• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.53
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• pp.233-264
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• 2012

This study proposes and verifies an integrated model that reflects and helps to explain complexities and comprehensiveness of e-Trade in practice. The primary objective was to widen and deepen our understanding about the phenomena of paperless trading which will enable us to formulate an effective means to promote the adoption and utilization of e-Trade infrastructure. This investigation combined and extended the theories and models of TAM, TOE framework, and TTF in order to identify and hypothesize the causal relationships between factors of technology, organization and environment, and the usage level and performance of e-Trade. The previous research on e-Trade was reviewed and incorporated into the extended model. The integrated model was tested based on the survey data collected from a sample of 417 trading firms. Overall, the regression and path analysis demonstrated the usefulness of the proposed model as a conceptual framework for better understanding and explanation of e-Trade. The result of the analysis implies the relevancy of the factors of technology, organization and environment for facilitating usage of and increasing performance of e-Trade. However, rejection of a few hypothesized relationships implies the necessity of extensive promotion and education about the related laws and regulations, and education, supervision and incentives for e-Trade practitioners.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.108-122
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• 2001

As bridge design is advancing toward the performance-based design. it becomes increasingly important to monitor and re-evaluate the long-term structural performance of bridges. Such information is essential in developing performance criteria for design. In this research. sensor systems for long-term structural performance monitoring have been installed on two highway bridges. Pre1iminary vibration measurement and data analysis have been performed on these instrumented bridges. On one bridge, ambient vibration data have been collected. based on which natural frequencies and mode shapes have been extracted using various methods and compared with those obtained by the preliminary finite element analysis. On the other bridge, braking and bumping vibration tests have been carried out using a water truck In addition to ambient vibration tests. Natural frequencies and mode shapes have been derived and the results by the breaking and bumping vibration tests have been compared. For the development of a three dimensional baseline finite element model, the new methodology using a neural network is proposed. The proposed one have been verified and applied to develop the baseline model of the bridge.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.963-966
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• 2002

This paper presents a new generic Petri net model for design and performance evaluation of a flexible assembly system with dual kanban. The architectural design of the model is derived from a generic bill of materials and the combination of FMS and FAS concepts. Two approaches for analysis and performance evaluation of the new model base on the theory of invariant analysis and linear programming are also introduced. Finally, the effect of different processing times between FMS-FAS on the number of kanban cards is investigated.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.429-438
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• 2015

Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

• Water for future
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• v.12 no.2
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• pp.63-69
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• 1979

The sequences of monthly streamflows constitute a non-statonary time series. The purely stochastic model has been applied to data generation of non-stationary time series. Tow different mothods--single site and multisite generation--have been used on the hydrologic time series. In this study the synthetic generation method by bivariate analysis, studied by Thomas Fiering, one of multi-site models, has been applied to the historical data on monthly streamflows at two sites in Nakdong River, and also for validity of this model the single site Thomas Fiering model applied. Through statistical analysis it has been shown that the performance of bivariate Thomas Fiering model was better than that of the other. By comparison of mean and standard deviaion between the historical and the generated, and cross correlogram interpretation, it has been known that the model used herein has good performance to simultaneously generate the monthly streamflows at two sites in a river hasin.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.273-289
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• 2023

In this paper, we develop a new time series model for predicting IPO (initial public offering) data with non-negative integer value. The proposed model is based on integer-valued autoregressive (INAR) model with a Poisson thinning operator. Just as the heterogeneous autoregressive (HAR) model with daily, weekly and monthly averages in a form of cascade, the integer-valued heterogeneous autoregressive (INHAR) model is considered to reflect efficiently the long memory. The parameters of the INHAR model are estimated using the conditional least squares estimate and Yule-Walker estimate. Through simulations, bias and standard error are calculated to compare the performance of the estimates. Effects of model fitting to the Korea's IPO are evaluated using performance measures such as mean square error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) etc. The results show that INHAR model provides better performance than traditional INAR model. The empirical analysis of the Korea's IPO indicates that our proposed model is efficient in forecasting monthly IPO volumes.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.105-108
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• 2002

This paper analytical models of a centralized approach based on SNMP Protocol, distributed approach based on mobile agent, and mixed model which is tile existing mobile agent model in order to overcome large communication numbers of SNMP and accumulated data of mobile agent. And then, we compare and analyze these analytical models. Performance evaluation results show that performance of mobile agent and the mixed model is less sensitive to the network traffic and more profitable for complex network environment than that of SNMP.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• The KSFM Journal of Fluid Machinery
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• v.10 no.2 s.41
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• pp.46-53
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• 2007

An improved performance characteristics analysis model of a regenerative pump is proposed in the present paper. For its low characteristic speed, a regenerative pump generates high head with low flow rate. However, the efficiency is fairly low due to the skin friction between impeller and casing. Also, the complexity of its internal flow pattern makes prediction of performance characteristics difficult. In the present research, a one-dimensional analysis model was improved with consideration of disc friction loss, minor loss, and modified flow length, and the result was proven to be close in range with the results from experiments.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.7
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• pp.649-658
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• 2000

Thermodynamic modeling of low-pressure scroll compressor was developed by combining continuity and energy conservation equation. Suction gas heating was considered using energy balance inside the low pressure shell. Pressure, temperature and mass of refrigerant-22 as a function of orbiting angle were calculated by solving the governing equations using fourth order Rung-Kutta scheme. Motor efficiency was taken by experiments with a variation of frequency. The developed model was applied to the analysis of an inverter driven scroll compressor with a variation of frequency, pressure ratio and operating conditions. The model was verified with the experimental results at the same operating conditions. The developed model was adequate to predict performance of the inverter driven scroll compressor as a function of operating conditions. Calculated parameters from the model were discharge temperature, mass flow rate, power input, COP, and thermodynamic properties with respect to orbiting angle. To enhance the performance of a scroll compressor, it is essential to diminish leakage at low frequency level and improve the mechanical efficiency at high frequency level.