• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1-9
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• 2021

UAE has rapidly developed into one of the leading global financial hubs, with significant transformations in its stock exchanges. In its attempt at economic diversification in the last two decades, the country has also taken a lead in the GCC region in introducing extensive reforms to attract FDI to the Emirates. However, oil price volatilities have posed a significant challenge to all oil-exporting countries. The main aim of this study is to explore the impact of economic diversification and oil price on the UAE stock market. The study applies Granger Causality and Vector Autoregressive Model on monthly Abu Dhabi stock exchange index, Dubai Fateh crude oil spot price, and FDI inflows during 2001-19. The short-term interbank rate has been included as a monetary policy variable. The results show a substantial difference between the two phases of reforms. Oil price and Abu Dhabi stock index show bidirectional relationship during 2001-09 but no causality was found during 2010-19. Furthermore, the second phase was characterized by unidirectional causation from FDI to ADX index. This study highlights FDI inflows as a key driver of stock market performance during the last decade and emphasizes the success of the intense reforms in the UAE initiated for the diversification of its economy.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.4
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• pp.432-439
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• 2013

This study was performed to assess the current stock condition of elkhorn sculpin along the Uljin area in the East Sea of Korea. To assess the state of the stock, yield-per-recruit (YPR) and spawning biomass-perrecruit (SBPR) analyses were performed. Estimates of $F_{max}$ and $F_{0.1}$ were 2.10/year and 0.48/year, respectively, and those of $F_{35%}$ and $F_{40%}$ were 0.66/year and 0.54/year, respectively. Current fishing mortality was estimated at 0.63/year and the current age at first capture was 2.41years. $F_{40%}$ was set as the target reference point of the stock. SBPR at $F_{40%}$ and current SBPR were estimated to be 41.85g and 37.77g, respectively. Estimated FOTY which is the fishing mortality for the overfished threshold yield was 0.49/year. The ratio of SBPR/$SBPR_{MSY}$ was calculated as 0.90 and that of $F/F_{OTY}$ was 1.05. The ratio of $t_c/t_{c\;opt}$ was calculated as 1.15 and that of $F/F_{OTY}$ was 1.17. Therefore, the current stock condition of elkhorn sculpin along the Uljin area of Korea has not been overfished, however, it indicates that a light overfishing is going on this stock.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.353-358
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• 2010

This research introduces a new and improved design for a pneumatic cylinder driven roll feeder wherein each of the principal rotating feeder parts is configured so as to have feeding accuracy and to be low manufacturing cost. The feed pitch accuracy of the proposed roll feeder was evaluated by measuring lengths of cut offs of the strip stock with a shear attached to an air press. The air press was designed, manufactured, and mounted on the same table of the proposed roll feeder such that the strip stock maintained horizontal plane until the strip stock entered into the shear. The proposed roll feeder and the air press were designed to be operated automatically by a PLC employed controller. The feed pitch accuracy of the proposed roll feeder was analyzed by setting the pitch as 10, 12.5, and 15mm. At each predetermined feed pitch, the proposed roll feeder was tested 300 times as one test set and replicated three times. The average lengths of the cut offs of the strip stock ranged from 9.98 to 10.13mm, from 12.42 to 12.57mm, and from 14.96 to 15.06mm at the predetermined 10, 12.5, and 15mm feed pitch, respectively, among the total of 900 samples of each feed pitch. Main cause of variation of the length of the cut off of the strip stock fed by the proposed roll feeder was considered to be fluctuation of the air press during recompressing period of the air compressor to pressurize the air in the air tank. The largest difference between the maximum and the minimum length of the cut off was appeared while the air compressor recompressing the air. The air compressor used for this study restricted the air delivered to the proposed roll feeder while it was still running. Thus, this air delivery restriction problem should be improved by stabilizing the air press while the proposed roll feeder is running.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2973-2978
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• 2011

In this paper, a system is developed to support multi-attribute decision making for designing light-weight of rolling stock. Conceptual design of light-weight of rolling stock does not only mean reducing weight. It should be considered about some attributes like safety and environment, technology, etc. So technical attributes and needs of customers, manufacturers and management companies, passengers, should be reflected and qualitative evaluation methods are required. AHP(Analytical Hierarchy Process) and QFD(Quality Function Deployment) are used to decide weighted values of technical attributes and needs from customers. Finally, Alternatives for light-weight of rolling stock that are composed of alternatives of equipment are evaluated by TOPSIS(Technique for Order Preference by Similarity to Ideal Solution). A series of this process are made as a S/W. It could suggest a near-optimal alternative for light-weight of rolling stock.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1418-1425
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• 2011

Subway operators in the country have their own heavy maintenance facilities for maintaining rolling stock(EMU). However, it is true that the heavy maintenance facilities are not utilized 100% with the recent trend of lengthening maintenance cycle(intervals). With the fact, this enabled the existing maintenance facilities to be utilized for other purposes. By taking advantage of spare facilities and the maintenance staff with rolling stock assembly abilities, subway operators can assemble rolling stock by procuring parts for the assembly instead of purchasing trains from other companies. It is estimated that this will enhance the operator's technology and have a great impact on the management skill as well. This study attempts to find out how the heavy maintenance factory can be utilized for rolling stock assembly.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.73-88
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• 1999

There have been a series of debates to determine whether it would be possible to forecast dynamic systems such as stock markets. Recently the introduction of chaos theory has allowed many researchers to bring back this issue. Their main concern was whether the behavior of stock markets is chaotic or not. These studies, however, present divergent opinions on this question, depending upon the method applied and the data used. And the issue of predictability based on the nonlinear, chaotic nature was not dealt extensively. This paper is to test the nonlinear nature of the Korea stock market and accordingly attempts to predict its behavior. The result indicates that our stock market represents a chaotic behavior. We also found out based on our simulation that executing buy/sell transactions based upon forecasts which were derived using the local approximation method outperforms the decision of holding without a buy/sell transaction.

• Journal of Aquaculture
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• v.16 no.2
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• pp.69-75
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• 2003

Genetic variability and population structure of 11 natural ayu, Plecoglossus altivelis populations and one hatchery stock were assessed by starch gel electrophoretic analysis with 10 enzyme coding loci. Three loci were polymorphic (lower than 0.95 in major allele frequency) in natural populations,2 loci in hatchery stock. The average number of alleles per locus was 1.38. Observed heterozygosities ranged from 0.0235 to 0.088 (0.055 on the average) in natural population while 0.0925 in hatchery stock. The genetic distance among natural populations measured 0.000047-0.005407 and no significant differentiation was observed among them. On the other hand, a signifcant genetic distance was found between natural populations and the hatchery stock with measuring 0.002032-0.O08605. The results in this study suggest that the hatchery stock has diverged from natural populations, and also that careful to maintain sustainable and effective population size (parents number) should be made.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1201-1210
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• 2019

Stock price is characterized as being mutable, non-linear and stochastic. These key characteristics are known to have a direct influence on the stock markets globally. Given that the stock price data often contain both linear and non-linear patterns, no single model can be adequate in modelling and predicting time series data. The autoregressive integrated moving average (ARIMA) model cannot deal with non-linear relationships, however, it provides an accurate and effective way to process autocorrelation and non-stationary data in time series forecasting. On the other hand, the neural network provides an effective prediction of non-linear sequences. As a result, in this study, we used a hybrid ARIMA and neural network model to forecast the monthly closing price of the Shanghai composite index and Shenzhen component index.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.204-208
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• 2018

In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.11-18
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• 2020

This paper analyzes factors affecting enterprise's financial risk listed on the Vietnam stock market. The panel data of research sample includes 524 non-financial listed enterprises on the Vietnam stock market for a period of eleven years, from 2009 to 2019. The Generalized Least Square (GLS) is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, financial risk is measured by the Alexander Bathory model. Debt structure, Solvency, Profitability, Operational ability, Capital structure are independent variables in the study. Firm Size, firm age, growth rate are control variables. The model results show that in order to prevent and limit financial risk for enterprises listed on the Vietnam Stock Market, attention should be paid to variables reflecting Liability structure ratio, Quick Ratio, Return on Assets, Total asset turnover, Accounts receivable turnover, Net assets ratio and Fixed assets ratio. The empirical results show that there are differences in the impact of these factors on the financial risk in state-owned enterprises and non-state enterprises listed on the Vietnam stock market. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to improve the efficiency of financial risk management in enterprises.