• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1182-1194
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• 2016

The single image dehazing algorithm in existence can satisfy the demand only for improving either the effectiveness or efficiency. In order to solve the problem, a novel variational framework for single image dehazing based on restoration is proposed. Firstly, the initial atmospheric scattering model is transformed to meet the kimmel's Retinex variational model. Then, the green light component of image is considered as an input of the variational framework, which is generated by the sensitivity of green wavelength. Finally, the atmospheric transmission map is achieved by multi-resolution pyramid reduction to improve the visual effect of the results. Experimental results demonstrate that the proposed method can remove haze effectively with less memory consumption.

• 반도체디스플레이기술학회지
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• 제19권3호
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• pp.12-18
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• 2020

In semiconductor manufacturing, defect detection is critical to maintain high yield. Currently, computer vision systems used in semiconductor photo lithography still have adopt to digital image processing algorithm, which often occur inspection faults due to sensitivity to external environment. Thus, we intend to handle this problem by means of using Mask R-CNN instead of digital image processing algorithm. Additionally, Mask R-CNN can be trained with image dataset pre-processed by means of the specific designed digital image filter to extract the enhanced feature map of Convolutional Neural Network (CNN). Our approach converged advantage of digital image processing and instance segmentation with deep learning yields more efficient semiconductor photo lithography inspection system than conventional system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.255-256
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• 2006

Raman spectroscopy has strong potential for providing noninvasive dermatological diagnosis of skin cancer. In this study, we investigated two classification methods with maximum a posteriori (MAP) probability and multi-layer perceptron (MLP) classification. The classification framework consists of preprocessing of Raman spectra, feature extraction, and classification. In the preprocessing step, a simple windowing method is proposed to obtain robust features. Classification results with MLP involving 216 spectra preprocessed with the proposed method gave 97.3% sensitivity, which is very promising results for automatic Basal Cell Carcinoma (BCC) detection.

• Mass Spectrometry Letters
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• 제14권3호
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• pp.57-78
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• 2023

Understanding the chemical composition of the brain helps researchers comprehend various neurological processes effectively. Understanding of the fundamental pathological processes that underpin many neurodegenerative disorders has recently advanced thanks to the advent of innovative bioanalytical techniques that allow high sensitivity and specificity with chemical imaging at high resolution in tissues and cells. Mass spectrometry imaging [MSI] has become more common in biomedical research to map the spatial distribution of biomolecules in situ. The technique enables complete and untargeted delineation of the in-situ distribution characteristics of proteins, metabolites, lipids, and peptides. MSI's superior molecular specificity gives it a significant edge over traditional histochemical methods. Recent years have seen a significant increase in MSI, which is capable of simultaneously mapping the distribution of thousands of biomolecules in the tissue specimen at a high resolution and is otherwise beyond the scope of other molecular imaging techniques. This review aims to acquaint the reader with the MSI experimental workflow, significant recent advancements, and implementations of MSI techniques in visualizing the anatomical distribution of neurochemicals in the human brain in relation to various neurogenerative diseases.

• International Journal of Computer Science & Network Security
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• 제24권8호
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• pp.61-71
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• 2024

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.

• 한국정보과학회논문지:정보통신
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• 제31권4호
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• pp.375-383
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• 2004

최근에 사용 편이성으로 인해 다양한 무선 이동 네트워크들이 널리 보급되면서, 무선 네트워크성능을 향상시키기 위한 연구가 활발히 진행되고 있다. 무선 네트워크에서의 패킷 손실은 유선 네트워크의 혼잡이 아닌, 전파 오류로 인해 빈번히 발생되기 때문에, 시뮬레이션에서 무선 네트워크의 성능을 정확히 평가하기 위해서는 알맞은 무선 채널 모델을 채택해야 한다. 적합한 채널 모델은 사용 주파수 영역, 신호출력, 방해물 존재 유무, 평가하는 프로토콜의 비트 오류에 대한 민감성 둥 여러 가지 변수를 고려하여 선택해야 한다. 본 논문에서는 센서(Sensor) 채널의 고 전파 오류 특성을 분석하고, 센서 채널에 알맞은 채널 모델을 결정한다. 또한 센서 네트워크에서 수집한 비트 오류 데이타와 다양한 이론적 무선 채널 모델링 방식을 이용하여 링크계층 FEC(Forward Error Correction) 알고리즘과 TCP 성능 변화를 평가한다. 10일간의 센서 채널 트레이스와의 비교 분석에 의하면, CM(Chaotic Map) 모델은 센서 채널의 BER 편차와 PER(Packet Error Rate) 같을 각각 3배와 10배 이내의 오차 범위에서, 다른 모델은 수십 배 이상 오차범위에서 예측한다. FEC 알고리즘과 세가지 TCP (Tahoe, Reno, 그리고 Vegas) 시뮬레이션 실험에서도 CM 모델은 트레이스와 유사한 성능 변화를, 다른 모델은 최대 10배 이상의 오차를 보인다.

• 물과 미래
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• 제27권1호
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• pp.89-99
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• 1994

현재까지 국내의 홍수예측업무는 과거에 수집된 자료집단을 이용한 변수추정에 의하여 시행되고 있으나, 최근 여러 가지 순환추정 알고리즘을 적용한 홍수예측 또는 변수추정에 관한 많은 연구가 이루어지고 있다. 본 논문은 실시간 홍수예측 및 변수추정에 관한 연구로서, 특히 강우-유출모형의 상태 및 매개변수의 동시추정에 관한 추계학적 현상을 고려하였다. 홍수예측에 관한 시스템은 $\phi$ 지수에 의한 유효강우의 산정과 지체효과를 고려한 n개의 비선형 저수지모형에 의한 홍수축적으로 구성하였다. 그리고 변수추정모형과 홍수추적 모형을 상호연계하여 변수를 포함하는 확대 상태-공간모형으로 상태 및 매개변수의 동시추정에 관한 시스템을 구성하였다. 상태-공간모형에 대한 상태 및 변수추정기법으로 GLS 추정과 MAP 추정에 대하여 비교 검토하였다. 모형의 식별을 위한 민감도 분석은 추정변수의 공분산 행렬을 사용하였다.

• 지식경영연구
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• 제21권1호
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• pp.197-210
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• 2020

The smart speaker includes an AI assistant function in the existing portable speaker, which enables a person to give various commands using a voice and provides various offline services associated with control of a connected device. The speed of domestic distribution is also increasing, and the functions and linked services available through smart speakers are expanding to shopping and food orders. Through text mining-based customer review analysis, there have been many proposals for identifying the impact on customer attitudes, sentiment analysis, and product evaluation of product functions and attributes. Emotional investigation has been performed by extracting words corresponding to characteristics or features from product reviews and analyzing the impact on assessment. After obtaining the topic from the review, the effect on the evaluation was analyzed. And the market competition of similar products was visualized. Also, a study was conducted to analyze the reviews of smart speaker users through text mining and to identify the main attributes, emotional sensitivity analysis, and the effects of artificial intelligence attributes on product satisfaction. The purpose of this study is to collect blog posts about the user's experiences of smart speakers released in Korea and to analyze the attitudes of customers according to their attributes. Through this, customers' attitudes can be identified and visualized by each smart speaker product, and the positioning map of the product was derived based on customer recognition of smart speaker products by collecting the information identified by each property.

• The Korean Journal of Physiology
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• 제24권1호
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• pp.115-121
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• 1990

Pentobarbital 마취한 정상혈압 및 신성 고혈압 흰쥐에서 calcium channel 봉쇄 약물 nifedipine과 atrial natriuretic peptide(ANP)의 상호작용을 조사하였다. 정상혈압 흰쥐에서 nifedipine$(1.0\;{\mu}g/kg/min)$ 또는 ANP(60 ng/kg/min)의 주입은 각각 유의하게 혈압을 내렸으며 두 약물의 동시 주입시에 개별적으로 주입하였을 때보다 그 혈압내림의 정도가 더욱 컸다. Nifedipine은 단독 주입하였을 때에 신기능에 유의한 영향을 미치지 않았으나 ANP와 동시에 주입하였을 때에는 ANP의 요량 및 Na 배설 증가 효과를 항진시켰다. 한편 고혈압 흰쥐에서도 ANP의 혈압내림효과와 신장효과는 nifedipine과 함께 주입하였을 때에 더 컸다. 적출 흉부대동맥 표본을 phenylephrine으로 미리 수축시킨 후 ANP를 첨가하면 용량의존 이완반응을 보였고 nifedipine 존재하에서 더 예민하였다. 이상의 실험결과는 calcium channel 봉쇄약물이 ANP의 혈압내림효과를 항진시킴을 보인 것이며 그 기전으로 요중 배설 증가 및 혈관이완효과 증가 등이 관여함을 시사하였다.