• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.79-91
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• 2016

This paper is the first of its kind using a non-linear approach based on cross-correlation function (CCF) to investigate the information arrival hypothesis in crude palm oil (CPO) futures market. Based on daily data from 1986 to 2010, our empirical results reveal that: First, the volume of volatility is not a proxy of information flow. Second, dependence causality running from current return to future volume in conditional variance exhibit an asymmetric pattern of time span with different signs of correlation between price and volume series. This finding indicates the presence of noise traders' hypothesis of price-volume interaction in CPO futures market. Both findings suggest that this futures market is weak-form inefficiency. In terms of investors' behavior, they tend to change their expectations on current return based on errors made in previous trade in generating abnormal volume in the subsequent period. As implied, it is advisable for the investors devise their future trading strategies according to time span and changes of return.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.71-84
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• 2017

Radon, which enters the interior environment from soil, rocks, and groundwater, is a radioactive gas that poses a serious risk to humans. Indoor radon concentrations are measured to investigate the risk of radon gas exposure and reliable radon concentration mapping is then performed for further analysis. In this study, we compared the predictive performance of various univariate kriging algorithms, including ordinary kriging and three nonlinear transform-based kriging algorithms (log-normal, multi-Gaussian, and indicator kriging), for mapping radon concentrations with an asymmetric distribution. To compare and analyze the predictive performance, we carried out jackknife-based validation and analyzed the errors according to the differences in the data intervals and sampling densities. From a case study in South Korea, the overall nonlinear transform-based kriging algorithms showed better predictive performance than ordinary kriging. Among the nonlinear transform-based kriging algorithms, log-normal kriging had the best performance, followed by multi-Gaussian kriging. Ordinary kriging was the best for predicting high values within the spatial pattern. The results from this study are expected to be useful in the selection of kriging algorithms for the spatial prediction of data with an asymmetric distribution.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.71-78
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• 2009

An 8${\times}$8-Gb/s/channel 4-PAM transceiver was designed for high speed memory applications by using 70nm DRAM process with 1.35V supply. An asymmetric 4-PAM signaling scheme is proposed to increase the voltage and time margin of upper and lower eyes in 3-class eye opening. A mathematical basis shows that this scheme statistically reduces 33% of reference noise effect in a receiver. Also, an adaptive pre-emphasis scheme, which utilizes a lone-bit pulse with integrator at the receiver, is introduced to reduce ISI for a simple DRAM channel. In this scheme, an integrating clock timing calibration by using a pre-determined pattern is proposed for the optimum ISI measurement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2481-2493
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• 1996

A simple iterative design method is presented for the miniaturized dielectric filter with finite transimmission zeros. Circuit-network transformations are used to place transission zeros in the stop band. This method is simple and quick compared with conventional pole-synthesis methods. the design of the coupling EM patternof the filter needs the much computation time because its design is carried out through the field simulatior. In this paper, an efficient implementation technique of coupling circuit parameters is presented. This technique uses a linear mapping function between the circuit parameter domain and EM parameter domain to save the high computational time of EM simulator. A narrow band asymmetric filter with a transmission zero is designed and fiblicated through these technique in 1900 MHz band.

• Health Policy and Management
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• v.14 no.4
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• pp.48-74
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• 2004

Considering the existence of asymmetric information between doctor and patient, the doctor's reimbursement method has been considered as a desirable policy device of improving efficiency of patient's use of medical care in terms of its affecting doctor's practice pattern by determining doctor's practice revenue. By using the Community Tracking Study (CTS) physician data set, which includes not only various information on doctors practice arrangements and sources of practice revenue, but also vignettes of various clinical presentations, this paper investigates doctor's reaction to the financial incentive under the control of patient's specific medical situation. Under the econometric model for exploring the effect of doctor's reimbursement method on his/her practice patterns; referring patients, recommend doctor-visit or medical tests, the Hausman's specification test was used for checking out the possibility of the doctor's reimbursement method being endogeneized explanatory variable. In the case where the endogeneity problem of doctor's reimbursement method exists, the 2SLS method was used for correcting that problem, and the multiple regression method was used in the case where the problem is found to be nonexistent. Based on the empirical results, this paper finds that doctors do appear to respond to financial incentive. The empirical results show that the doctor's reimbursement method statistically significantly affects doctor's practice pattern and are coincident with the theoretical result proposed by previous researches, This results suggest, as doctor's practice revenues are mainly determined by prospective method, such as capitation, doctors would more refer their patients to specialists, and hesitate in recommending doctor-visit or medical exam.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.8-11
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• 2019

In this paper, a Ku-band 50-W internally-matched power amplifier is designed and fabricated using a CGHV1J070D GaN HEMT from Wolfspeed. To obtain the same magnitudes and phases for the output signals of the unit transistor cells, which constitute a power transistor, a slit pattern and an asymmetric T-junction are used in the input and output matching circuits. The internally-matched power amplifier is fabricated on two different thin-film substrates with relative dielectric constants of 40 and 9.8, respectively, and is measured under pulsed conditions with a pulse period of $330{\mu}s$ and a duty cycle of 6%. The measured results show a maximum output power of 50~73 W, a drain efficiency of 35.4~46.4%, and a power gain of 4.5~6.5 dB from 16.2 to 16.8 GHz.

• Information Systems Review
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• v.19 no.3
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• pp.47-67
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• 2017

The sharing economy has emerged as a new form of consumption pattern along with the advancement of information technology and the changes in the consumers' desires for economic spending. In a C2C-sharing economy platform, the user side and supplier side share the same assets, thereby making both sides of the market closely related. However, an information asymmetry exists within the platform that makes the players from one side reluctant to participate. This information asymmetry warrants a strategic approach for solving the fundamental "chicken and egg" problem for platform development. Motivated by this phenomenon, this study aims to analyze how the participation intentions from both sides of the platform are influenced by certain anteceding factors, such as trust, perceived risk, and perceived economic profit. Our findings show that the anteceding factors affect the participation intentions in different paths for both sides of the platform. As a managerial implication, these findings highlight the necessity of employing different approaches for each side of market development.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.68-76
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• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the ring connection neural network in which each neuron is only to its nearest neurons with binary synaptic weights of ±1, has been inconnected vestigated Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of n-neuron network to produce a limit cycle of n- or 2n-period are also given The results show that the estimated number of limit cycle is an exponential function of n. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.76-85
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• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the cyclic connection neural network, in which each neuron is connected only to its nearest neurons with binary synaptic weights of $\pm$ 1, has been investigated. Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of $n$-neuron network to produce a limit cycle of $n$- or 2$n$-period are also given. The results show that the estimated number of limit cycles is an exponential function of $n$. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.