• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.82-96
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• 2024

While analyzing traffic flow, speed, traffic volume, and density are important macroscopic indicators, and acceleration and spacing are the important microscopic indicators. The speed and traffic volume can be collected with the currently installed traffic information collection devices. However, acceleration and spacing data are necessary for safety and autonomous driving but cannot be collected using the current traffic information collection devices. 'You Look Only Once'(YOLO), an object recognition technique, has excellent accuracy and real-time performance and is used in various fields, including the transportation field. In this study, to measure acceleration and spacing using YOLO, we developed a model that measures acceleration and spacing through changes in vehicle speed at each interval and the differences in the travel time between vehicles by setting the measurement intervals closely. It was confirmed that the range of acceleration and spacing is different depending on the traffic characteristics of each point, and a comparative analysis was performed according to the reference distance and screen angle to secure the measurement rate. The measurement interval was 20m, and the closer the angle was to a right angle, the higher the measurement rate. These results will contribute to the analysis of safety by intersection and the domestic vehicle behavior model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.157-167
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• 2010

Density is the most important congestion indicator among the three fundamental flow variables, flow, speed and density. Measuring density in the field has two different ways, direct and indirect. Taking photos with wide views is one of direct ways, which is not widely used because of its cost and lacking of proper positions. Another direct density measuring method using two point detectors has been introduced with the concept of instantaneous density, average density and measurement interval. The relationship between accuracy and measurement interval has been investigated using the SIMULATION data produced by Paramics Application Programming Interface function. We analyze the affect of segment density accuracy by sensing gap each road condition such as sensing segment length, lane and LOS after gathering data by Paramics Application Programming Interface.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.457-464
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• 2019

The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig's weight is an important issue in productivity perspective. In order to estimate the pig's weight by using the number of pig's pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig's posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig's head by using light weighted image processing technique. First, we determine the pig's posture by comparing the length from the center of the pig's body to the outline of the pig in the binary image. Then, we train the location of pig's head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig's head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig's head. In the Experiment result, we confirmed that the pig's posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig's head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.10-16
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• 2004

In this paper the aeroacoustic characteristics of a helicopter main rotor system is measured by using a pair of scaled rotor blades. A low noise rotor test jig is developed for noise measurement and the rotational speed, thrust and torque are measured simultaneously in order to match the aerodynamic conditions with the full scale rotor. The accuracy of the force measurement device was checked through a calibration procedure. The measured thurst and torque with a 1.2m rotor are compared to the results of analytical prediction and showed that the thrust data at various rotational speed followed the prediction relatively well, but the torque data considered less accurate. It is also found that the background noise level of the test rig is sufficiently low, and the measured noise level from the rotor can be scaled with rotor tip speed. However, the Mach number dependancy and the directivity changes depend on the noise source characteristics.

• Proceedings of the KWS Conference
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• 2010.05a
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• pp.77-77
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• 2010

본 연구에서는 Sn-3.0Ag-0.5Cu (SAC305) 무연솔더의 최적 인쇄성을 위한 PCB 및 마스크설계, 스크린프린팅 공정변수의 최적값을 실험계획법을 통해 평가하였다. 사용된 칩은 가로 0.4mm 세로 0.2mm의 0402 MLCC칩이며, 사용된 시험보드는 OSP 표면처리된 PCB이었다. 인쇄성을 판단하기 위한 공정인자는 금속마스크 두께, 마스크홀 크기, 패드크기 및 모양, 인쇄각도, 인쇄속도, 판분리속도이었다. ANOVA분석을 통해 주인자를 파악하였으며, 인쇄성에 영향을 미치는 주인자는 마스크두께와 인쇄각도임이 확인되었다. 그 후 중심 합성법을 이용하여 인쇄성 최적 조건을 확인하였다. 결과로 나타난 등고선/표면도를 통해, 마스크두께가 작을 때에는 인쇄각도가 작아야 높은 인쇄성을 갖으며, 또한 마스크 두께가 클 경우에는 인쇄각도가 커야 높은 인쇄성을 가짐을 알 수 있었다. 추가실험을 통해서 인쇄성 표면도의 정확도를 확인하였으며, 실험값은 표면도에서 표시된 인쇄성값과 비슷함을 알 수 있었다. 또한, 인쇄성이 낮은 영역과 높은 영역에서 접합강도값을 측정하였으며, 인쇄성이 좋은 영역에서 접합강도도 높음을 알 수 있었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.169-175
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• 2018

Recently, power dissipation issue is very significant not only in high-end modern processors but also in embedded systems and mobile devices. Based on the power dissipation, hardware and software designers can correctly find the power/performance tradeoffs. Most power analysis tools calculate power dissipation when chip layout or floor planning are finished. In this paper, a trace-driven simulator that can interact with power analysis tool for an embedded microprocessor has been developed. Using MiBench embedded benchmarks as input, the trace-driven simulation has been performed to estimate the average power dissipation which is faster than the conventional tools.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.447-452
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• 2013

Vessel traffic system uses multiple sea surveillance radars as a primary sensor to obtain maritime traffic information like as ship's position, speed, course. The systematic errors such as the range bias and the azimuth bias of the two-dimensional radar system can significantly degrade the accuracy of the radar image and target tracking information. Therefore, the systematic errors of the radar system should be corrected precisely in order to provide the accurate target information in the vessel traffic system. In this paper, it is proposed that the method compensates the range bias and the azimuth bias using AtoN information installed at VTS coverage. The radar measurement residual error model is derived from the standard error model of two-dimensional radar measurements and the position information of AtoN, and then the linear Kalman filter is designed for estimation of the systematic errors of the radar system. The proposed method is validated via Monte-Carlo runs. Also, the convergence characteristics of the designed filter and the accuracy of the systematic error estimates according to the number of AtoN information are analyzed.

• Journal of the Korean Geotechnical Society
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• v.27 no.7
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• pp.5-16
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• 2011

Digital image analysis techniques have been developed and utilized in the field of solid mechanics and fluid mechanics to measure the deformation and velocity of a target object. The deformation measurement systems based on Particle Image Velocimetry (PIV) and Digital Image Correlation (DIC) have been attempted in geotechnical testings (e.g., physical model tests) for observing the deformation of soils. The digital image analysis is influenced by image pattern of test materials, resolution of the used digital camera, target area, image analysis techniques, and analysis conditions. Therefore, optimal analysis conditions should be determined to obtain high quality results on soil deformations. In the present study, various influence factors on the digital image analysis were described and summarized. The optimizing procedure for high accurate results was then proposed. Finally, the applicability of the developed procedure was examined.