• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.136-152
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• 2017

The thermodynamic models, PC-SAFT (Perturbed-Chain Statistical Associated Fluid Theory) state equation and the Two-model approach liquid activity coefficient model NRTL (Non Random Two Liquid) + Henry + Peng-Robinson, for modeling the Rectisol process using methanol aqueous solution as the $CO_2$ removal solvent were compared. In addition, to determine the new binary interaction parameters of the PC-SAFT state equations and the Henry's constant of the two-model approach, absorption equilibrium experiments between carbon dioxide and methanol at 273.25K and 262.35K were carried out and regression analysis was performed. The accuracy of the newly determined parameters was verified through the regression results of the experimental data. These model equations and validated parameters were used to model the carbon dioxide removal process. In the case of using the two-model approach, the methanol solvent flow rate required to remove 99.00% of $CO_2$ was estimated to be approximately 43.72% higher, the cooling water consumption in the distillation tower was 39.22% higher, and the steam consumption was 43.09% higher than that using PC-SAFT EOS. In conclusion, the Rectisol process operating under high pressure was designed to be larger than that using the PC-SAFT state equation when modeled using the liquid activity coefficient model equation with Henry's relation. For this reason, if the quantity of low-solubility gas components dissolved in a liquid at a constant temperature is proportional to the partial pressure of the gas phase, the carbon dioxide with high solubility in methanol does not predict the absorption characteristics between methanol and carbon dioxide.

• Journal of radiological science and technology
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• v.33 no.2
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• pp.97-107
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• 2010

The objectives of this study is to figure out the unknown image processing methods of commercial CR system. We have implemented the processing curve of each Look up table(LUT) in REGIUS 150 CR system by using virtual digital test pattern method. The characteristic of Dry Imager was measured also. First of all, we have generated the virtual digital test pattern file with binary file editor. This file was used as an input data of CR system (REGIUS 150 CR system, KONICA MINOLTA). The DICOM files which were automatically generated output files by the CR system, were used to figure out the processing curves of each LUT modes (THX, ST, STM, LUM, BONE, LIN). The gradation curves of Dry Imager were also measured to figure out the characteristics of hard copy image. According to the results of each parameters, we identified the characteristics of image processing parameter in CR system. The processing curves which were measured by this proposed method showed the characteristics of CR system. And we found the linearity of Dry Imager in the middle area of processing curves. With these results, we found that the relationships between the curves and each parameters. The G value is related to the slope and the S value is related to the shift in x-axis of processing curves. In conclusion, the image processing method of the each commercial CR systems are different, and they are concealed. This proposed method which uses virtual digital test pattern can measure the characteristics of parameters for the image processing patterns in the CR system. We expect that the proposed method is useful to analogize the image processing means not only for this CR system, but also for the other commercial CR systems.

• Economic and Environmental Geology
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• v.35 no.2
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• pp.113-120
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• 2002

Oxygen and hydrogen isotopic compositions of stream water in the Han river basin are expressed by the equation of $\delta$D=6.6$\delta$$^{18}$ O-7.4, which is not satisfy the meteoric water line ($\delta$D=8$\delta$$^{18}$ O+10). It might be depended on the local climatic condition and the evaporation effect in the Han river basin. The $\delta$$^{18}$ O and $\delta$D values of stream water in the Han river basin range from -8.2 to -10$\textperthousand$ (avg. -9.1$\textperthousand$) and -60 to -96$\textperthousand$ (avg. -69$\textperthousand$), respectively. The stream water from the South Han river (8$\delta$$^{18}$ O= -8.9~ -10$\textperthousand$, avg.-9.3$\textperthousand$ $\delta$D: -66~ -96$\textperthousand$, avg.-69$\textperthousand$) is slightly more depleted in $^{18}$ O and D than those of North Han river ($\textperthousand$$^{18}$ O= -8.4~ -9.7$\textperthousand$, avg. -9.2$\textperthousand$, $\delta$D= -64~ -95$\textperthousand$, avg. -69$\textperthousand$). It reflects more altitude effect than the effect of latitude and Inflow of the $^{18}$ O eniched S $O_4$$^{2-}$ and HC $O_3$- from the carbonate rock and sulfide minerals in the Taebagsan and Hwanggangri mineralized zone. The Main stream water of the Han river having $\delta$D: -60~ -76$\textperthousand$ (avg.-68$\textperthousand$) and $\textperthousand$$^{18}$ O= -8.2~-10$\textperthousand$ (avg.9.0$\textperthousand$) is enriched in $^{18}$ O compared to the South and North Han river waters, which is caused by the evaporation effect. Binary simple mixing ratio of the Main Han river water between South and North Han river waters was obtained to be 6 : 4 by the isotopic data, suggesting a strong influence of South Han river water to the Main Han river water.

• 한국균학회소식:학술대회논문집
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• 2014.10a
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• pp.9-9
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• 2014

Null mutants generated by targeted gene replacement are frequently used to reveal function of the genes in fungi. However, targeted gene deletions may be difficult to obtain or it may not be applicable, such as in the case of redundant or lethal genes. Constitutive expression system could be an alternative to avoid these difficulties and to provide new platform in fungal functional genomics research. Here we developed a novel platform for functional analysis genes in Magnaporthe oryzae by constitutive expression under a strong promoter. Employing a binary vector (pGOF1), carrying $EF1{\beta}$ promoter, we generated a total of 4,432 transformants by Agrobacterium tumefaciens-mediated transformation. We have analyzed a subset of 54 transformants that have the vector inserted in the promoter region of individual genes, at distances ranging from 44 to 1,479 bp. These transformants showed increased transcript levels of the genes that are found immediately adjacent to the vector, compared to those of wild type. Ten transformants showed higher levels of expression relative to the wild type not only in mycelial stage but also during infection-related development. Two transformants that T-DNA was inserted in the promotor regions of putative lethal genes, MoRPT4 and MoDBP5, showed decreased conidiation and pathogenicity, respectively. We also characterized two transformants that T-DNA was inserted in functionally redundant genes encoding alpha-glucosidase and alpha-mannosidase. These transformants also showed decreased mycelial growth and pathogenicity, implying successful application of this platform in functional analysis of the genes. Our data also demonstrated that comparative phenotypic analysis under over-expression and suppression of gene expression could prove a highly efficient system for functional analysis of the genes. Our over-expressed transformants library would be a valuable resource for functional characterization of the redundant or lethal genes in M. oryzae and this system may be applicable in other fungi.

• Journal of dental hygiene science
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• v.14 no.3
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• pp.311-318
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• 2014

The purpose of this study was to look into the perception, experience, treatment of early childhood caries (ECC) and influential factors of perception in order to provide basic data useful for preventing the ECC by examining the relationship between oral health of young children in infancy and mother. In this study, 277 mothers were surveyed who had children in children under 6 years old and visiting the pediatrics, day care center, and pediatric dental clinics located in Daegu and Gyeongsangbuk-do from July 10, 2013 to September 5 of the same year. The results obtained from the survey were analyzed through chi-square test, t-test, and binary logistic regression analysis by using the SPSS 18.0, a statistical program. The results of analysis showed that ECC in children under 6 years old was associated with mother's age, education background of mothers, number of children and monthly income and had a significant correlation with mother's oral health-related knowledge and oral health care of their children. Thus, it would be necessary to develop oral health education programs and implement such oral health education programs at a national level on a regular basis for the mothers of young children in infancy and would-be mothers in order to reduce the ECC in infancy and promote oral health.

• 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.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.135-151
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• 2021

This research attempts to analyze the factors influencing the entrepreneurial intention of employees in manufacturing field. In particular, key factors of entrepreneurship and personal characteristics explain a significant association with the intention to start-up. And study whether R&D support from public enterprise adjusts intention to entrepreneurial Intention. This study conducted a online survey on 292 small and medium-sized enterprise manufacturing employees in May 2020. Using linear regression model and binary logistic model. The main study results are the following: First, among the key factors(innovativeness, proactiveness, risk-taking) of entrepreneurship, proactiveness hardly influenced the opportunity competency. Second, among the factors(risk-taking propensity, locus of control, tolerance for ambiguity) of personal characteristics, locus of control hardly influenced the opportunity competency. Third, opportunity competency(opportunity recognition and opportunity evaluation) had positive influence to entrepreneurial intention. Fourth, the study investigated the mediated effect of opportunity competency. The result showed that among the factors of entrepreneurship and personal characteristics, only two factors that are proactiveness and locus of control were not mediated by opportunity competency. and opportunity evaluation was acted as a mediator between proactiveness and entrepreneurial Intention, compared with opportunity recognition. Lastly, public enterprise's R&D supporting moderated the entrepreneurial intention). Based on the result, the study showed that first, the key factors of entrepreneurship except for proactiveness and personal characteristics(risk-taking propensity, locus of control, tolerance for ambiguity) except for locus of control affect the intention to start-up, repeatedly. This results are explained that employees have not started a business yet. Second, research on start-up suggests the need to analyze factors differentiated before and after the start-ups. Based on the results, entrepreneurship and personal characteristics show that study on the effects of start-up intentions should be carried out before and after the actual start-up takes place, and can be used as effective data in policies to promoting start-ups in manufacturing field.

• Journal of agricultural medicine and community health
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• v.46 no.3
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• pp.131-143
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• 2021

Objectives: This study aimed 1) to investigate high school students' reliability on COVID-19 responses in schools and private academies and 2) to identify the differences in COVID-19 prevention practice. Methods: This cross-sectional survey collected data from 200 high school respondents, using an anonymous online questionnaire designed by the Yonsei Global Health Center, from July 2 to 17, 2020 in this study. Chi-square tests were conducted to analyze the differences in preventative practices and practice rates between schools and private academies. Binary logistics regression analysis was conducted to identify the factor affecting the reliability of COVID-19 response. Results: These high school students reliabilityed the schools' COVID-19 response more than the private academy. In addition, students who studied only at school did more COVID-19 prevention practices than students who studied both at school and academy. There was a significant difference in avoiding public transportation (p=.028), sitting in one row while having a meal (p=.011) in the practice rates depending on the schools' COVID-19 response. A significant difference in Covering the mouth when coughing and sneezing (p-.041) was also found in the practice rates depending on the private academies' COVID-19 response. Conclusion: The reason why schools were more reliable than private academies was that there are health teachers. Because schools are supervised by the ministry of education, the Ministry of education and local government need to work together to manage and monitor the COVID-19 response in the academies through cooperation between two organizations. In addition, it is necessary to arrange a temporary circulation health teacher who will provide the COVID-19 prevention education at the academies.