• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.17-22
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• 2014

Watermarking is one of the methods that insist on a copyright as it append digital signals in digital informations like still mobile image, video, other informations. This paper proposed an improved DCT-based watermarking scheme using quantized coefficients of image. This process makes quantized coefficients through a Discrete Cosine Transform and Quantization. The watermark is embedded into the quantization coefficients in accordance with location(key). The quantized watermarked coefficients are converted to watermarked image through the inverse quantization and inverse DCT. Watermark extract process only use watermarked image and location(key). In watermark extract process, quantized coefficients is obtained from watermarked image through a DCT and quantization process. The quantized coefficients select coefficients using location(key). We perform it using inverse DCT and get the watermark'. Simulation results are satisfied with high quality of image (PSNR) and Normalized Correlation(NC) from the watermarked image and the extracted watermark.

• Journal of the Korean GEO-environmental Society
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• v.11 no.12
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• pp.63-74
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• 2010

Normally consolidated and slightly overconsolidated soft clay layer is widely distributed in the south coast of Korea. To ensure the efficient and economical construction design of any structure to be built on this soft soil, exhaustive studies related to geotechnical and physical engineering properties are required. In this study, the relationship of the physical properties of southern Gwangyang marine clay in the Korea Peninsula were examined, including natural water content, specific gravity, total unit weight, initial void ratio, liquid limit, plastic limit, and physical properties of activity and soil parameters. For the parameter relationship analysis, the latest relatively reliable data on the large harbor construction work were used, optimum values were deducted with linear regression and non-linear regression between soil parameters, water content or initial void ratio appears to be very large. Moreover, in the linear and involution pattern regression, equal coefficient of determination appeared. The relationship of the different parameters was shown to be excellent in the non-linear regression of involution equation and exponential equation pattern compared with the findings of linear regression analysis.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.309-310
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• 2010

본 논문에서는 패턴 분석 기반의 비접촉 사용자 인터페이스 제어 기법을 제안한다. 본 기법은 카메라가 장착된 기기에서 입력 받은 실시간 영상을 사용하여 패턴의 정보를 분석한다. 정의된 패턴을 기반으로 최초의 패턴 위치를 예측하고, 특징점 추출 기반 추적 기법을 통해 패턴의 위치를 갱신한다. 휴대용 기기의 다양한 사용 환경에 적합하도록, 정규 상관 계수와 특징점 추출 정보를 사용하여 패턴의 예측, 추적을 수행함으로써 밝기 변화에 강인한 사용자 인터페이스 기법을 제안한다. 실험을 통하여 본 논문이 제안하는 알고리즘이 기존의 방법에 비해 우수한 성능을 나타냄을 확인한다.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1139-1148
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• 2011

Team standings in the regular professional baseball league should be determined based on a reasonable criterion; however, an unreasonable Japanese method is being used in Korea as of 2011. In this paper, we suggest a new method of computing the percentage of victories constructed by combining the advantages of the methods to determine team standings used in Korean professional baseball. We also have applied preexistent methods and suggested method to past and present Korean professional baseball data.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.536-538
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• 2023

수출의존도가 높은 한국은 코로나19 팬데믹, 우크라이나-러시아 전쟁 등 대외환경의 변화에 따른 수출 여건에 민감할 수 밖에 없는 환경이다. 이에 발 빠르게 대응하기 위해 정확한 수출증감률 예측이 필요하며 이를 가장 잘 수행할 수 있는 예측모델을 찾고자 한다. 수출에 영향을 끼치는 주요변수 선정 후, min-max 정규화를 시행하고 변수간 상관계수와 다중공선성 확인을 통해 변수를 축소했다. 그리고 머신러닝 예측모델로 많이 사용되는 Linear Regression, Decision Tree, Gradient Boost Regressor, Random Forest 4가지 모델에 대입하여 수출 증감률 예측 정확도를 비교했다. 그 결과, Linear Regression의 MSE가 0.087로 가장 낮아 제일 우수한 모델이라는 결론에 도달했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.713-716
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• 2007

오늘날 인간 프로젝트와 같은 종합적인 연구의 궁극적 목적을 달성하기 위해서는 이들 연구로부터 획득한 대량의 관련 데이터에 대해 새로운 현실적 의미를 부여할 수 있어야 한다. 따라서 현재의 마이크로어레이 기술을 이용해서 효과적으로 종양을 분류하기 위해서는 특정 종양 분류와 밀접하게 관련이 있는 정보력 있는 유전자를 선택하는 과정이 필수적이다. 본 논문에서는 암에 걸린 흰쥐 외피 기간 세포 분화 실험에서 얻어진 3840 유전자의 마이크로어레이 cDNA를 이용해 데이터의 정규화를 거쳐 유사성 척도 방법으로 정보력 있는 유전자들을 추출한 후, DT, NB, SVM, MLP 알고리즘을 이용하여 클래스 분류 모델을 구축하고, 성능을 비교분석하였다. 피어슨 적률 상관 계수를 이용하여 선택된 50 유전자들을 멀티퍼셉트론 분류기로 분류한 결과 94.8%의 정확도를 보여 가장 최적의 조합을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.520-528
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• 2003

This paper proposes a method of implementing synthetic stereo and an acoustic echo cancellation algorithm for multiple participant conference system. Synthetic stereo is generated by HRTF and two loudspeakers. A robust adaptive algorithm for synthetic stereo echo cancellation is proposed to reduce the weight misalignment due to near-end speech signals and ambient noises. The proposed adaptive algorithm is modified version of SMAP algorithm and the coefficients of adaptive filter is updated with cross correlation of input and estimation error signal normalized with sum of the autocorrelation of input signal and the power of the estimation error signal multiplied with projection order. This is more robust to projection order and ambient noise than conventional SMAP. Computer simulation show that the proposed algorithm effectively attenuates synthetic stereo acoustic echo.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.9
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• pp.616-623
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• 2001

Effects of the grating period fluctuation on the wavelength distribution have been studied by an effective index transfer matrix method in quarter wavelength shifted (QWS) DFB lasers. The wavelength distribution is expressed by a probability density that is an analytical function of the correlation coefficient and normalized standard deviation of the grating period fluctuation. The probability density function of wavelength distribution is shown to be nearly Gaussian, and its standard deviation increases with normalized standard deviation of the grating period fluctuation, and decreases with the negative correlation between adjacent half-periods.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.671-676
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• 2016

Recently, according to the limelight of Fintech, simple payment using biometric at smartphone is widely used. In this paper, we propose a new contactless biometric method using thumb image without additional sensors unlike previous biometrics such as fingerprint, iris, and vein recognition. In our method, length, width, and skin texture information are used as features. For that, illumination normalization, skin region segmentation, size normalization and alignment procedures are sequentially performed from the captured thumb image. Then, correlation coefficient is calculated for similarity measurement. To analyze recognition accuracy, genuine and imposter matchings are performed. At result, we confirmed the FAR of 1.68% at the FRR of 1.55%. In here, because the distribution of imposter matching is almost normal distribution, our method has the advantage of low FAR. That is, because 0% FAR can be achieved at the FRR of 15%, the proposed method is enough to 1:1 matching for payment verification.

• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.75-81
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• 2000

The anisotropy of soils has an important effect on stress-strain behavior. In this study, an attempt has been made to implement artificial neural network model for modeling the stress-strain relationship and predicting the undrained shear strength of normally consolidated clay with varying consolidation pressure ratios. The multi-layer neural network model, adopted in this study, utilizes the error back-propagation loaming algorithm. The artificial neural networks use the results of undrained triaxial test with various consolidation pressure ratios and different effective vertical consolidation pressure fur learning and testing data. After learning from a set of actual laboratory testing data, the neural network model predictions of the undrained shear strength of the normally consolidated clay are found to agree well with actual measurements. The predicted values by the artificial neural network model have a determination coefficient$(r^2)$ above 0.973 compared with the measured data. Therefore, this results show a positive potential for the applications of well-trained neural network model in predicting the undrained shear strength of cohesive soils.