• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 춘계학술발표회 논문집
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• pp.229-236
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• 2003

In this study, for efficient replacemen of sensor modelling of high-resolution satellite imagery, image segmentation method is applied to the test area of the SPOT-3 satellite imagery. After that, a third-order polynomial model in the sectioned area is compared with the RFM which is to the entire in the test area. As results, plane error of the third-order polynomial model is lower(approximately 0.8m) than that of RFM. On the other hand, height error of RFM is lower(approximately 1.0m).

• 대한원격탐사학회지
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• 제19권2호
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• pp.149-157
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• 2003

본 연구에서는 향후 지속적으로 제공되어질 고해상도 위성영상의 효율적인 대체 센서모델링을 위하여 SPOT-3호의 위성영상으로부터 대상영역에 영상분할을 실시하고 분할된 영상으로부터 분모항이 없는 RFM 즉, 3차 다항식 모델의 적용성을 고찰하였다. 대상영역 전체에 적용한 분모항이 있는 기존 RFM의 적합도와 비교한 결과, 평면오차는 3차 다항식 모델링 방법이 0.8m 정도 낮게 산출된 반면 표고오차는 기존의 RFM이 1.0m 정도 낮게 산출되었다.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.519-536
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• 1995

In the design of experiments for response surface analysis, sometimes it is of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of response surface is important. This idea was conceptualized by slope rotatability by Hader & Park (1978) and Park (1987). Until now, second order polynomial models were only studied for slope ratatability. In this paper, we will propose the necessary and sufficient conditions for slope rotatability over all directions for the thired order polynomial models in two, three and four independent variables. Also practical slope rotatable designs over all directions for two independent variables are suggested.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.518-523
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• 2002

Nowadays the Rational Function Model (RFM), an abstract sensor model, is substituting physical sensor models for highly complicated imaging geometry. But RFM is algorithm to be required many Ground Control Points (GCP). In case of RFM of the third order, At least forty GCP are required far RFM generation. The purpose of this study is to research more efficient algorithm on GCP and accurate algorithm similar to RFM. The Polynomial Camera Model is relatively accurate and requires a little GCP in comparisons of RFM. This paper introduces how to generate Polynomial Camera Model and fundamental algorithms for construction of 3-D topographic data using the Polynomial Camera Model information in the Kompsat stereo pair and describes how to generate the 3-D ground coordinates by manual matching. Finally we tried to extract height information for the whole image area with the stereo matching technique based on the correlation.

• 전기학회논문지
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• 제67권3호
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• pp.460-466
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• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.98-101
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• 1998

The intermodulation distortion(IMD) due to laser diode nonlinearity of an asynhcronous direct sequence code diviion multiple access(DS/CDMA) system in wireless-optical transmission system model is analzed. A third order polynomial is used to represent laser diode nonlinearity. In DS/CDMA system, only one harmonic of the third-order intermodulation term falls on the signal frequency band and influences the system performance characteristics. To cancel multi-user interference and nonlinear distortion in a DS/CDMA wireless-optical transmission system model, the simple transversal filter structure with N-taps of (N-1) tap delay of 1 chip time delay line is used. It is necessary to select an optimal modulation index that provides a maximum signal-to-noise ratio and the results are useful for CDMA system design.

• 융합정보논문지
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• 제9권6호
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• pp.1-6
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• 2019

본 연구에서는 다항식 회귀분석(Polynomial regression analysis) 방법을 이용하여 비선형 특성을 갖는 전자저울의 질량 추정 모델 개발이 이루어 졌다. 전자저울에 사용되는 로드셀의 출력 단자 전압을 기준 질량 추를 사용하여 직접 측정하였고 이 데이터를 이용하여 MS Office 엑셀의 행렬식 계산과 데이터 추세선 분석 기능을 이용하여 다항식 회귀모델을 구하였다. 5kg까지 측정 가능한 로드셀 전자저울을 사용하여 100g단위로 질량을 측정하였고 다항식 회귀분석(Multiple regression analysis) 모델을 구하였으며, 단순(1차), 2차, 3차 다항식 회귀분석에 대한 오차를 구하였다. 각 모델에 대한 회귀 방정식의 적합도 분석을 위해 결정계수(Coefficient of determination)를 제시하여 추정 질량과 측정 데이터와의 상관관계를 나타내었다. 본 연구에서 제안하는 3차 다항식 모델을 이용하여 추정 값의 표준편차가 10g, 결정계수 1.0으로 상당히 정확한 모델을 얻었다. 본 연구에 사용된 선형 회귀 분석 이론을 바탕으로 최근 인공지능 분야에서 많이 사용되고 있는 로지스틱 회귀 분석(Logistic regression analysis)을 활용하여 기상예측, 신약개발, 경제지표 분석 등의 분야에 대한 다양한 연구를 수행할 수 있을 것으로 생각된다.

• 한국측량학회지
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• 제31권6_1호
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• pp.455-461
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• 2013

아리랑 3호는 2012년 5월 18일에 발사된 다목적실용위성으로서, 탑재된 AEISS센서는 고도 685km의 태양주기 궤도상에서 0.7m의 공간해상도 흑백 영상과 2.8m 공간해상도의 다중 파장대 영상을 폭 16.8km로 획득한다. 아리랑 3호는 아리랑 2호에 비해 많은 부분에서 성능의 향상이 이루어졌으며 그 중 단일 패스에서 스테레오 영상이 취득 가능하도록 설계되었다. 아리랑 3호를 이용하여 3차원 지형 정보의 추출을 하기 위해서는 정확한 에피폴라 기하를 규명하는 것이 필수적이며, 따라서 본 연구에서는 아리랑 3호 스테레오 영상으로부터 에피폴라 영상 제작을 위한 최적의 영상 변환식을 도출하기 위한 에피폴라 곡선의 특성에 대해 분석하였다. 영상과 함께 제공되는 RPCs(Rational Polynomial Coefficients)를 기반으로 영상 전역에 해당하는 에피폴라 커브를 도출하고 이에 대한 모양분석을 통해 에피폴라 커브가 최소 3차 다항식 이상의 변환식으로 모델링 될 수 있음을 알 수 있었다. 또한 아리랑 3호 AEISS센서의 두 개의 CCDs라인 특징 또한 확인 가능하였다. RPCs 업데이트 시에도 샘플 방향의 영상 오차를 최소화하기 위해 3차식이 필요했으며, 에피폴라 영상 리샘플링 시에도 3차 영상 변환식을 활용한 경우 최대 0.7 픽셀이내의 정밀한 y시차를 확보할 수 있었다.

• 한국축산식품학회지
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• 제39권2호
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• pp.222-228
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• 2019

This research was motivated by our encounter with the situation where an optimization was done based on statistically non-significant models having poor fits. Such a situation took place in a research to optimize manufacturing conditions for improving storage stability of coffee-supplemented milk beverage by using response surface methodology, where two responses are $Y_1$=particle size and $Y_2$=zeta-potential, two factors are $F_1$=speed of primary homogenization (rpm) and $F_2$=concentration of emulsifier (%), and the optimization objective is to simultaneously minimize $Y_1$ and maximize $Y_2$. For response surface analysis, practically, the second-order polynomial model is almost solely used. But, there exists the cases in which the second-order model fails to provide a good fit, to which remedies are seldom known to researchers. Thus, as an alternative to a failed second-order model, we present the heterogeneous third-order model, which can be used when the experimental plan is a two-factor central composite design having -1, 0, and 1 as the coded levels of factors. And, for multi-response optimization, we suggest a modified desirability function technique. Using these two methods, we have obtained statistical models with improved fits and multi-response optimization results with the predictions better than those in the previous research. Our predicted optimum combination of conditions is ($F_1$, $F_2$)=(5,000, 0.295), which is different from the previous combination. This research is expected to help improve the quality of response surface analysis in experimental sciences including food science of animal resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2483-2504
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• 2023

Most existing low-light enhancement algorithms either use a large number of training parameters or lack generalization to real-world scenarios. This paper presents a novel lightweight and robust pixel-wise polynomial approximation-based deep network for low-light image enhancement. For mapping the low-light image to the enhanced image, pixel-wise higher-order polynomials are employed. A deep convolution network is used to estimate the coefficients of these higher-order polynomials. The proposed network uses multiple branches to estimate pixel values based on different receptive fields. With a smaller receptive field, the first branch enhanced local features, the second and third branches focused on medium-level features, and the last branch enhanced global features. The low-light image is downsampled by the factor of 2b-1 (b is the branch number) and fed as input to each branch. After combining the outputs of each branch, the final enhanced image is obtained. A comprehensive evaluation of our proposed network on six publicly available no-reference test datasets shows that it outperforms state-of-the-art methods on both quantitative and qualitative measures.