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.11

The Sliding Cable Structure (SCS) is widely used in bridge construction by cable crane method. The SCS generally consists of cables and fixed pulleys and the cables will slide around the pulleys when the cables are loaded until the balanced state is achieved. In this paper, an efficient Angle Bisector Method (ABM) is proposed for the mechanical analysis of SCS. The constraint effect of pulley on the cable is simulated by fixed hinge and the constraint force perpendicular to the angle bisector of cable elements adjacent to the pulley is therefore zero at balanced state. By utilizing “Unit Length Influence Matrix” (ULIM), the adjustment of unstressed length of each sub-cable can be determined. As the angle bisector at each pulley will change when the unstressed lengths of cables are changed, iterative procedures are necessary to find the convergence solutions. The proposed method is firstly verified by two examples and then applied to the analysis of cable crane during construction of the world’s longest steel truss cable-stayed bridge, namely Yachihe Bridge. Satisfactory numerical solutions can be obtained only with several iterations and are in good agreement with field measurements from the cable crane load tests, which confirms the accuracy and validity of the proposed method.

Eye Fatigue State Recognition of Gabor Wavelet Optimization HMM Algorithm

Yu Xiang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.9

It is easy for the internet learners to generate learning fatigue because of the long-term lack of emotional interaction in the learning process, and learning fatigue often manifests through the eye condition, in order to do effective monitoring for remote intelligent tutoring system, the learning fatigue eye state recognition algorithm is put forward based on Gabor wavelet and HMM. The algorithm has certain distinguishing characteristics aiming at the degree of eye openness of network learner under 3 learning states: normal learning, fatigue and confusion, first, it does gray difference disposal for eye image by Laplace operator in YCbCr color space, then, it selects two-dimension Gabor kernel function to build 48 optimal filters, obtain 48 characteristic values, these 48 characteristic values generate 48 eigenvectors, at last, it use a set of observation sequence O formed by eigenvector of HMM for eye state image to do eye state recognition. Experimental results show that the recognition rate of this algorithm for network learning reaches 95.68%, and this algorithm has a good robustness.

Numerical simulation on the coupled chemo-mechanical damage of underground concrete pipe

Xiang-nan Li,Xiao-bao Zuo,Yu-xiao Zou,Yu-juan Tang 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.86 No.6

Long-termly used in water supply, an underground concrete pipe is easily subjected to the coupled action of pressure loading and flowing water, which can cause the chemo-mechanical damage of the pipe, resulting in its premature failure and lifetime reduction. Based on the leaching characteristics and damage mechanism of concrete pipe, this paper proposes a coupled chemo-mechanical damage and failure model of underground concrete pipe for water supply, including a calcium leaching model, mechanical damage equation and a failure criterion. By using the model, a numerical simulation is performed to analyze the failure process of underground concrete pipe, such as the time-varying calcium concentration in concrete, the thickness variation of pipe wall, the evolution of chemo-mechanical damage, the distribution of concrete stress on the pipe and the lifetime of the pipe. Results show that, the failure of the pipe is a coupled chemo-mechanical damage process companied with calcium leaching. During its damage and failure, the concentrations of calcium phase in concrete decrease obviously with the time, and it can cause an increase in the chemo-mechanical damage of the pipe, while the leaching and abrasion induced by flowing water can lead to the boundary movement and wall thickness reduction of the pipe, and it results in the stress redistribution on the pipe section, a premature failure and lifetime reduction of the pipe.