• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.407-416
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• 2013

This paper proposes an approach to analyzing the relationship between technology and services, and to identifying promising service areas for technology-based firms with the analysis of business model (BM) patents. First, BM patents and technology patents are collected and classified into their relevant categories, respectively. Second, patent citation analysis is conducted to analyze the linkage and impacts between each technology and service field at macro level. Third, as a micro level analysis, patent co-classification analysis is employed to identify the interrelationships among specific technology and service areas. Finally, the promising service areas for technology-based firms seeking service areas for diversification is investigated with portfolio analysis. The working of the proposed approach is provided with the help of a case study of IT and mobile services. The proposed approach could guide and help managers of technology-based firms to discover the opportunity of the diversification to new areas in emerging service fields.

• Knowledge Management Research
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• v.3 no.1
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• pp.1-18
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• 2002

Many organizations implement knowledge management initiates by developing knowledge management systems. This study aims at investigating knowledge sharing behaviors in a knowledge management system and identifying factors affecting such behaviors. To do this, we defined knowledge sharing behaviors in a knowledge management system as registration and view of knowledge at a system. Based on this definition, we established a research model by identifying seven factors affecting both behaviors as independent variables: Learning orientation, Pressure to share knowledge, Top management support, Reward for knowledge sharing, Level of experience in IT, System quality, and Knowledge quality. The 14 hypotheses derived from a research model were tested by a correlation analysis and a multiple regression analysis with data from 165 respondents of the 21 organizations which implemented knowledge management initiatives. As results, both of knowledge registration and knowledge review were strongly affected by the learning-orientedness of an organization. Finally, we discussed results and limitations of this study.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.812-820
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• 1995

This paper proposes an approach of identifying nonlinear mappings from input/output data. The approach is based on the universal approximation by the fuzzy integration of local affine mappings. A connectionist model realizing the universal approximator is suggested by using a processing unit based on both the radial basis function and the weighted sum scheme. In addition, a learning method with self-organizing capability is proposed for the identifying of nonlinear mapping relationships with the given input/output data. To show the effectiveness of our approach, the proposed model is applied to the function approximation and the prediction of Mackey-Glass chaotic time series, and the performances are compared with other approaches.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.112-117
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• 2004

This paper suggests the design and analysis of the fuzzy sliding mode control for a nonlinear system using Takagi-Sugeno(T-S) fuzzy model. In this control scheme, identifying procedure that the input gain matrices in a T-S fuzzy model are manipulated into the same one is needed. The input disturbances generated in the identifying procedure are resolved by incorporating the disturbance treatment method of the conventional sliding mode control. The proposed control strategy can also treat the input disturbances that can not be linearized in the linearization procedure of T-S fuzzy modeling. Design example for the nonlinear system, an inverted pendulum on a cart, demonstrates the utility and validity of the proposed control scheme.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.91-94
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• 1996

A simulation procedure was developed for identifying Yungnam unit 2 excitation model parameters to improve the accuracy of stability simulation of KEPCO. First, generator model parameters are derived by using modified load rejection technique from measured load rejection test. For identifying excitation model parameters, switch was changed from MVR mode to AVR mode in Yungnam unit 2 excitation system instead of applying to a small step to the voltage reference($V_{ref}$) because of saving time and efforts, assuming the test result would show coincided result with applying to a small step to the $V_{ref}$. However, it was found that the response of switching from MVR to AVR is greatly different from it of applying small signal to the $V_{ref}$. A simulation procedure was needed to take into accounts of real AVR component status before and after switching from MVR to AVR. This paper reports the procedure which duplicated the measured response and addresses the merits of this test on conventional AVR step test.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.245-258
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• 2022

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

• Journal of Distribution Science
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• v.21 no.12
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• pp.23-34
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• 2023

Purpose: The purpose of this study is to identify factors affecting satisfaction as well as the intention of Gen Z customers to reorder food online in the context of a crisis. Research design, data and methodology: Data for this cross-sectional study were collected via the Internet by conducting an online survey of 652 Gen Z respondents, aged 15-25, in the south of Vietnam and using a convenience sampling method. To analyse the reliability of the scales, SPSS was used to run Cronbach's alpha. Then, SmartPLS was used to assess the measurement model, including variable reliability and validity, convergent validity, and discriminant validity of the proposed model, as well as test the hypotheses with partial least squares structural equation modelling (PLS-SEM). Results: Social influence, price value, and convenience all have a positive effect on satisfaction and repurchase intention. Satisfaction not only plays a critical role in mediating the relationship between social influence, price value, convenience and repurchase intention but also has a positive impact on repurchase intention towards buying food online. Conclusions: This study was successful in identifying the factors of repurchase intention in a crisis setting among Gen Z customers by developing a theoretical research model via literature to complete a brief Theory of Planned Behaviour model. This study also took an innovative approach to earlier ones by demonstrating not just the significant effect of social influence on satisfaction and repurchase intention, but also by identifying critical variables that managers should focus on increasing and improving management.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.841-849
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• 2001

The influence in fitting an equicorrelation model is investigated using the influence function. The influence functions for the model parameters are derived and its sample versions are used for investigating the influence of observations on the estimators of the parameters. Some relationships among the sample versions are found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model using the influence function method. An example is given for illustration.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.447-458
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• 2002

The influence of observations in the equicorrelation model is investigated using the local influence approach when all parameters or subsets of parameters are of interest. When a parameter of interest is scalar, an analytical form of the local influence measure can be found. We will derive a measure for identifying observations that have a large influence on the test of fitting the equicorrelation model. An example is given for illustration.