• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.254-257
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• 1996

A Rapid Thermal Processing (RTP) system operated below $500^{\circ}C$ has been designed and constructed. It uses an optical pyrometer for measuring wafer temperature, the sensing range of pyrometer is from $2.0{\mu}m$ to $2.4{\mu}m$. To remove the interference effect by IR emitted from lamps an IR filter is adapted which uses water. The best condition for Al alloy using the RTP system is $425^{\circ}C$ for ten seconds. The RTP system uses many lamps for supplying enough power in processing wafer because the absorption wavelength range of IF filter is from $1.3{\mu}m$ to $4.0{\mu}m$. However, reproducibility and uniformity is reduced due to the difference of lamp characteristics. Therefore, for improving the reproducibility and uniformity new RTP system using one lamp is designed. The new RTP system uses a focusing mirror and it focuses the light of lamp. The curverture of the focusing mirror is controlled to supply uniform power in processing wafer. The result of computer simulation shows the possibility of new RTP system using one lamp.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.311-317
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• 2011

The blind spot is an area where drivers visibility does not reach. When drivers change a lane to adjacent lane, they need to give an attention because of the blind spot. If drivers try to change lane without notice of vehicle approaching in the blind spot, it causes a reason to have a car accident. This paper proposes a night-time blind spot vehicle detection using cameras. At nighttime, head-lights are used as characteristics to detect vehicles. Candidates of headlight are selected by high luminance feature and then shape filter and kalman filter are employed to remove other noisy blobs having similar luminance to head-lights. In addition, vehicle position is estimated from detected head-light, using virtual center line represented by approximated the first order linear equation. Experiments show that proposed method has relatively high detection porformance in clear weather independent to the road types, but has not sufficient performance in rainy weather because of various ground reflectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.353-368
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• 2023

The four wing unmanned aerial vehicle owns the characteristics of small size, light weight, convenient operation and well stability. But it is easily disturbed by external environmental factors during flight with these disadvantages of short endurance and poor attitude solving ability. For solving these problems, a microprocessor based on STM32 chip is designed and the overall development is completed by the resources such as built-in timer and multi-function mode general-purpose input/output provided by the master micro controller unit, together with radio receiver, attitude meter, barometer, electronic speed control and other devices. The unmanned aerial vehicle can be remotely controlled and send radio waves to its corresponding receiver, control the analog level change of its corresponding channel pins. The master control chip can analyze and process the data to send multiple sets pulse signals of pulse width modulation to each electronic speed control. Then the electronic speed control will transform different pulse signals into different sizes of current value to drive the motor located in each direction of the frame to generate different rotational speed and generate lift force. To control the body of the unmanned aerial vehicle, so as to achieve the operator's requirements for attitude control, the PID controller based on Kalman filter is used to achieve quick response time and control accuracy. Test results show that the design is feasible.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.7
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• pp.46-52
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• 1995

This paper proposes methodologies for the development of radiation thermometer using InSb photo-detector of which spectral sensitivity is excellent over the wave length range of 2 .mu. m .approx. 5 .mu. m. The proposed radiation thermometer has broad measurement range from normal to high, up to more than 1000 .deg. C, with high accuracy, and can measure temperature on the material surface or heat emission noncontactely with high speed. Optical system was consisted of two convex lens with foruslength of 15.2mm for infrared lay focusing, Ge filter to cut the short wave length components and sapphire filter to cut the long wave length components. The cold shielded was installed in the whole surface of the light-absorbing element to remove the error- mometer, calibration using black body furnace which has temperature range of 90 .deg. C .approx. 1100 .deg. C was carried out, and temperature calaibration curve was obtained by exponential function curvefitting. The result shows maximum error less than 0.24%(640K .+-. 1.6K) over the measurement range of 90 .deg. C .approx. 700 .deg. C, and from this result the usefulness of the developed thermometer has been confirmed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.174-179
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• 2003

Through the simultaneous localization and map building (SLAM) technique, a robot can create maps about its unknown environment while it continuously localizes its position. Grid maps and feature maps have been widely used for SLAM together with application of probability methods and POMDP (partially observed Markov decision process). But this approach based on grid maps suffers from enormous computational burden. Topological maps, however, have drawn more attention these days because they are compact, provide natural interfaces, and are easily applicable to path planning in comparison with grid maps. Some topological SLAM techniques like GVG (generalized Voronoi diagram) were introduced, but it enables the robot to decide only whether the current position is part of GVG branch or not in the GVG algorithm. In this paper, therefore, to overcome these problems, we present a method for updating a global topological map from the local topological maps. These local topological maps are created through a labeled Voronoi diagram algorithm from the local grid map built based on the sensor information at the current robot position. And the nodes of a local topological map can be utilized as the features of the environment because it is robust in light of visibility problem. The geometric information of the feature is applied to the extended Kalman filter and the SLAM in the indoor environment is accomplished. A series of simulations have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can be applied relatively well.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.212-217
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• 2007

As a preliminary study for the development of electrical stimulation strategy of artificial retina, we set up a method fur the reconstruction of input intensity variation from retinal ganglion cell(RGC) responses. In order to estimate light intensity variation, we used an optimal linear filter trained from given stimulus intensity variation and multiple single unit spike trains from RGCs. By applying ON/OFF stimulation(ON duration: 2 sec, OFF duration: 5 sec) repetitively, we identified three functional types of ganglion cells according to when they respond to the ON/OFF stimulus actively: ON cell, OFF cell, and ON-OFF cell. Experiments were also performed using a Gaussian random stimulus and a binary random stimulus. The input intensity was updated once every 90 msec(i. e. 11 Hz) to present the stimulus. The result of reconstructing 11 Hz Gaussian and binary random stimulus was not satisfactory and showed low correlation between the original and reconstructed stimulus. In the case of ON/OFF stimulus in which temporal variation is slow, successful reconstruction was achieved and the correlation coefficient was as high as 0.8.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.81-87
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• 2006

In this paper, an experimental optical head tracker system is designed and constructed. The system is composed of the infrared LEDs and two infrared CCD cameras to filter out the interference of another light in the limited environment like the cockpit. Then the optical head tracker algorithm is designed by using the feature detection algorithm and the 3D motion estimation algorithm. The feature detection algorithm, used to obtain the 2D position coordinates of the features on the image plane, is implemented by using the thresholding and the masking techniques. The 3D motion estimation algorithm which estimates the motion of a pilot's head is implemented by using the extended Kalman filter (EKF). Also, we used the precise rate table to verify the performance of the experimental optical head tracker system and compared the rotational performance of this system with the inertial sensor.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.1-10
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• 2011

In this paper, we propose the algorithm for the AR(Augmented Reality) system, which is robust to the brightness change of light. In the proposed method, the histogram specification is achieved using the sample histogram, obtained from the frames in which the target objects could be detected successful. And When the object key-points couldn't be detected by the displacement of camera positions, the positions of non-detected key-points ware estimated using the linear KF(Kalman Filter). When the proposed algorithm is applied in the AR systems, the object key-points can be detected three times as much as the existing others. In addition, to prove the more efficiency of the proposed algorithm, we implemented the AR game, and could know that the performance is the more advanced than the others. The proposed algorithm can be used for the AR environments, which high efficiency is required such as the AR game, or the implementation of AR systems which are robust to the change of lights, etc.