• KSBB Journal
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• 제29권5호
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• pp.361-371
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• 2014

Mycoplasma is well recognized as one of the most prevalent and serious microbial contaminants of biologic manufacturing processes. Conventional methods for mycoplasma testing, direct culture method and indirect indicator cell culture method, are lengthy, costly and less sensitive to noncultivable species. In this report, we describe a new TaqMan probe-based real-time PCR method for rapid and quantitative detection of mycoplasma contamination during manufacture of biologics. Universal mycoplasma primers were used for mycoplasma PCR and mycoplasma DNA was quantified by use of a specific TaqMan probe. Specificity, sensitivity, and robustness of the real-time PCR method was validated according to the European Pharmacopoeia. The validation results met required criteria to justify its use as a replacement for the culture method. The established real-time PCR assay was successfully applied to the detection of mycoplasma from human keratinocyte and mesenchymal stem cell as well as Vero cell lines artificially infected with mycoplasma. The overall results indicated that this rapid, specific, sensitive, and robust assay can be reliably used for quantitative detection of mycoplasma contamination during manufacture of biologics.

• 한국항행학회논문지
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• 제10권4호
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• pp.377-384
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• 2006

본 논문에서는 선박이나 항공기 조난에 대비하여 운용 중인 인공위성을 기반으로 하는 수색 및 구조 시스템의 조난신호 탐지시간에 관한 문제를 고려한다. 현재 운용 중인 LEOSAR 시스템은 저궤도 위성을 사용하며 시스템에 속한 위성의 수가 적고 커버리지는 지구전체가 아닌 국지이다. 따라서 조난자의 비컨 신호가 탐지되어 구조본부까지 전달되려면 장시간이 소요된다. 이와 대조적으로 새로 제안된 중궤도 항행위성시스템에 기반한 MEOSAR 시스템을 추가로 도입하는 경우를 가정하면 커버리지가 지구전역으로 확대되고 시스템의 안정도가 개선되어 조난신호 검출 또는 탐지시간이 크게 감소하므로 수색구조 효율이 크게 개선된 결과를 얻는다. 본 논문에서는 비컨에 대한 장애물의 영향을 고려했을 경우에 대하여 LEOSAR 및 MEOSAR 시스템에 대한 조난신호 탐지시간을 시뮬레이션을 통하여 계산하고 그 결과를 비교 해석한다.

• 한국컴퓨터정보학회논문지
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• 제21권8호
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• pp.21-28
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• 2016

In this paper, we propose a fast small target detection method using multiple filters, and describe system implementation using IPP libraries. To detect small targets in Infra-Red images, it is mandatory that you should apply a filter to eliminate a background and identify the target information. Moreover, by using a suitable algorithm for the environments and characteristics of the target, the filter must remove the background information while maintaining the target information as possible. For this reason, in the proposed method we have detected small targets by applying multi area(spatial) filters in a low luminous environment. In order to apply the multi spatial filters, the computation time can be increased exponentially in case of the sequential operation. To build this algorithm in real-time systems, we have applied IPP library to secure a software optimization and reduce the computation time. As a result of applying real environments, we have confirmed a detection rate more than 90%, also the computation time of the proposed algorithm have been improved about 90% than a typical sequential computation time.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2004년도 추계학술대회 및 정기총회
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• pp.13-16
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• 2004

This paper deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection award, if detected, which represents the detection priority of target and is non-increasing with time. The objective is to establish the optimal search plan which allocates the search resource effort over the search areas in each time interval in order to maximize the total detection award. In the analysis, the given problem is decomposed into intervalwise individual search problems each being treated as a single stationary target problem for each time interval. An associated iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.

• 한국음향학회지
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• 제31권8호
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• pp.551-560
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• 2012

시역전 기술을 활용한 수중음향장벽에 의한 수중물체 탐지는 능동소나와 수동소나의 기법과 이론적 배경이 명확한 시역전 처리의 개념을 포함하고 있다. 본 논문에서는 수동형 해양 시역전에 의한 수중탐지의 개념과 이론을 수립하였다. 또한 수중음향 전파모델을 활용하여 모델링을 통해 수동형 시역전 수중음향장벽의 성능 예측을 수행하였다. 본 연구의 결과는 수동형 시역전 개념을 이용한 수중음향장벽 탐지시스템의 설계 시 유용한 성능예측 도구로 활용될 수 있다.

• 제어로봇시스템학회논문지
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• 제15권8호
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• pp.839-844
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• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.

• 한국정밀공학회지
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• 제12권10호
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• pp.50-56
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• 1995

Chatter Vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life, machine life and the productivity of machining process. The real-time detection of the chatter vibration is is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer, Accelermeter and AE sensor. Especially, Acoustic Emission(AE) generated during turning was investigated the possibility for real-time detection of chatter vibration. Turning experiments were performed using carbide insert tip under realistic cutting conditions and tapered workpiece of SM45C. Consquently, the real-time detection using multi-sensing system can be used for Inprocess monitoring of chatter vibration.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4093-4097
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• 2021

This study presents a new dead-time measurement method using the gamma attenuation law and generalized dead-time models for nuclear gamma-ray detectors. The dead-time of the NaI(Tl) detection system was obtained to validate the new dead-time determination method using very thin lead and polyethylene absorbers. Non-paralyzing dead-time was found to be 8.39 ㎲, and paralyzing dead-time was found to be 8.35 ㎲ using lead absorber for NaI(Tl) scintillator detection system. These dead-time values are consistent with the previously reported dead-time values for scintillator detection systems. The gamma build-up factor's contribution to the dead-time was neglected because a very thin material was used.

• 사물인터넷융복합논문지
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• 제6권1호
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• pp.83-95
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• 2020

실제 복잡다난한 농작물 밭 환경에서 잡초를 정밀하게 검출하는 것은 이전의 접근방법들로는 이미지 프레임을 정확하게 처리하는 속도 면에서 부족했다. 식물의 질병 분류 문제가 중요시 되는 상황에서 특히 작물의 잡초 문제는 큰 화제가 되고 있다. 이전의 접근방식들은 빠른 알고리즘을 사용하지만 추론 시간이 실시간에 가깝지 않아 통제되지 않은 조건에서 비현실적인 해결책이 된다. 따라서, 복잡한 벼 잡초 검출 과제에 대한 탐지 모델을 제안한다. 실험 결과에 따르면, 우리의 접근 방식의 추론 시간은 잡초 검출 과제에서 상당한 시간절약을 보여준다. 실제 조건에서 실제로 적용할 수 있는 것으로 나타난다. 주어진 예시들은 쌀의 두 가지 성장 단계에서 수집되었고 직접 주석을 달았다.

• 대한임베디드공학회논문지
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• 제7권4호
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• pp.163-172
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• 2012

A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.