• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.71-90
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• 2015

This article aims to explore the performance evaluation framework for assessing the contribution of national research and development(R&D) program to productivity growth. The key idea starts with the development of methodology for evaluating the returns to R&D. The method of this study is based on the comparison of productivity growth between different periods, not cross-sectional approach with one period. In this context, backward effect and forward effect are operationally defined as a measurement for contributions of R&D in this paper. The analysis results gives that the backward effect of R&D is greater than the forward effect, while the difference was especially evident with the case of sales variable, not operating profit variable.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.69-77
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• 2011

This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.6
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• pp.47-53
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• 2008

This research focuses on the issue of seismic retrofit prioritization based on the Caltrans' highway network serving Los Angeles and Orange counties. Retrofit prioritization is one of most important problems in earthquake engineering, and it is a problem that most decision makers face in the process of resource allocation. This study demonstrates the methods of prioritized resource allocation in the process of retrofitting a regional highway network. For the criteria of a retrofit ranking, seismic vulnerability and the importance of network link are first introduced. Subsequently, link-based seismic retrofit cases are simulated, investigating the effects of the seismic retrofit in terms of seismic performance, such as driver's delay. In this study, probabilistic scenario earthquakes are used to perform a probabilistic seismic risk analysis. The results show that the retrofit prioritization can be differently defined and ranked depending on the stakeholders. This study provides general guidelines for prioritization strategy for the effective retrofitting of a highway network system.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.355-369
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• 2015

Purpose: This study aimed to identify on the attitudes toward the life support care among elderly people using Q methodology. Methods: Thirty-nine elderly people classified 34 selected Q statements into a shape of normal distribution using a 9 point scale. The obtained data were analyzed by using a PQ Method PC program. Results: Principal component analysis identified 4 types of the attitudes toward the life support care among elderly people. Type I is "Situational & Self-determination linear type", type II is "Destiny & Life support care denied type", type III is "Avoidant & Family decision emphasis type" and type IV is "Respect for life & life support care approved type". Most of elderly people have been attitude that wish to receive honor their own decisions toward the prolongation treatment. Conclusion: The findings indicate a need to policy guidelines and public information that express self-determination of elderly people.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.151-159
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• 2017

This paper proposes various policies for improving the process of performance analysis on R&D expenditure of the public funds in the Korean ICT industry. In order to do so, this paper figures out the present issues relating to performance indicators, methodologies for performance evaluation, release and comparison of evaluation results, follow-up study, integrated management system for performance analysis in ICT industry. In this paper, we suggest some new policies such as consulting an expert for improving performance indicators, maintaining the pre-determined performance indicators, introducing the qualitative performance indicators for measuring effectiveness, adopting the new methodologies reflecting R&D characteristics, introducing the new performance index for comparing annual performance, requiring follow-up study for major ICT R&D, introducing the independent and temporary organization for R&D performance analysis in ICT industry. In conclusion, these new policies will raise effectiveness and efficiency of the government R&D expenditure in ICT industry as well as strengthen the industry competitiveness.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.1-14
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• 2015

This study utilizes Monte Carlo simulation to forecast the time charter rate of vessels, the three-month Libor interest rate, and the ship demolition price, to mitigate future uncertainties involving these factors. The simulation was performed 10,000 times to obtain an exact result. For the empirical analysis - based on considerations in ordering ships in 2010-a comparison between the Monte Carlo simulation-based stochastic discounted cash flow (DCF) method and traditional DCF methods was made. The analysis revealed that the net present value obtained through Monte Carlo simulation was lower than that obtained via regular DCF methods, alerting the owners to risks and preventing them from placing injudicious orders for ships. This research has implications in reducing the uncertainties that future shipping markets face, through the use of a stochastic DCF approach with relevant variables and probability methods.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.149-163
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• 2012

Logistics systems provide their service to customers by coordinating the resources with limited capacity throughout the underlying processes involved to each other. To maintain the high level of service under such complicated condition, it is essential to carry out the real-time monitoring and continuous management of logistics processes. In this study, we propose a method of estimating the service completion time of key processes based on process-state information collected in real time. We first identify the factors that influence the process completion time by modeling and analyzing an influence diagram, and then suggest algorithms for quantifying the factors. We suppose the container terminal logistics and the process of discharging and loading containers to a vessel. The remaining service time of a vessel is estimated using a decision tree which is the result of machine-learning using historical data. We validated the estimation model using container terminal simulation. The proposed model is expected to improve competitiveness of logistics systems by forecasting service completion in real time, as well as to prevent the waste of resources.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.49-56
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• 2012

In this paper, we propose the method that decides the shot types using face detection technique. The shot types, such as close-up shot, medium shot, and long shot, can be applied as useful information for understanding narrative structure of movies. The narrative structure of movie is builded by characters. Also their mental and emotional changes become inextricably bound up with them of narrative. The shot types are decided by distance between character and camera. If put together above them, shot types can be found by using detection technique of face size of characters and understand narrative of movie. To do this, we propose the methodology to detect shot type by face detecting and implement the system to do it. Additionally, we evaluate the performance of the system. The implementation system has been evaluated as 95% for close-up shot detection and 90% for medium shot detection, while 53.3% is just detected for long shots.

• Journal of Digital Convergence
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• v.8 no.1
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• pp.93-107
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• 2010

Performance of software development is measured by two major criteria - roductivity and quality. Although the criteria is empirically tested in software engineering research, they often present with a limited way under consideration of a few factors or contexts for developers to focus on the either productivity facets or quality facets. Analyzing data on software development performance collected over a 13-year period from 20 countries, we investigated how major software development factors - development type, development platform, development technique, language type, DBMS, methodology, methodology acquisition, CASE,, summary of work effort, resource level, max team size, affect the performance of software development. The results suggest that productivity and quality of software development are affected by different factors and context: function points, line of code, extreme defects, major defects, or minor defects. This research provides the empirical evidence that the two performance criteria require for software developer to have careful attention to find the optimal balance between the two performance criteria.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.65-74
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• 2021

Recently, studies on Korean spelling correction have been actively conducted based on machine translation and automatic noise generation. These methods generate noise and use as train and data set. This has limitation in that it is difficult to accurately measure performance because it is unlikely that noise other than the noise used for learning is included in the test set In addition, there is no practical error type standard, so the type of error used in each study is different, making qualitative analysis difficult. This paper proposes new 'error type classification' for deep learning-based Korean spelling correction research, and error analysis perform on existing commercialized Korean spelling correctors (System A, B, C). As a result of analysis, it was found the three correction systems did not perform well in correcting other error types presented in this paper other than spacing, and hardly recognized errors in word order or tense.