• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.303-311
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• 1998

We developed a pattern drafting computer program using a popular CAD program for the purpose of the automatic manufacturing and education based on the concept of the easy -order-system which can easily reflect body characteristics and design favors of individuals to the ready-made clothing. The programs were written in Auto LISP which can utilise most of frictions of the Auto CAD, and the result of the design for an full-pleated skirt was shown. Also, we devised an easy way to set the location of reference points by inputting of tangential angle only for the use of the cubic spline curve which can represent body shape very well. Finally, by marking down all of symbols needed in manufacturing process, we completed the automatic pattern drafting program to make it useful as an industrial pattern without any amendment or correction in cutting and sewing operation.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.23-27
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• 2024

Underwater images are typically degraded due to color distortion, light absorption, scattering, and noise from artificial light sources. Restoration of these images is an essential task in many underwater applications. In this paper, we propose a two-phase deep learning-based method, Underwater Deep Curve Estimation (UWDCE), designed to effectively enhance the quality of underwater images. The first phase involves a white balancing and color correction technique to compensate for color imbalances. The second phase introduces a novel deep learning model, UWDCE, to learn the mapping between the color-corrected image and its best-fitting curve parameter maps. The model operates iteratively, applying light-enhancement curves to achieve better contrast and maintain pixel values within a normalized range. The results demonstrate the effectiveness of our method, producing higher-quality images compared to state-of-the-art methods.

• Journal of Environmental Policy
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• v.10 no.4
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• pp.3-37
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• 2011

This paper investigates the existence of the environmental Kuznets curve (EKC) for carbon dioxide $CO_2$ emissions and its causal relationships with economic growth and openness by using time series data (1971-2006) from China (an emerging market), Korea (a newly industrialized country), and Japan (a developed country). The sample countries span a whole range of development stages from industrialized to newly industrialized and emerging market economies. The environmental consequences according to openness and economic growth do not show uniform results across the countries. Depending on the national characteristics, the estimated EKC show different temporal patterns. China shows an N-shaped curve while Japan has a U-shaped curve. Such dissimilarities are also found in the relationship between $CO_2$ emissions and openness. In the case of Korea, and Japan it represents an inverted U-shaped curve while China shows a U-shaped curve. We also analyze the dynamic relationships between the variables by adopting a vector auto regression or vector error correction model. These models through the impulse response functions allow for analysis of the causal variable's influence on the dynamic response of emission variables, and it adopts a variance decomposition to explain the magnitude of the forecast error variance determined by the shocks to each of the causal variables over time. Results show evidence of large heterogeneity among the countries and variables impacts.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.295-300
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• 2013

The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.

• 전자공학회논문지 IE
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• v.46 no.3
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• pp.12-18
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• 2009

In this paper, we developed white balance correction processor for Full Color LED Display System which could be display uniformity color and soft light by adjusting brightness of red, green, blue pixel, individually. This processor correct brightness by calculating operating current of each pixel(red, green, blue LED) on the basis of characteristic curve of LED device when we named "a" as a specific characteristic value, "b" as a brightness correction value according to using time, "X" as a operating current value, and "Y" as brightness value. As the results, we solved the reduction problem of brightness for long used LED devices, according to increase entire mean of brightness value by adjusting "b" value from the brightness characteristic function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.881-886
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• 2013

Even though a multi-view camera system is able to capture multiple images at different viewpoints, the color distributions of captured multi-view images can be inconsistent. This problem decreases the quality of multi-view images and the performance of post-image processes. In this paper, we propose an improved polynomial model for effectively correcting the color inconsistency problem. This algorithm is fully automatic without any pre-process and considers occlusion regions of the multi-view image. We use the 5th order polynomial model to define a relative mapping curve between reference and source views. Sometimes the estimated curve is seriously distorted if the dynamic range of extracted correspondences is quite low. Therefore we additionally estimate the first order polynomial model for the bottom and top regions of the dynamic range. Afterwards, colors of the source view are modified via these models. The proposed algorithm shows the good subjective results and has better objective quality than the conventional color correction algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.63-73
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• 2011

The Pseudorange Corrections (PRC), which are used in DGPS as calibration messages, can contain outliers, noise, and anomalies, and these abnormal events are unpredictable. When those irregular PRC are used, the positioning error gets higher. In this paper, we propose a strategy of detecting and correcting outliers, noise, and anomalies by modeling the changing pattern of PRC through polynomial curve fitting techniques. To validate our strategy, we compared positioning errors obtained without PRC calibation with those with PRC calibration. As a result, we found that our algorithm performs very well; the horizontal RMS error was 3.84 m before the correction and 1.49 m after the correction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.718-725
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• 2016

In this study, the plastic flow curve of commercially pure titanium sheet (CP Ti) actively used in the plate heat exchanger etc., was evaluated. The plastic flow curve known as hardening curve is a key factor needed in conducting finite element analyses (FEA) for the forming process of a sheet material. A hydraulic bulge test was performed on the CP Ti sheet and the strain in this test was measured using the DIC method and ARAMIS system. The measured true stress-true strain curve from the hydraulic bulge test (HBT) was compared with that from the tensile test. The measured true stress-true strain curve from the hydraulic bulge test showed stable plastic flow curve over the strain range of 0.7 which cannot be obtained in the case of the uniaxial tensile test. The measured true stress-true strain curve from the hydraulic bulge test can be fitted well by the hardening equation known as the Kim-Tuan model.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.83-88
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• 2002

An over current relay(OCR), one of the most frequently used protective devices, has time-current characteristics (TCC) to control its trip time according to the current level. It is because an appropriate operating time interval is necessary for coordination with other protective devices. A set of TCC curves of an OCR is, in general, given by the supplier from which a curve is selected by the operator. Therefore, in many cases, it is impossible to consider the operation condition of the given power system exactly. A novel concept of an OCR is suggested in this paper. The proposed OCR has an internal correction module so that it may produce the most adequate TCC curve according to the given protective information for coordination with other devices. With the generated TCC curve, a variety of operation and coordination conditions can be taken into consideration in an effective manner. The suggested OCR is applied to a simple test power system to show very promising results from a coordination point of view.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.16-22
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• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.