• Journal of Advanced Marine Engineering and Technology
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• v.35 no.2
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• pp.288-294
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• 2011

In this paper, the FPGA-based SoC board (Xilinx Virtex-4 ML401 EVM) is adopted to control electrical power inverter system. For marine application, its performance is shown on PC-based system for monitoring electrical characteristics of a power inverter using by the NMEA 2000 protocol. This power inverter system is achieved in Real-Time monitoring and control by dual micro-processor operation on embedded FPGA-based SoC board. One micro processor is for control (Control processor) electrical power inverter using by PWM signal. And the other microprocessor (Communication processor) is for communication with PC-based monitoring system. The two-processor is communicating each other using by dual-port ram (DPRAM). PC-based system user can control and monitor information of the electrical power inverter via NMEA 2000 based communication processor. Control and monitoring information includes the inverter status and configuration. SoC board converts this information to Parameter Group Numbers (PGNs) in the NMEA 2000 protocol. This system can be applied to marine power electronics for distributed power generation, transmission or regulation systems on the ship.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.466-472
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• 2009

An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.417-422
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• 2015

A service size of the IoT environment is determined by the number of sensors. The number of sensors increase means increases the amount of data generated by the IoT environment. There are studies to reliably operate a network for research and operational dynamic buffer for data when network congestion control congestion in the network environment. There are also studies of the stream data that has been processed in the connectionless network environment. In this study, we propose a sensor gateway for processing big data of the IoT environment. For this, review the RESTful for designing a sensor middleware, and apply the double-buffer algorithm to process the stream data efficiently. Finally, it generates a big data traffic using the MJpeg stream that is based on the HTTP protocol over TCP to evaluate the proposed system, with open source media player VLC using the image received and compare the throughput performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.315-322
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• 2002

A thin film oxide semiconductor micro gas sensor array which shows only 60㎽ of power consumption at an operating temperature of 30$0^{\circ}C$ has been fabricated using microfabrication and rnicrornachining techniques. Excellent thermal insulation of the membrane is achieved by the use of a double la! or structure of 0.1${\mu}{\textrm}{m}$ thick Si$_3$N$_4$ and 1${\mu}{\textrm}{m}$ thick phosphosilicate glass(PSG) prepared by low pressure chemical vapor deposition(LPCVD) and atmospheric－pressure chemical-vapor deposition(APCVD), respectively. The sensor way consists of such thin film oxide semiconductor sensing materials as 1wt.％ Pd-doped SnO$_2$, 6wt.% AI$_2$O$_3$-doped ZnO, WO$_3$ and ZnO. The thin film oxide semiconductor micro gas sensor array exhibited resistance changes usable for subsequent data processing upon exposure to various gases and the sensitivity strongly depended on the sensing layer materials. Heater Part of the sensor structure has been modified in order to improve the process yield of the sensor, and as a result of modified heater structure improved process yield has been achieved.

• Journal of the Korean Ceramic Society
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• v.40 no.10
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• pp.973-980
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• 2003

The effects of additives in n-type semiconducting SnO$_2$-based gas sensors on oxidizing gases were investigated. The resistivity of SnO$_2$ sensors decreased when exposed to reducing gases, which act as electronic donors. However, the resistivities of the SnO$_2$ sensors increased when exposed to oxidizing gases, which act as electronic accepters. The products formed from the reaction of oxidizing gases ever SnO$_2$-based powders were analyzed by gas chromatography as compared with those formed from the reaction of reducing gases of alcohols. The SnO$_2$ sensors doped with PdCl$_2$ or A1$_2$O$_3$ showed unique dual response patterns toward oxidizing gases of $CH_3$CN and $CH_3$NO$_2$ depending on the operating temperature. The combination of these two sensors along with proper pattern recognition technique could enhance the selectivity for the gases with electron-accepting groups.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1505-1510
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• 2008

In large-scale wireless sensor networks, the deployed nodes cannot be replaced or recharged after first deployment. Also, dead nodes maγ lead to the partition of whole networks. While performing data dissemination under a battery power constraint, energy efficiency is a key design factor of routing protocol. As a solution for the efficient data dissemination, in this paper, we propose a protocol namely Hierarchical Data Dissemination (HDD) which provides scalable and efficient data delivery to multiple sources and mobile sinks. HDD uses the facts that sink nodes are central gathering Points and source-centric data forwarding paths are constructed and it is maintained with two-tier communications. The performance of HDD is compared with TTDD about the energy consumption, data delivery time and data success ration. The extensive simulation results show that HDD Routing Protocol outperforms TIDD by more than $1.5{\sim}3times$ on energy consumption.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.551-556
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• 2018

In recent years, drones have been used to measure aircraft flights data and weather information. Related applications include the measure for low-altitude atmospheric data, the measure for atmospheric fine dust, and the measure for air pollution. However, the mounting position of the atmospheric measurement sensor should be mounted by considering the effects of propeller flow, the EMI effects, and the changes in the weight of the drone. Among these, the upper flow of the propeller affects the wind speed and direction, so the optimal position should be selected. This study deals with the proper height of the atmospheric data measurement sensor. Through the flow analysis, we study the flow characteristics of around a drone and suggest the proper sensor mounting height.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.401-408
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• 1998

A dual-channel automatic ac-dc voltage transfer error measurement system in which the output voltages of two thermal voltage converters which are ac voltage standard are directly measured at the same time to reduce the output voltage drift is described. Forward-reverse measurement method by using a two-channel scanner is used to cancel the offset voltage of the voltmeters. The agreements of the 4-V TVC comparison results between other national standards institute and Korea Research Institute of Standards and Science were less than about ${\pm}2\;ppm$ in the frequency range of $40\;Hz{\sim}100\;kHz$, and were less than about ${\pm}4\;ppm$ at $200\;kHz{\sim}1\;MHz$. Measurement uncertainty is reduced significantly from ${\pm}4\;ppm$ of manual system to ${\pm}3\;ppm$ of new system(up to 100 kHz) typically and great increase in comparison efficiency has been achieved by this system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.158-164
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• 2009

The real time security system using web camera shall correspond in commensurate with it in real time through classifying moving object and analyzing the behavior. But, as to the detection of moving object in real time image through a camera, it is difficult to detect movement correctly according to the change of unnecessary noises, lighting conditions and screened phenomenon. This paper proposes real time security system by dual camera and ultrasonic sensor, a method of advanced detection in order to detect correct movement of specific object. That is, we could improve the tracing characteristics by using ultrasonic sensor as measurement factor of changed position and verify through experiments that the information interchanged between camera upwards and in front of it have effect on tracing a specific object continuously. The results of the experiment show that recognition rate of object was 97.4% and the correct tracing could be done lastingly in a phenomena of screening object.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.66-74
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• 2018

Recently, there has been active studies on hand gesture recognition to increase immersion and provide user-friendly interaction in a virtual reality environment. However, most studies require specialized sensors or equipment, or show low recognition rates. This paper proposes a hand gesture recognition method using Deep Learning technology without separate sensors or equipment other than camera to recognize static and dynamic hand gestures. First, a series of hand gesture input images are converted into high-frequency images, then each of the hand gestures RGB images and their high-frequency images is learned through the DenseNet three-dimensional Convolutional Neural Network. Experimental results on 6 static hand gestures and 9 dynamic hand gestures showed an average of 92.6% recognition rate and increased 4.6% compared to previous DenseNet. The 3D defense game was implemented to verify the results of our study, and an average speed of 30 ms of gesture recognition was found to be available as a real-time user interface for virtual reality applications.