• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.102-114
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• 2021

India has recently experienced an acute crisis confronting the COVID-19 pandemic as confirmed cases exceeded 11.73 million in March 2021, which was the second worst scale only after the United States. The strict lockdown measures as well as the pandemic itself posed a serious threat of survival, in particular, to immigrant workers engaged in informal sectors, which triggered their reverse immigration. In case the COVID-19 pandemic continues in 2021, it is estimated that in the sector of tourism and service alone, more than 20 million jobs will disappear. The damage on industry is already being realized with the significant decrease of workforce. It is important to note, however, that jobless growth and labor polarization were observed even before the outbreak of COVID-19, and that the pandemic only served as one of the trigger catalysts that made those submerged problems burst out. In this study, we examine the structural problems in industry and labor market in India and consider the social context and efficacy of the "Make in India" or "Atmanirbhar Bhrat" policy. The latter initiative was presented in the trenches of the pandemic in 2020. While considering the complexity of problems, we would like to pursue a future-oriented approach and propose a direction in restructuring the labor market, attempted at reversing the critical conditions following the fourth industrial revolution and digitization into the shortcut to labor market restructuring.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.514-524
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• 2016

The Bio-Climatic impact Assessment System, BioCAS was utilized to produce analysis maps of daily maximum perceived temperature ($PT_{max}$) and excess mortality ($r_{EM}$) over the entire Seoul area on a heat wave event. The spatial resolution was 25 m and the Aug. 5, 2012 was the selected heat event date. The analyzed results were evaluated by comparing with observed health impact data - mortality and morbidity - during heat waves in 2004-2013 and 2006-2011,respectively. They were aggregated for 25 districts in Seoul. Spatial resolution of the comparison was equalized to district to match the lower data resolution of mortality and morbidity. Spatial maximum, minimum, average, and total of $PT_{max}$ and $r_{EM}$ were generated and correlated to the health impact data of mortality and morbidity. Correlation results show that the spatial averages of $PT_{max}$ and $r_{EM}$ were not able to explain the observed health impact. Instead, spatial minimum and maximum of $PT_{max}$ were correlated with mortality (r=0.53) and morbidity (r=0.42),respectively. Spatial maximum of $PT_{max}$, determined by building density, affected increasing morbidity at daytime by heat-related diseases such as sunstroke, whereas spatial minimum, determined by vegetation, affected decreasing mortality at nighttime by reducing heat stress. On the other hand, spatial maximum of $r_{EM}$ was correlated with morbidity (r=0.52) but not with mortality. It may have been affected by the limit of district-level irregularity such as difference in base-line heat vulnerability due to the age structure of the population. Areal distribution of the heat impact by local building and vegetation, such as spatial maximum and minimum, was more important than spatial mean. Such high resolution analyses are able to produce quantitative results in health impact and can also be used for economic analyses of localized urban development.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.

• The Korean Journal of Air & Space Law and Policy
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• v.31 no.2
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• pp.215-236
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• 2016

This paper is related to a study on safety management of cosmic radiation in the aviation area, and as a comprehensive study encompassing not only aviation crew but also aviation traffic users, presents issues on an exposure to the cosmic radiation which authors predict may be intensified in a time to come. Although the government of the Republic of Korea has recently activated regulations related to the cosmic radiation, the following improvement measures are further urged to be carried out not only as a regulatory improvement for pushing ahead with effectiveness but also as a supplementary tool. Firstly, a dose limit corresponding to the international standard needs to be applied. Since the dose limit imposed by the Korean government is improperly higher than the international dose limit of the cosmic radiation, the present dose limit needs to be re-established in a range of "not exceeding the international recommendation". Secondly, a new methodology is needed such that aviation companies observe a yearly effective dose limit of passengers. A fact that only aviation crew is specified but passengers are excluded in the related regulation is based on a recommendation presented by the International Commission on Radiological Protection (ICRP). According to the recommendation, Korean government excluded passengers in the "Cosmic Radiation Safety Requirements for Crew". Among the present aviation regulations, there exists a protection standard for protecting aviation traffic users. However, it presents a damage protection only for ticket-related issues. Since this regulatory weakness provides a cause of endangering national health, the authors believe that an improvement in the regulation is needed without sticking to the recommendation from the ICRP. To this end, new regulations are strongly demanded from aspects of not only legal but also regulatory areas. The dose limit in accordance with the international standard is established. However, at least a minute amount of cosmic radiation is continuously acting on all people of Korea. Since more and higher level of cosmic ration may exist in the aviation space, an improved method of representing the minute amount of cosmic radiation in figures. As a result, a desirable regulation may be established for protecting not only crew but also aviation traffic users from being exposed to the cosmic radiation via a legislation of the desirable regulation.

• Korean Journal of Environmental Agriculture
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• v.27 no.1
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• pp.1-9
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• 2008

The main purpose of this study is to accumulate the fundamental data representing groundwater of plastic film houses by means of water quality and its multivariate statistical analysis. Groundwater samples were collected in every two years since 2000 to 2004 from total 211 sites. According to the result of water quality analysis, ground water quality was suitable for irrigation purpose averagely. Correlation analysis showed that EC was highest positively correlated with $Mg^{2+}$ to 0.810(p<0.01), 0.776(p<0.01) in April and July, respectively. $NO_3-N$ was highest positively correlated with T-N to 0.794(p<0.01) in October. This result shows that it can lead to a different result even in similar case sometimes. Four factors were extracted through factor analysis in April and July, but five factors were extracted in October. The proportions of cumulative variance by the factor were 64.9, 60.2, and 70.7 in April, July, and October, respectively. The first factor was highly related to anions and cations such as $Ca^{2+},\;Mg^{2+},\;Cl^-,\;{SO_4}^{2-}$, and EC in contrast to that of stream water. According to the cluster analysis, 211 sites are classified into four groups. Common type of ground water quality was shown in group A. The pH and $PO_4-P$ were highest in Group B. The anions and cations were highest in Group C. $COD_{Cr}$ was highest in Group D.

• Korean Journal of Heritage: History & Science
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• v.42 no.1
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• pp.144-157
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• 2009

Nondestructive methods to check the vitality of trees and to find out internal decay of old-giant trees include the use of electrical resistance, ultrasound transmission time, microdrilling, and infrared thermography etc. Among these, ultrasound transmission offers some advantages compared to others such as it is an entirely nondestructive detection method and it can be applied to very big trees. However, the ultrasound equipment is comparatively expensive and not broadly spread yet. On the other hand, Shigometer is versatile to be applied to check vitality of the tree and find out internal decay. Electrical conductivity of plant tissues is a very useful characteristics to determine the vitality and internal decay of trees. Electrical resistance of cambial area tells about the vitality of a tree and electrical resistance of heartwood reveals discoloration or decay of it. For determination of the vitality of the tree, the standard equation for calibration of measured electrical resistances should be developed by measuring and analyzing electrical resistance from at least 30-40 trees of the same species with that tree. All the factors, especially tree species, diameter of the stem, and temperature, which can altered the electrical resistance of trees, should be taken into consideration in the development of the equation. If the standard equation is developed for old-giant trees that we should conserve, it will be very useful. In addition, periodical and continued measuring of a certain tree will help to determine the condition of the tree by comparing the measurement with accumulated data of the tree. Measuring electrical resistance of wood might not require the standard equation. But it also needs to check electrical resistance of sound wood of the same tree species. If the stems that should be examined is thicker than 40cm, it is better to use the ultrasound measurement combined to Shigometer.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.