• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.159-164
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• 2005

When an optical pulse propagates through the atmospheric channel, the atmospheric turbulence attenuates and spreads this pulse. This attenuation and broadening of pulse are occurred by the fluctuation in the arrival time of pulse at the optical receiver. This pulse broadening induces the intersymbol interference (ISI) between the adjacent pulses. finally, the adjacent pulses are overlapped and the bit rate and the repeaterless transmission length are limited by the ISI. In digital communication system, therefore, the pulse broadening is more important factor than the attenuation. In this paper, thus, we find the ISI in the atmospheric turbulence as the function of the structure constant for the refractive index fluctuation that presents the strength of turbulence using the temporal momentum function and present it by numerical analysis.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.473-473
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• 2009

There have been many academic researches on the aerodynamic design of wind turbine based on blade element method (BEM) and momentum theory (MT, or actuating disk theory). However, in the real world, the turbine blade design requires many additional constraints more than theoretical analysis. The standard procedure is studied in the present paper to design new blades for the wind turbine system ranged from the small size from 1 to 10 kW. From the experience of full design of a 10 kW blade, the authors tried to set up a standard procedure for the aerodynamic design based on IEC 61400-2. Wind-turbine scale, rotating speed, and geometrical chord/twist distribution at the segmented span positions are calculated with a suitable BEM/MT code, and the geometrical shape of tip and root should be modified after considering various parameters: wing-tip vortex, aerodynamic noise, turbine efficiency, structural safety, convenience of fabrication, and even economic factor likes price, etc. The evaluated data is passed to the next procedure of structural design, but some of them should still be corresponded with each other: the fluid-structure interaction is one of those problems not yet solved, for example. Consequently, the design procedure of small wind-turbine blades is set up for the mass production of commercial products in this research.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, 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 abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the 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.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.243-254
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• 2020

Purpose - This paper explores whether overnight returns measured from the last closing price to today's opening price explain the cross-section of stock returns. Design/methodology/approach - This study is conducted using the Korean stock market data from 1998 to 2018, obtained from DataGuide database. The analysis begins with portfolio-level tests, followed by firm-level cross-sectional regressions. Findings - First, when decile portfolios sorted on the daily average of overnight returns in the previous months, the highest decile portfolio exhibits a significant negative risk-adjusted return. This suggests that stocks with higher average overnight returns are temporarily overvalued due to buying pressure from investors. Second, at least 6 months of persistence exists in average overnight returns, which is in line with the results reported by Barber, Odean and Zhu (2009) that investor sentiment persists over several weeks. Finally, Fama-MacBeth cross-sectional regression of expected returns after controlling for a variety of firm characteristic variables such as firm size, book-to-market ratio, market beta, momentum, liquidity, short-term reversal, the slope coefficient for overnight returns remains negative and statistically significant. Research implications or Originality - Overall, the evidence consistently suggests that overnight return is considered as a new priced factor in the cross-section of expected returns. The findings of this paper not only adds to finance literature, but also could be useful to practitioners in making stock investment decision.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.4
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• pp.350-357
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• 1991

A speech recognition system based on a neural network, which can be used for telephon number services was tested. Because in Korea two different cardinal number systems, a koreanic one and a sinokoreanic one, are in use, it is necessary that the used systems is able to recognize 22 discret words. The structure of the neural network used had two layers, also a structure with 3 layers, one hidden layreformed of each 11, 22 and 44 hidden units was tested. During the learning phase of the system the so called BP-algorithm (back propagation) was applied. The process of learning can e influenced by using a different learning factor and also by the method of learning(for instance random or cycle). The optimal rate of speaker independent recognition by using a 2 layer neural network was 96%. A drop of recognition was observed by overtraining. This phenomen appeared more clearly if a 3 layer neural network was used. These phenomens are described in this paper in more detail. Especially the influence of the construction of the neural network and the several states during the learning phase are examined.

• Journal of Astronomy and Space Sciences
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• v.27 no.3
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• pp.205-212
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• 2010

To better understand the physical processes that maintain the high-latitude lower thermospheric dynamics, we have identified relative contributions of the momentum forcing and the heating to the high-latitude lower thermospheric winds depending on the interplanetary magnetic field (IMF) and altitude. For this study, we performed a term analysis of the potential vorticity equation for the high-latitude neutral wind field in the lower thermosphere during the southern summertime for different IMF conditions, with the aid of the National Center for Atmospheric Research Thermosphere-Ionosphere Electrodynamics General Circulation Model (NCAR-TIEGCM). Difference potential vorticity forcing and heating terms, obtained by subtracting values with zero IMF from those with non-zero IMF, are influenced by the IMF conditions. The difference forcing is more significant for strong IMF $B_y$ condition than for strong IMF $B_z$ condition. For negative or positive $B_y$ conditions, the difference forcings in the polar cap are larger by a factor of about 2 than those in the auroral region. The difference heating is the most significant for negative IMF $B_z$ condition, and the difference heatings in the auroral region are larger by a factor of about 1.5 than those in the polar cap region. The magnitudes of the difference forcing and heating decrease rapidly with descending altitudes. It is confirmed that the contribution of the forcing to the high-latitude lower thermospheric dynamics is stronger than the contribution of the heating to it. Especially, it is obvious that the contribution of the forcing to the dynamics is much larger in the polar cap region than in the auroral region and at higher altitude than at lower altitude. It is evident that when $B_z$ is negative condition the contribution of the forcing is the lowest and the contribution of the heating is the highest among the different IMF conditions.

• Korean Journal of Applied Biomechanics
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• v.23 no.4
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• pp.295-306
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• 2013

The purpose of this study was to provide high school male shot putters training methods of gliding and delivery motion through comparative analysis of kinematic characteristics. To accomplish this purpose, three dimensional motion analysis was performed for the subjects(PKC, KKH, YDL) who participated in high school male shot putter competition on 92nd (2011), 93rd (2013) National Sports Festival. The subjects were filmed by four Sony HXR-MC2000 video cameras with 60 fields/s. The three-dimensional kinematic data of the glide, conversion and delivery phase were obtained by Kwon3d 3.1 version. The data of the shoulder rotational angles and projection angles were calculated with Matlab R2009a. The following conclusions had been made. With the analysis of the gliding and stance length ratio, the gliding length was shorter at the TG than the SG with short-long technique but the gliding and stance length ratio was 46.8:53.2% respectively. The deviation of the shots trajectory from APSS(Athlete-plus-shot-system) revealed that the PKC showed similar to "n-a-b-c-I" of skilled S-shape type, KKH and YDL showed "n-a-d-f-I'" of unskilled type. Furthermore, they showed smaller radial distance from the central axis of the APSS and the shots were away from the linear trajectory. From this characteristics, The PKC who performed more TG than SG had shorter glide with S-shape of APSS(skilled type) showed the better record than others with technical skill. But KKH and YDL had bigger glide ratio with "n-a-d-f-I'" of unskilled type and improved their records with technical factor. The projection factor had an effect on the record directly. Because PKC maintained more lower glide and transition posture with momentum transfer through COG's rapid horizontal velocity respectively the subject possessed the characteristics of high horizontal and vertical velocity with large turning radius from shot putter to APSS.