• 대한교통학회지
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• 제27권6호
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• pp.79-88
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• 2009

본 연구는 차종분류기법을 개발하여, 가장 일반적인 교통정보 수집장치인 루프검지기에 피에조타입의 축검지센서를 추가 설치하여 2006년 하반기 국토해양부에서 제시하고 있는 "통합12종 교통량조사 차종분류가이드"에 따라 차종을 12종으로 자동분류하고, 분류시 오분류를 최소화하는 방안을 목적으로 한다. 차종의 세분류를 위해 차종분류인자를 차량의 길이, 축간거리, 축형식, 각 축별 윤거, 윤형식으로 두고, 각 분류인자의 판독을 위해 루프센서와 축검지센서를 조합한 차종분류시스템을 구성하였다. 본 차종분류시스템에서는 원더링 기법을 적용하였다. 원더링 기법은 차량의 좌우 각 차륜의 횡방향 주행 패턴을 분석하는 것으로서 주행차량의 윤거, 윤형식 등이 판독가능하다. 본 시스템을 이용하여 약 한달간 실증분석을 실시하였으며, 총 교통량 762,420대를 자동분류한 결과 12종 분류로 분류되지 못한 차량이 47대로 전체의 0.006%로 나타났으며, 이는 분류결과를 통계적으로 활용함에 있어서 무시할 수 있는 정도의 높은 수준의 분류율을 나타내는 것이다. 본 시스템을 이용하여 실제 공용도로에서 확보한 신뢰성 높은 차종분류 데이터는 도로의 계획 및 설계, 도로 운영 등에 폭넓게 이용할 수 있으며, 도로 교통계획과 관리계획 수립을 위한 기초적 정보를 제공할 수 있다. 또한 도로 및 교통분야의 다양한 연구에 활용할 수 있는 중요한 자료가 될 것이다.

• 한국자동차공학회논문집
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• 제14권6호
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• pp.120-126
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• 2006

Vehicle dynamic simulation has been carried out using the coherence of road roughness between left and right wheels. The generated twin tracks with the coherence of road roughness between left and right wheels are in good agreements with the measured coherence relation of left and right wheels. And these tracks reflect well on the roughness characteristics of real roads. Using the generated roads and multibody dynamic simulation program, vehicle dynamic simulation is performed. The vertical and roll motion analysis of a vehicle are carried out using the realistic road profiles with the coherence between left and right wheels and the results are in good agreements with the dynamic characteristics of a vehicle.

• 전기학회논문지
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• 제65권10호
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• pp.1731-1737
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• 2016

In this paper, a method is proposed to recognize human actions as nonverbal expression; the proposed method is composed of two steps which are action representation and action recognition. First, MHI(Motion History Image) is used in the action representation step. This method includes segmentation based on depth information and generates spatio-temporal templates to describe actions. Second, CNN(Convolution Neural Network) which includes feature extraction and classification is employed in the action recognition step. It extracts convolution feature vectors and then uses a classifier to recognize actions. The recognition performance of the proposed method is demonstrated by comparing other action recognition methods in experimental results.

• 대한전기학회논문지
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• 제37권8호
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• pp.563-569
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• 1988

본 논문에서는 공통의 작업장에서 운용되는 두 개의 매니퓰레이터의 충돌회피를 위한 속도변형 방법들이 연구된다. 두 매니퓰레이터의 상호충돌시 현저한 특성으로 인한 여러 종류의 새로운 충돌양상이 연구되며 무충돌 운용을 계획하는데 사용된다. 충돌지도와 속도변형의 개념들이 무충돌 운용을 계{획하기 위해 개발 적용된다. 한가지 예가 궤적의 속도 가감을 보이기 위해 예시도었으며, 이 예는 움직이는 두 로보트 매니퓰레이터의 무충돌 궤도 계획을 위한 제안된 방법들의 유용성을 보여준다.

• 전기학회논문지
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• 제65권1호
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• pp.194-199
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• 2016

EMG has specific information which is related to movements according to the activities of muscles. Therefore, users can intuitively control a prosthesis. For this reason, biosignals are very useful and convenient in this kind of application. Bioimpednace also provides specific information about movements like EMG. In this study, we used both EMG and bioimpedance to classify the typical hand gestures such as hand open, hand close, no motion (rest), supination, and pronation. Nine able-bodied subjects and one amputee were used as experimental data set. The accuracy was $98{\pm}1.9%$ when 2 bio-impedance and 8 EMG channels were used together for normal subjects. The number of EMG channels affected the accuracy, but it was stable when more than 5 channels were used. For the amputee, the accuracy is higher when we use both of them than when using only EMG. Therefore, accurate and stable hand motion estimation is possible by adding bioimepedance which shows structural information and EMG together.

• 방송공학회논문지
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• 제7권4호
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• pp.291-299
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• 2002

본 논문은 밝기 변화가 심한 비디오 시퀀스에 대해 효율적인 움직임 보상 알고리즘을 제안한다 제안한 알고리즘에서는 화면간의 밝기 변화 변수들을 추정하고 지역적인 움직임 보상을 수행한다. 밝기 변화가 심한 화면을 검출하기 위해 화면간의 히스토그램의 크로스 엔트로피를 계산하여 밝기 변화가 심한 화면을 그렇지 않은 화면과 나누어 불필요한 계산량을 줄였다. 밝기 변화가 심한 비디오 시퀀스에 대한 실험결과 제안한 알고리즘은 기존의 알고리즘에 비해 적은 계산량으로 높은 PSNR (peak signal to noise ratio) 성능을 나타내었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1254-1257
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• 1993

Presented in this paper is a newly developed motion planning method of an autonomous mobile robot(MAR) which can be applied to flexible manufacturing systems(FMS). The mobile robot is designed for transporting tools and workpieces between a set-up station and machines according to production schedules of the whole FMS. The proposed method is implemented based on an earlier developed real-time obstacle avoidance method which employs Kohonen network for pattern classification of sonar readings and fuzzy logic for local path planning. Particulary, a novel obstacle avoidance method for moving objects using a collision index, collision possibility measure, is described. Our method has been tested on the SNU mobile robot. The experimental results show that the robot successfully navigates to its target while avoiding moving objects.

• 산업공학
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• 제16권1호
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• pp.85-93
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• 2003

The purposes of this study are to investigate perceived discomfort for static joint motions, and to propose rankings for the joint motions based on the perceived discomfort. The perceived discomfort was measured through an experiment using the free modulus method of the magnitude estimation, in which ten healthy college-age female students participated. The results showed that joints, joint motions and their levels significantly affected the perceived discomfort at $\alpha$=0.01, and that the interaction of joints and joint motion levels was also significant. Based on the experimental results, three rankings were proposed by joint and joint motions, by joints and by joint motions, which were very different from the existing ones. Especially, the proposed rankings were different from the males' published before in their order and magnitude. These rankings can be used as a valuable tool for better understanding potentially adverse effects of poor working postures in industrial sites, and as basic data for developing the postural classification scheme.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2003년도 춘계 학술발표회논문집
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• pp.61-68
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• 2003

The H/V ratio (Horizontal to Vertical spectral ratio) has been used to infer site amplification without previous knowledge of near-surface geology and in fact may provide useful general site condition information. This method is used to classify the site characteristics of seismic stations in Korea by comparison with known H/V ratios representative of various sites all over the world. In addition, differences between horizontal and vertical kappa values were evaluated for each seismic stations by comparing WV ratio and Weak Motion amplification derived from inversion of stochastic ground motion parameters and were used as index to quantitatively classify the site characteristics.

• 한국컴퓨터정보학회논문지
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• 제24권6호
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.