• Korea Trade Review
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• v.46 no.1
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• pp.23-38
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• 2021

This paper investigated the preference change of payment terms in international trade along with counteroffer or first offer conditions of the other parties. Studies on trade payment terms have mainly focused on payment term determination factors such as firm size, product price level, country credit rate, etc. We tried to find other factors affecting payment terms choice, during the negotiation process. We applied behavioral economics theories such as 'Status Quo Bias' and 'Anchoring effect' to build our research model. To prove the existence of the above effects, we proceeded with field experiments to the exporting companies in Alibaba.com. Both 'Status Quo Bias' and 'Anchoring effect' were found in the field experiment. Most of the exporting companies preferred traditional payment methods to new payment methods. And an initial request for a low advance payment ratio led to a lower advance payment ratio. Also, the experience of using new payment methods could diminish status quo bias. This paper applied behavioral economics theories and field experiment methodology to the payment term studies in international trades. These attempts could contribute to expanding the diversity of methodology and scope of international trade studies.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.235-245
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• 2014

This paper presents an envelope tracking power amplifier using a standard CMOS process for the 3GPP long-term evolution transmitters. An efficiency of the CMOS power amplifier for the modulated signals can be improved using a highly efficient and wideband CMOS bias modulator. The CMOS PA is based on a two-stage differential common-source structure for high gain and large voltage swing. The bias modulator is based on a hybrid buck converter which consists of a linear stage and a switching stage. The dynamic load condition according to the envelope signal level is taken into account for the bias modulator design. By applying the bias modulator to the power amplifier, an overall efficiency of 41.7 % was achieved at an output power of 24 dBm using the 16-QAM uplink LTE signal. It is 5.3 % points higher than that of the power amplifier alone at the same output power and linearity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.368-377
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• 2009

In this paper we study the gyro bias calibration method of SDINS(Strap-Down Inertial Navigation System). Generally, SDINS's calibration is performed in 2-axis(or 3-axis) rate table with chamber for varying ambient temperature. We assumed that the majority of calibration-parameter except for gyro bias is knowned. During gyrobias calibration procedure, it can be induced some disturbances(accelerometer's short-term error induced rate table rotation and anti-vibration mount's rotation). In these cases, old gyro-bias calibration methods(using velocity error or attitude error) have an error, because these disturbances are not detectable at the same time. So that, we propose a new gyro-bias calibration method(heading error minimizing using equivalent linear transformation) that can detect anti-vibration mount's rotation. And we confirm efficiency of the new gyro-bias calibration method by simulation.

• Journal of Electrochemical Science and Technology
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• v.12 no.3
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• pp.358-364
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• 2021

In this study, an anion exchange membrane water electrolysis (AEMWE) cell was operated for ~1000 h at a voltage bias of 1.95 V. Impedance spectra were regularly measured every ~ 100 h, and changes in the ohmic and non-ohmic resistance were traced as a function of time. While there was relatively little change in the I-V curves and the total cell resistance during the long-term test, we observed various electrochemical phenomena in the cell: 1) initial activation with a decrease in both ohmic and non-ohmic resistance; 2) momentary and non-permanent bubble resistance (non-ohmic resistance) depending on the voltage bias, and 3) membrane degradation with a slight increase in the ohmic resistance. Thus, the regular test protocol used in this study provided clear insights into the performance degradation (or improvement) mechanism of AEMWE cells.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.222-232
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• 2022

In this study we investigated the characteristics of long-term tidal constituents based on 30 tidal gauge data along the coasts of Korea and its the effects on total water level (TWL) forecasts. The results show that the solar annual (Sa) and semiannual (Ssa) tides were dominant among long-term tidal constituents, and they are relatively large in western coast of Korea peninsula. To investigate the effect of long-term tidal constituents on TWL forecasts, we produced predicted tides in 2021 with and without long-term tidal constituents. The TWL forecasts with and without long-term tidal constituents are then calculated by adding surge forecasts into predicted tides. Comparing with the TWL without long-term tidal constituents, the results with long-term tidal constituents reveals small bias in summer and relatively large negative bias in winter. It is concluded that the large error found in winter generally caused by double-counting of meteorological factors in predicted tides and surge forecasts. The predicted surge for 2021 based on the harmonic analysis shows seasonality, and it reduces the large negative bias shown in winter when it subtracted from the TWL forecasts with long-term tidal constituents.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.46 no.2
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• pp.87-98
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• 2020

The aim of this study was to determine the efficacy of oral splints in reducing the intensity of pain in patients with temporomandibular joint dysfunction in both short and long-term treatment durations. Electronic databases, Cochrane Library, MEDLINE via PubMed, Web of Science, Egyptian Knowledge Bank, and EMBASE were searched for randomized controlled trials comparing different types of splints to non-occluding splints, behavioral therapy, pharmacotherapy, counseling, and no treatment. The risk of bias was assessed by using Cochrane risk of bias recommendations. Fixed and random effects were used to summarize the outcomes. The effect estimates were expressed as standardized mean differences (SMD) or risk ratios with a 95% confidence interval (CI). Subgroup analyses were carried out according to the treatment duration. Twenty-two studies met the inclusion criteria. A meta-analysis of short-term studies up to three months revealed no significant difference between the study groups. However, long-term studies exhibited a significant difference in pain reduction in favor of the control group. Total analysis revealed that the control group resulted in significant pain reduction (SMD 0.14, 95% CI 0.05-0.23, P=0.002, I²=0%). Oral splints are not effective in reducing pain intensity or improving function in patients with temporomandibular joint dysfunction.

• Journal of Distribution Science
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• v.14 no.1
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• pp.93-102
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• 2016

Purpose - The purpose of paper is studying the static and dynamic side for long-term memory storage properties, and increase the explanatory power regarding the long-term memory process by looking at the long-term storage attributes, Korea Composite Stock Price Index. The reason for the use of GPH statistic is to derive the modified statistic Korea's stock market, and to research a process of long-term memory. Research design, data, and methodology - Level shifts were subjected to be an empirical analysis by applying the GPH method. It has been modified by taking into account the daily log return of the Korea Composite Stock Price Index a. The Data, used for the stock market to analyze whether deciding the action by the long-term memory process, yield daily stock price index of the Korea Composite Stock Price Index and the rate of return a log. The studies were proceeded with long-term memory and long-term semiparametric method in deriving the long-term memory estimators. Chapter 2 examines the leading research, and Chapter 3 describes the long-term memory processes and estimation methods. GPH statistics induced modifications of statistics and discussed Whittle statistic. Chapter 4 used Korea Composite Stock Price Index to estimate the long-term memory process parameters. Chapter 6 presents the conclusions and implications. Results - If the price of the time series is generated by the abnormal process, it may be located in long-term memory by a time series. However, test results by price fixed GPH method is not followed by long-term memory process or fractional differential process. In the case of the time-series level shift, the present test method for a long-term memory processes has a considerable amount of bias, and there exists a structural change in the stock distribution market. This structural change has implications in level shift. Stratum level shift assays are not considered as shifted strata. They exist distinctly in the stock secondary market as bias, and are presented in the test statistic of non-long-term memory process. It also generates an error as a long-term memory that could lead to false results. Conclusions - Changes in long-term memory characteristics associated with level shift present the following two suggestions. One, if any impact outside is flowed for a long period of time, we can know that the long-term memory processes have characteristic of the average return gradually. When the investor makes an investment, the same reasoning applies to him in the light of the characteristics of the long-term memory. It is suggested that when investors make decisions on investment, it is necessary to consider the characters of the long-term storage in reference with causing investors to increase the uncertainty and potential. The other one is the thing which must be considered variously according to time-series. The research for price-earnings ratio and investment risk should be composed of the long-term memory characters, and it would have more predictability.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.40.2-40
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• 2002

This paper presents the reconfigurable flight controller in the presence of jammed actuator fault using the adaptive sliding mode control scheme. It is developed under the assumption that the control surface fault cannot be detected and the positions of stuck control surfaces are unknown. It is well known that sliding mode controller shows good performance for the systems with various uncertainties. None-operating stuck actuator makes the system behave like bias which degrades the system performance and sometimes destabilizes the system. Therefore, the bias term generated by actuator faults has to be compensated by the control system. To the objective, we adopt the adaptive sliding mode cont...

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.