• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.361-364
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• 2008

The Application Model in Wireless Sensor Networks(WSNs) consist of wireless sensor network based on sensor hardwares which is combined the micro-controller, chipset for wireless communication and sensors, middleware for dealing with data processing and user application for common service. Applications in WSN have been applied for environmental monitoring, smart factory and have concentrated the services based on remote monitoring applications which is difficult to watch the situation by human. In this paper, we described the construction model for applying for the Ubiquitous disaster prevention system and deal with its conformity. The proposed system includes the selecting the wireless sensor hardware, routing technique for u-Disaster Prevention, composition of middleware and web-interface for application services.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.346-349
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• 2018

In North-East asian countries, laver cultivation has been an important marine industry in coastal areas as well as fishery because laver (Porphyra) is nutrient-rich food and has been used in many Asian cuisines. Laver is characterized by high concentrations of fiber and minerals, a low fat content, and, in some cases, relatively high protein levels. In this paper we inplimented design of fully automatic laver harvesting, nowdays most peoples are used to collect a laver harvesting by human, it is very defficult working, due to wind, waves, and the weather conditions which is hard to stand on the ship and holding the seaweed nets it can be injurced human, this is the reason to we are developed automatic harvesting method, in this project we proposed automatic harvesting collect method which is operated without human. Mainly we design and developed automated ship, This ship is devided in to three parts frist part is supporting roller, second part is drum screener, thried part is lifting mechanism. Thise are operated with hydro pnumatic equimpment, this divice are control with micro controller. The system prototype has implemented and satisfied by the performance to realize the further level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5403-5408
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• 2012

In this paper, we introduce the multiple frequency bio-electrical impedance analysis method for body composition analysis. And then we implement the multiple frequency bio-electrical impedance analysis system. Overall system consists of: multiple frequency alternating current signal generator contained alternating current signal, phase signal detector, voltage signal detector, micro controller, in-out device(key-pad LCD), conductivity electrodes, system power. We explain the architecture of the system and required theory to implement the system. In order to investigate the clinical significance of the body composition data, compare to the data measured by the expert body composition analyzer which provide high reproduction and precision. Finally, experimental results which are the correlation between the measured data show the very high reproduction performance of the body composition analysis in the proposed system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.11
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• pp.521-527
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• 2002

The Hemodialysis system is the device for the patients who have suffered from end stage renal failure as the kidney which removes the waste products in a human body. The existing hemodialysis is based on a 8-bit micro-controller and it is not a touch-screen type but a manual type. This paper is focused on hemodialysis system based on high control and expension embedded system. The whole system consists of main control unit and sub control unit(dialysis control unit, blood control unit, monitoring control unit, networking unit). The dialysis control unit, blood control unit, monitoring control unit are processed by 3 microcontrollers and network unit is for monitoring a renal failure patient's condition. For the evaluation of the system performance, the saline was pured into blood unit and then water removal rate, conductivity and temperature of hemodialysis liquid were measured 10 times in an each state suing the UF pump in the fluid unit varing the quantity of saline to 1000cc, 2000cc, 3000cc and 4000cc. As a result, the rates of water removal are 98.6% in condition of 000cc saline, 96.9% in 2000cc, 98.9% in 3000cc and 98.3% in 4000cc. The conductivities of hemodialysis liquid are 99.6% in the first to third condition and 99.7% in the forth condition. The temperatures of hemodialysis liquid are 99.8% in the first to third condition and 99.6% in th forth condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.889-890
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• 2016

Existing machine-to-machine collaboration system is a centralized structure system fo built OpenWrt and a Web server on the router. But scarce resources of the router are getting more requests from the collaboration client when a problem has occurred with increasing probability of a client object, the higher the traffic. In this paper, in order to solve the problem, we propose a distributed system utilizing Machine Socialization cooperation algorithm. The MCU attached to the machine to minimize the traffic occurrence probability and loss of the data by processing to distribute the data between the server and the client. Also improve the response speed between the server and the client and the operation stop caused by the loss of data. The proposed system will be utilized if the IoT field will be high efficiency compared to existing systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2820-2827
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• 2015

HSMS communication system using low-cost micro controller units(MCUs) is an essential technique for online semiconductor equipment system developments. It is intended as an alternative to SEMI E4 (SECS-I) for applications where higher speed communication is needed and the facilitated hardware setup is convenient. In this paper, an HSMS communication system using low-cost MCUS is designed and implemented. Using a MCU with a low price but high-performance as a main board, a module which processes HSMS communication is designed, and a circuit is designed to process BCR independently with a microminiature MCU. To convert tag data which is recognized from BCR into data based on HSMS communication protocol, SECS-II message is designed. Lastly, an HSMS communication system is implemented based on these designs. A low-cost HSMS communication module developed in this study can be applied in realtime monitoring and controlling system for semiconductor processes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.517-524
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• 2017

The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.582-587
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• 2004

Ultrasonic sensors are widely used in mobile robot applications to recognize external environments, because they are cheap, easy to use, and robust under varying lighting conditions. However, the recognition of objects using a ultrasonic sensor is not so easy due to its characteristics such as narrow beam width and no reflected signal from a inclined object. As one of the alternatives to resolve these problems, use of multiple sensors has been studied. A sequential driving system needs a long measurement time and does not take advantage of multiple sensors. Simultaneous and pulse coding driving system of ultrasonic sensor array cannot measure short distance as the length of the code becomes long. This problem can be resolved by multi-frequency driving of ultrasonic sensors, which allows multi-sensors to be fired simultaneously and adjacent objects to be distinguished. Accordingly, this paper presents a simultaneous and multi-frequency driving system for an ultrasonic sensor array for object recognition. The proposed system is designed and implemented using a DSP and FPGA. A micro-controller board is made using a DSP, Polaroid 6500 ranging modules are modified for firing the multi-frequency signals, and a 5-channel frequency modulated signal generating board is made using a FPGA. To verify the proposed method, experiments were conducted in an environment with overlapping signals, and the flight distances for each sensor were obtained from filtering of the received overlapping signals and calculation of the time-of-flights.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.129-140
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• 2017

In this paper, a $4{\times}32$-channel neural recording system capable of acquiring neural signals is introduced. Four 32-channel neural recording ICs, complex programmable logic devices (CPLDs), a micro controller unit (MCU) with USB interface, and a PC are used. Each neural recording IC, implemented in $0.18{\mu}m$ CMOS technology, includes 32 channels of analog front-ends (AFEs), a 32-to-1 analog multiplexer, and an analog-to-digital converter (ADC). The mid-band gain of the AFE is adjustable in four steps, and have a tunable bandwidth. The AFE has a mid-band gain of 54.5 dB to 65.7 dB and a bandwidth of 35.3 Hz to 5.8 kHz. The high-pass cutoff frequency of the AFE varies from 18.6 Hz to 154.7 Hz. The input-referred noise (IRN) of the AFE is $10.2{\mu}V_{rms}$. A high-resolution, low-power ADC with a high conversion speed achieves a signal-to-noise and distortion ratio (SNDR) of 50.63 dB and a spurious-free dynamic range (SFDR) of 63.88 dB, at a sampling-rate of 2.5 MS/s. The effectiveness of our neural recording system is validated in in-vivo recording of the primary somatosensory cortex of a rat.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.8-13
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• 2006

In this thesis, an automatic door lock system using a dual tone multiple frequency(DTMF) signal generated as pushing the key button of mobile phone is proposed and implemented. This system consists of a transmitter module and a receiver module for processing the DTMF signal of mobile phone. The DTMF signal of mobile phone connected with ear-phone jack enter into the input terminal of DTMF receiver and those are encoded by a code-converter with 4-bits binary format in the DTMF receiver. The encoded output signals are transmitted to the amplitude shift keying(ASK) modulator of transmitter module and the modulated ASK signals which are converted into radio frequency(RF) signals propagate in a free space. The RF signals passed through a free space are demodulated by the ASK demodulator of receiver module and the demodulated ASK signals are sent to a micro-controller unit(MCU). The output signals processed by the MCU are compared with the secreted identification number which is prerecorded in a microprocessor and are transferred to a power relay. If the result is the same, the automatic door lock system opens a door. In the opposite case, it maintains closing the door. The implemented automatic door lock system operates well in mobile environments.