• Journal of Distribution Science
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• v.13 no.9
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• pp.37-45
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• 2015

Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Bulletin of the Korean Chemical Society
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• v.33 no.9
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• pp.2873-2877
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• 2012

Quasi-classical trajectory (QCT) calculations of H+HLi reaction have been carried out on a new potential energy surface of the ground state reported by Prudente et al. [Chem. Phys. Lett. 2009, 474, 18]. The four polarization-dependent differential cross sections have been carried out in the center of mass (CM) frame at various collision energies. The reaction probability for the depletion channel has been studied over a wide collision energy range. It has been found that the collision energy decreases remarkably reaction probability, which shows the expected behavior of the title reaction belonging to an exothermic barrierless reaction. The results are in good agreement with previous RMP results. The P(${\theta}_r$), P(${\phi}_r$) and P(${\theta}_r,\;{\phi}_r$) distributions, the k-k'-j' correlation and the angular distribution of product rotational vectors are presented in the form of polar plots. The average rotational alignment factor <$P_2(j{\prime}{\cdot}k)$> as a function of collision energy is also calculated. The results indicate that the collision energy has a great influence on the polarization of the product rotational angular momentum vector j'.

• Journal of Radiation Protection and Research
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• v.23 no.1
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• pp.1-6
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• 1998

A diffusion model of radioactive liquid effluents is developed and applied for YGN NPP's site, based on the Gaussian plume type model. Due to the complexity of oceanic diffusion characteristics of YGN site, a simple and reliable statistical model based on Reg. Guide 1.113 is developed. Also, a computer code package to calculate dilution factors as a function of plant operation conditions and pathway of radioactive materials. A liquid effluents diffusion model is developed by dividing the diffusion range into two categories, i. e, a near field mixing region and a far field mixing region. In the near field, the initial mixing is affected by a buoyance force, a high initial turbulence and momentum which is characterized by a plant operation condition and environmental conditions. The far field mixing is similar to gaseous effluents diffusion. So, beyond the near field region, wellknown Gaussian plume model was adopted. A different area averages of Gaussian plume equation was taken for each radioactive exposure pathway. As a result, we can get different dilution factors for different pathways. Results shows that present dilution factors used for YGN ODCM is too much overestimated compared with dilution factors calculated with the developed model.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.4
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• pp.31-34
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• 2016

System In Package (SiP) is getting popular and momentum for the recent wearable, IoT and connectivity application apart from mobile phone. This is driven by market demands of cost competitive, lighter and smaller/thinner and higher performance. As one of many semiconducting assembly products, Leadframe product has been widely used for low cost solution, light/ small and thin form factor. But It has not been applied for SiP although Leadframe product has many advantages in cost, size and reliability performance. SiP is mostly based on laminate substrate and technically difficult on Leadframe substrate because of a limitation in SMT performance. In this paper, Leadframe based SiP product has been evaluated about key technical challenges in SMT performance and electrical shield technology. Mostly Leadframe is considered not available to apply EMI shield because of tie-bar around package edge. In order to overcome two major challenges, connection bars were deployed properly for SMT pad to pad and additional back-side etching was implemented after molding process to achieve electrical isolation from outer shield coating. This product was confirmed assembly workability as well as reliability.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.28.1-28.1
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• 2017

To investigate AGN outflows as a tracer of AGN feedback on the host galaxies, we perform integral-field spectroscopy of 20 type 2 AGNs at z<0.1 using the Magellan/IMACS and the VLT/VIMOS. The observed objects are luminous AGNs with the [O III] luminosity >$10^{41.5}erg/s$, and exhibit strong outflow signatures in the [O III] kinematics. We obtain the maps of the narrow and broad components of [O III] and $H{\alpha}$ lines by decomposing the emission-line profile. The broad components in both [O III] and $H{\alpha}$ represent the non-gravitational kinematics, (i.e., gas outflows), while the narrow components represent the gravitational kinematics (i.e., rotational disks), especially in $H{\alpha}$. By using the spatially integrated spectra within the flux-weighted size of the narrow-line region, we estimate the outflow energetics. The ionized gas mass is $(1.0-38.5){\times}10^5M_{\odot}$, and the mean mass outflow rate is $4.6{\pm}4.3M_{\odot}/yr$, which is a factor of ~260 higher than the mean mass accretion rate $0.02{\pm}0.01M_{\odot}/yr$. The mean energy injection rate is $0.8{\pm}0.6%$ of the AGN bolometric luminosity Lbol, while the mean momentum flux is $(5.4{\pm}3.6){\times}L_{bol}/c$, except for two most kinematically energetic AGNs. The estimated energetics are consistent with the expectations for energy-conserving outflows from AGNs, yet we do not find any supporting evidence of instantaneous star-formation quenching due to the outflows.

• Journal of Korea Foundry Society
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• v.12 no.3
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• pp.220-229
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• 1992

The degree of purification and the macrostructure of high purity aluminium were studied through the alternate stirring method in order to improve the nonuniformity of solute concentration in the unidirectional stirring method. The $2^3$ factorial design was done to examine the effects of experimental factors more qualitatively. In the relatively low stirring speed of 1500 rpm with alternate stirring mode, the uniform solute profile and refined grain structure were obtained due to strong washing effect and turbulent fluid flow. It was induced by the transition of the momentum boundary layer by alternation of the stirrer. It was concluded from this study that the alternate stirring mode was more effective to obtain the uniformity of solute even in the stirring speed of 1500 rpm. But the degree of purification decreased below the critical alternating period. When 2N(99.8wt.%) aluminium was used as the starting material the morphology of solid-liquid showed the cellular shape and the columnar grains were inclined to the direction of rotation. This inclined grain growth resulted from the difference of relative velocities of solid and liquid. The inclined angle was increased as the stirring speed increased and solidification proceeded. In the case of 4N aluminium, there was no inclined grain growth and it was confirmed from the macrostructure and SEM work that the morphology of solid-liquid interface was planar. From the factorial design, it was found that the alternate stirring mode showed poorer purification effect than that of unidirectional stirring mode at low speed(500 rpm). In addition, the factor that had the most significant effect on the degree of purification was the stirring speed.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.69-76
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• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.