• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2866-2880
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• 2014

We propose a video denoising method based on Kalman filter to reduce the noise in video sequences. Firstly, with the strong spatiotemporal correlations of neighboring frames, motion estimation is performed on video frames consisting of previous denoised frames and current noisy frame based on intensity and structure tensor. The current noisy frame is processed in temporal domain by using motion estimation result as the parameter in the Kalman filter, while it is also processed in spatial domain using the Wiener filter. Finally, by weighting the denoised frames from the Kalman and the Wiener filtering, a satisfactory result can be obtained. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.137-152
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• 2014

In this paper, I suggest several techniques to estimate covariance matrix and compare the performance of the global minimum variance portfolio (GMVP) in terms of out of sample mean standard deviation and return. As a result, the return differences among the GMVPs are insignificant. The mean standard deviation of the GMVP using historical covariance is sensitive to the estimation window and the number of assets in the portfolio. Among the model covariance, the GMVP using constant systematic risk ratio model or using short sale restriction shows the best performance. The performance difference between the GMVPs using historical covariance and model covariance becomes insignificant as the historical covariance is estimated with longer estimation window. Lastly, the implied volatilities from ELW prices do not lead to superior performance to the historical variance.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.1-7
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• 2010

The efficient safety estimation for a business should analyze an accident data by considering every possible and potential factor. Thus, we consider several factors to build the safety estimation model to meet fairness and rationality. This paper present the yearly statistic data of accident from KOSHA analyze the data by industry, scale, year of service of a employee, age and other factors; build the safety estimation model for the business based on the accident report derived the analysis. The estimation model is established by the weights for accident type, degree, scale, industry, year of service, and age of the employee derived from AHP(Analytic Hierarchy Process).

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.75-81
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• 2017

This paper estimate a desired signal in a correlation wireless communication. The transmitted signal is mixed with the information signal, interference, and noise in wireless channel, and it is incident on the receiver. In this paper, we apply MUSIC algorithm and sub-array method to recover the total rank of the correlation matrix in order to estimation a desired signal among receiving signals. Through simulation, we analyze to compare the proposed method with the classical MUSIC algorithm. As a result of the simulation, the proposed method improved the resolution about 10degrees compared to the conventional MUSIC algorithm. We prove the superiority of the proposed method for the desired signal estimation in correlation channel.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.143-147
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• 2007

This paper presents various interval estimation methods of binomial proportion for small n in multi-product small volume production and extremely small ^P like PPM or PPB fraction of defectives. This study classifies interval estimation of binomial proportion into three categories such as exact, approximate, Bayesian methods. These confidence intervals proposed in this paper can be applied to attribute process capability and attribute acceptance sampling plan for PPM or PPB.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.53-61
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• 2014

In this paper, we proposed covariance weight matrix using SPT matrix in order to accurate target estimation. We have estimated a target using modified covariance matrix and beam steering error method. We have minimized beam steering error in order to estimation desired a target. This method obtain optimum covariance weight using modified SPT matrix. This paper of proposal method is showed good performance than general method. We updated a weight of covariance matrix using modified SPT matrix. We obtain optimum covariance matrix weight to application beam steering error method in order to beam steering toward desired target. Through simulation, we showed that compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.798-805
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• 2005

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expect it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. Above factors make the sales dynamic and unstable. We develop a time series model to evaluate the sales patterns with stockpiling and short term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.179-187
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• 2009

In this paper, an efficient multi-level successive elimination algorithm using the locality in block was proposed for motion estimation. If SAD(sum of absolute difference) is calculated from large absolute difference values to small absolute difference values, SAD is increased rapidly. So, partial distortion elimination in SAD calculation can be done very early. Hence, the computations of SAD calculation can be reduced. In this paper, an efficient algorithm to calculate SAD from large absolute difference values to small absolute difference values by using the locality in block. Experimental results show that the proposed algorithm is an efficient algorithm with 100% motion estimation accuracy for the motion estimation of motion vectors.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.157-167
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• 2006

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expects it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. These factors make the sales dynamic and unstable. In this paper we develop a time series model to evaluate the sales patterns with stockpiling and short-term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.17-24
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• 2016

Many organizations have transformed their business in order to survive and compete in the future. They generate projects by creating a vision, using strategies and objectives with funds aligning strategies and make efforts to complete them successfully because project success leads to business success. All projects have triple constraints such as scope, time, and cost to be completed. Project cost performance is a key factor to achieve project goals and which is mostly related with risks among various cost drivers. Projects require a cost estimation method to complete them within their budget and on time. An accurate budget cannot be estimated due to the uncertainties and risks. Thus some additional money should be funded in addition to the base budget as a contingency reserve for identified risks and a management reserve for unidentified risks. While research on contingency reserve for identified risks included in project budget baseline have been presented, research on management reserve for unidentified risks included in total project budget is still scarce. The lack of research on estimation method and role of the management reserve have made project managers little confidence to estimate project budget accurately with reasonable basis. This study proposes a practical model to estimate budgets including contingency and management reserves for not only project cost management but also to keep the balance of organization's total funds to maximize return on investments for project portfolio management. The advantages of the proposed model are demonstrated by its application to construction projects in Korea and the processes to apply this model for verification are also provided.