• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.82-90
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• 2011

This paper proposes an advanced outdoor localization algorithm of a GPS(global positioning system)-INS(inertial navigation system) integration system. In order to reduce noise from the internal INS sensors, discrete wavelet transform and variable threshold method are utilized. The UPF (unscented particle filter) combines GPS information and INS signals to implement precise outdoor localization algorithm and to reduce noise caused by the acceleration, deceleration, and unexpected slips. The conventional de-noising method is mainly carried out using a low pass filter and a high pass filter which essentially result in signal distortions. This newly proposed system utilizes the vibration information of actuator according to fluctuations of the velocity to minimize signal distortions. The UPF also resolves non-linearities of the actuator and non-normal distributions of noises. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.141.2-141.2
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• 2015

교류임피던스 측정기법을 이용하여 전기화학적으로 외부환경에서 소재 금속까지 물질 및 전하이동에 관한 임피던스 측정이 가능하며 도막의 부식 및 노화정도 및 내식성의 평가가 가능하여 산업체에서 널리 이용되고 있다. RPCS(Remote Plasma Cleaning Source)는 패널 및 반도체 제조공정에서 CVD 증착공정 후 챔버 내부에 입혀지는 Si(실리콘)을 화학적으로 세정하기 위한 F(불소) Radical을 공급하는 원격 고밀도 플라즈마를 발생시키는 제품이다. RPCS의 바디는 알루미늄을 사용하고 절연 및 플라즈마에 대한 내구성을 확보하기 위해 아노다이징 코팅을 한다. 반응기 내벽의 표면이 공정 플라즈마에 노출될 때 소재는 화학적으로 매우 활성이 높은 라디칼과의 반응뿐만 아니라 이온의 충격을 동시에 받게 되며 이 과정에서 다량의 불소 (Fluorine) 라디칼과 전계에 반응한 이온의 운동에 노출되면서 아노다이징 코팅이 손상되는데 이는 기기의 수명 단축 및 파티클을 발생시키며, Arc의 원인이 되기도 한다. 실제 사용 환경에서는 기기의 분해 없이 아노다이징의 상태를 주기적으로 모니터링 하기가 대단히 어려워, 정기적으로 교체하고 있는 실정이다. 본 연구에서는 RPCS내 발생된 플라즈마 현상을 컨덕터로 활용하여 고주파 리액턴스를 임피던스로 환산하여 아노다이징 코팅의 손상 정도를 진단 및 모니터링하였다. 아노다이징이 손상된 내부 블럭과 정상상태인 내부 블럭의 임피던스를 비교하였고, 아노다이징 두께별 임피던스를 측정하였다. 그 결과 아노다이징 절연막이 손상된 블록의 임피던스가 정상 블록에 비해 낮았으며 두께별 임피던스도 비례함을 알 수 있었다. 향후에는 장기간 현장에서 축척되어진 시험데이터를 바탕으로 아노다이징 코팅의 수명예측진단 시스템을 구축하고자 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.25-40
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• 2012

This paper suggests the way to build the integration of internal server by using link server with virtualization method. With the development of on-line games, game communities began to be formed by users, players get fun from playing games, sharing online space with friends, clans, and parties. However, the limit of physical server restrict the allows under average a hundred users to play at same time and place, and three thousand to ten thousand people to access to game community with chat, message, friends functions. By following the explanation of the method from this paper, this limit can be overcome. It will give the function to share information of all connected users in one displayed server. This paper demonstrates the key quality requirements of the server built by this way such as scalable architecture, consistency, and latency is fulfilled.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.421-429
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• 2015

This paper is about an approach for pedestrian detection and tracking with infrared imagery. We used the CUDA(Computer Unified Device Architecture) that is a parallel processing language in order to improve the speed of video-based pedestrian detection and tracking. The detection phase is performed by Adaboost algorithm based on Haar-like features. Adaboost classifier is trained with datasets generated from infrared images. After detecting the pedestrian with the Adaboost classifier, we proposed a particle filter tracking strategies on HSV histogram feature that exploit adaptively at the same time. The proposed approach is implemented on an NVIDIA Jetson TK1 developer board that is full-featured device ideal for software development within the Linux environment. In this paper, we presented the results of parallel processing with the NVIDIA GPU on the CUDA development environment for detection and tracking of pedestrians. We compared the object detection and tracking processing time for night-time images on both GPU and CPU. The result showed that the detection and tracking speed of the pedestrian with GPU is approximately 6 times faster than that for CPU.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.59-65
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• 2020

Lately the VR (Virtual Reality) game genre is becoming increasingly more popular and it has been cementing its place in the market as its own independent game genre. The key advantage of VR is that it lowers the barrier between player and the virtual world, thus creating an immersive experience. The suggested method develops a game that allows the player to experience what it is like to be visually impaired using the unique characteristics of VR. A distinctive feature of this game is that the character is provided only a limited range of sight, which is created using silhouette outlines. This restrictive visual field is then grafted onto VR and the player can indirectly experience blindness in a highly immersive manner. The silhouette outline along with the particle system is created using Oculus Rift, a headset highly used in VR game development, and Unity 3D game engine. We will also explain in detail regarding the removal of borders between the objects.

• Proceedings of the Materials Research Society of Korea Conference
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• 2010.05a
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• pp.58.2-58.2
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• 2010

FPD (Flat Panel Display) 제조 공정에서 사용되는 패턴은 수 ${\mu}m$ 수준까지 감소하였으며, FPD의 크기는 급격하게 대형화 되여 현재 8세대(2200mm*2500mm)에 이르고 있다. 이에 따라, $1\;{\mu}m$ 이상의 크기를 갖는 오염입자에 의한 수율 저하를 극복하기 위한 세정효율의 향상 및 다량의 초순수 사용에 따른 폐수 발생으로 인한 환경오염, 또한 장비의 크기에 따른 공간 효용성 감소와 이에 따른 공정 비용의 증가 등의 어려움에 직면하고 있다. 따라서, 현장에서는 고효율, 저비용의 세정 공정 기술 개발에 대한 연구가 활발히 진행되고 있다. 이러한 문제점들을 해결 하고자 이류체 노즐 세정 장치와, 화학액 린스를 위한 초순수 Spray, 건조 공정에 해당하는 Air-knife, Halogen lamp로 구성된 소형화 된 고속 FPD(Flat Panel Display) 세정기에 대한 연구를 진행 하였다. 이류체 노즐은 초순수와 $N_2$ 가스를 내부에서 혼합하여 액적(Droplet)을 형성하여 고압으로 분사시키는 장치로서 화학액을 사용하지 않고 물리적인 방법으로 오염입자를 제거한다. Spray는 유기 오염입자 제거를 위한 오존수의 린스 공정을 위해 설치 하였다. 세정 후 표면에 남아있는 기판의 액막(water film)은 고압의 가스를 분사하는 Air-knife를 통해 제거하였으며, 고속 공정시 발생할 수 있는 Air-knife에서 제거하지 못한 잔류 액막을 Halogen lamp를 사용하여 효과적으로 제거함으로써, 물반점(water mark) 없는 건조 공정을 얻을 수 있었다. 실험에는 미세 입자의 정량적인 측정을 위하여 유리 기판 대신에 6인치 실리콘 웨이퍼(P-type (100))를 사용하였으며, > $\;1{\mu}m$ 실리카 입자를 스핀방식을 사용하여 정량적으로 균일하게 오염하였으며, 오염물의 개수 및 분포는 파티클 스캐너 (Surfscan 6200, KLA-Tancor, USA)를 사용하여 분포 및 개수를 정량적으로 측정 하였다. 이류체 노즐은 $N_2$ 가스의 압력과 초순수의 압력을 변화시켜 측정하여, 각각 0.20 MPa, 0.01 MPa에서 최적의 세정 결과를 얻을 수 있었으며, 건조 효율은 Air-Knife의 입사 각도와 건조면 간격, 할로겐 램프의 온도를 조절 하여 최적의 조건을 얻을 수 있었다.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1131-1142
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• 2018

The autonomous vehicles are being developed and operated widely because of the advantages of reducing the traffic accident and saving time and cost for driving. The vehicle localization is an essential component for autonomous vehicle operation. In this paper, localization algorithm based on sensor fusion is developed for cost-effective localization using in-vehicle sensors, GNSS, an image sensor and reference images that made in advance. Information of the reference images can overcome the limitation of the low positioning accuracy that occurs when only the sensor information is used. And it also can acquire estimated result of stable position even if the car is located in the satellite signal blockage area. The particle filter is used for sensor fusion that can reflect various probability density distributions of individual sensors. For evaluating the performance of the algorithm, a data acquisition system was built and the driving data and the reference image data were acquired. Finally, we can verify that the vehicle positioning can be performed with an accuracy of about 0.7 m when the route image and the reference image information are integrated with the route path having a relatively large error by the satellite sensor.