• 터널과지하공간
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• 제19권1호
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• pp.1-10
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• 2009

암반 내 구조물을 시공하는 경우 역학적 안정성을 평가하기 위하여 암반의 특성을 조사한다. 이 경우 암반의 특성은 주로 암반 내 절리의 특성에 의하여 좌우된다. 지금까지는 암반 내 절리의 특성을 조사하기 위하여 암반이 노출된 사면이나 노두에 접근하고 육안으로 직접 관찰하였다. 이때 급사면과 같은 곳에서 접근의 문제, 작업의 안전 문제, 많은 시판이 걸리는 문제, 조사시간에 비하여 얻은 정보량의 부족, 정보의 재현 문제, 측정 오차 문제 등의 제한이 있었다. 따라서 이와 같은 문제를 개선하기 위하여 LIDAR (light detection and ranging)로 암반을 스캔하여 얻은 포인트 클라우드(point cloud)글 Split-FX 소프트웨어로 처리한 결과 절기의 방향과 간격 및 절리면의 거칠기 등 절리의 특성을 정확하고 효율적으로 분석할 수 있었다.

• 한국정밀공학회지
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• 제7권3호
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• pp.75-82
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• 1990

Automatic monitoring of the cutting conditions is one of the most improtant technologies in machining. In this study, the feasibility in applying acoustic emission(AE) signals for the in-process detection of endmill wear and fracture has been investigated by performing experimental test on the NC vertical milling machine with SM45C for specimen. As the results of detecting and analyzing AE signals on various cutting conditions, the followings have confirmed. (1) The RMS value of acoustic emission is related sensitively to the cutting velocity, but is not affected largely by feed rate. (2) The burst type AE signals of high level have been observed when removing chips distorderly and discontinuously. (3) When the RMS value grows up rapidly due to the increase of wear the endmill are generally broken or fractured, but when the endmills fracture at the conditions of smooth chip-flow or built-up-edge(BUE) occurred frequently, the rapid change of the RMS arenot found. And it is expected that this technigue will be quite useful for in-process sensing of tool wear and fracture.

• 대한의용생체공학회:의공학회지
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• 제36권5호
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• pp.143-149
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• 2015

In this paper, we proposed a novel method for automatic detection for snoring and heart beat using a single piezoelectric sensor. For this study multi-rate signal processing technique was applied to detect snoring and heart beat from the single source signal. The sound event duration and intensity features were used to snore detection and heart beat was found by autocorrelation. The performance of the proposed method was evaluated on clinical database, which is the nocturnal piezoelectric snoring data of 30 patients that suffered obstructive sleep apnea. The method achieved sensitivity of 88.6%, specificity of 96.1% with accuracy of 95.6% for snoring and sensitivity of 94.1% and positive predictive value of 87.6% for heart beat, respectively. These results suggest that the proposed method can be a useful tool in sleep monitoring and sleep disordered breathing diagnosis.

• Journal of Microbiology and Biotechnology
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• 제16권5호
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• pp.740-747
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• 2006

Amplification by universal consensus sequences in pathogenic bacterial DNA would allow rapid identification of pathogenic bacteria, and amplification of genus-specific and species-specific sequences of pathogenic bacterial DNA might be used for genotyping at the genus and species levels. For design of probes for molecular diagnostics, several tools are available as stand-alone programs or as Web application. However, since most programs can design only a few probe sets at one time, they are not suitable for large-scale and automatic probes design. Therefore, for high-throughput design of specific probes in diagnostic array development, an automated design tool is necessary. Thus, we developed a Web-based automatic system for design of genus-specific and species-specific probes for pathogen detection. The system is available at http://www.miprobe.com.

• 한국멀티미디어학회논문지
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• 제18권10호
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• pp.1189-1196
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• 2015

In this paper, we proposed automatic extraction of brain tumor using morphological operation and statistical tumors size in MR images. Neurosurgery have used gamma-knife therapy by MR images. However, the gamma-knife plan systems needs the brain tumor regions, because gamma-ray should intensively radiate to the brain tumor except for normal cells. Therefore, gamma-knife plan systems spend too much time on designating the tumor regions. In order to reduce the time of designation of tumors, we progress the automatical extraction of tumors using proposed method. The proposed method consist of two steps. First, the information of skull at MRI slices remove using statistical tumors size. Second, the ROI is extracted by tumor feature and average of tumors size. The detection of tumor is progressed using proposed and threshold method. Moreover, in order to compare the effeminacy of proposed method, we compared snap-shot and results of proposed method.

• 대한전자공학회논문지TE
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• 제39권4호
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• pp.379-388
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• 2002

본 논문에서는 실시간 얼굴인식 시스템을 위한 얼굴의 위치 및 얼굴의 각 부위 자동 검출에 관한 알고리즘을 제안하였다. 얼굴의 각 부위 기반 특징점 추출을 위해 검출된 얼굴영역에서 얼굴의 눈, 코, 입의 탐색 과정을 수행하면서, 얼굴 각 부위의 크기 및 위치의 구조적인 정보를 이용하거나 가우시안 2차 미분 연산자를 통한 신호처리의 두 가지 방법을 이용하였다. 이들은 전체 영상이 아닌 검출된 얼굴 영역에 대해서 탐색하기 때문에 전체 영상을 탐색할 때에 비해 처리 시간을 줄일 수 있을 뿐만 아니라, 정확성을 높일 수 있다. 제안된 알고리즘을 통해 95%에 근접한 얼굴 검출률과 1초미만의 속도 향상, 그리고 얼굴 검출의 장애요인이 되었던 조명의 영향을 줄이는 동시에 얼굴의 각도 변화를 보정할 수 있었다.

• International Journal of Internet, Broadcasting and Communication
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• 제9권3호
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1125-1135
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• 2010

A fundamental characteristic of PMHT (Probabilistic Multi-Hypothesis Tracker) is that the number of targets and initial states of targets in the surveillance area must be a priori known. This requirement is impossible to fulfil in almost every realistic scenario. In the paper, we present two track initiation methods to solve the problem. The proposed track initiation methods are 2-point track initiation and Hough transform track initiation, and they are used to evaluate track initial states and weights for FTD (False Track Discrimination) of the PMHT algorithm. Also suggested as automatic target detection for tracking systems that combines track initiation for target detection with the PMHT algorithm for target tracking in a cluttered environment. A series of Monte-Carlo simulation runs is employed to evaluate the overall system performance with the two track initiation methods and the results are compared and analyzed.

• 대한전자공학회논문지TC
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• 제48권4호
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• pp.47-52
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• 2011

CFAR(constant false alarm rate)는 능동 소나 시스템에서 사용되는 자동 탐지 신호처리 알고리듬이다. CFAR 알고리듬 중에서도 OS(ordered statistics) CFAR는 CA(cell averaging), SO(smallest of), GO(greatest of)에 비해 비균일 환경에서 탐지 성능이 우수하다. 그러나 OS CFAR는 다중 표적 상황에서 일정 개수 이상의 표적이 나타나면 탐지 성능이 나빠지는 단점을 갖고 있다. 이에 본 논문에서는 다중 표적 환경에서 OS CFAR보다 좀 더 강인한 OSR(ordered statistics ratio) CFAR 알고리듬을 제안하고 컴퓨터 모의실험을 통하여 간섭 표적 개수에 따른 성능을 기존의 CFAR 기법과 비교 분석하였다.

• 한국통신학회논문지
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• 제21권3호
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• pp.553-563
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• 1996

Detecting edges is one of issues with essentialimprotance in the area of image analysis. An edge in an image is a boundary or contour at which a significant change occurs in image intensity. Edge detection has been studied in many addlications such as imagesegmentation, robot vision, and image compression. In this paper, we propose an automatic threshold selection scheme for edge detection and show its application to noise elimination. The scheme suggested here applied statistical properties of the noise estimated from a noisy image to threshold selection. Since a selected threshold value in the scheme depends on not the characgreistic of an orginal image but the statistical feature of added noise, we can remove ad-hoc manners used for selecting the threshold value as well as decide the value theoretically. Furthermore, that shceme can reduce the number of edge pixels either generated or lost by noise. an application of the scheme to noise elimination is shown here. Noise in the input image can be eliminated with considering the direction of each edge pixedl on the edge map obtained by applying the threshold selection scheme proposed in this paper. Achieving significantly improved results in terms of SNR as well as subjective quality, we can claim that the suggested method works well.