• Journal of Intelligence and Information Systems
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• 제26권3호
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• pp.37-50
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• 2020

Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

• Journal of Korean Society of Coastal and Ocean Engineers
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• 제31권1호
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• pp.28-39
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• 2019

In the design process of counter measures against the beach erosion, information like the main sediment transport mode and yearly net amount of longshore and cross shore transport is of great engineering value. In this rationale, we numerically analyzed the yearly sediment budget of the Mang-Bang beach which is suffering from erosion problem. For the case of cross sediment transport, Bailard's model (1981) having its roots on the Bagnold's energy model (1963) is utilized. In doing so, longshore sediment transport rate is estimated based on the assumption that longshore transport rate is determined by the available wave energy influx toward the beach. Velocity moments required for the application of Bailard's model (1981) is deduced from numerical simulation of the nonlinear shoaling process over the Mang-Bang beach of the 71 wave conditions carefully chosen from the wave records. As a wave driver, we used the consistent frequency Boussinesq Eq. by Frelich and Guza (1984). Numerical results show that contrary to the Bailard's study (1981), Irribaren NO. has non negligible influence on the velocity moments. We also proceeds to numerically simulate the yearly sediment budget of Mang-Bang beach. Numerical results show that for ${\beta}=41.6^{\circ}$, the mean orientation of Mang-Bang beach, north-westwardly moving longshore sediment is prevailing over the south-eastwardly moving sediment, the yearly amount of which is simulated to reach its maxima at $125,000m^3/m$. And the null pint where north-westwardly moving longshore sediment is balanced by the south-eastwardly moving longshore sediment is located at ${\beta}=47^{\circ}$. For the case of cross shore sediment, the sediment is gradually moving toward the shore from the April to mid October, whereas these trends are reversed by sporadically occurring energetic wind waves at the end of October and March. We also complete the littoral drift rose of the Mang-Bang beach, which shows that even though the shore line is temporarily retreated, and as a result, the orientation of Mang-Bang beach is larger than the orientation of null pont, south-eastwardly moving longshore sediment is prevailing. In a case that the orientation of Mang-Bang beach is smaller than the orientation of null pont, north-westwardly moving longshore sediment is prevailing. And these trend imply that the Mang-Bang beach is stable one, which has the self restoring capability once exposed to erosion.

• Korean Journal of Agricultural and Forest Meteorology
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• 제24권1호
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.

• Journal of Bio-Environment Control
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• 제31권4호
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• pp.401-408
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• 2022

As research on a controlled environment system based on crop growth environment sensing for sustainable production of horticultural crops and its industrial use has been important, research on how to properly utilize soil moisture sensors for outdoor cultivation is being actively conducted. This experiment was conducted to suggest the proper method of utilizing the TEROS 12, an FDR (frequency domain reflectometry) sensor, which is frequently used in industry and research fields, for each orchard soil in three regions in Korea. We collected soils from each orchard where fruit trees were grown, investigated the soil characteristics and soil water retention curve, and compared TEROS 12 sensor calibration equations to correlate the sensor output to the corresponding soil volumetric water content through linear and cubic regressions for each soil sample. The estimated value from the calibration equation provided by the manufacturer was also compared. The soil collected from all three orchards showed different soil characteristics and volumetric water content values by each soil water retention level across the soil samples. In addition, the cubic calibration equation for TEROS 12 sensor showed the highest coefficient of determination higher than 0.95, and the lowest RMSE for all soil samples. When estimating volumetric water contents from TEROS 12 sensor output using the calibration equation provided by the manufacturer, their calculated volumetric water contents were lower than the actual volumetric water contents, with the difference up to 0.09-0.17 m³·m^-3 depending on the soil samples, indicating an appropriate calibration for each soil should be preceded before FDR sensor utilization. Also, there was a difference in the range of soil volumetric water content corresponding to the soil water retention levels across the soil samples, suggesting that the soil water retention information should be required to properly interpret the volumetric water content value of the soil. Moreover, soil with a high content of sand had a relatively narrow range of volumetric water contents for irrigation, thus reducing the accuracy of an FDR sensor measurement. In conclusion, analyzing soil water retention characteristics of the target soil and the soil-specific calibration would be necessary to properly quantify the soil water status and determine their adequate irrigation point using an FDR sensor.

• Journal of Intelligence and Information Systems
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• 제28권3호
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• pp.105-117
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• 2022

This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.

• Journal of Intelligence and Information Systems
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• 제29권1호
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Clean Technology
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• 제29권3호
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• pp.193-199
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• 2023

Biomass has been used to secure renewable energy certificates (REC) in domestic and overseas coal-fired power plants. In recent years, biofuel has been diversified from traditional wood pellets to non-woody biomass. Non-woody biomass has a higher content of alkaline metals such as K and Na than wood-based biomass, resulting in a lower melting point and an increase in slagging on boiler tubes, which reduces boiler efficiency. This study analyzed the effect of kaolin, an additive commonly used to increase melting points, on biomass co-firing to coal through thermochemical equilibrium calculations. In a previous experiment on biomass co-firing to coal conducted at 80 kW_th, it was interpreted that the use of kaolin actually increased the amount of fouling. In this study, analysis showed that when kaolin was added, aluminosilicate compounds were generated due to Al₂O₃, which is abundant in coal, and mullite was formed. Thus, it was confirmed that the amount of slag increased when more kaolin was used. Further analysis was conducted by increasing the biomass co-firing rate from 0% to 100% at 10% intervals, and the results showed non-linear liquid slag generation. As a result, it was found that the least amount of liquid slag was generated when the biomass co-firing rate was between 50 and 60%. The phase diagram analysis showed that high melting point compounds such as leucite and feldspar were most abundantly generated under these conditions.

• Korean Journal of Mineralogy and Petrology
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• 제36권4호
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• pp.355-363
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• 2023

In this study, we explore the nature of clumped isotopes of H₂O molecule using quantum chemical calculations. Particularly, we estimated the relative clumping strength between diverse isotopologues, consisting of oxygen (¹⁶O, ¹⁷O, and ¹⁸O) and hydrogen (hydrogen, deuterium, and tritium) isotopes and quantify the effect of temperature on the extent of isotope clumping. The optimized equilibrium bond lengths and the bond angles of the molecules are 0.9631-0.9633 Å and 104.59-104.62°, respectively, and show a negligible variation among the isotopologues. The calculated frequencies of the modes of H₂O molecules decrease as isotope mass number increases, and show a more prominent change with varying hydrogen isotopes over those with oxygen isotopes. The equilibrium constants of isotope substitution reactions involving these isotopologues reveal a greater effect of hydrogen mass number than oxygen mass number. The calculated equilibrium constants of clumping reaction for four heavy isotopologues showed a strong correlation; particularly, the relative clumping strength of three isotopologues was 1.86 times (HT¹⁸O), 1.16 times (HT¹⁷O), and 0.703 times (HD¹⁷O) relative to HD¹⁸O, respectively. The relative clumping strength decreases with increasing temperature, and therefore, has potential for a novel paleo-temperature proxy. The current calculation results highlight the first theoretical study to establish the nature of clumped isotope fractions in H₂O including ¹⁷O and tritium. The current results help to account for diverse geochemical processes in earth's surface environments. Future efforts include the calculations of isotope fractionations among various phases of H₂O isotopologues with a full consideration of the effect of anharmonicity in molecular vibration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제23권2호
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• pp.132-141
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• 2024

In this study, the differences in user satisfaction and the variables influencing the satisfaction with demand response transport (DRT) by travel purpose were compared. The purpose of DRT travel was divided into commuting/school and shopping/leisure travel. A survey conducted on 'Shucle' users in Sejong City was used for the analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis was applied to minimize the overfitting problems of the multilinear model. The results of the analysis confirmed the possibility that the introduction of the DRT service could eliminate the blind spot in the existing public transportation, reduce the use of private cars, encourage low-carbon and public transportation revitalization policies, and provide optimal transportation services to people who exhibit intermittent travel behaviors (e.g., elderly people, housewives, etc.). In addition, factors such as the waiting time after calling a DRT, travel time after boarding the DRT, convenience of using the DRT app, punctuality of expected departure/arrival time, and location of pickup and drop-off points were the common factors that positively influenced the satisfaction of users of the DRT services during their commuting/school and shopping/leisure travel. Meanwhile, the method of transfer to other transport modes was found to affect satisfaction only in the case of commuting/school travel, but not in the case of shopping/leisure travel. To activate the DRT service, it is necessary to consider the five influencing factors analyzed above. In addition, the differentiating factors between commuting/school and shopping/leisure travel were also identified. In the case of commuting/school travel, people value time and consider it to be important, so it is necessary to promote the convenience of transfer to other transport modes to reduce the total travel time. Regarding shopping/leisure travel, it is necessary to consider ways to create a facility that allows users to easily and conveniently designate the location of the pickup and drop-off point.

• Journal of Internet Computing and Services
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• 제25권4호
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• pp.121-130
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• 2024

As internet and communication technology (ICT) is improved exponentially, types and amount of available data also increase. Even though data analysis including statistics is significant to utilize this large amount of data, there are inevitable limits to process various and complex data in general way. Meanwhile, there are many attempts to apply machine learning (ML) in various fields to solve the problems according to the enhancement in computational performance and increase in demands for autonomous systems. Especially, data processing for the model input and designing the model to solve the objective function are critical to achieve the model performance. Data processing methods according to the type and property have been presented through many studies and the performance of ML highly varies depending on the methods. Nevertheless, there are difficulties in deciding which data processing method for data analysis since the types and characteristics of data have become more diverse. Specifically, multi-variate data processing is essential for solving non-linear problem based on ML. In this paper, we present a multi-variate tabular data processing scheme for ML-aided data analysis by using Titanic dataset from Kaggle including various kinds of data. We present the methods like input variable filtering applying statistical analysis and normalization according to the data property. In addition, we analyze the data structure using visualization. Lastly, we design an ML model and train the model by applying the proposed multi-variate data process. After that, we analyze the passenger's survival prediction performance of the trained model. We expect that the proposed multi-variate data processing and visualization can be extended to various environments for ML based analysis.