• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.119-127
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• 2015

This study is to analyse the causality and volatility spillover between farming fish species in consumption replacement relation using flatfish(oliver flounder) and rockfish's wholesale market price data from September 2006 to July 2015. For the analysis, VAR(5) model and bivariate asymmetric GARCH-BEKK model are employed. The empirical results of this study are summarized as follows: First, the price volatility of flatfish and rockfish is very large without the trend during the sample period. Second, the correlation coefficient between flatfish and rockfish wholesale markets has positive 0.1059 value. Third, causality relation is unidirectional from rockfish market to flatfish market. Fourth, conditional volatility spillover effect is unidirectional from rockfish market to flatfish market, but asymmetric volatility effect is bidirectional between flatfish and rockfish markets that implies the bad news arising from flatfish wholesale market impact on rockfish market's volatility and the bad news arising from rockfish wholesale market impact on flatfish market's volaltilty. Consequently, based on the thus results, the volatility spillover effect interacts and is bidirectional between flatfish and rockfish wholesale markets.

• Journal of Environmental Health Sciences
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• v.1 no.1
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• pp.21-27
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• 1974

This work was carried out to investigate the chemical properties of the chelate compounds which were produced with 2-methoxy-5-nitrophenol(MNG) and metal salt such as copper nitrate and manganese nitrate. And obtained results were as in the followings. 1) The binding ratio of the chelate compounds formation were determined by using the molar ratio concentration method and their chemical structures were identified by IR-spectrum. 2) In the absorbance measuring, 2-methoxy-5-nitrophenol coordinated with manganese and copper showed the maximum absorbance at $430 m\mu$ and $410 m\mu$ respectively. 3) The binding ratio of chelated compounds were measured by molar ratio method and continuous variation method with spectrophotometer, which was identified as 1:2. 4) The conditional formation constant(log Kn value) of manganese and copper chelate compounds were 6.70, 6.75, respectively according to the equation of $log\frac{A-AM\circ n MNG}{AMm MNG-A}=n log (M\circ)+log Kn$ 5) The dissociations degree of manganese and copper chelate compound were $2, 300{\times} 10^{-7}$, $2, 346{\times} 10^{-7}$ respectively according to the molar calculation method.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1333-1343
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• 2014

Hansen and Lund (2005) documented that a univariate GARCH(1,1) model is no worse than other sophisticated GARCH models in terms of prediction errors such as MSPE and MAE. Here, we extend Hansen and Lund (2005) by considering multivariate GARCH models and incorporating risk management measures such as VaR and fail percentage. Our Monte Carlo simulations study shows that multivariate GARCH(1,1) model also performs well compared to asymmetric GARCH models. However, we suggest that actual model selection should be done with care in light of risk management. It is applied to the realized volatilities of KOSPI, NASDAQ and HANG SENG index for recent 10 years.

• Journal of Power Electronics
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• v.15 no.1
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• pp.177-189
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• 2015

The output of the controller is said to exceed the input limits of the plant being controlled when a control system operates in a non-linear region. This process is called the windup phenomenon. The windup phenomenon is not preferable in the control system because it leads to performance degradation, such as overshoot and system instability. Many anti-windup strategies involve switching, where the integral component differently operates between the linear and the non-linear states. The range of state for the non-overshoot performance is better illustrated by the boundary integral error plane than the proportional-integral (PI) plane in windup inspection. This study proposes a PI controller with a separate closed-loop integral controller and reference value set with respect to the input command and external torque. The PI controller is compared with existing conventional proportional integral, conditional integration, tracking back calculation, and integral state prediction schemes by using ScicosLab simulations. The controller is also experimentally verified on a direct current motor under no-load and loading conditions. The proposed controller shows a promising potential with its ability to eliminate overshoot with short settling time using the decoupling mode in both conditions.

• Journal of Biosystems Engineering
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• v.14 no.3
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• pp.158-167
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• 1989

This study was conducted to investigate the applicability of true model theory in a powered lugged wheel-soil system and to examine the possibility of using principles of similitude in investigating the dimensions of soil parameters pertinent to a powered lugged wheel-soil system concerning the sinkage prediction. The following conclusions were derived from the study; 1) The sinkage of prototype wheels proved to be predicted by those of the model wheels for the range of the dynamic weight tested. 2) A conditional equation which can be used for the prediction of sinkage of prototype by model test was derived as $n_f=n{_\ell}{^{-b}}$. The range of the numerical value of b, which is the exponent on the length dimension of the soil property ${\alpha}$, was found to be -1.48~-2.54. 3) Considering a relatively wide variation of b values, it was concluded that there are several soil properties which are pertinent to the powered lugged-wheel soil system concerning the sinkage prediction.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.12
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• pp.1372-1378
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• 2011

The smart air condition system is superior to conventional air condition system in the aspect of control accuracy, environmental preservation and it is foundation for intelligent vehicle such as electric vehicle, fuel cell vehicle. In this paper, failure analyses of smart air condition system will be performed and then sensor fusion technique will be proposed for fail safety of smart air condition system. A sensor fusion logic of air condition system by using CO sensor, $CO_2$ sensor and VOC, $NO_x$ sensor will be developed and simulated by fault injection simulation. The fusion technology of smart air condition system is generated in an experiment and a performance analysis is conducted with fusion algorithms. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4601-4619
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• 2022

The classical Probabilistic Safety Analysis (PSA) does not include any time dependence explicitly. However, the success criteria (SC) could evolve during the cycle for some initiating events. In that sense, there is a type of sequence in which this time-dependency is quite important, the family of Anticipated Transient without Scram (ATWS) sequences in Pressurized Water Reactors. Therefore, a new risk-informed approach is proposed in this paper, which makes it possible to obtain the time-dependent SC evolution of the safety functions affected by the Moderator Temperature Coefficient (MTC) value. Then, the evolution of the ATWS conditional core damage probability (CCDP) could be obtained using a PSA model. To quantify the CCDP, the average values of the time-dependent failure probabilities must be computed. Finally, the comparison between the CCDP obtained through the application of the classical PSA approach and the new one makes it possible to quantify the impact of time-dependence on the SC of the headers that this new risk-informed ATWS approach can provide.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.43.1-43.1
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• 2019

In this study, we apply a deep learning model to denoising solar magnetograms. For this, we design a model based on conditional generative adversarial network, which is one of the deep learning algorithms, for the image-to-image translation from a single magnetogram to a denoised magnetogram. For the single magnetogram, we use SDO/HMI line-of-sight magnetograms at the center of solar disk. For the denoised magnetogram, we make 21-frame-stacked magnetograms at the center of solar disk considering solar rotation. We train a model using 7004 paris of the single and denoised magnetograms from 2013 January to 2013 October and test the model using 1432 pairs from 2013 November to 2013 December. Our results from this study are as follows. First, our model successfully denoise SDO/HMI magnetograms and the denoised magnetograms from our model are similar to the stacked magnetograms. Second, the average pixel-to-pixel correlation coefficient value between denoised magnetograms from our model and stacked magnetogrmas is larger than 0.93. Third, the average noise level of denoised magnetograms from our model is greatly reduced from 10.29 G to 3.89 G, and it is consistent with or smaller than that of stacked magnetograms 4.11 G. Our results can be applied to many scientific field in which the integration of many frames are used to improve the signal-to-noise ratio.

• Journal of Korea Trade
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• v.27 no.5
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• pp.91-112
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• 2023

Purpose - This study empirically investigates how the effects of localized knowledge spillovers on technology adoption are conditional on the organizational capabilities of potential adopters. Design/methodology - The empirical model utilized in this study examines how the presence of prior adopters of advanced manufacturing technologies affects a plant's technology adoption decision differently based on its organizational capabilities, measured by plant size and plant status (single-plant firm vs. multi-plant firm). Moreover, this study investigates how the scope of knowledge spillovers from prior adopters, both in terms of geographical and functional proximities, differ for plants with different organizational capabilities. Findings - The main findings of this study are as follows: 1. Although plants with lower organizational capabilities are less likely to adopt advanced technologies, such plants receive greater marginal benefits from knowledge spillovers from prior adopters in their region. 2. Plants with greater organizational capabilities can benefit from knowledge spillovers from a wider set of prior adopters. In other words, while plants with lower organizational capabilities tend to benefit from knowledge spillovers from "similar" and "local" adopters, plants with greater organizational capabilities can also benefit from knowledge spillovers from "not-too-similar" or are geographically distant prior adopters. Originality/value - While existing studies mainly focus on the effects of the various kinds of regional agglomeration, few studies investigate localized knowledge spillovers in technology adoption. Moreover, no prior studies have explored how the effects of knowledge spillovers on technology adoption depend on a plant's organizational capabilities and how the scope of knowledge spillovers differs for plants with different organizational capabilities. This study is the first to empirically investigate this topic.