• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.298-309
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• 2001

This research aims to unravel the significant features of the human immune system, which would be successfully employed for a novel network intrusion detection model. Several salient features of the human immune system, which detects intruding pathogens, are carefully studied and the possibility and the advantages of adopting these features for network intrusion detection are reviewed and assessed.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2001년도 종합학술발표회논문집
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• pp.147-152
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• 2001

This research aims to unravel the significant features of the human immune system, which would be successfully employed for a novel network intrusion detection model. Several salient features of the human immune system, which detects intruding pathogens, are carefully studied and the possibility and the advantages of adopting these features for network intrusion detection are reviewed and assessed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.97-100
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• 2006

최근 절전에 대한 의식이 높아짐에 따라 이 문제를 해결하기 위해 많은 연구가 진행되고 있다. 본 논문은 건물 내의 인체를 검지하여 불필요한 전력 소모를 줄이기 위한 방법으로써 카메라를 통하여 실시간으로 영상을 취득하여 인체의 유무를 판단하기 위한 알고리즘을 구현하였다. 실험을 통하여 제안된 방법이 환경 변화에 강인한 특성과 인체 검출율이 우수함을 보이고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• 한국정보전자통신기술학회논문지
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• 제15권1호
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• pp.69-75
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• 2022

지금까지 발전 설비 터빈 블레이드의 이상 탐지는 사람에 의해 진행되어왔다. 하지만 발전 설비 노후화로 인한 이상 탐지 수요 증가와 터빈 블레이드의 이상을 검사하는 검사자 간의 기량 차로 인해 발생하는 검출 결과의 상이성으로 인해, 이러한 터빈 블레이드 이상 탐지 수요 증가와 인적 요소로 인해 발생하는 오류를 줄이고 높은 신뢰성의 터빈 블레이드 이상 검출성능을 안정적으로 제공할 수 있는 기법 개발의 필요성이 지속해서 제기되어 왔다. 이번 논문에서는 최근 다양한 분야에서 인상적인 성능 향상을 달성한 깊은 신경망을 이용한 발전 설비 터빈 블레이드의 이상 탐지 기술을 제안한다. 실험 결과는 제안된 기술이 인적 요소의 개입을 최소화함과 동시에 안정적인 이상 검출성능을 달성함을 증명한다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Asian Pacific Journal of Cancer Prevention
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• 제14권5호
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• pp.3177-3181
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• 2013

Background: Human papillomavirus (HPV) infection is the main causes of cervical cancer in women worldwide. The goal of the present study was to determine the prevalence and distribution of HPV genotypes in women from Saudi Arabia. Recently, several HPV detection methods have been developed, each with different sensitivities and specificities. Methods: In this study, total forty cervical samples were subjected to polymerase chain reaction and hybridization to BioFilmChip microarray assessment. Results: Human papillomavirus (HPV) infections were found in 43% of the specimens. The most prevalent genotypes were HPV 16 (30%) HPV 18 (8.0%) followed by type HPV 45, occurring at 5.0%. Conclusion: Our finding showed the HPV infection and prevalence is increasing at alarming rate in women of Saudi Arabia. There was no low risk infection detected in the tested samples. The BioFilmChip microarray detection system is highly accurate and suitable for detection of single and multiple infections, allowing rapid detection with less time-consumption and easier performance as compared with other methods.

• 한국식품위생안전성학회지
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• 제23권4호
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• pp.314-318
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• 2008

This research aimed to compare the detection methods of Anisakis simplex in Sea fish by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and macroscopic inspection. We examined 18 Trichiurus lepturus, 11 Scomber japonicus, and 65 Todarodes pacificus collected from the retail markets in the areas of Uljin, Kyuonggi province and Seoul. As the result of examinations, we found that detection rate of Anisakis simplex by macroscopic observation was 89% in Trichiurus lepturus, 90.9% in Scomber japonicus, 32.3% in Todarodes pacificus. The detection rate of Anisakis simplex by PCR-RFLP was 77.7% in Trichiurus lepturus, 81.8% in Scomber japonicus, 26.1% in Todarodes pacificus. We could conclude that PCR-RFLP method of Anisakis simplex was more specific rather than macroscopic observation.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.659-666
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• 2021

With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.783-786
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• 1997

Automatic realization of on-off human decision making was derived based on a conditional probability. Following the proposed procedure, problems of insulator washing timing in power substations and spike detection on EEG(electroencephalogram) records were appropriately solved.