• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.161-172
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• 2005

This study is to develop Bus Transit Route Analysis and Evaluation Model that can product the quantitative performance measures for Bus Transit Route Network Design. So far, in Korea, there are no so many models that evaluate a variety of other performance measures or service quality that are of concern to both the transit users and operator because of lower-level bus database system and transit route network analysis algorithm's limit. The BTRAEM in this research differ from the previous approach in that the BTRAEM employs a multiple path transit trip assignment model that explicitly considers the transfer and different travel time after boarding. And we develop input-output data structure and quantitative performance measure for the BTRAEM. In the numerical experimental applying BTRAEM to Mandl transit network, We got the meaningful results on performance measure of bus transit route network. In the future, we expect BTRAEM to give a good solution in real transit network.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.11-22
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• 2021

Sonobuoy is widely used as a very important sensor in combat management system using P-3 patrol aircraft due to its advantages of rapid searching into wide exploration range. It is necessary to verify the performance of developed sonobuoy system using various maritime test data in order to be successfully applied in combat management system. But it is difficult to acquire various real maritime data because it needs much time and effort. Therefore we have developed in this paper a synthetic signal generator and a simulator that they can verify the performance of sonobuoy system and evaluate its operational effectiveness without conducting maritime test. We have synthesized target signals based on the characteristics of underwater sound sources, and then developed the synthesized signal generator which consider to sound propagation etc. like as underwater environment. And in the simulator development we use a HMI technique to enhance the convenience of operator, and design to verify the performance of sonobuoy system. The developed signal generator and simulator can be used as useful tools to evaluate the operational effectiveness such as optimal deployment of sonobuoy in combat management system using P-3 patrol aircraft.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1031-1037
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• 2021

The frequency of marine accidents of vessels in Korea is steadily increasing and it is concentrated on small vessels with less than 10 tons of gross tonnage. Therefore, preventing capsizing accidents in small vessels is important to reduce the cost in terms of human and property damage due to such accidents. However, research on the seakeeping performance of small vessels has been insufficient, and there are no domestic and international regulations on seakeeping performance. Therefore, in this study, capsizing accidents caused by poor loading conditions were investigated by examining the adjudications of the small vessels in which the capsizing accidents occurred. Hydrostatic calculations and seakeeping performance analysis were performed for a representative vessel. A vessel generally performs a six-degree-of-freedom motion during operation. In this study, the response amplitude operator and response spectrum of a representative vessel were calculated to determine the roll motion. Moreover, a short-term statistical analysis of the vessel according to the loading conditions was performed for the wave stationary status for 3 h. From the results, it was estimated that, when the loading condition of a small vessel is poor, its roll motion increases, greatly reducing its stability.

• The Korean Journal of Franchise Management
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• v.3 no.2
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• pp.20-38
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• 2012

After being introduced into franchises industry, franchise has made a phenomenal growth in a short time and a substantial contribution to job creation and economic revitalization. Nevertheless, franchise business operators failed a business or low profit because of a lack of information and indiscriminate foundation. Therefore the first object of this study is characteristics of franchise's factors on disclosure agreement in franchise associate website. second is examinations about casual relationship between factor and franchise performance with using Excel and SPSS 18.0 versions. The findings of present study were as follows. First, franchises manage small business mostly(financial data, scale so on) and franchise's type focused the food service industry. Specially, a business district select unprotected contract. Second, in franchise's factors, we could find statistically significant effect on annual average sales and annual average net profit. However growth rate of franchise don't have statistically significant effect. Third, we could find statistically significant difference on analysis both franchises' factors and financial data. In conclusion, we must consider of franchise industry environment and success effect on performance in starting one's business. Furthermore franchises plan ways for their sustained growth and protection of rights and interests. Finally business operator draw up their information and upgrade continuously for franchises industry growth. Discussion and theoretical and managerial implications of the results were described along with future franchise research suggestions.

• The Korean Journal of Nuclear Medicine
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• v.33 no.2
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• pp.131-142
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• 1999

Purpose: Either gated myocardial perfusion SPECT or attenuation corrected SPECT can be used to improve specificity in the diagnosis of coronary artery disease. We investigated in this study whether gating or attenuation correction improved diagnostic performance of rest/stress perfusion SPECT in patients having intermediate pre-test likelihood of coronary artery disease. Materials and Methods: Sixty-eight patients underwent rest attenuation-corrected T1-20l/dipyridamole stress gated attenuation-corrected Tc-99m -MIBI SPECT using an ADAC vertex camera (M:F=29:39, aged $59{\pm}12$ years, coronary artery stenosis ${\geq}70%$, one vessel: 13, two vessel: 18, three vessel: 8, normal: 29). Using a five-point scale, three physicians graded the post-test likelihood of coronary artery disease for each arterial territory (1:normal, 2: possibly normal, 3:equivocal, 4. possibly abnormal, 5: abnormal). Sensitivity, specificity and area under receiver-operating-characteristic curves were compared for each operator between three methods : (A) non-attenuation-corrected SPECT; (B) gated SPECT added to (A): and (C) attenuation-corrected SPECT added to (B). Results: When grade 3 was used as the criteria for coronary artery disease, no differences in sensitivity and specificity were found between the three methods for each operator. Areas under receiver-operating-characteristic curves for diagnosis of coronary artery disease revealed no differences between each modality (p>0.05). Conclusion: In patients at intermediate risk of coronary artery disease, gated SPECT and attenuation- corrected SPECT did not improve diagnostic performance.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.71-79
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• 2005

Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.497-514
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• 2017

This study quantitatively analyzes the effects of emission inventory choices on the simulated particulate matter (PM) concentrations and the domestic/foreign contributions in the Seoul Metropolitan Area (SMA) with an air quality forecasting system. The forecasting system is composed of Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multi-Scale Air Quality (CMAQ). Different domestic and foreign emission inventories were selectively adopted to set up four sets of emissions inputs for air quality simulations in this study. All modeling cases showed that model performance statistics satisfied the criteria levels (correlation coefficient >0.7, fractional error <50%) suggested by previous studies. Notwithstanding the apparently good model performance of total PM concentrations by all emission cases, annual average concentrations of simulated total PM concentrations varied up to $20{\mu}g/m^3$ (160%) depending on the combination of emission inventories. In detail, the difference in simulated annual average concentrations of the primary PM coarse (PMC) was up to $25.2{\mu}g/m^3$ (6.5 times) compared with other cases. Furthermore, model performance analyses on PM species showed that the difference in the simulated primary PMC led to gross model overestimation in general, which indicates that the primary PMC emissions need to be improved. The contribution analysis using model direct outputs indicated that the domestic contributions to the annual average PM concentrations in the SMA vary from 44% to 67%. To account for the uncertainty of the simulated concentration, the contribution correction factor method proposed by Bae et al. (2017) was applied, which resulted in converged contributions(from 48% to 57%). We believe this study shows that it is necessary to improve the simulated concentrations of PM components in order to enhance the accuracy of the forecasting model. It is deemed that these improvements will provide more accurate contribution results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.471-480
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• 2015

The market of public-private partnership (PPP) projects has reduced from 9.4 trillion won in 2007 to 4.5 trillion won in 2012. However, the need of PPP projects is brought up by a massive down scale of government financial business. Previous studies regarding PPP projects mostly evaluate profitability from the financial perspective or analyze risk factors as a whole. Although PPP projects generally have complex structure involving diverse stakeholders, such as contractor, financial investor, and special purpose company (SPC) operators, existing studies have rarely considered the different viewpoints of PPP project stakeholders. Therefore, purpose of this study is to develop a structural equation model (SEM) considering the diverse stakeholders of PPP projects. To this end, the authors first reviewed the organizational structure of PPP projects. Next, the identification of the factors affecting project profitability are done via comprehensive literature reviews. After that, we conducted in-depth interviews and questionnaire surveys to reflect stakeholders' perspectives (contractors, financial investors, and SPC operators). As a result, a SEM model is developed to analyze direct and indirect effect on the PPP project performances. Finally, using the analysis results, relevant implications and directions for improvements are discussed. The prediction of the business performance of contractor, financial investor, and SPC operator is expect to be possible through the model developed and supports the strategy deduction that is appropriate for the participants.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.436-442
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• 2020

ESS(energy storage system) has recently become an important power source in various areas due to increased renewable energy resources. The more ESS is used, the less the effective capacity of the ESS. Therefore, it is important to manage the remaining useful lifetime(RUL). RUL can be checked regularly by inspectors, but it is common to be monitored and estimated by an automated monitoring system. The accurate state estimation is important to ESS operator for economical and efficient operation. RUL estimation model usually requires complex mathematical calculations consisting of cycle aging and calendar aging that are caused by the operation frequency and over time, respectively. A lightweight RUL estimation model is required to be embedded in low-performance processors that are installed on ESS. In this paper, a lightweight ESS RUL estimation model is proposed to operate on low-performance micro-processors. The simulation results show less than 1% errors compared to the original RUL model case. In addition, a performance analysis is conducted based on ATmega 328. The results show 76.8 to 78.3 % of computational time reduction.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.