• The Journal of Information Systems
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• v.25 no.4
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• pp.63-85
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• 2016

Purpose While the popularity of C2C auction platforms such as eBay is gradually decreased, this domain is still undermined to explain online bidding behaviors. Online bidders sometimes engage in impulsive bidding due to some of the online auction characteristics. Therefore, this study develops and tests a model of the impulsive bidding exhibited by online bidders in C2C auction platforms. Based on S-O-R framework, our model posits that both perceived time-pressure and competition intensity affect cognitive absorption which ultimately influences the impulsive bidding. Design/methodology/approach This study collected survey data from 214 C2C auction participants, who have prior experience on impulsive bidding and tested both measurement model and structural model by using CB-SEM (covariate-based structural equation modelling) technique. In this study, by using AMOS 20.0, we tested the measurement model for its overall fit, item reliability, and validity and further conducted the structural model to test our proposed hypotheses. Findings Based on our results, we found that perceived tim-pressure and competition intensity were positively related to cognitive absorption. We also found that the cognitive absorption was positively associated with impulsive bidding behavior. In this study, by developing our research model in S-O-R framework, we provide an alternative theoretical mechanism to describe online impulsive bidding behavior.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.387-394
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• 1999

Artificial Neural Network (ANN) is a computational model inspired by the structure and operations of the brain. It is massively parallel system consisting of a large number of highly interconnected and simple processing units. The purpose of this paper is to verify the applicability of ANN to predict experimental results through the use of measured experimental data. Although there have been accumulated data based on hysteretic characteristics of structural element with cyclic loading tests, it is difficult to directly apply them for the analysis of elastic and plastic response. Thus, simple models with mathematical formula such as Bi-Linear Model, Ramberg-Osgood Model, Degrading Tri Model, Takeda Model, Slip type Model, and etc, have been used. To verify the practicality and capability of this study, ANN is adapted to several models with mathematical formula using numerical data To show the efficiency of ANN in nonlinear analysis, it is important to determine the adequate input and output variables of hysteretic models and to minimize an error in ANN process. The application example is Beam-Column joint test using the ANN in modeling of the linear and nonlinear hysteretic behavior of structure.

• Structural Engineering and Mechanics
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• v.74 no.2
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.92-99
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• 2006

Design capability for high safety vehicle with light weight is crucial to enhancing competitive power in vehicle market. The structural foam can contribute to restraining section distortion in body members undergoing bending collapse at vehicle crash. In this study, first, the validation of analysis model including structural foam model for simulating fracture behavior was discussed, and the bending collapse characteristics of five representative section types were analyzed and compared. Next, with changing the laminate foam shape, load carrying capability and absorbed energy were observed. The results suggests a design strategy of body members filled with laminate foam, leading to effectively elevating bending collapse characteristics with weight increase in the minimum.

• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.807-812
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• 2005

The objective of this study is to empirically investigate the effect of gender discrimination to female workers in Korean shipping firms on the their organization commitment and organizational citizenship behavior. In carrying out the objective of this study, two hypotheses about the structural relationship among gender discrimination, organization commitment and organizational citizenship behaviors in the Korean shipping firms are established after reviewing the related studies. Survey questionnaires are distributed and analyzed to test the reliability and validity of the response. Also, a structural equation model is established and the model is analyzed by AMOS. In conclusion, there are a negative effect of gender discrimination on female workers' organizational commitment and a positive effect of their commitment on OCB. Through this paper, the comprehensive understanding of the structural relationship among gender discrimination, organization commitment and organizational citizenship behavior would be promoted.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• Smart Structures and Systems
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• v.4 no.2
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• pp.195-208
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• 2008

This paper summarizes the experimental vibration-based structural health monitoring study on a historical monument in Jordan. In this work, and within the framework of the European Commission funded project "wide-Range Non-Intrusive Devices Toward Conservation of Historical Monuments in the Mediterranean Area", a seven and a half century old minaret located in Ajloun (73 km north of the capital Amman) is studied. Because of their cultural value, touristic importance and the desire to preserve them for the future, only non-destructive tests were allowed for the experimental investigation of such heritage structures. Therefore, after dimensional measurements and determination of the current state of damage in the selected monument, ambient vibration tests are conducted to measure the accelerations at strategic locations of the system. Output-only modal identification technique is applied to extract the modal parameters such as natural frequencies and mode shapes. A Non-linear version of SAP 2000 computer program is used to develop a three-dimensional finite element model of the minaret. The developed numerical model is then updated according to the modal parameters obtained experimentally by the ambient-vibration test-results and the measured characteristics of old stone and deteriorated mortar. Moreover, a parametric identification method using the N4Sid state space model is employed to model the dynamic behavior of the minaret and to build up a robust, immune and noise tolerant model.

• Journal of Korean Academy of Nursing
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• v.48 no.2
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• pp.195-207
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• 2018

Purpose: The purpose of the study was to develop and test a model for predicting problem gambling in speculative game users based on Blaszczynski and Nower's pathways model of problem and pathological gambling. Methods: The participants were 262 speculative game users recruited from seven speculative gambling places located in Seoul, Gangwon, and Gyeonggi, Korea. They completed a structured self-report questionnaire comprising measures of problem gambling, negative emotions, attentional impulsivity, motor impulsivity, non-planning impulsivity, gambler's fallacy, and gambling self-efficacy. Structural Equation Modeling was used to test the hypothesized model and to examine the direct and indirect effects on problem gambling in speculative game users using SPSS 22.0 and AMOS 20.0 programs. Results: The hypothetical research model provided a reasonable fit to the data. Negative emotions, motor impulsivity, gambler's fallacy, and gambling self-efficacy had direct effects on problem gambling in speculative game users, while indirect effects were reported for negative emotions, motor impulsivity, and gambler's fallacy. These predictors explained 75.2% problem gambling in speculative game users. Conclusion: The findings suggest that developing intervention programs to reduce negative emotions, motor impulsivity, and gambler's fallacy, and to increase gambling self-efficacy in speculative game users are needed to prevent their problem gambling.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.473-480
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• 1998

The substructuring pseudodynamic test is a hybrid testing method consisting of a numerical simulation of the earthquake response of an analytical model and a loading test of a specimen. The substructuring pseudodynamic testing technique has been applied to various seismic experiments since it has advantages over the shaking table test to study dynamic behaviors of relatively large scale structures. However, experimental errors are inevitable in substructuring pseudodynamic testing. Some of these errors can be monitored during the test, but, due to limitations in control system, they cannot be eliminated. For example, one cannot control exactly the displacements that are actually imposed on the structures at each time step. This paper focuses on a technique to minimize the cumulative effect of such control errors for MDOF system. For this purpose, the modified posterior adjustment of the time increment from a target value $\Delta$t$_{n}$ to an adjusted value is performed to minimize the effect of the control errors for MDOF system.for MDOF system.

• Journal of Korean Biological Nursing Science
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• v.20 no.2
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• pp.84-91
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• 2018

Purpose: The purpose of this study was to construct and test a structural equation model to investigate the risk factors of metabolic syndrome in rural women. Methods: The raw data in this study was collected from the Korean Genome and Epidemiology Study supervised by the Korea Centers for Disease Control and Prevention from 2005 to 2010. The data included physical examinations and surveys of 1,125 women, who resided in three rural areas of South Korea. The structural model in this study was composed of five latent variables: depression, stress, social support, health behavior, and metabolic syndrome. The structural equation model was used to assess the relationships among the variables. Results: The results of the study showed that depression and stress had direct effects on metabolic syndrome. Social support had a direct effect on health behavior and metabolic syndrome. Also, health behavior had a direct effect on metabolic syndrome. Conclusion: This study may serve as a guideline for interventions and strategies used to reduce metabolic syndrome in rural women.