• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.47-59
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• 2017

The objective of this study is to determine the short run and long run dynamics between maritime import volume (IMV), industrial production (IP), and real effective exchange rate (REER) of the Korean Won over the REER of certain major currencies (US Dollar, Chinese Yuan, and Japanese Yen) in Korea's Jeonnam province. The Johansen and Juselius cointegration results reveal that at least one cointegration vector or long-run relationship exists. Hence, this study estimated the long run equilibrium equation, which indicates that both IP and REER are inelastic, although the former is bigger than the latter. Moreover, the dynamic causality analysis reveals short and long-run unidirectional causality from IP and REER to IMV in all three models. Further, in all the models, the results indicate short run unidirectional causality from REER to IP. In addition, the impulse response (IR) results show that the impulse of IP and REER decayed after four months. Additionally, the IR analysis results indicate that the REER of the Korean Won over the REER of Japanese Yen is the biggest with respect to the impact of relative REER on IP, which is the proxy variable of regional real income. Thus, empirical results indicated that real income and REER play an important role in determining the Jeonnam's maritime import demand behavior in the short run and long run. More importantly, substantial actions reducing unexpected fluctuation of the REER and real income based on micro and macro economic policies will increase the imported volume in the ports of the Jeonnam province.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.43-52
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• 2021

This study is the first to scrutinize how real effective exchange rate, together with the vehicle currency exchange rate, asymmetrically influences the total trade balance between ASEAN (Association of Southeast Asian Nations) and the EU (European Union). This research employs quarterly data between 2000Q1 and 2018Q1, which is derived from several sources. We introduce a method for constructing the double-aggregated real effective exchange rate between ASEAN and the EU that captures the roles of all their currencies. Moreover, we propose the formula to compute vehicle currency exchange rate to assess the importance of vehicle currency in ASEAN-EU trade. Additionally, as asymmetrical impacts of exchange rate on trade balance are well documented by current studies, we employ Nonlinear Autoregressive Distributed Lag (NARDL) model of Shin et al. (2014) to analyze the impacts of currency depreciation as well as appreciation in detail. The findings confirm the prominence of USD as vehicle currency in ASEAN-EU trade. Both depreciation and appreciation of ASEAN's currencies against USD can foster ASEAN's trade balance in the long run. Short-run asymmetrical impacts as well as J-curve effect are found in the vehicle currency models only. The results are robust for the cases of EU-28 and EU-27.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.231-238
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• 2022

In this paper, among short-range wireless communication technologies such as Beacon, Bluetooth, UWB (Ultra-wideband), ZigBee, NFC (Near Field Communication), Z-Wave, 6LoWPAN (IPv6 over Low power WPAN), D2D (Device to Device), etc., proposed an IoT service platform based on a beacon that can provide indoor positioning. And, a beacon-linked web server was designed by blocking indiscriminate beacon spam signals and applying REST web service technology with flexibility and scalability. Data accessibility between different devices was verified by testing the success rate of data transmission, the success rate of blocking beacon push, the success rate of IoT interlocking processing, the accuracy of location positioning, and the success rate of REST web service-based data processing. Through the designed IoT service platform, various proposals and research on short-distance-based business models and service platforms will be conducted in the future.

• Korean Journal of Ecology and Environment
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• v.45 no.4
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• pp.420-443
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• 2012

An Individual-Based Model (IBM) was developed by employing natural and toxic survival rates of individuals to elucidate the community responses of benthic macroin-vertebrates to anthropogenic disturbance in the streams. Experimental models (dose-response and relative sensitivity) and mathematical models (power law and negative exponential distribution) were applied to determinate the individual survival rates due to acute toxicity in stressful conditions. A power law was additionally used to present the natural survival rate. Life events, covering movement, exposure to contaminants, death and reproduction, were simulated in the IBM at the individual level in small (1 m) and short (1 week) scales to produce species abundance distributions (SADs) at the community level in large (5 km) and long (1~2 years) scales. Consequently, the SADs, such as geometric series, log-series, and log-normal distribution, were accordingly observed at severely (Biological Monitoring Working Party (BMWP<10), intermediately (BMWP<40) and weakly (BMWP${\geq}50$) polluted sites. The results from a power law and negative exponential distribution were suitably fitted to the field data across the different levels of pollution, according to the Kolmogorov-Smirnov test. The IBMs incorporating natural and toxic survival rates in individuals were useful for presenting community responses to disturbances and could be utilized as an integrative tool to elucidate community establishment processes in benthic macroin-vertebrates in the streams.

• Journal of Preventive Medicine and Public Health
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• v.51 no.3
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• pp.140-147
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• 2018

Objectives: Environmental pollution is a negative consequence of the development process, and many countries are grappling with this phenomenon. As a developing country, Iran is not exempt from this rule, and Iran pays huge expenditures for the consequences of pollution. The aim of this study was to analyze the long- and short-run impact of air pollution, along with other health indicators, on private and public health expenditures. Methods: This study was an applied and developmental study. Autoregressive distributed lag estimating models were used for the period of 1972 to 2014. In order to determine the co-integration between health expenditures and the infant mortality rate, fertility rate, per capita income, and pollution, we used the Wald test in Microfit version 4.1. We then used Eviews version 8 to evaluate the stationarity of the variables and to estimate the long- and short-run relationships. Results: Long-run air pollution had a positive and significant effect on health expenditures, so that a 1.00% increase in the index of carbon dioxide led to an increase of 3.32% and 1.16% in public and private health expenditures, respectively. Air pollution also had a greater impact on health expenditures in the long term than in the short term. Conclusions: The findings of this study indicate that among the factors affecting health expenditures, environmental quality and contaminants played the most important role. Therefore, in order to reduce the financial burden of health expenditures in Iran, it is essential to reduce air pollution by enacting and implementing laws that protect the environment.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.52.1-52.1
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• 2010

The relationship between orbital periods of cataclysmic variables (CV) and mass-loss rates of their donor stars is an important subject of theoretical researches. The observed donor's radii are oversized in comparison with those of isolated unperturbed stars of the same mass, which is thought to be a consequence of the mass-loss. Using the empirical mass-radius relation of CVs and the Hayashi theory for changes in effective temperature, orbital period, and luminosity of the donor with the stellar radius, we find the mass-loss rate of CVs as a function of the orbital period P. The derived mass-loss rate is more or less constant at 10-9.6-10-10M$\odot$ yr-1 with P above 90 minutes and declines very rapidly with P below 90 minutes, reaching 10-10.3-10-11.7M$\odot$ yr-1 when P is close to the minimum period. The turnaround behavior of the mass-loss rate shape with P near the minimal period is much less pronounced than suggested by earlier numerical models, making observational detection of the turnaround highly unlikely. When applied to our new results, SDSS 1035, 1507, 1501 and 1433 systems, previously known as post-bounce CVs, are more likely to be systems that have yet to reach the minimal period.

• Journal of ILASS-Korea
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• v.25 no.4
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• pp.188-195
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• 2020

To meet stringent emission regulations of automotive engines, fuel injection control techniques have advanced based on reliable and fast computing prediction models. This study aims to develop a reliable lightweight prediction model of fuel injection rates using a small number of input parameters and based on simple fluid dynamic theories. The prediction model uses the geometry of the injector nozzle, needle motion data, injection conditions and the fuel properties. A commercial diesel injector and US No. 2 diesel were used as the test injector and fuel, respectively. The needle motion data were measured using X-ray phase-contrast imaging technique under various fuel injection pressures and injection pulse durations. The actual injector rate profiles were measured using an injection rate meter for the validation of the model prediction results. In the case of long injection durations with the steady-state operation, the model prediction results showed over 99 % consistency with the measurement results. However, in the case of short injection cases with the transient operation, the prediction model overestimated the injection rate that needs to be further improved.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.857-871
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• 2013

Export credit insurance is a policy tool for export growth. In the era of free trade under the governance of WTO, export credit insurance is still allowed as one of the few instruments to increase exports. This paper, using data on short-term export insurance contracts issued to foreign subsidiaries of Korean companies, calculates the expected loss per exposure by combining the effect of risk factors (credit rate of foreign importers, size of mother company, and payment period) on loss frequency and loss severity in different levels. We, applying generalized linear models (GLM), first fit loss frequency and loss severity to negative binomial and lognormal distribution, respectively, and then estimate the loss frequency rate per contract and the ratio of loss severity to coverage amount. Finally, we calculate the expected loss per exposure for each level of risk factors by combining these two rates. Based on the result of statistical analysis, we present the implication for the current premium rate of export insurance.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.43-50
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• 2017

These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.