• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.8-17
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• 2015

This paper presents a sound into color signal conversion using a colored-hearing synesthesia. The aim of the present paper is to implement a real-time conversion system which focuses on both hearing and sight which account for a great part of bodily senses. The proposed method of the real-time conversion of color into sound, in this paper, was simple and intuitive where scale, octave and velocity were extracted from MIDI input signals, which were converted into hue, intensity and saturation, respectively, as basic elements of HSI color model. In experiments, we implemented both the hardware system for delivering MIDI signals to PC and the VC++ based software system for monitoring both input and output signals, so we made certain that the conversion was correctly performed by the proposed method.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.476-478
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• 2008

분산 전원의 기저 전원으로써 개발된 일체형 원자로(REX-10)를 지역에너지시스템에 도입하고 안정적인 운전을 하기 위해서 본 논문은 전압원형 인버터를 설계하고 일체형 원자로가 변동 없이 정출력을 하도록 지역에너지시스템의 전력 변동 상황을 모니터링하여 제어하는 모델을 개발하였다. 제안된 모델의 효용성을 확인하기 위해서 PSCAD/EMTDC를 사용하였다.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.327-330
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• 2001

본 논문에서는 위험요소를 내재하고 있는 로켓시스템에 대해 원거리에서 실시간 모니터링 및 제어를 할 수 있도록 원격 제어시스템을 설계, 개발하였다. 뿐만 아니라 로켓 근처에 위치한 무인 시설물 내에는 원격제어에 따른 로켓내부 시스템의 각종 센서 출력값을 멀티채널방식을 이용하여 장시간에 걸쳐 저장하고 원격지에 위치한 유인 시설물 내에서 LAN 통신을 통해 데이터를 분석할 수 있도록 DAS(Data Acquisition System)을 설계하고 개발하였다. 개발된 시스템은 간이 연계시험을 통해 입증하였으며, 향후 3단형 과학로켓발사통제시스템에 적용할 예정이다.

• Proceedings of the Korean Magnestics Society Conference
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• 2012.05a
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• pp.58-60
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• 2012

전류센서는 전기차 시대의 도래와 함께 전기차의 주용 부품으로써, 차량용 전기가 충방전하는 동안의 전류의 흐름을 측정하고, 전지관리시스템이 모니터링하는 목적으로 사용되어 진다. 본 논문은 Hall-effect를 이용하여 전류에 의해 의기된 자장이 자성코어에 집중되어 코어의 공극에서 측정되도록 전류센서를 구성하였다. 공극간의 자속을 측정하기 위하여, GaAs 게열의 Hall 센서가 사용되었다. 본 논문이 제안하는 센서는 측정 결과, 출력 특성의 선형성과 온도 안정성이 우수한 것으로 나타났다. 이는 제안된 전류센서가 산업용으로 적용이 가능함을 보여준다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.11-18
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• 2010

In this paper, it introduced the device that was fabricated for monitoring sleeping positions of infants with 3-axis accelerometer. Sleep monitoring studies has been usually conducted two ways. To monitor sleeping posture by installing a camera and then recording of sleep in the sleeping room continuously is the first one. The other one is monitoring pressure sensor's results data for sleeping. Those two ways' benefits are that are able to get relatively accurate sleeping posture data but, there are many disadvantages like constraints of spaces and places, the installation of sensors or cameras, and high cost. In addition, it has a lot of problems that difficult to solve. For babies, it's not easy to apply, as well as uncomfortable. The proposed method uses a 3-axis accelerometer's X axis, Y axis, Z axis position output values in order to recognize the bad ground sleeping position that use of the buzzer alarm. This method uses a 3-axis acceleration sensor to measure the data and transmit sleeping posture using Bluetooth wireless in real time monitoring. The data is helpful for prevention safety hazard such as choked themselves when they slept back side on.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.249-252
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• 2008

A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.233-235
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• 2012

해저보행로봇 CR200은 여러 개의 관절로 이루어진 6개의 다리를 이용하여 해저면에서 보행으로 이동하며 해저 정밀탐사 및 작업을 수행하는 로봇으로, 케이블로 연결된 선상제어실에서 원격 제어된다. CR200 시스템에서는 16개의 카메라가 장착될 예정이며, 취득된 카메라의 영상은 선상제어실의 비디오 컴퓨터로 전송되어 모니터링 및 녹화된다. 설계된 비디오 시스템에서 영상 전송은 전자기 간섭에 의한 화질 열화를 최소화하기 위하여 기가비트의 대역폭을 가진 이더넷과 광케이블을 통하여 디지털 형태로 전송되며, 아날로그 카메라의 영상은 비디오 인코더를 사용하여 디지털 영상으로 변환된 후에 전송된다. 본 논문에서는 CR200의 비디오 시스템의 설계를 소개하고, 실제로 제작하기 전에 설계된 비디오 시스템을 검증하기 위하여 테스트베드를 사용한 통합 테스트 결과를 제시한다. 아직 준비되지 않은 카메라에 대해서는 아이패드의 아날로그 영상 출력을 비디오 인코더의 입력으로 전달하여, 설계된 모든 카메라들이 동작하는 상황을 테스트베드로 실험하였다. 16개 카메라의 영상이 모니터링 및 녹화되는 상황을 테스트베드로 실험한 결과에 따르면, 압축률 10%의 H.264 동영상 압축 알고리즘을 사용할 경우에 30fps 영상의 모니터링 및 녹화에 각각 60Mbps의 전송량으로 비디오 시스템이 정상적으로 동작하는 것을 확인할 수 있었다. 비디오 데이터의 전송은 센서 및 제어 데이터의 전송과 같은 네트워크를 사용하지만, 비디오 데이터의 기가비트 네트워크 사용률은 평균 12%이기 때문에 비디오 데이터 전송으로 인하여 데이터 통신은 거의 영향을 받지 않는다.

• Journal of Sensor Science and Technology
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• v.9 no.2
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• pp.127-133
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• 2000

We propose a novel monitoring system for a recycling piggery slurry treatment system through neural networks. Here we tried to model treatment process for each tank(influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) in the system based on population densities of heterotrophic and lactic acid bacteria. Principle component analysis(PCA) was first applied to identify a relation between input(microbial densities and parameters for the treatment) and output, and then multilayer neural networks were employed to model the treatment process for each tank. PCA filtration of input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of input. Neural networks independently trained for each treatment tank and their subsequent combinatorial data analysis allowed a successful prediction of the treatment system for at least two days.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.3
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• pp.89-96
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• 2018

This study aims to develop a fully passive smart sensing tag utilizing RF (Radio Frequency) energy harvesting technology at UHF (Ultra High Frequency) band of 915MHz. To optimize the power collected under various radiated conditions, an efficient energy harvesting module exploiting a boost circuit with maximum power point tracking (MPPT) is employed. Specifically, the proposed tag features two orthogonal antennas to enhance its capability of both energy scavenging and data transmissions. The experimental result shows that the developed smart sensor tag can scavenge an RF input power of as low as 0.19mW at a distance of 4 meters for a 3.6Vdc output. Furthermore, the proposed smart sensor tag performs the feasibility of completely autonomous monitoring food freshness at 2 meters with a low-power sensor array.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.137-146
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• 2011

In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.