• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• Water for future
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• v.14 no.4
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• pp.19-26
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• 1981

The auto-and cross-correlation function, power spectrum, coherence function and Markov model are applied to investigate the statistical characteristics of discharge and each factor of water quality and the interrelation-ship between the variation of discharge and water quality factors. The analysis of discharge, dissolved oxygen and electric conductivity, which were only obtainable data at the Indogyo gagining station in the downstream of the Han River, clearly showed that they hace distinct period of 12 months and three different periods of 6, 4 and 3 months weaker than the former. The cross-correlation between the discharge and water quality(DO, COND) is rather weak and the crosscorrelation function has its peak at lag one. It is considered therefrom that the variation of discharge behaves on water quality facotrs with one day's difference. In the examination of linear regression model for the serial generation and predictive measures, discharge series is fit to first and second order Markov model and DO, COND to first order Markov model.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.249-255
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• 2016

Since the elderly voices include a lot of noise caused by physiological changes in respiration, phonation, and resonance, the performance of the convergence health-care equipments such as speech recognition, synthesis, analysis program done by elderly voice is deteriorated. Therefore it is necessary to develop researches to operate health-care instruments with elderly voices. In this study, a voice activity detection using a symmetric higher-order differential energy function (SHODEO) was developed and was compared with auto-correlation function(ACF) and the average magnitude difference function(AMDF). It was confirmed to have a better performance than other methods in the voice interval detection. The voice activity detection will be applied to a voice interface for the elderly to improve the accessibility of the smart devices.

• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.433-442
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• 2005

An increase In traffic has a large Influence on the performance of a total network. Therefore, traffic management has become an important issue of network management. In this paper, we propose a new routing algorithm that attempts to analyze network conditions using time series prediction models and to propose predictive optimal routing decisions. Traffic congestion is assumed when the predicting result is bigger than the permitted bandwidth. By collecting traffic in real network, the predictable model is obtained when it minimizes statistical errors. In order to predict network traffic based on time series models, we assume that models satisfy a stationary assumption. The stationary assumption can be evaluated by using ACF(Auto Correlation Function) and PACF(Partial Auto Correlation Function). We can obtain the result of these two functions when it satisfies the stationary assumption. We modify routing oaths by predicting traffic in order to avoid traffic congestion through experiments. As a result, Predicting traffic and balancing load by modifying paths allows us to avoid path congestion and increase network performance.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.13-18
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• 2019

This paper analyzes the signal acquisition performance of the legacy GNSS spreading codes and a polyphase code. The code length and chip rate of a polyphase code are assumed to be same as those of the GPS L1 C/A and Galileo E1C codes. The autocorrelation and cross correlation characteristics are analyzed. In addition, a way to calculate a more accurate probability of false alarm for a code with sidelobe non-zero auto-correlation function is proposed. Finally, we estimate the probability of detection and the mean acquisition time for a given signal strength and the probability of false alarm.

• Bulletin of the Korean Chemical Society
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• v.12 no.3
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• pp.315-322
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• 1991

In a recent $paper^1$ we reported equilibrium (EMD) and non-equilibrium (NEMD) molecular dynamics simulations of liquid argon using the Green-Kubo relations and NEMD algorithms to calculate the thermal transport coefficients-the self-diffusion coefficient, shear viscosity, and thermal conductivity. The overall agreement with experimental data is quite good. In this paper the same technique is applied to calculate the thermal transport coefficients of liquid water at 298.15 K and 1 atm using TIP4P model for the interaction between water molecules. The EMD results show difficulty to apply the Green-Kubo relations since the time-correlation functions of liquid water are oscillating and not decaying rapidly enough except the velocity auto-correlation function. The NEMD results are found to be within approximately ${\pm}$30-40% error bars, which makes it possible to apply the NEMD technique to other molecular liquids.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.111-117
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• 2001

In this paper, we will propose the new method that estimates the sensing ability of smart sensor. A study is estimation method that evaluates the sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated the sensing ability of smart sensor using the SAI(Sensing Ability Index) method respectively. We made the smart sensors in our experiment. The types of smart sensor are three types(H1, H1, H3 smart sensor). The smart sensors were developed for recognition of materials. Experiments and analysis were executed to estimated the sensing abili-ty of smarty sensor. Dynamic characteristics of smart sensors(acceleration changing) were evaluated respectively through a new method(SAI) that uses the power spectrum density.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.23-26
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• 2000

This paper descrtbcs our prlmary study for a new mncthod of recogninng materials. which is need for precision work system. This IS a study of dynarnlc characteristics of sensor. new melhod ($R_{SAI}$) has thc sensing ability of distinguishing materials. Experiment and annlysis are executed for proper dynamic scnslng condition. First. we developed advanced smart sensor Second, we develop new methods that have a sensing ability of distinguish matarialsAccording to frequency changing. mtluence of smart sensor are evaluated through new recognition Index ($R_{SAI}$) that ratioof sensing ability index. Disungush of object is cxucuted wllh RsA, method relalivcly according to liequency changing. Wecan use the RsAl for finding materids. Applfciltionr of thls method are linding abnormal condition of obicct (automanufacturing).keling ofobject (medlcal product). tobolics, safety diagnosis of structure, etc

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.510-510
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• 2010

우리나라에서 고속철도는 이미 중요한 대중교통수단 중 하나가 되었으며 향후에도 운행구간을 확대할 예정인 만큼 승객수도 더욱 증가할 것으로 보인다. 또한 승객수가 증가하는 만큼 정숙한 실내환경의 조성 또한 요구되고 있다. 하지만 현재 철도차량 소음에 관한 연구는 대부분 철도 외부에서 방사되는 소음에 한정되어 있으며 철도차량의 내부 소음 특성에 대한 연구는 미비한 상황이다. 현재 국내 환경소음에 대한 규정은 음압레벨만을 기준으로 하고 있지만 실제로 사람이 소음에 대하여 느끼는 청감특성을 나타내기에는 음압레벨만으로는 부족하다. 사람의 청감특성을 효과적으로 반영하기 위하여 음질(Sound Quality)평가의 방법에 대해 현재 활발하게 연구되고 있다. 본 연구에서는 국내에서 운행중인 고속철도 실내 소음의 특성에 대하여 연구하였다. 음압레벨과 loudness의 관계에 대하여 분석하였고 Zwicker parameter과 ACF, IACF 분석을 통하여 객관적인 음질평가를 실시하였다. 또한 청감실험을 통하여 주관적인 음질평가를 수행하여 청감특성에 대하여 분석하고 객관적 평가의 결과를 검증하였다.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.5-13
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• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.