• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.161-161
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• 2012

본 연구에서는 InGaAs을 이용한 테라헤르쯔(THz) 발생과 검출 특성을 GaAs에 의한 특성과 비교, 조사하였다. 고온성장(HTG, $530^{\circ}C$) InGaAs를 이용하여 photo-Dember (pD) 효과(표면방출)에 의한 THz 발생 특성을 조사하였으며, THz 검출 특성에는 저온성장(LTG, $530^{\circ}C$) InGaAs: Be을 이용하였다. HTG-InGaAs 기판 위에 패턴한 금속전극 (Ti/Au, ${\sim}500{\times}500{\mu}m$)의 가장자리에 Ti: Sapphire fs 펄스 레이저(30 ps/90 MHz)를 조사하여 LTG-GaAs 수신기(Rx)로 THz를 검출, 전류신호(a)와 Fourier transform (FT) 주파수 스펙트럼(b)을 얻었다. HTG-InGaAs에서 얻은 파형은 SI-GaAs에서와 거의 비슷한 모양이었으나, 주파수 범위(0.5~2 THz)는 SI-GaAs의 1~3 THz 보다 좁고 FT 스펙트럼의 세기는 약 1/8 정도로 낮았다. LTG-InGaAs 수신기 (Rx)의 안테나는 쌍극자 ($5/20{\mu}m$) 형태를 가지고 있으며, SI-GaAs Tx로 발생시킨 광원을 사용하여 THz 영역의 검출 특성을 조사하였다. HTG-InGaAs Tx 및 LTG-InGaAs Rx의 이득은 각각 약 $5{\times}10^{-8}$ A/W과 $2.5{\times}10^{-8}$ A/W인 것으로 분석되었다.

• 한국생물공학회:학술대회논문집
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• 2003.04a
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• pp.74-78
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• 2003

Multi-channel images of 11-MUA and 11-MUOH self-assembled monolayers were obtained by using two-dimensional surface plasmon resonance (SPR) absorption. Patterning process was simplified by exploiting direct photo-oxidation of thiol bonding (photolysis) instead of conventional photolithography. Sharper images were resolved by using a white light source in combination with a narrow bandpass filter in the visible region, minimizing the diffraction patterns on the images. The line profile calibration of the image contrast caused by different resonance conditions at each points on the sensor surface (at a fixed incident angle) enables us to discriminate the monolayer thickness in sub-nanometer scale. Furthermore, there is no signal degradation such as photo bleaching or quenching which are common in the detection methods based on the fluorescence.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.131-142
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• 1994

Generally, there are two methods which generates the base map of Geo-Spatial Information System(GSIS). one is the digitizing of existing map, and the other is the analytical plotting method editing data acquired by sensors using computers. But the analytical plotting method and method of the digitizing of existing map is technically complex and has the disadvantages in the costs and time. The subject region of study(the Kwangyang province), was photographed by aircraft, and photographing scale was 1/6,000. Then this area was divided into two specific regions, the residential area, and the agricultural area. In this study, we developed the algorithm that generated base map of database in GSIS from the aerial photo. This algorithm is as followed. First, the digital aerial photos were generated using these aerial photos. Second, these digital aerial photos were enhanced by implementing the histogram equalization. Third, the objects of the enhanced images were extracted by implementing thresholding and edged detection techiques of image segmentation. Finally, these images could be used to updated the base map of database in GSIS. The result obtained from this study showed that method used by this study were more efficient than existing method in costs and time.

• Korean Journal of Food Science and Technology
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• v.25 no.4
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• pp.391-394
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• 1993

For the automation of Tackjoo fermentation, a sensor measurable gas production during brewing and a controller were built. The performance tests were carried out at 10 litter Tackjoo fermentor, The sensor was consisted of a transparent acryl cell for bubble formation and photo-interrupter for the detection of bubbles of 0.018ml size. The fermentation controller was fabricated with a single chip microcomputer (MC68705R3) and provided with both the monitoring module of temperature measurement and the valve controling device for the cooling water circulation in coil type heat exchanger. The operation programs were developed and systemized in ROM. With this computer system, the gas production amount and rate were acquired during the Tackjoo fermentation. The fermentation curve based on the gas production rate showed a good agreement with that of alcohol concentration. The maximum rate of gas production was found after 24 hr at $30^{\circ}C$. The correlation equation between the gas production and alcohol concentration was established and used as the control algorithm of the fermentation.

• Korean Journal of Optics and Photonics
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• v.14 no.1
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• pp.97-102
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• 2003

Multi-channel images of 11-MUA(11-Mercaptoundecanoic acid) and 11-MUOH(11-Mercaptoundecanol) self-assembled monolayers were obtained by using two-dimensional surface plasmon resonance (SPR) absorption. The patterning process was simplified by exploiting direct photo-oxidation of thiol bonding (photolysis) instead of conventional photolithography. Sharper images were resolved by using a white light source in combination with a narrow bandpass filter in the visible region, minimizing the diffraction patterns on the images. The line profile calibration of the image contrast caused by different resonance conditions at each point on the sensor surface (at a fixed incident angle) enables us to discriminate the monolayer thickness in nanometer scale. Furthermore, there is no signal degradation such as photo bleaching or quenching, which are common in the detection methods based on fluorescence.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.3
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• pp.459-464
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• 2012

The point of impact, the shot group, and the flight traces depend on the combination of unique features which decide moving traces of the arrow (paradox of the archer, length of the arrow shaft, weight, angle of the feather, and spline of the arrow shaft). The more dense the impact points in the shot group and the earlier elimination of paradox of the archer, the higher assessment is given for the product. However, there is no way to objectively assess the efficiency and quality of the arrow, and there is no numeric data to be used as the basis for comparison with other products. Although capturing the images of flying arrow using a high-speed motion picture camera is possible, we are limited to observation from specific view angle only. Hence, the criteria for efficiency and quality assessment are mostly based on subjective opinions of experts or hunters, or review on consumers' remarks. In this paper, we propose a hardware composition that are based on three detection frames consisting of line lasers and photo diode arrays without the high-speed motion picture camera. Predicated on measured coordinates data, a nobel method for the archer's paradox measurement, a key parameter that determine the arrow's trajectory, and corresponding numerical analysis model is proposed.

• Journal of Sensor Science and Technology
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• v.12 no.4
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• pp.191-197
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• 2003

Due to explosive increase of internet usage, broadband data transmission using optical fibers is broadly used. In order to decrease distortion during long distance transmission, the optical signal need to be restored, typically, by converting the optical signal into the electrical signal. The optical signal is converted into the electrical signal using a photo-diode, and then a clock-and-recovery (CDR) circuit is used to recover the clock and retime the data. In this study, a clock-and-data recovery circuit has been designed using a standard 1.8 V $0.18\;{\mu}m$ CMOS process. With this CDR circuit, the improved phase detector and charge pump have been utilized. Also, by using a ring oscillator, the CDR circuit can recover clock and data from broadband multi-rate data ranging between 750 Mb/s and 2.85 Gb/s.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.65-75
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• 2017

As a 360-degree image carries information of all directions, it often has too much information. Moreover, in order to investigate a 360-degree image on a 2D display, a user has to either click and drag the image with a mouse, or project it to a 2D panorama image, which inevitably introduces severe distortions. In consequence, investigating a 360-degree image and finding an object of interest in such a 360-degree image could be a tedious task. To resolve this issue, this paper proposes a method to find a region of interest and produces a 2D naturally looking image from a given 360-degree image that best matches a description given by a user in a natural language sentence. Our method also considers photo composition so that the resulting image is aesthetically pleasing. Our method first converts a 360-degree image to a 2D cubemap. As objects in a 360-degree image may appear distorted or split into multiple pieces in a typical cubemap, leading to failure of detection of such objects, we introduce a modified cubemap. Then our method applies a Long Short Term Memory (LSTM) network based object detection method to find a region of interest with a given natural language sentence. Finally, our method produces an image that contains the detected region, and also has aesthetically pleasing composition.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.