• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.684-692
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• 2016

In the manufacturing process of the LQFP/TQFP (Low-profile Quad Flat Package/Thin Quad Flat Package), the requirement of a 3 dimensional inspection is increasing rapidly and a 3D inspection of the shape of a chip has become an important report of quality control. This study developed a 3 dimensional measurement system based on PMP (Phase Measuring Profilometry) for an inspection of the LQFP/TQFP chip and image processing algorithms. The defects of the LQFP/TQFP chip were classified according to the dimensions. The 2 dimensional optical system was designed by the dorm illumination to achieve constant light distribution, In the 3 dimensional optical system, PZT was used for moving 90 degree in phase. The problem of 2 ambiguity was solved from the measured moir? pattern using the ambiguity elimination algorithm that finds the point of ambiguity and refines the phase value. The proposed 3D measurement system was evaluated experimentally.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.644-649
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• 2013

For effective DC-free coding in the optical storage systems, the Guided Scrambling algorithm is widely used. To reduce digital discrepancy of the coded sequence, functions of digital sum value (DSV) are used as criteria to choose the best candidate. Among these criteria, the minimum digital sum value (MDSV), minium squared weight (MSW), and minimum threshold overrun (MTO) are popular methods for effective DC-suppression. In this paper, we formulate integer programming models that are equivalent to MDSV, MSW, and MTO GS coding. Incorporating the MDSV integer programming model in MaxMin setting, we develop an integer programming model that computes the worst case MDSV bound given scrambling polynomial and control bit size. In the simulation, we compared the worst case MDSV bound for different scrambling polynomial and control bit sizes. We find that careful selection of scrambling polynomial and control bit size are important factor to guarantee the worst case MDSV performance.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3717-3729
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• 2024

Accurately predicting evacuation time in a ventilated main control room (MCR) during fire emergencies is crucial for ensuring the safety of personnel at nuclear power plants. This study proposes to use neural networks alongside consolidated fire and smoke transport (CFAST) simulations to serve as a surrogate model for physics-based simulation tools. Our neural networks can promptly predict the evacuation time in MCRs, proving to be a valuable asset in fire emergencies and eliminating the need for time-consuming rollouts of the CFAST simulations. The CFAST model simulates fire and evacuation scenarios in a ventilated MCR with variations in input parameters such as door conditions, ventilation flow rate, leakage area, and fire propagation time. Target output parameters, such as hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD), are used alongside standardized evacuation variables to train a machine learning model for predicting evacuation time. The findings suggest that high ventilation flow rates help to dilute smoke and discharge hot gas, leading to lower target output parameters and quicker evacuation. Standardized evacuation variables exceed the required abandonment criteria for all door conditions, indicating the importance of proper evacuation procedures. The results show that neural networks can generate evacuation times close to those obtained from CFAST simulations.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.160-167
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• 2007

In this paper, we presented the development results of high speed wavefront sensor which is used in diagnosing the beam quality of He-Ne laser for adaptive optics system. The beam quality information of laser in AO system is necessarily required for diagnosing the optical components or correcting the distorted wavefront afterward. According to system requirements, normally, it is requested that there are high precision of measurement and real time processing speed. The developed wavefront sensor in this paper achieved maximum 30Hz of measurement rate and ${\lambda}/20(\;{@}\;{\lambda}=0.6328{\mu}m)$ of measurement precision in RMS. We also applied the developed into an experimental adaptive system and verified the performance of it by correcting the aberrated wavefront with a rate of 30Hz and $\lambda$/20 precision using the combination of the developed and PID control algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.673-683
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• 2010

This study investigates Terrain Aided Inertial Navigation(TAIN) which consists of Inertial Navigation System (INS) with the optical sensor for precise planetary landing. Image processing is conducted to extract the feature points between measured terrain data and on-board implemented terrain information. The navigation algorithm with Iterated Extended Kalman Filter(IEKF) can compensate for the navigation error, and provide precise navigation information compared to single INS. Simulation results are used to demonstrate the feasibility of integration to accomplish precise planetary landing. The proposed navigation approach can be implemented to the whole system coupled with guidance and control laws.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.12
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• pp.1217-1222
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• 2012

A wall flow sensor has been used for feedback flow control and wall shear stress measurement. In this study, we developed a new wall flow sensor by combining the PIV algorithm and the micro image sensor used in an optical mouse. The feasibility of the wall flow sensor was investigated by using simulated fluid flow experiments. Compared with the quadrature signal from imaging devices, the accuracy of the wall flow velocity measurement was improved and the dynamic range increased. In addition, the depth information of particles was also measured by using the defocusing imaging technique.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.83-83
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• 2000

Recently, Vision system has being used all around industry. Sensor systems are used for Mark Reader, for example, optical scanning is proximity sensor system, have many disadvantages, such as, lacking user interface and difficulty to store original specimens. In contrast with this, Vision systems for Mark Reader has many advantages, including function conversion to achieve other work, high accuracy, high speed, etc. In this thesis, we have researched the development of Mark Reader by using a Vision system. The processing course of this s)'stem is consist to Image Pre-Processing such as noise reduction, edge detection, threshold processing. And then, we have carried out camera calibration to calibrate images which are acquired from camera. After searching for reference point within scanning area(60pixe1${\times}$30pixe1), we have calculated points crossing by using line equations. And then, we decide to each ROI(region of interest) which are expressed by four points. Next we have converted absolute coordinate into relative coordinate for analysis a translation component. Finally we carry out Mark Reading with images classified by six patterns. As a result of experiment which follows the algorithm has proposed, we have get error within 0.5% from total image.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.405-412
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• 2013

Purpose: In this paper, the improvement of the image quality is investigated. The image quality is degraded by the drift phenomenon of EO/IR (Electro-Optical/Infrared) device on UAV. The drift phenomenon means that the image of EO/IR equipment on UAV(Unmanned Aerial Vehicle) moves to the unintended direction. This phenomenon should be improved for successful flight mission. Methods: To improve the drift phenomenon, the drift compensation method, the combination algorithm of FMC(Forward Motion Compensation) and AMC(Angular Motion Compensation) method, are introduced to calculate pitch and azimuth angle. Result values of pitch and azimuth angle are used for the improvement of image quality in EO/IR control logic. Results: The image quality is quantitatively improved more than 15 times through field test data of flight. Conclusion: Using the drift compensation technique, the image quality for EO/IR equipment is improved over 15 times than existing methods. This means the user of UAV with EO/IR device can perform a successful mission by keeping the line of sight for the target accurately.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.923-928
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• 2018

We developed a compact gamma camera based on a modified uniformly redundant array coded aperture to investigate the position of a $UO_2$ pellet emitting characteristic X-rays (98.4 keV) and ${\gamma}-rays$ (185.7 keV). Experiments using an only-mask method and an antimask subtractive method were conducted, and the maximum-likelihood expectation maximization algorithm was used for image reconstruction. The images obtained via the antimask subtractive method were compared with those obtained using the only-mask method with regard to the signal-to-noise ratio. The reconstructed images of the antimask subtractive method were superior. The reconstructed images of the characteristic X-rays and the ${\gamma}-rays$ were combined with the obtained image using the optical camera. The combined images showed the precise position of the $UO_2$ pellet. According to the self-absorption ratios of the nuclear material and the minimum number of effective events for image reconstruction, we estimated the minimum detection time depending on the amount of nuclear material.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.