• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.422-422
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• 2000

Parallel manipulators have been used to a variety of applications, including the motion simulators and mechanism for precise machining. A Stewart-Gough type parallel manipulator is composed of six linear joints which have wider contact areas than revolute ones, so linear joints are more affected by frictional force. First, the reference trajectories are computed from the model of the parallel manipulator assuming that it is subject to only the gravitational force and no friction exists. In the actual operation where friction exists, the control inputs, which correspond to the friction forces, are obtained by forcing the actual joint variables to follow these trojectories by proper control. It is shown that control performance can be improved when the friction compensation based on this information is added to the controller for position control of the moving plate of a parallel manipulator.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.103-110
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• 2008

In this thesis, we describe a statistical method for 3D object detection. In this method, we decompose the 3D geometry of each object into a small number of viewpoints. For each viewpoint, we construct a decision rule that determines if the object is present at that specific orientation. Each decision rule uses the statistics of both object appearance and "non-object" visual appearance. We represent each set of statistics using a product of histograms. Each histogram represents the joint statistics of a subset of wavelet coefficients and their position on the object. Our approach is to use many such histograms representing a wide variety of visual attributes. Using this method, we have developed the first algorithm that can reliably detect faces that vary from frontal view to full profile view and the first algorithm that can reliably detect cars over a wide range of viewpoints.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.215-216
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• 2005

To decrease and remove of much noises that is detected in PD (partial discharge) measuring test. we forced on detection of those. We made W-LC filter for measuring PD. which adapted that to field test. We tested after design laboratory circumstances like field line. and then the phase change properties of detected signal in UHF sensor were measured by Lemke Probe and oscilloscope (TDS-3054. Tektronix). Eventually we checked decrement of noises from experimental result. Also from experimental result at the joint box of 22.9[kV] distribution line. we obtained reasonable data which enable noises to decrease. Hereafter those results will be adapted at ultra-high voltage for trouble prevention and on-line cable watch. diagnosis of those.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.345-354
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• 2021

Recently, deep learning-based image recognition systems have been adopted to various surveillance environments, but most of them are still picture-type object recognition methods, which are insufficient for the long term temporal analysis and high-dimensional situation management. Therefore, we propose a method recognizing the specific dangerous situation generated by human in real-time, and utilizing deep learning-based object analysis techniques. The proposed method uses deep learning-based object detection and tracking algorithms in order to recognize the situations such as 'trespassing', 'loitering', and so on. In addition, human's joint pose data are extracted and analyzed for the emergent awareness function such as 'falling down' to notify not only in the security but also in the emergency environmental utilizations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.861-880
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• 2023

Semantic segmentation of road scene is the key technology of autonomous driving, and the improvement of convolutional neural network architecture promotes the improvement of model segmentation performance. The existing convolutional neural network has the simplification of learning knowledge and the complexity of the model. To address this issue, we proposed a road scene semantic segmentation algorithm based on multi-task collaborative learning. Firstly, a depthwise separable convolution atrous spatial pyramid pooling is proposed to reduce model complexity. Secondly, a collaborative learning framework is proposed involved with saliency detection, and the joint loss function is defined using homoscedastic uncertainty to meet the new learning model. Experiments are conducted on the road and nature scenes datasets. The proposed method achieves 70.94% and 64.90% mIoU on Cityscapes and PASCAL VOC 2012 datasets, respectively. Qualitatively, Compared to methods with excellent performance, the method proposed in this paper has significant advantages in the segmentation of fine targets and boundaries.

• Tunnel and Underground Space
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• v.13 no.5
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• pp.373-388
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• 2003

The investigation on the rock discontinuity geometry has been usually undergone by direct measurement on the rock exposures. But this sort of field work has disadvantages, which we, for example, restriction of surveying areas and consuming excessive times and labors. To cover these kinds of disadvantages, image processing could be regarded as an altemative way, with additional advantages such as automatic and objective tools when used under adequate computerized algorithm. This study was focused on the recognition of the rock discontinuities captured in the image of rock exposure by digital camera and the production of the discontinuity map automatically. The whole process was written using macro commands builtin image analyzer, ImagePro Plus. ver 4.1(Media Cybernetic). The procedure of image processing developed in this research could be divided with three steps, which are enhancement, recognition and extraction of discontinuity traces from the digital image. Enhancement contains combining and applying several filters to remove and relieve various types of noises from the image of rock surface. For the next step, recognition of discontinuity traces was executed. It used local topographic features characterized by the differences of gray scales between discontinuity and rock. Such segments of discontinuity traces extracted from the image were reformulated using an algorithm of computer decision-making criteria and linked to form complete discontinuity traces. To verify the image processing algorithms and their sequences developed in this research, discontinuity traces digitally photographed on the rock slope were analyzed. The result showed about 75～80% of discontinuities could be detected. It is thought to be necessary that the algorithms and computer codes developed in this research need to be advanced further especially in combining digital filters to produce images to be more acceptable for extraction of discontinuity traces and setting seed pixels automatically when linking trace segments to make a complete discontinuity trace.

• Proceedings of the Optical Society of Korea Conference
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• 2000.08a
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• pp.228-229
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• 2000

Buried channel JET-X CCDs (Joint European X-ray Telescope Charge Coupled Devices: EEV CCD12) with a deep depletion have been analyzed to provide an optimized condition for a charge storage and transfer. A maximum charge capacity has been found for the supplementary narrow channel by considering the potential distribution as a function of a mobile charge. Analysis for the depletion edges of JET-X CCDs have been successfully performed, showing good agreement with the depths estimated from X-ray detection efficiency measurements [1]. (omitted)

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.317-318
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• 2020

언택트 문화가 활성화되면서 다양한 업체에서 홈트레이닝 어플리케이션이 출시되고 있다. 많은 어플리케이션이 관절 특징점 검출 기능을 제공하여 사용자에게 편리함을 제공하지만, 자체 컨텐츠만 사용가능하다는 점에서 한계를 갖는다. 본 작품에서는 딥러닝 기반의 관절 특징점 검출기 및 특징 추출기를 결합하여 실시간 자세 유사도 측정기를 구현하였다. 목표영상 및 사용자의 관절 위치를 파악함과 동시에 관절 위치 정보에 대한 특징을 추출하여 자세 유사도를 실시간으로 점수화해 사용자에게 제공한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.929-933
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• 2014

The measurement of joint angle is important to evaluate the patient's disability. The modified fiber tip and light propagation of the developed fiber sensor were investigated to increase the range of angle detection. Different shapes of fiber tips were manufactured with a polishing machine to deliver light signal in various patterns. Output signals were analyzed to obtain joint angle change with inverse polynomial models. The measured joint angles were displayed with LabVIEW program and the reliability was tested by comparing with a commercial angle sensor. This method can be used in rehabilitation field to determine patient's progress.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.10
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• pp.856-867
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• 2018

This paper presents the applicability of MIMO joint decoding to dual-contact satellite systems in which two LEO satellites using X-band frequency band are transmitting each image data to two ground station antennas, simultaneously. When two satellites are closely positioned within the looking angle of the two antennas, each satellite interferes with each other by the relative antenna gain corresponding to an offset angle and this might cause the performance degradation without interference mitigation. To mitigate the performance degradation, SM MIMO techniques for joint decoding are applied. Especially, the relative antenna gain of ground station depending on the angle difference between two satellites in ground station antenna plays an important role in modelling the dual-contact satellite systems. The condition number of MIMO channel including the antenna gain calculated from the mathematical gain pattern model was primarily analyzed. Simulation results showed that the SM MIMO techniques using detection schemes such as ZF-SIC, MMSE-SIC, and ML can be applicable to dual-contact satellite systems.