• 대한의용생체공학회:의공학회지
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• 제30권2호
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• pp.122-128
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• 2009

Cancer serum biomarkers have advanced our ability to more accurately predict tumor classification, prognostic/metastatic potential, and response potential to novel chemotherapies. Serum amyloid A (SAA) and Vascular endothelial growth factor (VEGF) have potential utility as a serum biomarker for lung cancer. Quantum dots, nanometer-sized crystals, have a high quantum yield, sensitivity, and pronounced photostability. The properties of quantum dots can be efficiently applied to the detection of serum biomarkers in immunoassays as fluorescent probe. We used quantum dots as fluorescent probes in immunoassays and attempted to detect serum amyloid A and vascular endothelial growth factor as serum biomarkers of lung cancer. This fluorescence immunoassay based on the properties of quantum dots is applicable to the detection of serum biomarkers for lung cancer. The fluorescence immunoassay with quantum dots should allow the efficient and specific detection of serum amyloid A (SAA) for the possible diagnosis of lung cancer.

• 디지털산업정보학회논문지
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• 제14권2호
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• pp.11-17
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• 2018

IDS/IPS and networked computer systems are playing an increasingly important role in our society. They have been the targets of a malicious attacks that actually turn into intrusions. That is why computer security has become an important concern for network administrators. Recently, various Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems is useful for existing intrusion patterns on standard-only systems. Therefore, probe detection of private clouds using BlockChain has become a major security protection technology to detection potential attacks. In addition, BlockChain and Probe detection need to take into account the relationship between the various factors. We should develop a new probe detection technology that uses BlockChain to fine new pattern detection probes in cloud service security in the end. In this paper, we propose a probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) based on service security using BlockChain technology.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.255-258
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• 2008

For rapidly increasing amount of medical images, it is difficult for radiologist to interpretate the medical images fastly and for sufficient time. We investigated whether liver CT image has good features to be analyzed by computer algorithm, We examed the CT images of liver tumors (Hepetocellular carcinomas; HCCs) and searched any potential morphologic characteristics to be analyzed by computer algorithms. On unenhanced CT, HCCs appeared hypodense After enhancement, most HCCs were hyperdense, and then. as a consequence of rapid washout, HCCS became hypodense compared with the liver parenchyma. Most CT images of HCCs showed synchronous phase-specific.morphologic features. We applied various edge detection filters to these images and some filters showed favorable performance in the detection of tile edge of liver and HCC. Therefore, theses features seems to be analyzed by computer algorithms effectively.Further studies may be warranted.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.153-156
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• 2007

In this paper, we propose a fast face detection approach using PCA and SVM. In our detection system, first we filter the face potential area using statistical feature which is generated by analyzing local histogram distribution. And then, we use SVM classifier to detect whether there are faces present in the test image. Support Vector Machine (SVM) has great performance in classification task. PCA is used for dimension reduction of sample data. After PCA transform, the feature vectors, which are used for training SVM classifier, are generated. Our tests in this paper are based on CMU face database.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.24-27
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• 2005

The NDT(Non-Destructive Testing) is valid fur the defect detection of rolling stocks because it can be used to detect defects in invisible places. For example, in case of wheelsets fatigue cracks are initiated in the wheel seat that suffers from fretting fatigue damage. But the conventional ICFPD method can not be applied to detect such cracks in press-fit area of the axle by some technical problems. In this study, we introduced a new ICFPD (Induced Current Focusing Potential Drop) method that can be applied in press-fit area of the axle. And we performed the finite element analysis of the new ICFPD method using measured electromagnetic properties of the wheel and axle. It seems that our approach is very useful f3r the detection of defects in invisible places.

• 한국정보통신학회논문지
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• 제11권6호
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• pp.1129-1135
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• 2007

얼굴인식기술은 컴퓨터비전 분야에서 중요한 역할을 담당하고 있다. 본 논문에서는, PCA와 SVM 기술을 사용하는 빠른 얼굴인식기술을 제안한다. 제안한 시스템에서는, 먼저 지역 히스토그램 분포를 분석하여 생성한 통계적 특성을 사용함으로써 얼굴가능영역을 필터링한다. 이 과정에서 대부분의 비얼굴 영역이 제거되기 때문에 탐지 과정의 처리속도가 향상된다. 다음으로는 PCA 특징 벡터가 생성되고, SVM 분류기를 사용하여 테스트 영상 내에 얼굴이 존재하는지를 탐지한다. 본 논문에서의 테스트 영상은 CMU 얼굴 데이터베이스를 사용하였으며, SVM의 학습을 위한 얼굴과 비얼굴 샘플들은 MIT 데이터 세트로부터 선택하였다. 얼굴탐지 실험결과, 제안한 방법에서 좋은 성능을 나타내었다.

• ETRI Journal
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• 제41권4호
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• pp.437-451
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• 2019

Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph-based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state-of-the-art methods in terms of accuracy and work well with various data types.

• Bulletin of the Korean Chemical Society
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• 제35권6호
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• pp.1867-1870
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• 2014

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.554-557
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• 2002

This paper describes power potential field method for the collision-free path planning of stereo-vision based mobile robot. Area based stereo matching is performed for obstacle detection in uncertain environment. The repulsive potential is constructed by distributing source points discretely and evenly on the boundaries of obstacles and superposing the power potential which is defined so that the source potential will have more influence on the robot than the sink potential when the robot is near to source point. The mobile robot approaches the goal point by moving the robot directly in negative gradient direction of the main potential. We have investigated the possibility of power potential method for the collision-free path planning of mobile robot through various experiments.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1547-1548
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• 2011