• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.648-657
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• 2021

This study was conducted to estimate the volume growth by forest type and major species using the national forest resource inventory and to predict the final age of maturity by deriving the mean annual increment (MAI) and the current annual increment (CAI). We estimated the volume growth using the Chapman-Richards model. In the volume estimation equations by forest type, coniferous forests exhibited the highest growth. According to the estimation formula for each major species, Larix kaempferi will grow the highest among coniferous tree species and Quercus mongolica among broad-leaved tree species. And these estimation formulas showed that the fitness index was generally low, such as 0.32 for L. kaempferi and 0.21 for Quercus variabilis. In the analysis of residual amount, which indicates the applicability of the volume estimation formula, the estimates of the estimation formula tended to be underestimated in about 30 years or more, but most of the residuals were evenly distributed around zero. Therefore, these estimation formulas have no difficulty estimating the volume of actual forest species in Korea. The maximum age attained by calculating MAI was 34 years for P. densiflora, 35 years for L. kaempferi, and 31 years for P. rigida among coniferous tree species. In broad-leaved tree species, we discovered that the maximum age was 32 years for Q. variabilis, 30 years for Q. acutissima, and 29 years for Q. mongolica. We calculated MAI and CAI to detect the point at which these two curves intersected. This point was defined by the maximum volume harvesting age. These results revealed no significant difference between the current standard cutting age in public and private forests recommended by the Korea Forest Service, supporting the reliability of forestry policy data.

• Land and Housing Review
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• v.12 no.2
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• pp.47-59
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• 2021

This study aims to review the trends of the population outflows in the metropolitan area of Busan and to investigate the factors that affect population out-migration to the Seoul metropolitan area. The following variables are considered for analysis: traditional population movement variables and quality of life variables, such as population, society, employment, housing, culture, safety, medical care, greenery, education, and childcare. The 'domestic population movement data', provided by the MDIS of the National Statistical Office, was used for this research. Out of the total of 57 million population movement data in the period 2012 - 2017, population outmigration from Busan to the Seoul metropolitan area was extracted. Independent variables were drawn from public data sources in accordance with the temporal and spatial settings of the study. The multiple linear regression model was specified based on the dataset, and the fit of the model was measured by the p-value, and the values of Adjusted R2, Durbin-Watson analysis, and F-statistics. The results of the analysis showed that the variables that have a significant effect on population movement from Busan to the Seoul metropolitan area were as follows: 'single-person households', 'the elderly population', 'the total birth rate', 'the number of companies', 'the number of employees', 'the housing sales price index', 'cultural facilities', and 'the number of students per teacher'. More positive (+) influences of the population out-movement were observed in areas with higher numbers of single-person households, lowers proportions of the elderly, lower numbers of businesses, higher numbers of employees, higher numbers of housing sales, lower numbers of cultural facilities, and lower numbers of students. The findings suggest that policies should enhance the environments such as quality jobs, culture, and welfare that can retain young people within Busan. Improvements in the quality of life and job creation are critical factors that can mitigate the outflows of the Busan residents to the Seoul metropolitan area.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.175-190
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• 2018

Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.283-302
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• 2022

Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM₁₀ levels of 88-98 ㎍ m^-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM₁₀ aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM₁₀ measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM₁₀ aerosol transport in Korea. Regional PM₁₀ transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM₁₀ in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Asia Marketing Journal
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• v.14 no.1
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• pp.25-51
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• 2012

Researches about the relationship between SST(Self Service Technology) and TRI(Technology Readiness Index) have been carried out after TRI was developed by Parasuraman and his colleagues(2000). We hypothesize Consumer Readiness can also influence consumer's motivation, attitude, and intent to use SST. Currently, there has been no research on this subject. In this study, we investigated the relationship between TR, Consumer Readiness and SST Core Attitudinal Model which Dabholkar & Bagozzi(1994) proposed. The researchers also investigated moderating effects of consumer traits and situational factors to verify the acceptance of such forms of service delivery by all kinds of consumers and under different situational contexts. Self consciousness, the need for interaction with an employee, and the technology anxiety were used as consumer trait variables. Perceived waiting time and perceived crowding were used as situational variables. 380 questionnaires were distributed to a sample group of people in their 20's and 30's, and the data were analyzed with structural equation model using AMOS 18.0 program. All of Cronbach's alpha values representing reliabilities were satisfactory. The values of Composite Reliability(CR) and Average Variance Extracted(AVE) also showed the above criteria, thus providing evidence of convergent validity. To confirm discriminant validity among the constructs, confirmatory factor analysis and correlations among all the variables were examined. The results were satisfactory. The results of this study are summarized as follows. 1. Optimism and innovativeness of TR partially influenced the motivation to use SST. People who tend to be optimistic use SST because of ease of use and fun. The innovative however, usually use SST due to its performance. However, consumer readiness of role clarity, ability and self-efficacy influence all the components of motivation to use SST, ease of use, performance and fun. The relative effect of consumer readiness on the motivation to use SST was much stronger and more significant than that of TR. No other previous studies have examined the effects of Consumer Readiness on SST usage motivation, attitude and intention. It is academically meaningful that the researchers verified that Consumer Readiness is the important precedent construct influencing the self service technology core Attitudinal Model. Our findings suggest that marketers should consider fun and ease of use attributes to promote the use of self service technology. In addition, the SST usage frequency will rise rapidly when role clarity, ability, and self-efficacy which anybody can easily handle SST is assured. If the SST usage rate is increased, waiting times for customers could be decreased. Shorter waiting time could lead to higher customer satisfaction. It may also result in making a long-term profit owing to the reduced number of employees. Thus, presentation of using SST by employees or videos showing how to use it will promote the usage attitude and intent. 2. In SST core attitudinal model, performance and fun factors among SST usage motivation affected attitudes of using SST. The attitude of using SST highly influenced intent to use SST. This result is consistent with previous researches that dealt with the relationship between motivation, attitude and intention. Expectation of using SST could result in good performance just like the effect of ordering menu to service employees and to have fun since fun during its use could promote more SST usage rate. 3. In the relationship among motivation, attitude and intent in SST core attitudinal model, the moderating effect of consumer traits(self-consciousness, need for interaction with service employees and technology anxiety) and situational factors(perceived crowding and perceived waiting time) were tested. The results also supported the hypothesized moderating effects except perceived crowding. The highly self-conscious tended to form attitudes to use SST because of its fun compared to those who were less self-conscious because of its performance. People who had a high need for interaction with service employees tended to use SST for its performance. This result indicates that if ordering results are assured, SST is easily accessible to even consumers who have a high need for interaction with a service employee. When SST is easy to use, attitudes strengthen intent among people who had a high level of anxiety of technology. People who had low technology anxiety formed attitudes to use SST because of its performance. Service firms must ensure their self service technology is designed to be easy to use for those who have a high level of technology anxiety. Shorter perceived waiting times strengthened the attitude to use self service technology because of its fun. If the fun aspect is assured, people willing to use self service technology even perceive waiting time to be shorter than it actually is. Greater perceived waiting times form higher level of intent to use self service technology than those of shorter perceived waiting times. This implies that people view self service technology as a faster alternative to ordering service employees. The fun aspect of self service technology will attract a higher rate of usage for self service technology. 4. It has been proven that ease of use, performance and fun aspects are very important factors in motivation to form attitudes and intent to use self service technology regardless of the amount of perceived waiting time, self-consciousness, need for interaction with service employees, and technology anxiety. Service firms must consider these motivation aspects(ease of use, performance and fun)strongly in their promotion to use self service technology. Ease of use, assuring absolute performance compared to interaction with service employees', and adding a fun aspect will positively strengthen consumers' attitudes and intent to use self service technology. Summarizing the moderating effects, fun is the most valuable factor triggering SST usage attitude and intention. Therefore, designing self service technology to be fun will be the key to its success. This study focused on the touch screen self service technology in fast food restaurant. Although it has its limits due to the fact that it is hard to generalize the results to any other self service technology, the conceptual framework of this study can be applied to future research of any other service site.

• Korean Security Journal
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• no.48
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• pp.9-33
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• 2016

The purpose of the present study was to find out cause-and-effect relationship between job requirements and job resources, with job burnout as a mediator variable, and the effects of these variables on organizational effectiveness. The population in the present study was private security guards employed by 13 private security companies in Seoul and Gyeonggi-do areas, and a survey was conducted on 500 security guards selected using purposive sampling technique. Out of 460 questionnaires distributed, 429 responses, excluding 31 outliers or insincere responses, were used for data analysis. For analysis, data were coded and entered into SPSS 18.0 and AMOS 18.0, which were used to analyze the data. Descriptive analyses were performed to find out sociodemographic characteristics of the respondents. The exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to test the validity of the measurement tool, and the Cronbach's Alpha coefficients were calculated to test the reliability. To find out the significance of relationships among variables, Pearson's correlation analysis was performed. Covariance Structure Analysis (CSA) was performed to test the relationship among latent factors of a model for job requirements, job resources, job burnout, and organizational effectiveness of the private security guards, and the fitness of the model analyzed with CSA was determined by the goodness-of-fit index ($x^2$, df, p, RMR, GFI, CFI, TLI, RMSEA). The level of significance was set at .05, and the following results were obtained. First, even though the effect of job requirements on job burnout was not statistically significant, it had a positive influence overall, and this result can be considered such that the higher the perception of job requirements by the member of the organization, the higher the perception of job burnout. Second, the influence of job resources on job burnout was negative, which can be considered that the higher the perception of job resources, the lower the perception of job burnout. Third, even though the influence of job requirements on organizational effectiveness was statistically nonsignificant, it had a negative influence overall, and this result can be considered that the higher the perception of job requirements, the lower the perception of organizational effectiveness. Fourth, job resources had a positive influence on organizational effectiveness, and it can be considered that the higher the perception of job resources, the higher the perception of organizational effectiveness. Fifth, the results of the analysis between job burnout and organizational effectiveness revealed that, even though the influence of job burnout on organizational effectiveness was statistically nonsignificant, it had partial negative influences on sublevels of organizational effectiveness, and this may suggest that the higher the perception of job burnout by the organization members, the lower the organizational effectiveness. Sixth, the analysis of mediating role in the relationship between job requirements and organizational effectiveness, job burnout was taking partial mediating role between job requirements and organizational effectiveness. These results suggest that reducing job burnout by managing job requirements, organizational effectiveness that leads to job satisfaction, organizational commitment, and turnover intention can be maximized. Seventh, the analysis of mediating role in the relationship among job requirements, job resources, and organizational effectiveness, job burnout was assuming a partial mediating role in the relationships among job requirements, job resources, and organizational effectiveness. These results suggest that organizational effectiveness can be maximized by either lowering job requirements or burnout management through reorganizing job resources.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in