• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.594-597
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• 2003

본 논문에서는 비디오 패킷 손실 복구를 위한 새로운 시간적 에러 은폐기법을 제안한다. 제안된 기법에서, 영상의 손실된 블록은 먼저 시간적 에러은폐 기법이 적용되고, 얻어진 결과에 대해 공간적 스무딩 기법이 적용된다. 제안된 공간적 스무딩 기법은 시간적 에러은폐 기법이 적용된 블럭과 손실되지 않은 인접 블록 사이의 불연속을 제거하거나 최소화하는데 적용된다. 제안된 기법은 기존의 여러 가지 시간적 에러 은폐 기법에 대해 컴퓨터 모의 실험을 행한 결과, 객관적, 주관적 성능을 상당히 개선시킴을 확인할 수 있었다.

• 한국정보통신학회논문지
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• 제7권8호
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• pp.1708-1713
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• 2003

본 논문에서는 비디오 패킷 손실을 위한 새로운 시간적 에러 은폐 기법을 제안한다. 각 손실 블록에 대한 에러 은폐는 시간적 움직임 보상을 바탕으로 보상된 블록과 주변 블록간의 경계에 대한 공간적 스무딩 동작에 의해 수행된다. 모의실험에서 제안된 기법은 기존의 기법들에 비해 약 2㏈의 화질 향상을 가져왔다.

• Journal of Radiation Protection and Research
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• 제42권2호
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• pp.91-97
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• 2017

Background: A gamma energy identifying algorithm using spectral decomposition combined with smoothing method was suggested to confirm the existence of the artificial radio isotopes. The algorithm is composed by original pattern recognition method and smoothing method to enhance the performance to identify gamma energy of radiation sensors that have low energy resolution. Materials and Methods: The gamma energy identifying algorithm for the compact radiation sensor is a three-step of refinement process. Firstly, the magnitude set is calculated by the original spectral decomposition. Secondly, the magnitude of modeling error in the magnitude set is reduced by the smoothing method. Thirdly, the expected gamma energy is finally decided based on the enhanced magnitude set as a result of the spectral decomposition with the smoothing method. The algorithm was optimized for the designed radiation sensor composed of a CsI (Tl) scintillator and a silicon pin diode. Results and Discussion: The two performance parameters used to estimate the algorithm are the accuracy of expected gamma energy and the number of repeated calculations. The original gamma energy was accurately identified with the single energy of gamma radiation by adapting this modeling error reduction method. Also the average error decreased by half with the multi energies of gamma radiation in comparison to the original spectral decomposition. In addition, the number of repeated calculations also decreased by half even in low fluence conditions under $10^4$ ($/0.09cm^2$ of the scintillator surface). Conclusion: Through the development of this algorithm, we have confirmed the possibility of developing a product that can identify artificial radionuclides nearby using inexpensive radiation sensors that are easy to use by the public. Therefore, it can contribute to reduce the anxiety of the public exposure by determining the presence of artificial radionuclides in the vicinity.

• Industrial Engineering and Management Systems
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• 제8권4호
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• pp.257-263
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• 2009

Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.

• 소성∙가공
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• 제12권4호
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• pp.340-347
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• 2003

In the rigid-plastic finite element simulation of hot forging processes using hexahedral mesh, remeshing of a flash is important for design and control of the process to obtain desirable defect-free products. The mesh compression method is a remeshing technique which enables the construction of an effective hexahedral mesh in the flash. However, because the mesh is distorted during the compression procedure of the mesh compression method, when it is used in resuming the analysis, it causes discretization error and decreases the conversance rate. Therefore, mesh smoothing is necessary to improve the mesh quality. In this study, several geometric mesh smoothing techniques and optimization techniques are introduced and modified to improve mesh quality. Then, the most adaptive technique is recommended for the mesh compression method.

• Journal of Astronomy and Space Sciences
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• 제21권4호
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• pp.371-382
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• 2004

GPS 단일 주파수(L1) 수신기의 상대 측위 정밀도 향상을 위해 가중 평활화 기법(weighted smoothing technique)을 적용하고 다양한 기선에 대해 자료 처리를 수행하였다. C/A 코드를 이용한 의사거리의 측정 오차를 최소화하기 위하여 위상 가중 평활화 기법을 활용하였으며, 위상 신호의 끊김 현상으로 인한 결과를 보완하기 위해 위치 평활화 기법을 적용하였다. 대전에 위치한 IGS 기준점을 기점으로 중${\cdot}$장기선(5km, 10km, 30km, 40km, 150km)에 대해 자료 처리를 수행하였으며, 이때 기선에 따라 대기 모델(이온층${\cdot}$대류층)등 추가적인 오차 요인들을 고려하였다. 이 논문은 이러한 가중 평활화 기법을 활용하여 시간이 경과함에 따라 보다 안정적인 결과를 산출할 수 있었음을 제시하고 있으며, 사이클 슬립등 주의 환경에 민감한 오차들은 위치 평활화 기법을 써서 보완할 수 있음을 나타내고 있다. 이러한 결과들을 토대로 가중 평활화 기법을 실시간 응용분야는 물론 후처리 응용분야에도 적용이 가능함을 발견하였고, 이러한 기법들은 반송파 위상 자료를 이용하는 모호 정수 결정기술과 유사한 결과를 산출할 수 있어, 대체 기법으로 활용가능 할 것으로 기대된다.

• 전기학회논문지
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• 제63권11호
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• pp.1497-1502
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• 2014

Electric load forecasting is essential for stable electric power supply, efficient operation and management of power systems, and safe operation of power generation systems. The results are utilized in generator preventive maintenance planning and the systemization of power reserve management. Development and improvement of electric load forecasting model is necessary for power system maintenance and operation. This paper proposes daily maximum electric load forecasting methods for the next 4 weeks with a seasonal autoregressive integrated moving average model and an exponential smoothing model. According to the results of forecasting of daily maximum electric load forecasting for the next 4 weeks of March, April, November 2010~2012 using the constructed forecasting models, the seasonal autoregressive integrated moving average model showed an average error rate of 6,66%, 5.26%, 3.61% respectively and the exponential smoothing model showed an average error rate of 3.82%, 4.07%, 3.59% respectively.

• 한국진공학회지
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• 제5권2호
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• pp.99-106
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• 1996

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonhstrates its excellent utility for the complex depth profile system . It includes the stable restoration of depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.413-423
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• 2005

Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

• 응용통계연구
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• 제25권6호
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• pp.1049-1058
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• 2012

Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.