• Journal of the Korea Organic Resources Recycling Association
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• v.23 no.4
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• pp.52-62
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• 2015

This study estimated the contribution rates of inlet air flow, moisture content, air-filled porosity and particle size on the total pressure drop for the sawdust used as the bulking agent in the composting. The statistical model for pressure drop including the affecting factors was proposed.($R^2=0.998{\sim}0.950$) While the laminar air flow(v) and particle size(SIZE*v) had the positive relations to the total pressure drop, the turbulent air flow($v^2$), moisture content(MC*v) and air-filled porosity(AFP*v) had the negative relations. Total pressure drop sharply increased with increasing of the inlet air flow. And the most significant factors affecting to total pressure drop were the particle size(SIZE*v) as positive factor and air-filled porosity(AFP*v) as negative factor. The contribution rate to total pressure drop by the particle size(SIZE*v) was continuously increased with increasing of the inlet air flow, but the contribution rate by air-filled porosity(AFP*v) was decreased. And total pressure drop was little changed even though the increasing of moisture content above the range of dry moisture content 0.25. The contribution rates of affecting factors had the different tendencies with increasing of the moisture content, especially in the negative factors as air-filled porosity(AFP*v) and moisture content(MC*v). For effective composting process, it is preferable to select the sawdust with higher air-filled porosity as bulking agent to enhance the air permeability.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.458-460
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• 1998

본 논문은 주성분 분석으로 시점 기반 고유얼굴(view-based eigenface)을 생성하고, 그에 기반한 얼굴 인식을 수행하고자 한다. 주성분 분석을 통한 고유얼굴 생성은 얼굴 인식의 어려운 문제 중 하나인 특징 선택과 추출이라는 문제를 해결해 준다. 또한 얼굴 표정이나 방향의 변화에도 인식률이 저하되는 것을 방지할 수 있다. 얼굴 영상을 특징공간(고유공간)으로 변환할 때, 원 얼굴영상의 정보를 최대한으로 나타낼 수 있는 최적의 고유치 개수 선택은 얼굴 데이터베이스의 크기와 인식 속도에 영향을 끼친다. 따라서 본 논문에서는 고유치 개수를 고유치의 누적기여율을 이용해서 구한다. 이는 64$\times$64(=4096)차원의 원 얼굴 영상을 5~7차원으로 표현 가능하게 하였다. 그리고, 각 얼굴 방향에 따라 특징공간을 분리해서 생성함으로써 얼굴 방향의 변화에 따라 오인식률을 줄였다. 축소된 차원과 분리된 특징공간은 메모리 사용과 인식속도의 향상에 기여한다. 본 논문에서 얼굴의 인식은 Mahalanobis distance와 재구성 오차율을 고려해서 이루어졌다. 실험은 개인당 세가지 다른 방향을 가지는 얼굴 영상을 이용하여 이루어졌고, 실험결과, 약 93%의 인식률을 보여주었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.359-362
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• 2013

최근 지능형 차량에 대한 관심이 늘어나면서 차선검출에 대한 관심도 많이 늘어나고 있다. 그 중에서도 실시간 적용을 위하여 연산량이 적은 허프변환을 이용한 차선검출 방법이 많이 연구되고 있다. 하지만 허프변환은 안개와 같은 열악한 환경에서와 같이 에지성분이 두드러지게 나타나지 않은 경우에 대해서는 정확한 차선검출이 어렵다는 단점을 가지고 있다. 따라서 본 논문에서는 열악한 환경의 영상에 차선의 에지를 강조하는 전처리를 수행하고 허프변환을 이용하여 차선검출을 수행하는 방식을 제시한다. 제안하는 전처리 방법은 처리 속도와 성능에서 기존의 전처리 기법과 비교하여 높은 처리속도와 차선 검출률을 보였다. 특히 안개와 같은 열악한 영상에서의 결과에서 기존의 전처리 방법보다 제안한 전처리 방법이 더 높은 검출률을 보였다.

• Journal of the Korean Geotechnical Society
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• v.31 no.9
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• pp.17-27
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• 2015

We perform a series of experimental tests to evaluate whether the shear strength of clean sands can be reliably predicted from shear wave velocity. Isotropic drained triaxial tests on clean sands reconstituted at different relative densities are performed to measure the shear strength and bender elements are used to measure the shear wave velocity. Laboratory tests reveal that a correlation between shear wave velocity, void ratio, and confining pressure can be made. The correlation can be used to determine the void ratio from measured shear wave velocity, from which the shear strength is predicted. We also show that a unique relationship exists between maximum shear modulus and effective axial stress at failure. The accuracy of the equation can be enhanced by including the normalized confining pressure in the equation. Comparisons between measured and predicted effective friction angle demonstrate that the proposed equation can accurately predict the internal friction angle of granular soils, accounting for the effect of the relative density, from shear wave velocity.

• Journal of IKEEE
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• v.18 no.4
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• pp.581-585
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• 2014

In this paper, we propose a pedestrian detection by applying the HOG feature using ROI. Conventional HOG method has high accuracy, but shows the disadvantage of slow processing speed. By applying the ROI to the conventional method reduce computations for unnecessary area. Therefore proposed method improves the processing speed. In order to set the ROI area, we propose a structure that combined odd frames and even frames. Odd frame is in charge of operation for the entire area. And even frame does the operation for the ROI area. Implementation results of proposed method maintaining the same accuracy as the conventional method show a 20% improved performance of 8.3 frames per second.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.11-12
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• 2016

플래시 메모리의 수요가 증가하면서, 플래시 메모리를 기반으로 한 SSD는 빠른 I/O 속도를 보이며 충격에 강하고, 저전력과 비휘발성인 특징을 가지고 있다. 하지만 플레시 메모리는 지우기와 쓰기 성능이 읽기 작업에 비해 현저히 느리다는 단점이 있다. 본 논문에서는 버퍼에서 각 논리 페이지가 hot 또는 cold 인지를 정확히 예측할 수 있는 PSO 기반의 버퍼 관리 모델을 제안한다. 이러한 모델을 통하여 기존 모델에서의 기법보다 읽기 및 쓰기 적중 횟수와 적중률이 향상되는 것을 증명하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.48-53
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• 2002

In this paper, we presented a new approach to the recognition of unconstrained handwritten numerals using an improved RBF(Radial Basis Function) Neural Networks. The RBF Neural Networks used Raised Cosine as a basis function to improve discrimination and reduce processing time. The performance of Raised Cosine RBF Neural Networks classifier was evaluated using totally unconstrained handwritten numeral database of Concordia University, Montreal, Canada, and the experimental results showed the recognition rate of 98.05%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.451-457
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• 2020

Format recognition and OCR techniques are widely used as methods for detecting and protecting personal information from electronic documents. However, due to the poor recognition rate of the OCR engine, personal information cannot be detected or false positives commonly occur. It also takes a long time to analyze a large amount of electronic documents. In this paper, we propose a method to improve the speed of image analysis of electronic documents, character recognition rate of the OCR engine, and detection rate of personal information by improving the existing method. The analysis speed was increased using the format recognition method while the analysis speed and character recognition rate of the OCR engine was improved by image correction. An algorithm for analyzing personal information from images was proposed to increase the reconnaissance rate of personal information. Through the experiments, 1755 image format recognition samples were analyzed in an average time of 0.24 seconds, which was 0.5 seconds higher than the conventional PAID system format recognition method, and the image recognition rate was 99%. The proposed method in this paper can be used in various fields such as public, telecommunications, finance, tourism, and security as a system to protect personal information in electronic documents.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.39-47
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• 2019

In this paper, we proposed extracting modified Histogram of Oriented Gradients (HOG) features using background removal when tracking pedestrians in real time. HOG feature extraction has a problem of slow processing speed due to large computation amount. Background removal has been studied to improve computation reductions and tracking rate. Area removal was carried out using S and V channels in HSV color space to reduce feature extraction in unnecessary areas. The average S and V channels of the video were removed and the input video was totally dark, so that the object tracking may fail. Histogram equalization was performed to prevent this case. HOG features extracted from the removed region are reduced, and processing speed and tracking rates were improved by extracting clear HOG features. In this experiment, we experimented with videos with a large number of pedestrians or one pedestrian, complicated videos with backgrounds, and videos with severe tremors. Compared with the existing HOG-SVM method, the proposed method improved the processing speed by 41.84% and the error rate was reduced by 52.29%.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.392-394
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• 1999

PSTN(Public Switch Telephone Network)에서 동영상을 전송하기 위해 H.263이라는 표준이 발표되었다. 저속의 전송률을 가지는 PSTN을 이용해서 영상회의나 영상전화 등을 구현하기 위해서는 기존의 코딩방식으로는 데이터를 전송하는데 문제점이 많았다. 이를 위해서 개발된 것이 H.263이다. H.263은 H.261에 기반을 두고 있으며 .261에 비해서 동일화질을 제공하는데 반정도의 데이터 양으로도 가능하게 해준다. 영상 압축 Encoder는 일반적으로 Decoder에 비하여 영상을 처리하는데 많은 시간이 소요된다. 그러나 VOD등과 같은 실시간으로 압축할 필요가 없는 경우에 대해서는 인코더가 많은 시간을 소비하더라고 큰 문제가 없는 반면에, 영상 회의나 영상 전화 등은 실시간 영상 Encoding, Decoding을 수행해야 한다. 그러기 위해서 고가의 하드웨어를 사용하게 된다. 이와 같은 이유에서 본 연구에서는 H.263을 소프트웨어만으로 Encoding 속도향상을 꾀하고자 하는 것이 이 논문의 목표이다.