• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.7
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• pp.710-718
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• 2009

The time difference of arrival(TDOA) algorithm is being used widely for identifying the location of a source emanating either electrical or acoustic signal. It's application areas will not be limited to identifying the source at a fixed location, for example the origin of an earthquake, but will also include the trajectory monitoring for a moving source equipped with a GPS sensor. Most of the TDOA algorithm uses time correlation technique to find the time delay between received signals, and therefore difficult to be used for identifying the location of multiple sources. In this paper a TDOA algorithm based on cross-spectrum is developed to find the trajectory of two sound sources with different frequencies. Although its application is limited to for the sources on a disk plane, it can be applied for identifying the locations of more than two sources simultaneously.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.400-404
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• 2008

무인항공기를 이용한 실시간 공중 모니터링은 재난 재해, 테러 등의 위기상황을 사전에 대비하고, 사고 발생 시 피해상황을 신속하게 파악할 수 있는 효율적인 관리 시스템이다. 실시간 공중 모니터링을 위해 무인항공부문에서는 고성능의 카메라, 관성항법장치, 레이저 스캐너, GPS 수신기 등의 다중 센서들을 장착하고, 제어하며 각 센서들로부터 입력받은 데이터 처리 및 지상국으로 데이터 전송이 실시간으로 가능해야 한다. 기존 무인 모니터링 시스템들은 카메라와 같이 단일 센서의 운용을 목적으로 설계되었으나, 본 연구에서는 레이져 스캐너, 적외선카메라를 포함하는 다중센서를 위한 컴퓨터를 설계하였다. 최근 다중센서를 장착한 관측시스템에 관한 연구가 미국 및 유럽에서 수행되고 있으나, 아직 개발이 완료되지 않은 상태이다. 본 논문에서는 고성능 다중 센서 데이터 처리를 위해 실시간 소프트웨어, 고속 대용량 데이터처리 기술, 고속 압축 기술, 이기종 다중 센서들 간의 시각 동기화 기능을 제공하는 탑재컴퓨터의 설계결과를 소개하였다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.82-89
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• 2008

최근, GIS 분야에서 RFID와 GPS 센서 같은 위치 및 공간 데이타를 포함하는 다양한 GeoSensor의 활용으로 수집되는 공간 데이타가 크게 증가하면서, 대용량 공간 데이타의 빠른 처리를 위한 공간 인덱스의 중요성이 높아지고 있다. 특히, 대표적인 공간 인덱스인 R-Tree를 기반으로 검색 성능을 높이기 위한 연구가 활발히 진행되고 있다. 그러나, 기존 연구는 R-Tree에서 노드의 MBR 간의 겹침이나 트리 높이를 어느 정도 줄임으로써 다소 검색 성능을 향상시켰지만, 트리 검색에서 발생하는 불필요한 노드 접근 비용 문제를 효율적으로 해결하지 못하고 있다. 본 논문에서는 이러한 문제를 해결하고 R-Tree에서 대용량 공간 데이타의 빠른 검색을 제공하는 인덱스인 HR-Tree(Hash based R-Tree)를 제시한다. HR-Tree는 트리 검색 없이 R-Tree 리프 노드를 직접 접근할 수 있는 해시 테이블을 이용함으로써 R-Tree의 검색 성능을 높인다. 해시 테이블은 데이타 영역을 차원에 따라 반복적으로 분할한 Partition과 대응되는 R-Tree 리프 노드의 MBR과 포인터들로 구성된다. 각 Partition은 생성 과정에서 고유의 식별 코드를 갖기 때문에 Partition 코드가 주어지면 해시 테이블에서 해당 레코드를 쉽게 접근할 수 있다. 또한, HR-Tree는 R-Tree구조의 변경없이 다양한 R-Tree 변형 구조에 쉽게 적용할 수 있는 장점이 있다. 마지막으로 실험을 통하여 HR-Tree의 우수성을 입증하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.845-847
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• 2015

In this paper, we develope a detachable wearable device consisting of two parts: main module and accessary module including battery. The main module can display any tracking information and alarms related to the smart phone. In addition, it has small sensors such as heart rate sensor, NFC, T-money, and GPS that can be selected by user's requirement. The accessary module includes battery. The suggested wearable device can also solve the problems faced with today's many other wearable devices: 1) limited battery life 2) the lack of compatibility and expandability due to run on internal components designed for smart phone 3) the design has always been a crucial factor in determining the success of main stream consumer wearable devices.

• Convergence Security Journal
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• v.11 no.6
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• pp.17-23
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• 2011

In this paper, we propose mobile Augmented Reality(AR) for smart learning system which is advanced e-learning. AR is technology that seamlessly overlays computer graphics on the real world. AR has become widely available because of mobile AR. Mobile AR is possible to get information from real world anytime, anywhere. Nowadays, there are various areas using AR such as entertainment, marketing, location-based AR. One of the most promising areas is education. AR in education shows lifelike images to users for realism. It's a good way for improving concentration and attention. We utilize only a camera for image-based AR without other sensor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.483-489
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• 2009

The Time Difference of Arrival (TDOA) algorithm is being used widely for identifying the location of a source emanating either electrical or acoustic signal. It's application areas will not be limited to identifying the source at a fixed location, for example the origin of an earthquake, but will also include the trajectory monitoring for a moving source equipped with a GPS sensor. Most of the TDOA algorithm uses time correlation technique to find the time delay between received signals, and therefore difficult to be used for identifying the location of multiple sources. In this paper a TDOA algorithm based on cross-spectrum is developed to find the trajectory of two sound sources with different frequencies. Although its application is limited to for the sources on a disk plane, but it can be applied for identifying the locations of more than two sources simultaneously.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.140-146
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• 2007

This paper demonstrates the development of a mobile robot for patrol. We fuse differential GPS, angle sensor and odometry data using the framework of extended Kalman filter to localize a mobile robot in outdoor environments. An important feature of road environment is the existence of curbs. So, we also propose an algorithm to find out the position of curbs from laser range finder data using Hough transform. The mobile robot builds the map of the curbs of roads and the map is used fur tracking and localization. The patrol robot system consists of a mobile robot and a control station. The mobile robot sends the image data from a camera to the control station. The remote control station receives and displays the image data. Also, the patrol robot system can be used in two modes, teleoperated or autonomous. In teleoperated mode, the teleoperator commands the mobile robot based on the image data. On the other hand, in autonomous mode, the mobile robot has to autonomously track the predefined waypoints. So, we have designed a path tracking controller to track the path. We have been able to confirm that the proposed algorithms show proper performances in outdoor environment through experiments in the road.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.387-400
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• 2015

A fuzzy logic based mobile robot navigation system was developed to improve the driving ability without trapping inside obstacles in complex terrains, which is one of the most concerns in robot navigation in unknown terrains. The navigation system utilizes the data from ultrasonic sensors to recognize the distances from obstacles and the position information from a GPS sensor. The fuzzy navigation system has two groups of behavior rules, and the robot chooses one of them based on the information from sensors while navigating for the targets. In plain terrains the robot with the proposed algorithm uses one rule group consisting of behavior rules for avoiding obstacle, target steering, and following edge of obstacle. Once trap is detected the robot uses the other rule group consisting of behavior rules strengthened for following edge of obstacle. The output signals from navigation system control the speed of two wheels of the robot through the fuzzy logic data process. The test was conducted in the Matlab based mobile robot simulator developed in this study, and the results show that escaping ability from obstacle is improved.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.5
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• pp.385-392
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• 2018

This paper suggests a new method to estimate the roll and pitch damping moment coefficients of a flying disc through sensor data from the onboard IMU module. This method can be easily performed than wind tunnel or computational fluid dynamics methods because it estimates aerodynamic coefficients simply after accumulating the inertial data through several repeated flight experiments. Estimated coefficients are applied to a simulator which is based on the flight dynamics of a flying disc. Finally, the predicted flight trajectory is compared with the true position provided by GPS, which demonstrated the validity of the proposed estimation method.