• Informatization Policy
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• v.28 no.4
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• pp.76-92
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• 2021

The value of personal information is increasing with the digital transformation of the 4th Industrial Revolution. The purpose of this study is to analyze the efficiency of personal information protection efforts of 2,000 private companies. It uses a stochastic frontier approach (SFA), a parametric estimation method that measures the absolute efficiency of protective activities. In particular, the personal information activity index is used as an output variable for efficiency analysis, with the personal information protection budget and number of personnel utilized as input variables. As a result of the analysis, efficiency is found to range from a minimum of 0.466 to a maximum of 0.949, and overall average efficiency is 0.818 (81.8%). The main causes of inefficiency include non-fulfillment of personal information management measures, lack of system for promoting personal information protection education, and non-fulfillment of obligations related to CCTV. Policy support is needed to implement safety measures and perform personal information encryption, especially customized support for small and medium-sized enterprises.

• Land and Housing Review
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• v.13 no.3
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• pp.125-140
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• 2022

Road Deposited Sediment (RDS) is the solids formed from the wear of road, wear of vehicles, exhausts, and the input of the emissions from various sources out of the roads. RDS is seriously polluted by organic matter, nutrients, and metals. RDS plays an important role as the sink and the transport medium of the associated pollutants because RDS can be carried to the adjacent water system via stormwater runoff. In this regard, the heavy metals in RDS were investigated based on the publications. The contents of the metals in RDS were highly variable. The concentration of Cr, Ni, Cu, Fe, Zn, As, Cd, and Pb in urban RDS in various regions was in a range of 3.16-3,410, 1.15-1,382, 20.2-9,069, 2,980-124,853, 81-2,550, 2.3-214, 0.19-21.3, and 15.21-1,125 mg/kg, respectively. The anthropogenic enrichment of the metals in RDS was confirmed by the high concentration of Cu, Zn, Cd, and Pb. The contents of the metals were higher in industrial and traffic areas than in residential areas, while they were generally increased with decreasing particle size. It is believed that this study's results would contribute to quantifying the metals' load via RDS and establishing control strategies.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.781-791
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• 2022

It is crucial to provide forest fire risk forecast information to minimize forest fire-related losses. In this research, forecast models of forest fire risk at a mid-range (with lead times up to 7 days) scale were developed considering past, present and future conditions (i.e., forest fire risk, drought, and weather) through random forest machine learning over South Korea. The models were developed using weather forecast data from the Global Data Assessment and Prediction System, historical and current Fire Risk Index (FRI) information, and environmental factors (i.e., elevation, forest fire hazard index, and drought index). Three schemes were examined: scheme 1 using historical values of FRI and drought index, scheme 2 using historical values of FRI only, and scheme 3 using the temporal patterns of FRI and drought index. The models showed high accuracy (Pearson correlation coefficient >0.8, relative root mean square error <10%), regardless of the lead times, resulting in a good agreement with actual forest fire events. The use of the historical FRI itself as an input variable rather than the trend of the historical FRI produced more accurate results, regardless of the drought index used.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.71-86
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• 2022

The water quality index (WQI) has been widely used to evaluate marine water quality. The WQI in Korea is categorized into five classes by marine environmental standards. But, the WQI calculation on huge datasets is a very complex and time-consuming process. In this regard, the current study proposed machine learning (ML) based models to predict WQI class by using water quality datasets. Sihwa Lake, one of specially-managed coastal zone, was selected as a modeling site. In this study, adaptive boosting (AdaBoost) and tree-based pipeline optimization (TPOT) algorithms were used to train models and each model performance was evaluated by metrics (accuracy, precision, F1, and Log loss) on classification. Before training, the feature importance and sensitivity analysis were conducted to find out the best input combination for each algorithm. The results proved that the bottom dissolved oxygen (DO_Bot) was the most important variable affecting model performance. Conversely, surface dissolved inorganic nitrogen (DIN_Sur) and dissolved inorganic phosphorus (DIP_Sur) had weaker effects on the prediction of WQI class. In addition, the performance varied over features including stations, seasons, and WQI classes by comparing spatio-temporal and class sensitivities of each best model. In conclusion, the modeling results showed that the TPOT algorithm has better performance rather than the AdaBoost algorithm without considering feature selection. Moreover, the WQI class for unknown water quality datasets could be surely predicted using the TPOT model trained with satisfactory training datasets.

• Journal of the Korean Wood Science and Technology
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• v.31 no.5
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• pp.72-79
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• 2003

In reliability based design(RBD) method, the distribution characteristics of mechanical properties of material are basic input variable. Therefore, distribution type and parameters of mechanical properties should be determined accurately. Until now, the properties were derived from tests with small, clear specimens. However, the test conditions should emulate as nearly as possible the way in which the timber would be used in practice and the test results should, as closely as possible, reflect the structural end use conditions to which the timber products would be subjected. In this study, structural timbers (38mm by 140mm, 3.0m long) were graded by visual assessment of growth characteristics and defects. And then bending tests were conducted on 498 structural size timbers. For each grade, the distribution type and the parameters of mechanical properties were determined for each grade. For the determination of best-fit distribution type, comparing of square error between distribution types and KS test were conducted. Best-fit distribution type of bending strength(MOR) is weibull distribution for all grade. In case of MOE, normal distribution is best-fit.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.135-140
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• 2022

In addition to the stack that directly generates electricity by the reaction of hydrogen and oxygen, the fuel cell power generation system has a reformer that generates hydrogen from various fuels such as methanol and natural gas. It also consists of a power converter that converts the DC voltage generated in the stack into a stable AC voltage. The fuel cell output of such a system is direct current, and in order to be used at home, an inverter device that converts it into alternating current through a power converter is required. In addition, a DC-DC step-up converter is used to boost the fuel cell voltage to about 30~70V, which is the inverter operating voltage, to about 380V. The DC-DC step-up converter is a DC voltage variable device that exists between the fuel cell output and the inverter. Accordingly, since a constant output voltage of the converter is generated in response to a change in the output voltage of the fuel cell, the inverter can receive constant power regardless of the voltage change of the fuel cell. Therefore, in this paper, we discuss the detailed hardware design of the full-bridge converter, which is the main power source of the inverter that receives the fuel cell output voltage (30~70V) as an input and is applied to the grid among the members of the fuel cell power generation system.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.135-140
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• 2022

A study to estimate the appropriate size for the quota of civil servants during the period of change of government is required. Therefore, in this study, we would like to introduce a study that uses DEA to estimate the appropriate size of public officials. The department of a public institution is DMU, and the number of employees in each department is applied as an input variable, and the number of electronic approval production documents and the number of electronic approval expenditures are applied as output variables. MaxDEA 8 was used as an analysis program for this purpose. As a result of the analysis, when the efficiency level was 1.00 (100%), 3 out of 14 departments showed the optimal level by satisfying the efficiency, and 10 of the remaining departments scored 0.50 (50%) with a score of 0.50 (50%), confirmed to be relatively inefficient. In other words, it was confirmed that most departments had inefficient surplus staff. As an additional analysis, we calculated the number of possible staff reductions using the efficiency level. Using this, it is expected that the field of manpower reduction can be discovered in advance through an analysis of manpower efficiency by department, and based on this, it can be used to relocate manpower by department according to future response strategies.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.457-467
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• 2016

Understanding professional baseball fans' expenditure is expected to provide fundamental marketing information that help increase each team's marketing profits and values and produce a better economic impact on its community. In this regard, this study employed a survey method with a total of 372 residents located in Changwon. A questionnaire included factors such as demographics, consumption patterns and perceived socio-psychic effect(PSE), all of which were derived from literature review. A binary logistic regression was modeled with a dichotomous dependent variable, expenditure(30,000 won more or less). The following were input in the model as the independent variables in order to see the relationships; gender, marriage, education, occupation, income, location, age, leisure type, distance, companion, transportation, interest, and PSE. The results of the logistic regression analysis are as follows. Overall, the model was statistically significant, χ²(21, N=372)=59.159, p=.000. Cox and Snell R² was reported as .147 and .200 respectively. So, the model accounted for between 14.7% and 20.0% of the variation in expenditure. Among the independent variables, income, location, companion, and PSE were found to be the significant factors to expenditure. For income, subjects with 2 million won less of income, compared to those with 4 million won more, were .38 times less likely to pay the money of 30,000 won more. For location, subjects in Masan, compared to those in Jinhae, were 3.49 times more likely to pay 30,000 won more. Subjects in Changwon, compared to those in Jinhae, were 3.05 times more likely to pay 30,000 won more. For companion, people visiting the stadium alone, compared to those with friends/colleague, were .36 times less likely to pay 30,000 won more. For PSE, the odds of 30,000 won more paid increased by 1.37 times with one-unit increase in PSE.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.