• Korean Journal of Ecology and Environment
• /
• v.55 no.1
• /
• pp.60-75
• /
• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Korean Journal of School Psychology
• /
• v.16 no.3
• /
• pp.433-451
• /
• 2019

This study aimed to develop and validate the Classroom Problem Behavior Scale - Elementary School Version (CPBS-E) measure which is unique to classroom problem behavior exhibited by Korean elementary school students. The focus was on developing a universal screening instrument designed to identify and provide intervention to students who are at-risk for severe social-emotional and behavioral problems. Items were initially drawn from the literature, interviews with elementary school teachers, common office discipline referral measures used in U.S. elementary schools, penalty point systems used in Korean schools, 'Green Mileage', and the Inventory of Emotional and Behavioral Traits. The content validity of the initially developed items was assessed by six classroom and subject teachers, which resulted in the development of a preliminary scale consisting of 63 two-dimensional items (i.e., Within Classroom Problem Behavior and Outside of Classroom Problem Behavior), each of which consisted of 3 to 4 factors. The Within Classroom Problem Behavior dimension consisted of 4 subscales (not being prepared for class, class disruption, aggression, and withdrawn) and the Outside of Classroom Problem Behavior dimension consisted of 3 subscales (rule-violation, aggression, and withdrawn). The CPBS-E was pilot tested on a sample of 154 elementary school students, which resulted in reducing the scale to 23 items. Following the scale revision, the CPBS-E was validated on a sample population of 209 elementary school students. The validation results indicated that the two-dimensional CPBS-E scale of classroom problem behavior was a reliable and valid measure. The test-retest reliability was stable at above .80 in most of the subscales. The CPBS-E measure demonstrated high internal consistency of .76-.94. In examining the criterion validity, the scale's correlation with the Teacher Observation of Classroom Adaptation-Checklist (TOCA-C) was high and the aggression and withdrawn subscales of the CPBS-E demonstrated high correlations with externalization and internalization, respectively, of the Child Behavior Checklist - Teacher Report Form CBCL-TRF). In addition, the factor structure of the CPBS-E scale was examined using the structural equation model and found to be acceptable. The results are discussed in relation to implications, contributions to the field, and limitations.

• Korean Journal of Environmental Biology
• /
• v.41 no.3
• /
• pp.179-192
• /
• 2023

In this study, changes in the microbial ecosystem of the Yeongheungdo island coastal waters were investigated for five years to collect basic data. To evaluate the influence of distance from the coast on the microbial ecosystem, four sites, coastal Site (S1) and 0.75, 1.5, and 3 km away from the coast, were set up and the changes in physicochemical and biological factors were monitored. The results showed seasonal changes in water temperature, dissolved oxygen, salinity, and pH but with no significant differences between sites. For nutrients, the concentration of dissolved inorganic nitrogen increased from 6.4 μM in April-June to 16.4 μM in July-November, while that of phosphorus and silicon phosphate increased from 0.4 μM and 2.5 μM in April-June to 1.1 μM and 12.0 μM in July-November, respectively. Notably, phosphorus phosphate concentrations were lower in 2014-2015 (up to 0.2 μM) compared to 2016-2018 (up to 2.2 μM), indicating phosphorus limitation during this period. However, there were no differences in nutrients with distance from the coast, indicating that there was no effect of distance on nutrients. Phytoplankton (average 511 cells mL^-1) showed relatively high biomass (up to 3,370 cells mL^-1) in 2014-2015 when phosphorus phosphate was limited. Notably, at that time, the concentration of dissolved organic carbon was not high, with concentrations ranging from 1.1-2.3 mg L^-1. However, no significant differences in biological factors were observed between the sites. Although this study revealed that there was no disturbance of the ecosystem, further research and more basic data on the microecosystem are necessary to understand the ecosystem of the Incheon.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.1-33
• /
• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Korean Journal of Weed Science
• /
• v.2 no.2
• /
• pp.75-113
• /
• 1982

Studies were carried out 1) to define the shape and size of sampling quadrat and its number of observations for weed experiments, 2) to characterize the growth and community of major summer weeds under upland condition and 3) to investigate the factors influencing competition between weeds and soybeans under weed-free and weedy conditions in early and late season cultures. No significant difference was noted among different shapes of quadrat (regular, rectangular, band, and circular) in the sampling efficiency of weeds. The results also suggested that the minimum size of quadrat was 0.25$m^2$ and the minimum number of replication was 2 times per plot. The major dominant weeds were about 10 species in the experimental field and the total number of weeds was in the range of 70 - 1,600 plants per $m^2$. Among the weeds Digitaria sanguinalis and Portulaca oleracea were the most dominant species. Growth amount and reproduction capability were also measured by weed species. Five different weed communities were identified in the field. The degree of dispersion by weed species and association among weeds were investigated. Intra-(within soybeans) and inter-specific (between soybeans and weeds) competition were studied in early and late season cultures of soybeans. The average yield of soybeans per plant was significantly decreased in both season cultures due to intra-specific competition as the planting density of soybeans increased, On the other hand, the average yield of soybeans per l0a was proportionally increased to the increase of planting density and the rate of its increase was more significant under weedy than weed-free condition. Most of the agronomic characteristics of soybeans were affected by weeds and its degree was greater in sparse planting than in dense planting and in early season than in late-season culture. Digitaria sanguinalis was the most competitive to soybeans in early season and both of Digitaria sanguinalis and Portulaca oleracea affected primarily the growth of soybeans in late season with about the same competitiveness. The occurrence of weeds was significantly decreased in early season and slightly decreased in late-season by dense planting of soybeans. The total growth amount of weeds was also considerably decreased by increase of soybean planting density both in early- and late-season cultures. The occurrence of Digitaria sanguinalis which was the most dominant in both seasons, and its growth amount was significantly decreased as the planting density of soybean was increased. On the other hand, the occurrence of Portulaca oleracea which was only dominant in late-season culture did not show significant response to the planting density of soybeans.

• Korean Journal of Environmental Biology
• /
• v.22
• /
• pp.54-62
• /
• 2004

We examined the impacts of anthyopogenic pollutant (benzo〔a〕pyrene) on the growth and photosynthesis of five marine phytoplankton species (Skeletonema costatum, Heterosigma akashiwo, Prorocentrum dentatum, P. minimum, Aknshiwo sanguinea), which are dominant in Korean coastal water. After the 72 h exposure to benzo〔a〕pyrene, the dramatic decrease in cell numbers was observed in the range of 1 to 10 $\mu\textrm{g}$ L$^{-1}$ for S. costatum, P. minimum, P. dentatum, whereas for A. sanguinea and H. akashiwo at the low concentrations 0.1 to 1 $\mu\textrm{g}$ L$^{-1}$ . Among the 5 phytoplankton species, the highest growth inhibition concentration ($IC_{50}$/) was 6.20 $\mu\textrm{g}$ L$^{-1}$ for P. minimum, followed by 2.14 $\mu\textrm{g}$ L$^{-1}$ for P. dentatum, 1.68 $\mu\textrm{g}$ L$^{-1}$ for S. costatum, 0.74 $\mu\textrm{g}$ L$^{-1}$ for H. akashiwo, 0.10 $\mu\textrm{g}$ L$^{-1}$ for A. sanguinea. The five species exposed to the low concentration of 1 $\mu\textrm{g}$ L$^{-1}$ were recovered after transferring to new media, but the species exposed to the high concentrations of 10 and 100 $\mu\textrm{g}$ L$^{-1}$ were not recovered, with the exception of P. minimum. Those results indicate that the thecate dinoflagellate P. minimum is most tolerant to the chemical and the athecate dinoflagellate A. sanguinea is not. Geneyally, the cell-specific photosynthetic capacity of H. akashiwo exposed to the low concentrations of 0.1 and 1 $\mu\textrm{g}$ L$^{-1}$ was higher than that of the cells in the control, whereas the cells exposed to the high concentrations of 5 and 10 $\mu\textrm{g}$ L$^{-1}$ showed the negligible photosynthetic level by the first few days of the experiment. In the case of the cells exposed to the concentration of 5 $\mu\textrm{g}$ L$^{-1}$ , after 12 days of the experiment the photosynthetic capacity was increased toward the end of the experiment. This indicates that H. akashiwo may utilize the benzo〔a〕pyrene as a carton source for its growth when exposed to low concentrations. Results suggest that anthropogenic pollutants such as benzo〔a〕pyrene may have significant influence on the succession of phytoplankton species composition and the primary production in coastal marine environments.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.91-108
• /
• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.