• 교육시설
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• 제9권1호
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• pp.27-36
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• 2002

This paper is to evaluate the campus master plan, which is influenced by Korean educational policy and managing organization, with respect to land use and block plans of buildings. It uses a case study method to periodically know specific details to form a master plan. It is found, at first, that design method of master plan was influenced by some educational policies and managing organization of ministry of education. Secondly, design methods have been changed according to the change of the times. Any master plan was not formulated until the 1960s. Seoul National University formed a master plan adopting radiated sector pattern for land use and a block plan in the early years of the 1970s. Chungnam National University used a squared space style with a trouble of the learned from the SNU design methods in the year 1974. A concept of axis according to topography] in Andong National University and environmental preservation in Yiosu National University was used in the 1980s. Korean Athletic Educational University used a transportation model for facilitating efficiency to use university land and making pedestrian convenient by classification with fast and slow walker's way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4502-4518
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• 2015

Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.

• 컴퓨터교육학회논문지
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• 제9권2호
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• pp.101-109
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• 2006

본 논문에서는 DCT 도메인에서 영상의 블록에 대한 분류에 따라 다른 블록들에 삽입될 워터마크의 강도를 적용적으로 조절하여 워터마크를 삽입하기 위해 인간 시각 시스템(HVS)과 선경회로망 중 SOM(Self-Organizing Map)을 이용한 적용적 디지털 이미지 워터마킹을 제안한다. 인간 시각 시스템을 기반으로 하여 블록의 특정벡터를 찾아낸다. 블록의 특정벡터를 입력으로 SOM에 의해 블록들은 4등급으로 분류된다. 이들 중 3개의 등급에 속하는 블록을 선택하여 DCT 계수들 중 DC성분을 제외한 저주파 성분을 가지는 6개의 계수들을 선택하여 워터마크를 삽입한다. 실험을 통해 새로 제안된 알고리즘은 좋은 화질을 얻을 수 얻을 수 있었고 JPEG 압축, 영상처리, 기하학적 변환과 잡음과 같은 공격에 아주 강인하였다.

• 대한원격탐사학회지
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• 제32권5호
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• pp.471-482
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• 2016

본 논문에서는 수계 영역의 감독 분류 성능을 향상시키기 위하여 블록 기반의 영상 분할과 수계 경계의 확장을 이용하는 수계 검출 방법을 제안한다. 초기 수계 영역을 추출하기 위하여 수계 훈련 지역의 Normalized Difference Water Index (NDWI) 및 Near Infrared (NIR) 밴드 영상의 분광 정보를 이용하여 Mahalanobis 거리 영상을 생성한다. Mahalanobis 거리 영상에 포함된 잡음 성분의 영향을 감소시키기 위해서 인접한 화소의 연결 강도에 의해 확산 계수가 제어되는 평균 곡률 확산을 적용한 후에 초기 수계 영역을 추출한다. 추출된 수계 영상을 같은 크기의 블록으로 분할한 후에 수계 경계에 속하는 수계 영역의 정보를 이용하여 수계 영역을 갱신한다. 수계 경계에 속하는 수계 영역과 수계 훈련 지역 사이의 통계적인 거리가 임계값 이하이면, 수계 영역 갱신을 반복적으로 수행한다. 제안한 알고리즘을 KOMPSAT-2 영상에 적용한 결과 블록 크기가 $11{\times}11$에서 $19{\times}19$사이인 경우에 overall accuracy는 99.47%에서 99.53%, Kappa coefficient는 95.07%에서 95.80%의 분류 정확도를 보였다.

• 대한예방한의학회지
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• 제14권1호
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• pp.111-123
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• 2010

Backgrounds : Stroke is characterized by loss of brain functions due to a disturbance in the blood vessels supplying blood to the brain, and classified into hemorrhage and ischemia. Stroke is known to be affected by genetic factors and other diseases such as hypertension and cardiovascular diseases. However, the distinctive association between stroke and genetic variations has not discovered yet. Objectives : This study investigated the effects of fibrinogen level and genetic variations in FGA (Fibrinogen alpha chain) gene on stroke in Korean stroke patients and controls. Methods : DNA samples from 674 stroke patients diagnosed by Oriental medical hospitals and 267 controls were used in this study. Two common single nucleotide polymorphism(SNP) with high minor allele frequency(MAF), rs2070011G/A of promoter region and nonsynonymous rs6050A/G of exon 5 in FGA gene, were targeted for Taqman genotyping. Because the TOAST classification is important to the factors and symptoms of stroke, ischemic patients were further classified into five subtypes using diagnosis and clinical data. One-way ANOVA and chi-square test were used for clinical data and genetic association, respectively. Haploview v4.1 program was used for linkage disequilibrium(LD), haplotype and haplotype block analysis. Results : The levels of red blood cells and fibrinogen from clinical data were shown to be significant factors for the sub-groups of TOAST classification. No significant associations of stroke, hemorrhage, ischemic and subtypes of TOAST with rs2070011 and rs6050 of FGA gene were found(P > 0.05). However, rs2070011 in promoter region and nonsynonymous rs6050 in exon 5 which produce the amino acid change from threonine to alanine showed a haplotype block and three haplotypes of A-G, G-A, A-A, suggesting that rs2070011 and rs6050 might be co-segregated in generic recombination. Although A-A haplotype of stroke patients showed 64-69% low frequency compared to controls, there was no significant association between stroke and haplotype(P > 0.05). Conclusion : This study showed that there was no significant association between stroke and two SNP of rs2070011G/A and nonsynonymous rs6050A/G in FGA gene. However, these two SNP compose a haplotype block and three haplotypes of A-G, G-A, A-A. This finding suggests that rs2070011 and rs6050 are so close as to be positioned as linkage disequilibrium. Nevertheless, no significant association between haplotypes and stroke was found.

• Journal of Korean Neurosurgical Society
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• 제51권5호
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• pp.281-285
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• 2012

Objective : Occipital neuralgia is characterized by paroxysmal jabbing pain in the dermatomes of the greater or lesser occipital nerves caused by irritation of these nerves. Although several therapies have been reported, they have only temporary therapeutic effects. We report the results of pulsed radiofrequency treatment of the occipital nerve, which was used to treat occipital neuralgia. Methods : Patients were diagnosed with occipital neuralgia according to the International Classification of Headache Disorders classification criteria. We performed pulsed radiofrequency neuromodulation when patients presented with clinical findings suggestive occipital neuralgia with positive diagnostic block of the occipital nerves with local anesthetics. Patients were analyzed according to age, duration of symptoms, surgical results, complications and recurrence. Pain was measured every month after the procedure using the visual analog and total pain indexes. Results : From 2010, ten patients were included in the study. The mean age was 52 years (34-70 years). The mean follow-up period was 7.5 months (6-10 months). Mean Visual Analog Scale and mean total pain index scores declined by 6.1 units and 192.1 units, respectively, during the follow-up period. No complications were reported. Conclusion : Pulsed radiofrequency neuromodulation of the occipital nerve is an effective treatment for occipital neuralgia. Further controlled prospective studies are necessary to evaluate the exact effects and long-term outcomes of this treatment method.

• Industrial Engineering and Management Systems
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• 제12권4호
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• pp.380-388
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• 2013

Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 학술대회
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.