• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.13-21
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• 2014

This study generated regression models to quantify storage and annual uptake of carbon from five native landscape tree species through a direct harvesting method, and established essential information to estimate carbon reduction effects from urban greenspaces. Tree species for the study included the Chionanthus retusus, Prunus armeniaca, Abies holophylla, Cornus officinalis, and Taxus cuspidata, which are usually planted in cities of middle Korea, but for which no information on carbon reduction is available. Ten tree individuals for each species were sampled reflecting various stem diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute total carbon storage per tree. The annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at breast height or ground level. Regression models were developed using diameter at breast height (dbh) or ground level (dg) as an independent variable to easily estimate storage and annual uptake of carbon per tree for each species. All the regression models showed high fitness with $r^2$ values of 0.92~0.99. Storage and annual uptake of carbon from a tree with dbh of 10 cm were greatest with C. retusus (20.0 kg and 5.9 kg/yr, respectively), followed by P. armeniaca (17.5 kg and 4.5 kg/yr) and A. holophylla (13.2kg and 1.8 kg/yr) in order. A C. officinalis tree and T. cuspidata tree with dg of 10 cm stored 9.3 and 6.3 kg of carbon and annually sequestered 3.2 and 0.6 kg, respectively. The above-mentioned carbon storage equaled the amount of carbon emitted from gasoline consumption of about 23~35 L for C. retusus, P. armeniaca, and A. holophylla, and 11~16 L for C. officinalis and T. cuspidata. A tree with the diameter size of 10 cm annually offset carbon emissions from gasoline use of about 6~10 L for C. retusus, P. armeniaca, and C. officinalis, and 1~3 L for A. holophylla and T. cuspidata. The study breaks new ground to easily quantify biomass and carbon reduction for the tree species by overcoming difficulties in direct cutting and root digging of urban landscape trees.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.589-597
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• 2016

In this study, we investigated the use of satellite-derived flow (SDF) signals and a data-based model for the estimation of outflow for the river reach where in situ measurements are either completely unavailable or are difficult to access for hydraulic and hydrology analysis such as the upper basin of Imjin River. It has been demonstrated by many studies that the SDF signals can be used as the river width estimates and the correlation between SDF signals and river width is related to the shape of cross sections. To extract the nonlinear relationship between SDF signals and river outflow, Artificial Neural Network (ANN) model with SDF signals as its inputs were applied for the computation of flow discharge at Imjin Bridge located in Imjin River. 15 pixels were considered to extract SDF signals and Partial Mutual Information (PMI) algorithm was applied to identify the most relevant input variables among 150 candidate SDF signals (including 0~10 day lagged observations). The estimated discharges by ANN model were compared with the measured ones at Imjin Bridge gauging station and correlation coefficients of the training and validation were 0.86 and 0.72, respectively. It was found that if the 1 day previous discharge at Imjin bridge is considered as an input variable for ANN model, the correlation coefficients were improved to 0.90 and 0.83, respectively. Based on the results in this study, SDF signals along with some local measured data can play an useful role in river flow estimation and especially in flood forecasting for data-scarce regions as it can simulate the peak discharge and peak time of flood events with satisfactory accuracy.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Management & Information Systems Review
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• v.36 no.2
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• pp.157-185
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• 2017

This study was carried out with the attention that the concept of entrepreneurial orientation has been applied at various levels of CEO, employee, management, and organization as a whole. The differences between these concepts were examined by discriminant validity and convergence validity, and the causal relationship between these concepts and performance was analyzed. A total of 96 questionnaires were collected and analyzed. The results show that CEO's entrepreneurial orientation, employee's entrepreneurial orientation, manager's entrepreneurial orientation and organizational entrepreneurial orientation have convergent validity and discriminant validity, and that these variables have different effects on the firm 's innovation performance and financial performance. In the analysis of the mediating effect, when the variables of all levels were put into a single variable, the innovation performance mediates between the entrepreneurial orientation and the financial performance in all variables. However, when all variables are applied simultaneously, innovation performance has mediating effect only on the relationship between organizational entrepreneurship orientation and financial performance. This shows that there is a conceptual difference according to applied level. As a result of the analysis of the causal relationship by the application level of entrepreneurial orientation, it is found that causality is formed among the entrepreneurial orientation variables. In particular, CEO's entrepreneurial orientation influences employee's entrepreneurial orientation, manager's entrepreneurial orientation, and organization's entrepreneurial orientation, and again, employee's entrepreneurial orientation and managerial entrepreneurial orientation form a causal relationship that influences organization's entrepreneurial orientation. In the relationship between innovation performance and financial performance, CEO's entrepreneurial orientation, organization's entrepreneurial orientation, and manager's entrepreneurial orientation are influencing innovation performance, and the only variables influencing financial performance are organization's entrepreneurial orientation. In conclusion, the limitations of the study and its future direction are presented.

• Korean journal of applied entomology
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• v.51 no.4
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• pp.431-438
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• 2012

The developmental time of the nymphs of Myzus persicae was studied in the laboratory (six constant temperatures from 15 to $30^{\circ}C$ with 50~60% RH, and a photoperiod of 14L:10D) and in a green-pepper plastic house. Mortality of M. persicae in laboratory was high in the first(6.7~13.3%) and second instar nymphs(6.7%) at low temperatures and high in the third (17.8%) and fourth instar nymphs(17.8%) at high temperatures. Mortality was 66.7% at $33^{\circ}C$ in laboratory and $26.7^{\circ}C$ in plastic house. The total developmental time was the longest at $14.6^{\circ}C$ (14.4 days) and shortest at $26.7^{\circ}C$ (6.0 days) in plastic house. The lower threshold temperature of the total nymphal stage was $3.0^{\circ}C$ in laboratory. The thermal constant required for nymphal stage was 111.1DD. The relationship between developmental rate and temperature was fitted nonlinear model by Logan-6 which has the lowest value on Akaike information criterion (AIC) and Bayesian information criterion (BIC). The distribution of completion of each developmental stage was well described by the 3-parameter Weibull function ($r^2=0.95{\sim}0.97$). This model accurately described the predicted and observed occurrences. Thus the model is considered to be good for use in predicting the optimal spray time for Myzus persicae.

• Management & Information Systems Review
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• v.36 no.5
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• pp.61-83
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• 2017

The purpose of this study is to investigate the mediating effects of psychological empowerment between participative leadership and creative behavior. Especially, it aims to analyze the unidimension and multidimension of psychological empowerment in an integrated manner, and to suggest effective practice of participative leadership together with theoretical and methodological implications. In this study, the dependent variable was measured separately with time lag as a method to solve the common method bias that can be shown by the self-report type survey method, and positive emotions and negative emotions expressing emotional states in job situations were employed as control variables along with rank. A total of 283 questionnaires were collected from employees who work for companies in various industries with more than 300 domestic employees. SPSS PROCESS macro program('model 4') was used for statistical analysis. Results, First, the full mediation effect of psychological empowerment(unidimension) was confirmed in the relationship between participative leadership and creative behavior. Second, the analysis of the multidimension of psychological empowerment revealed the full mediating effect of meaning, self-determination, and impact, and the mediating effect of competence was not significant. Third, as a result of comparing the mediating effects of unidimension of psychological empowerment and the mediating effects of multidimension, the magnitude of mediating effect of unidimension was found to be much greater than mediating effect of multidimension. And The magnitudes of the three multidimensional mediating effects were similar. This is a case in which the motivational model of participative leadership revealed in the overseas study is proven in the domestic management environment and is significant in that it is the basis of future research. Based on the results of the empirical studies, the implications and limitations of the study and future research directions are presented.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• 한국노년학
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• v.38 no.3
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• pp.551-567
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• 2018

Demographic and socio-structural information is useful to identify potential welfare recipients who are in need of disease-prevention and intervention services. Thus, the present study aims to explore the differences in grip strength among middle and old-aged adults by living conditions and by living area. The 5th wave data of Korean Longitudinal Study of Aging was utilized. The dependent variable was grip strength, and the independent variables were living alone (living alone or not) and living area (city or non-city). Covariates were age, education, log-transformed household income, spouse existence, body mass index, self-rated health conditions, depressive symptoms, cognitive function, smoking, regular exercise, frequency of meeting with friends, and the number of social participation. Regression analysis was performed for middle-aged men, middle-aged women, old-aged men, and old-aged women, respectively. ANOVA and Chi-test were additionally used to specifically discuss significant results. Cross-sectional weight was applied to all analyses. According to the results, living alone and living area did not have significant effects on grip strength among middle-aged men, old-aged men, and old-aged women. In middle-aged women, however, living alone and living area were significantly associated with grip strength. To be specific, middle-aged women who lived alone in rural areas had the lowest grip strength compared to other middle-aged women. Additional analysis showed that middle-aged women who lived alone in rural areas had risk factors, such as low education level, low income, or high depressive symptoms. It implies that middle-aged women living alone in rural areas may have physical health risks, so they might be in need of disease prevention. This study is meaningful in that it can provide reliable information on the latent welfare recipients by using representative panel data and applying weight values.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.135-149
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• 2019

Today, a growing number of companies are in trouble because leaders are lack of authentic leadership. Small and midium sized companies have the same issue. To correct the issue, there must be a real change in the relationship between managers and employees of the company as well as outside the company. In 21st century, authentic leadership is required. However, the research about determinants of change supportive behavior is not sufficient. Therefore, the purpose of this study is how manager's transformational leadership and authentic leadership affects change supportive behavior of employees in small and midium sized companies. The study also has to prove the role of positive psychological capital as a parameter. Data were collected from 424 employees working for small and midium sized companies in metropolitan area around Seoul and Gyeonggi. The data were analyzed using statistical package SPSS ver.21.0 and AMOS ver.18.0. Based on the research, First, the transformational leadership does not affect the change supportive behavior. However, authentic leadership affects the change supportive behavior. Also, positive psychological capital playes a role as parameter when transformational and authentic leadership, that are independent variable, affect change supportive behavior. On the other hand, the research shows that authentic leadership has more influence than transformational leadership on positive psychological capital. Transformational leadership without genuine attitude cannot affect change support behavior of employees in small and medium sized companies. Therefore, to affect change supportive behavior of employee, authentic leadership with genuine mind is required. After discussing the conclusions and implications of this study. the direction of the study for the follow - up study was suggested.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.99-112
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• 2021

This study was performed to predict spatial change of future forestland area in South Korea at regional level for supporting forest-related plans established by local governments. In the study, land use was classified to three types which are forestland, agricultural land, and urban and other lands. A logistic regression model was developed using transitional interaction between each land use type and topographical factors, land use restriction factors, socioeconomic indices, and development infrastructures. In this model, change probability from a target land use type to other land use types was estimated using raster dataset(30m×30m) for each variable. With priority order map based on the probability of land use change, the total annual amount of land use change was allocated to the cells in the order of the highest transition potential for the spatial analysis. In results, it was found that slope degree and slope standard value by the local government were the main factors affecting the probability of change from forestland to urban and other land. Also, forestland was more likely to change to urban and other land in the conditions of a more gentle slope, lower slope criterion allowed to developed, and higher land price and population density. Consequently, it was predicted that forestland area would decrease by 2027 due to the change from forestland to urban and others, especially in metropolitan and major cities, and that forestland area would increase between 2028 and 2050 in the most local provincial cities except Seoul, Gyeonggi-do, and Jeju Island due to locality extinction with decline in population. Thus, local government is required to set an adequate forestland use criterion for balanced development, reasonable use and conservation, and to establish the regional forest strategies and policies considering the future land use change trends.