• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.202-208
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• 2020

The objective of this study was to select the right species among Agastache in the family Lamiaceae as the result of growth analysis and functional substance analysis. Among 22 species of Agastache, five species (Agastache cana, Agastache foeniculum, Agastache rugosa 'Spike Blue', Agastache rugosa 'Spike Snow', Agastache rupestris) were selected by referring to United States Department of Agriculture (USDA)'s plant hardiness zone area and Korea's one based on USDAs. These plants were cultured at 24 ± 1℃ and 18 ± 1℃ (day and night temperatures, respectively) and 65 ~ 75% relative humidity in a hydroponic culture system for 4 weeks. In terms of growth analysis experiment, stem length, root length, leaf width, leaf area, leaf number, SPAD value, and fresh and dry weights of shoots and roots were measured. The results showed that A. rugosa SS and A. rugosa SB have a higher overall balance value than other species. When compared functional substance value (rosmarinic acid, tilianin, and acacetin) of five species, A. rugosa SS and A. rugosa SB are significantly higher than other species in Agastache. It seems to be directly proportional to the growth analysis results. When considering the growth and functional substance part comprehensively, A. rugosa SS and A. rugosa SB are the most optimal high-value species among Agastache.

• KSBB Journal
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• v.25 no.5
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• pp.429-436
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• 2010

Keratinase is widely used in certain industrial applications. The present study sought to improve the culture conditions of Bacillus subtilis SMMJ-2 to facilitate mass production of keratinase. Strain SMMJ-2 was irradiated by ultraviolet light and the resulting isolates were tested for keratinase activity. Isolates displaying elevated keratinase activity were selected and used to determine the optimum temperature (24, 30, 37, 45, $55^{\circ}C$) for bacterial keratinase production during a 4 day incubation period. The highest enzyme activity (55 units/mL/min), from a Bacillus subtilis SMMJ-2 mutant (mutant No. 2) was demonstrated following incubation at $30^{\circ}C$. The effects of carbon and nitrogen sources on keratinase production were confirmed by measuring the enzyme activity from the culture broth of the mutant strain cultured in various media containing different carbon source and nitrogen sources during a 4 day period. The optimal medium composition for producing keratinase consisted of 1% glucose, 0.7% $K_2HPO_4$, 0.2% $K_2HPO_4$, and 1.2% soybean meal. Optimal initial pH and temperature for producing keratinase were 7.0 and $30^{\circ}C$, respectively. Keratinases produced by B. subtilis SMMJ-2 and the mutant No. 2 were purified from the culture broth which used soybean meal as a nitrogen source. Membrane ultrafiltration, DEAE-sephacel ion exchange and Sephadex G-100 gel chromatography were used to purify the enzymes. The purified keratinases from both B. subtilis SMMJ-2 and the mutant No. 2 showed single bands and their molecular weights were estimated as 28 kDa and 42 kDa, respectively on SDS-polyacrylamide gel electrophoresis.

• Journal of Life Science
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• v.23 no.2
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• pp.273-281
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• 2013

The purpose of this research was to investigate the production and characterization of alkaline protease from Micrococcus sp. PS-1 newly isolated from seawater. Micrococcus sp. PS-1 was grown in Luria-Bertani (LB) medium. Its optimal temperature and pH for growth were $30^{\circ}C$ and 7.0, respectively. The effect of nitrogen sources was investigated on optimal enzyme production. A high level of alkaline protease production occurred in LB broth containing 2% skimmed milk. The protease was purified in a 3-step procedure involving ultrafiltration, acetone precipitation, and dialysis. The procedure yielded a 16.43-purification fold, with a yield of 54.25%. SDS-PAGE showed that the enzyme had molecular weights of 35.0 and 37.5 kDa. Its maximum protease activity was exhibited at pH 9.0 and $37^{\circ}C$, and its activity was stable at pH 8.0-11.0 and $25-37^{\circ}C$. The protease activity was strongly inhibited by PMSF, EDTA, and EGTA. Taken together, the results demonstrate that the protease enzyme from Micrococcus sp. PS-1 probably belongs to a subclass of alkaline metallo-serine proteases.

• Communications of Mathematical Education
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• v.31 no.1
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• pp.49-70
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• 2017

The purpose of this study was to investigate the relative influence of multiple error sources and to find optimal measurement conditions that obtain a desired level of reliability of a creative attitude test in mathematical creativity. This study analyzed the scores of the Creative Attitude Scale-Korea allowed to access publicly of 125 general students and 109 mathematically gifted students by performing a multivariate generalizability analysis. The main results were as follows. First, based on reliability, the Creative Attitude Scale-Korea was measured less precisely for mathematically gifted students. On the contrary, based on the conditional standard error of measurement, it was measured less precisely for general students. However, the Creative Attitude Scale-Korea showed strong reliability in both groups. Second, the optimal weights should adjust to .3, .3, .4 in mathematically gifted students and .4, .4, .2 in general students with three scoring components of divergent attitude, problem solving attitude, and convergent attitude based on the maximum reliability. Third, to approach desirable reliability, it is possible to use one component of divergent attitude in general students but three components of divergent attitude, problem solving attitude, and convergent attitude in mathematically gifted students. Finally this study proposed application plans for the Creative Attitude Scale-Korea and future directions of research.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.665-677
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• 2021

This study analyzed the optimization method of forest management to enhance economic and public functions, as well as the interrelationship among timber production, carbon storage, and water conservation functions in Mt.Gari leading forest management zone. For these purposes, a forest management planning model was developed using Multi-Objective Linear Programming. The model had an objective function to maximize the total NPV (Net Present Value) of weighted timber production, carbon storage, water conservation, and constraints to limit the rate of change in timber production, percentage of each age-class and tree species area, percentage of conifers and broad-leaved trees area in each management zone, minimum timber production and timber sales amount. Based on the description of forest inventory and the comprehensive plan of Mt.Gari, we analyzed stand information and management constraints of the study area. We compared management alternatives using different weights in the objective function. Therefore, the total NPV was maximized in the alternative considering the three functions in equal proportion, rather than the alternatives of maximizing only one function. When all three functions were considered simultaneously, timber production offset the carbon storage and water conservation, and carbon storage and water conservation interacted synergistically. However, when considering only two of the three functions, all combinations of functions demonstrated tradeoffs with one other. Therefore, we discovered that by considering all three functions equally, rather than only one or two functions, the economic and public values of the study area can be maximized.

• Journal of Plant Biotechnology
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• v.49 no.4
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• pp.307-315
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• 2022

Artemisinin is a secondary metabolite of Artemisia annua that shows potent anti-malarial, anti-bacterial, antiviral, and anti-tumor effects. The supply of artemisinin depends on its content in Artemisia annua, in which various environmental factors can affect the plant's biosynthetic yield. In this study, the effects of different light-emitting diode (LED)-irradiation conditions were tested to optimize the germination and growth of Artemisia annua for the enhanced production of artemisinin. Specifically, the ratio between the red and blue lights in the irradiating LED was varied for investigation as follows: [Red : Blue] = [6 : 4], [7 : 3], and [8 : 2]. Furthermore, additional stress factors like UV-B-irradiation (1,395 ㎼/cm²), low temperature (4℃), and dehydration were also explored to induce hormetic expressions of ADS, CYP, and ALDH1, which are essential genes for the biosynthesis of artemisinin. Quantitative polymerase chain reaction (qPCR) was used to analyze the expression levels of the respective genes and their correlation with the specified conditions. [8 : 2] LED-irradiation was the most optimal among the tested conditions for the cultivation of Artemisia annua in terms of both fresh and dry weights post-harvest. For the production of artemisinin, however, [7 : 3] LED-irradiation with dehydration for six hours pre-harvest was the most optimal condition by inducing around twofold enhancement in the biosynthetic yield of artemisinin. As expected, a correlation was observed between the expression levels of the genes and the contents of artemisinin accumulated.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2021.04a
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• pp.27-27
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• 2021

Yacon [Samallanthus sonchifolius (Poepp. & Endl.) H. Robinson], a member of Compositae plants, has sweet taste and crisp texture. Unlike other Andean root crops such as potato and sweet potato, the cultivation area of yacon has increased recently, since it is known to have large content of fructooligosaccharides (FOS). Since there are no yacon varieties bred in Korea, we have been trying to create new genetic resources using gamma-ray. The optimal gamma-ray dosage for mutation breeding in yacon was investigated. Crown bud and green bud of yacon were exposed to doses of gamma rays from 20 Gy to 80 Gy, and subsequently planted in a greenhouse. After 50 days of sowing, the survival rates and growth decreased rapidly at doses above 40 Gy, while all of crown bud individuals died above 60 Gy. The median lethal dose (LD50) of crown bud and green bud was 22.4 and 36.6 Gy, and the median reduction doses (RD50) for plant height, fresh weights, and tuberous root weight were 20-40 Gy, respectively. A dose of 20-40 Gy was found to be optimal for mutation breeding in yacon. Considering the growth factors, the optimum doses were determined to be within the range of 20-40 Gy for the selection of useful mutant lines. M2-M3 mutant lines were obtained from 20-60 Gy gamma-ray-irradiated M1 plants through clonal propagation. These mutant lines will be used for the development of a new variety of yacon plant with high FOS and no crack tuberous root.

• Clinical and Experimental Pediatrics
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• v.53 no.2
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• pp.203-209
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• 2010

Purpose : Growth impairment is usually observed in children with congenital heart disease (CHD). Studies on the final height and weight of this population are insufficient. Our aim was to evaluate the final height of children with CHD and to identify the relationship between CHD and growth. Methods : We recorded the values of final height and weights of 105 CHD patients (age, <19 years) who visited Chonnam National University Hospital between November 2000 and March 2009, and we reviewed the medical records. Results : The mean values of weight and height of male CHD patients were significantly lower than those of the normal subjects. Patients with severe growth impairment (below the third percentile of normal) included 5 males (8.6%) and 4 females (8.5%) with height less than normal and 9 males (15.5%) and 8 females (17.0%) with weight less than normal. The mean growth of the patients in the cyanotic heart disease group was lower than that of normal subjects, but a statistically significant difference was noted in the weights of males. In a comparative study based on the type of CHD, a significant difference was noted in weights of males. Patients with patent ductus arteriosus and those with tetralogy of Fallot had the highest and lowest mean values of weight, respectively. Conclusion : Growth impairment was more evident in children with CHD than normal children. Patients should be treated during an optimal time frame. Thus, CHD patients should be treated if follow-up studies indicate growth impairment.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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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 Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.