• 대한장애인치과학회지
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• 제8권1호
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• pp.15-21
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• 2012

Extraction of all nonrestorable teeth prior to bone marrow transplantation is the major dental management of the patient being prepared for the transplantation. But, there are four principal causes for excessive bleeding in the immediate postextraction phase ; (1) Vascular wall alteration (wound infection, scurvy, chemicals, allergy) (2) Disorders of platelet function (3) Thrombocytopenic purpuras (4) Disorders of coagulation (liver disease, anticoagulation drug-heparin, coumarin, aspirin, plavix) If the hemorrhage from postextraction wound is unusually aggressive, the socket must be packed with local hemostatic agent and wound closure & pressure dressing are applied. But, in dental alveoli, local hemostatic agent (gelfoam, surgcel etc) may absorb oral microorganisms and cause alveolar osteitis (infection). This is a case report of bleeding and infection control by suture, pressure packing and iodoform gauze drainage on infected active bleeding extraction socket under sedation and local anesthesia in a 57-years-old multiple disabled patient with anticoagulation drug.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.653-655
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• 2005

More than 70 percent of terrestrial territory of Korea is mountainous areas where degradation becomes serious year by year due to illegal tombs, expanding golf courses and stone mine development. We elaborate the potential usage of high resolution image for the monitoring of the phenomena. We made the classification of tombs and the statistical radiometric characteristics of graves were identified from this project. The graves could be classified to 4 groups from the field survey. As compared with grouping data after clustering and discriminant analysis, the two results coincided with each other. Object-oriented classification algorithm for feature extraction was theoretically researched in this project. And we did a pilot project, which was performed with mixed methods. That is, the conventional methods such as unsupervised and supervised classification were mixed up with the new method for feature extraction, object-oriented classification method. This methodology showed about $60\%$ classification accuracy for extracting tombs from satellite imagery. The extraction of tombs' geographical coordinates and graves themselves from satellite image was performed in this project. The stone mines and golf courses are extracted by NDVI and GVI. The accuracy of classification was around 89 percent. The location accuracy showed extraction of tombs from one-meter resolution image is cheaper and quicker way than GPS method. Finally we interviewed local government officers and made analyses on the current situation of mountainous area management and potential usage of KOMPSAT-II images. Based on the requirement analysis, we developed software, which is to management and monitoring system for mountainous area for local government.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.647-650
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• 1999

In this Paper, we propose an optimal feature extraction for multiclass problems through proper choice of initial feature vectors. Although numerous feature extraction algorithms have been proposed, those algorithms are not optimal for multiclass problems. Recently, an optimal feature extraction algorithm for multiclass problems has been proposed, which provides a better performance than the conventional feature extraction algorithms. In this paper, we improve the algorithm by choosing good initial feature vectors. As a result, the searching time is significantly reduced. The chance to be stuck in a local minimum is also reduced.

• 대한원격탐사학회지
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• 제37권1호
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• pp.111-122
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• 2021

Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

• Journal of Dental Anesthesia and Pain Medicine
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• 제23권6호
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• pp.347-355
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• 2023

Background: Eye movement desensitization and reprocessing (EMDR) therapy has been reported to be very efficacious for treating post-traumatic stress disorder (PTSD) and other anxiety-related conditions. However, a review of the literature reveals the sparse use of this therapy in the field of pediatric dentistry. This study aimed to evaluate anxiety trends in pediatric dental patients during local anesthesia and extraction with and without EMDR therapy. Methods: Children in the age range of 8-12 years who required dental extractions were assigned randomly into two groups: an EMDR group (group 1) and a routine behavior management therapy group (group 2; receiving more traditional interventions such as tender love and care behavioral modeling, and distraction). Anxiety scores were recorded at four levels using the visual facial anxiety scale (VFAS) preoperatively, after therapy, after the administration of local anesthesia (LA), and after extraction. Results: Reduced anxiety was observed after the delivery of EMDR therapy, after LA administration, and post-extraction in the EMDR group compared to pre-operative anxiety scores of anxiety (P < 0.001; unpaired Student's t and Mann-Whitney U tests). In the control group, mild reductions in anxiety after routine behavior management therapy were observed, accompanied by spikes in anxiety levels after LA and extractions. Conclusion: EMDR therapy was found to be valuable for reducing anxiety among pediatric dental patients during tooth extraction procedures.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.404-406
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• 2002

In this paper, the method of image feature extraction is proposed. This method employ the energy field analysis, outlier removal algorithm and ring projection. Using this algorithm, we achieve rotation-translation-scale invariant feature extraction. The force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. The image feature is acquired from relationship of local extrema using the ring projection method.

• 자원환경지질
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• 제54권4호
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• pp.427-439
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• 2021

이번 연구에서는 골재채취통계를 기초로 하여 골재의 채취현황을 분석하고, 향후 골재의 안정적이고 지속적인 수급을 예측하고자 하였다. 2019년에는 전국 229개 시군구 중 약 65%인 148개 시군구에서 한 종류 이상의 골재를 개발하였다. 7대 광역시에서는 19개 시군구에서 골재를 개발되었다. 광역시를 제외하면 8개도의 155개 시군 중 83%인 129개 시군에서 골재개발이 이루어져 우리나라의 대부분 시군에서 골재를 개발하고 있다고 볼 수 있다. 모래는 110개 시군구에서, 자갈은 132개 시군구에서 개발되었다. 골재원별로 볼 때 하천골재는 4개 시군구, 육상골재는 42개 시군구, 산림골재는 75개 시군구, 선별파쇄골재는 105개 시군구, 선별세척골재는 15개 시군구에서 개발되었다. 또한 육지원 골재의 채취가 전혀 이루어지지 않은 시군구는 81개 지역이다. 골재원별로 볼 때 한 종류의 골재만 개발하는 시군구는 71개, 두 종류의 골재를 개발하는 시군구는 55개, 3종류 이상은 22개 시군구이다. 2019년에 골재의 개발이 가장 많은 지역은 울주군이며, 그 다음으로 화성시, 청주시, 포천시, 파주시, 용인시, 김해시, 광주시의 순이다. 100만m³ 이상의 골재를 개발한 지역은 41개 시군구로 시군구은 골재채취 시군구의 약 28%이지만 골재개발량은 2019년도 총 개발량의 약 70%를 점유한다. 이는 각 시군의 골재채취가 대형화, 집중화되고 있음을 보여준다.

• 한국산업정보학회논문지
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• 제8권2호
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• pp.14-20
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• 2003

본 논문에서는 카메라로 획득한 문서영상에 대해 조명의 영향에 관계없이 고속으로 문자영역을 추출하는 알고리즘을 제안하였다. 카메라 문서는 스캐너 문서와는 달리 주변 환경이나 조명의 영향으로 인하여 문자영역을 추출하는 것이 매우 어렵다. 먼저 영상 사전처리 단계에서 컬러영상을 명도영상으로 변환한 후 조명의 영향에 무관하게 배경 그림으로부터 문자 영역을 정확히 추출하기 위해서 명도레벨 정규화를 사용하였다. 또한 배경 그림 및 잡음은 제거하고 문자 획의 손실 없이 문자 영역을 추출하기 위하여 국소-적응적-이진화-방법(local adaptive binarization method)을 새롭게 개발하여 문서영상을 이진화시켰다. 문자영역 추출 단계에서는 수평 및 수직 투영과 연결요소 정보에 의해 문자열, 단어 및 개별 문자 영역을 단계적으로 추출하였다. 제안된 방법의 타당성을 검증하기 위하여 ETRI에서 구축한 한글/영어/숫자/특수기호가 혼합된 현장 문서영상 DB를 가지고 실험해 보았다.

• 대한전자공학회논문지SP
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• 제40권6호
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• pp.1-9
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• 2003

본 논문에서는 지문 영상의 컨벡스 (convex) 구조를 이용하여 특징점을 추출하는 방법을 제안하였다. 지문영상에서 융선은 일정한 방향성을 가지며 융선의 단면은 주기성이 있는 사인파로 간주할 수 있다. 사인파 신호에서 국부 최대 위치를 검출함으로써 대략적인 한 화소 단위의 융선 추출이 가능하며 사인파 신호의 볼록한 컨벡스는 융선 영역에 해당한다. 이러한 지문의 특징을 이용하여 특징점을 효과적으로 찾는 방법을 제안한다. 이 과정에서 파라미터를 없애고 계산량을 줄임으로써 다양한 환경의 시스템에 적용 가능함을 보였다.

• International Journal of Contents
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• 제8권1호
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.