• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1791-1797
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• 2014

A water level measurement radar estimates beat frequencies to extract the corresponding water level information for water resource management. Therefore, it is required to maintain the high degree of reliability and accuracy in beat frequency estimates. However, Beat spectra of water surface return echoes can have very widely varying shapes according to system frequency linearity, measurement environments and weather conditions. Therefore, serious problems may arise in maintaining the reliability and accuracy of the conventional level estimation method. Therefore, in this paper, high resolution spectrum estimates are analyzed for improvement of the conventional method. These methods show that the more accurate level measurement can be possible on the condition that SNR is higher than a certain required threshold. However, if SNR is too low, the conventional method shows that estimates are more reliable than the suggested method though absolute errors are too large.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1515-1522
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• 2011

This paper proposed the finite element analysis technique for improving the correleration accuracy between FEA and test on a pedestrian lower legform impact. Europe has been evaluating the bumper pedestrian impact by Euro-NCAP, and it will also be applied in a domestic area by K-NCAP in 2013. By using the compression test result of bending resisting stiffener, a pedestrian bumper modeling guide was presented by analayzing the force-displacement curve of stiffener. And by using the sensor measurement results in car pedestrian test, pedestrian impact behavior was analyzed between test and finite element analysis result. Finally, the finite element analysis guide for a pedestrian bumper impact was presented to improve the correleration accuracy.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.178-189
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• 1995

In this pater, authors derive the state - space equiation about the patallel - type inverted pendulum which is adopted as control object, and constitute the control system by $H_\infty$control theory. The modeling error is unavoidably existed by linearization error, and so on. We regard this modeling error which is determined from the identification through frequency response as unstructured model uncertainty. An augmented state - space equiation with frequency weighting function is constructed for application of the $H_\infty$theory, and the mixed sensitivity problem is considered. The weighting functions are determined in consideration of the model uncertainty and the response of system in frequency region. The $H_\infty$controller is designed by using software package for controller design. From results of response simulation, the control system designed with $H_\infty$theory guarantees low sensitivity for disturbance as well as robustness against the model uncertainties.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.20-20
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• 2010

반도체 공정 등에서 10-6~10-8 Torr의 고진공 환경을 제공하기 위하여 사용되는 고진공 터보분자펌프 (Turbomolecular Pump, TMP)는 다층의 회전깃을 갖는 로터를 회전시켜 분자를 배출시키는 방식을 사용하는 진공펌프이다. 또한 최근에는 디스플레이 및 반도체 공정에서 높은 진공도뿐만 아니라, 높은 배기속도를 요구하는 추세에 따라, 터보 펌프와 드래그 펌프부분을 동시에 가지고 있어 상대적으로 작동 진공도 영역이 넓은 복합 분자펌프(Compound Turbomolecular Pump, CMP)의 활용도가 넓어지고 있다. 이러한 분자펌프가 장시간의 고속회전에 적합하도록 비접촉 방식인 자기부상 방식의 적용이 최근 거의 표준화되어 있다. 자기베어링 시스템은 전자기력을 이용하여 자성체인 회전축을 부상지지 함으로써 비접촉 고속 회전이 가능하여 윤활이 용이하지 않은 진공 환경 등 가혹한 환경에 적합하며, 터보분자펌프는 자기베어링이 가장 널리 사용되고 있는 분야이기도 하다. 자기베어링 시스템의 설계는 크게 하드웨어와 소프트웨어로 나누어질 수 있는데, 하드웨어의 경우 전체 로터 시스템의 특성을 고려하여 설계되어야 하며, 주로 자기베어링 코어와 코일, 변위센서 및 전력 증폭 시스템 등의 기전적인 요소들이 이루어져 있다. 하드웨어 설계와 함께 제어시스템의 설계도 매우 중요하며, 이는 자기베어링 시스템이 불안정한 특성을 갖는 개루프계를 갖고 있으므로 안정화를 위한 능동제어 시스템이 필수적이며 진동제어 등 여러 가지 기능이 요구되기 때문이다. 본 논문에서는 이러한 자기부상형 고진공 복합분자펌프의 제어를 위한 선형제어시스템의 구성을 실제 시스템의 적용을 통하여 설명하였다. 각 제어기는 DSP 를 이용한 디지털 제어시스템으로 구성되었으며, 2, 500 l/s 급의 복합 분자펌프 시작품에 적용하여 10,000 rpm까지의 기본성능시험을 수행하였다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.381-384
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• 2011

Wave drag reduction due to the repetitive laser induced energy deposition over a flat-nosed cylinder is experimentally conducted in this study. Irradiated laser pulses are focused by a convex lens installed in side of the in-draft wind tunnel of Mach 1.94. The maximum frequency of the energy deposition is limited up to 80. Time-averaged drag force is measured using a low friction piston which was backed by a load cell in a cavity as a controlled pressure. Stagnation pressure history, which is measured at the nose of the model, is synchronized with corresponding sequential schlieren images. With cylinder model, amount of drag reduction is linearly increased with input laser power. The power gain only depends upon the pulse energy. A drag reduction about 21% which corresponds to power gain of energy deposition of approximately 10 was obtained.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.4
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• pp.312-320
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• 2017

This paper deals with the development of structural test facility for the strength assessment of marine leisure boat built from carbon fiber reinforced plastics (CFRP) materials. The structural test facility consists of test jig, load application and control system, and data acquisition system. Test jig, and load application and control system are designed to accommodate various size and short span to depth ratios of single skin, top-hat stiffened and sandwich constructions in plated structural format such as square and rectangular shapes. A lateral pressure load, typical and important applied load condition to the plates of the hull structure for marine leisure boat, is simulated by employing a number of hydraulic cylinders operated automatically and manually. To examine and operate the structural test facility, five carbon/epoxy based FRP square plates having the test section area of $1m^2$, which are part of CFRP marine leisure boat hull, are prepared and they are subjected to monotonically increasing lateral pressure loads. In the test preparation, considering the symmetry of the plates geometry, various strain gauges and linear variable displacement transformer are used in conjunction with data acquisition system utilizing LabVIEW. From the test observation, the responses of the CFRP hull structure of marine leisure boat are understood by obtaining load to deflection and strain to load curves.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.97-103
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• 2005

Recent development of marine magnetic gradient systems, using arrays of sensors, has made it possible to survey large contaminated areas very quickly. However, underwater Unexploded Ordnances (UXO) can be moved by water currents. Because of this mobility, the cleanup process in such situations becomes dynamic rather than static. This implies that detection should occur in near real-time for successful remediation. Therefore, there is a need for a fast interpretation method to rapidly detect signatures of underwater objects in marine magnetic data. In this paper, we present a fast method for location and characterization of underwater UXOs. The approach utilises gradient interpretation techniques (analytic signal and Euler methods) to locate the objects precisely. Then, using an iterative linear least-squares technique, we obtain the magnetization characteristics of the sources. The approach was applied to a theoretical marine magnetic anomaly, with random errors, over a known source. We demonstrate the practical utility of the method using marine magnetic gradient data from Japan.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.271-278
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• 2021

This paper is a study on the implementation of smart filter system that recognizes the external environment and automatically removes pollutants according to pollution level. Recently, the occurrence of various pollutants in indoor and outdoor space has adversely affected the human body. Especially, various fine dust generated in the atmosphere becomes worse in closed residential space or office space. Although air pollution can be temporary lowered through ventilation, it is difficult to respond to fine dust changes in real time, and such problems become serious in the space where many people reside, such as at home or industry. Therefore, it is necessary to measure the pollution level of fine dust inside the residential space in real time and to reduce the pollution of indoor ventilation through automatic ventilation with the outside. To improve these problems, this paper proposes the implementation of smart filter system for external environment recognition. The structure of smart filter system that automatically measures air quality inside and outside, removes pollutants, implements the function, and confirms the operability by manufacturing prototypes. Finally, the effectiveness of the smart filter system for solving fine dust problems was examined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.