• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.2
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• pp.217-222
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• 2004

In this paper, the efficient channel estimation schemes for DRM system(AM band digital radio broadcasting standard) are investigated. In frequency domain, by means of the linear interpolation, the second order interpolation, cubic spline interpolation, and time domain interpolation, the channel impulse response is estimated respectively to compensate the attenuation due to the fading. And in time domain, the frequency channel impulse response is averaged to reduce the attenuation due to the AWGN. By the simulation, the performance of MSE, BER and the complexity of calculation is compared and analyzed for each interpolation scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.681-683
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• 2017

In the digital information age, image processing is essential for various digital devices such as smart phones, cameras, and TVs. However, degradation occurs in analyzing, recognizing, and processing image data, and salt & pepper noise occurs. Therefore, in this paper, we applied linear interpolation method, newton interpolation method, lagrange interpolation method, and spline interpolation method to the image damaged by salt & pepper noise in order to find more effective interpolation method in salt & pepper noise environment, The methods were compared using the PSNR (peak signal to noise ratio).

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1835_1836
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• 2009

본 논문에서는 비접촉식 미세 측정 광학기에 의해 측정된 이미지를 Stitching 기술과 B-Spline 보간법에 의해 보다 빠르고, 정밀한 복원 기법을 제안한다. 이를 위해 먼저 각각의 이미지로부터 매칭, 피매칭 템플릿(Template)을 검출한다. 그런 다음 두 이미지의 오버랩(Overlap)되는 부분을 기준하여 기준면으로부터 roll, pitch, yaw 오차를 계산하여 매칭시킨다. 마지막으로, B-Spline 보간법에 의해 매칭된 부분을 연속화한다. 제안된 방법은 실험을 통해 그 응용 가능성을 증명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.590-593
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• 2002

A study on gray image morphing using 2D spline interpolation and 2D wavelet transform is presented. The B-spline of splines is used for interframe specified points to determine and the wavelet transform of transforms is applied for generating interframe images. The results are a smoothing image transfer by 2D spline and a removed degrading images as a blotting by 2D wavelet transform is making a good morphing image.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.307-309
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• 2003

VoIP를 이용한 인터넷 전화에서 패킷 손실로 인한 음질 저하는 큰 문제이다. 본 논문에서는 VoIP에서 가장 많이 쓰이는 코덱 중 하나인 G.729 에서의 기존 패킷 손실 복구 방법들을 살펴보고 성능을 개선하고자 한다. 제안한 방법은 보간법의 적용을 위해 LSP 파라미터와 FCB 이득 파라미터의 미래값을 추정하며, 연속된 패킷 손실에서의 파라미터 자연성을 높이기 위해 LSP 파라미터와 ACB 길이 파라미터를 선택적으로 3차 spline 보간한다. TMIT 등의 환경에서 기존의 방법과 제안한 방법의 SD를 비교하여 객관적 평가를 수행하였고, 실험 결과 제안한 방법으로 성능이 개선됨을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.413-418
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• 2011

The thermodynamic properties of steam table are obtained by measurement or approximate calculation under appropriate assumptions. Therefore they are supposed to have basic measurement errors. And thermodynamic properties should be modeled through function approximation for using in numerical analysis. In order to make noised thermodynamic properties corresponding to measurement errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. Both neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure and temperature. In analysis spline interpolation method gives much less relative errors than neural networks at both ends of data. Excluding the both ends of data, the relative errors of neural networks is generally within ${\pm}0.2%$ and those of spline interpolation method within ${\pm}0.5$~1.5%. This means that the neural networks give smaller relative errors compared with quadratic spline interpolation method within range of use. From this fact it was confirmed that the neural networks trace the original values better than the quadratic interpolation method and neural networks are more appropriate method in modelling the saturated steam table.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.479-491
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• 2004

Location information of mobile objects is applied to vehicle tracking, digital battlefields, location based services, and telematics. Their location coordinates are periodically measured and stored in the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the mobile object moving on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function, although the proposed location estimation function uses the small amount of information. The proposed method has an advantage that drops the cost of data storage space and communication for the management of location information of the mobile objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2008-2013
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• 2006

In numerical analysis on evaluating the thermal performance of the thermal equipment, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table itself cannot be used without modelling. In this study applicability of neural networks in modelling the wide temperature range of wet saturated vapor region was examined. the multi-layer neural network consists of a input layer with 1 node, two hidden layers with 10 and 20 nodes respectively and a output layer with 6 nodes. Quadratic and cubic spline interpoations methods were also applied for comparison. Neural network model revealed similar percentage error to spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the wide range of the steam table.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.43-50
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• 2019

Purpose The principle of nuclear medicine test is divided into two main categories: competition(radioimmunoassay, RIA) and noncompetitive reaction(Immunoradiometric assay, IRMA). It is known that the curve fitting method, which is commonly used in inspection field, uses Spline interpolation in RIA method and Linear interpolation method in IRMA method. Among them, the insulin test using the IRMA test showed a significant difference, especially at low concentrations, despite the same algorithm of linear interpolation between fully automated radio immunoassay analyzers. In this study, we aim to obtain results from applying two different of algorithm using fully automated radio immunoassay analyzers including Gamma pro, Gamma 10, Cobra, and SR300. Materials and Methods A total of 30 test samples were selected for the test of TSH, ferritin, C-peptide, and insulin serum levels. Test was performed by IRMA method. We compared the difference in the results of applying the linear interpolation method and the spline interpolation method to Gamma Pro, Gamma 10, Cobra, and SR300 equipment. Results Two-way ANOVA was used for statistical analysis. The significance level was applied as P <0.05. The results of TSH, ferritin, C-peptide, and insulin tests were compared between the fully automated radio immunoassay analyzers. There was a significant difference between ferritin, C-peptide, and insulin serum levels(P<0.001). TSH didn't show any significant different between the devices(P=0.29). In the difference between linear and spline interpolation, there was no significant difference between insulin test(P=0.08), TSH test(P=0.81), and Ferritin test(P=0.06). However, C-peptide test showed a significant difference(P=0.03). Especially, the insulin test showed significant difference in lower ranges. As a result of comparing and analyzing the difference between the two interpolation methods, the devices in the low concentration group showed significant difference(P<0.001). Conclusion In case of new equipment in the laboratory it is necessary to recognize that there is a difference in the curve fitting method for each automated radio immunoassay analyzers in the low concentration area when the principle of inspection is IRMA method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.161-164
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• 2003

A study on the gray images morphing using morphology and spline interpolation is realized. The adapted method is that join the 2 broken line together with the dilation of morphology to the morphing image, remove the holes to be a soft edge at the image boundaries and extract the featuring points with the cubic spline interpolation. As a result of experiment the method elicits more smoothing image morphing in detail and speed up the interframe processing.