• Journal of The Korean Astronomical Society
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• v.34 no.2
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• pp.67-80
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• 2001

Chemical evolution of galaxies can be understood by studying the spatial distribution of heavy elements. We selected two nearby galaxies, M31 and M33 and investigated spectrum of their HII regions: a) the elec-tron densities have been derived from the [S II] 6717/6731 ratio along with the most recent atomic constants (Hyung & Aller 1996); b) the electron temperatures were determinated from the Pagel's empirical method. Nebula Model (Hyung 1994) has been employed to predict the spectral line intensities which gives the proper chemical abundances. The model would predict the line intensities correctly only when various input parameters such as the effective central star temperatures, gravity log g, model atmosphere as well as the geometry and the nebula physical condition are appropriate. Thus, the determination of chemical abundances of O, S, N of the two nearby galaxies M31 and M33 has been done, which shows a radial dependance of O/H and N/H: decrease with the distance, or increasing electron temperature due to the elemental deficiency. Abundances of M31 appear to be enhanced than those of M33.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.1
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• pp.33-46
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• 2013

A computational fluid dynamics (CFD) code, dubbed SNUFOAM, was developed to predict the performance of ship resistance using a CFD tool kit with open source libraries. SNUFOAM is based on a pressure-based cell-centered finite volume method and includes a turbulence model with wall functions. The mesh sensitivity, such as the skewness and aspect ratio, was evaluated for the convergence. Two wall functions were tested to solve the turbulent flow around a ship, and the one without the assumption of the equilibrium state between turbulent production and dissipation in the log law layer was selected. The turbulent flow around a ship simulated using SNUFOAM was compared to that by a commercial CFD code, FLUENT. SNUFOAM showed the nearly same results as FLUENT and proved to be an alternative to commercial CFD codes for the prediction of ship resistance performance.

• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.484-494
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• 2017

In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4788-4813
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• 2019

In this paper, we introduce concepts of optimal and near optimal secret data hiding schemes. We present a new digital image steganography approach based on the Galois field $GF(p^m)$ using graph and automata to design the data hiding scheme of the general form ($k,N,{\lfloor}{\log}_2p^{mn}{\rfloor}$) for binary, gray and palette images with the given assumptions, where k, m, n, N are positive integers and p is prime, show the sufficient conditions for the existence and prove the existence of some optimal and near optimal secret data hiding schemes. These results are derived from the concept of the maximal secret data ratio of embedded bits, the module approach and the fastest optimal parity assignment method proposed by Huy et al. in 2011 and 2013. An application of the schemes to the process of hiding a finite sequence of secret data in an image is also considered. Security analyses and experimental results confirm that our approach can create steganographic schemes which achieve high efficiency in embedding capacity, visual quality, speed as well as security, which are key properties of steganography.

• Bulletin of the Korean Chemical Society
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• v.16 no.3
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• pp.265-269
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• 1995

Complexation of ortho-xylyl-17-crown-5 (X17C5) with alkali metal ions in acetonitrile was studied by 7Li and 23Na NMR spectroscopy. The complex formation constants of X17C5 with LiI, LiSCN, NaI, and NaSCN were determined by investigating the changes in the chemical shifts as a function of the concentration ratio of X17C5 to metal ion. It was found that X17C5 forms 1:1 complex with Li+ and Na+ ions and the log Kf's for the complexation with LiI, LiSCN, NaI, and NaSCN were determined to be 2.88, 2.43, 2.53, and 2.30, respectively. In particular, the kinetics of complexation of X17C5 with Na+ was investigated by the method of 23Na NMR lineshape analysis. Activation energies were determined from Arrhenius plot of the resultant rate constant data to be 25.4 kJ/mol for NaI and 15.1 kJ/mol for NaSCN. Other kinetic parameters were also calculated by employing the Eyring equation. The decomplexation rates measured were 1.82 × 104 M-1s-1 for NaI and 1.50 × 104 M-1s-1 for NaSCN. It is concluded that the decomplexation mechanism is predominantly a bimolecular cation exchange for both cases.

• Korean journal of aerospace and environmental medicine
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• v.30 no.2
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• pp.51-53
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• 2020

In commemoration of Vol. 30, Issue 2, our journal prepared three review articles, two original papers, and a case report. The first review analyzed aircraft accidents caused by pilots' fatigue and presented a protocol to measure their fatigue, such as primary background survey, subjective drowsiness/arousal evaluation, sleep and activity log, sleep data, and performance measurement. The second review analyzed shift work patterns and work characteristics that may affect the fatigue of aviation mechanics. Also, desirable work principles for aviation mechanics (restrictions on working hours, appropriate rest hours, and night shift restrictions) were presented. The third review discussed the effects that allergic rhinitis can have on pilots (drowsiness and decreased arousal) and introduced a safe treatment method that can prevent these adverse effects. In the first original article, the ratio of 'incompatible (non-fit)' result in aerospace medical examination among Korean aircraft pilots for the past five years was investigated by age group and the common causes of nonconformity were analyzed. In the second original article, the prevalence, mortality, prevalence according to age groups, and regional characteristics of severe febrile thrombocytopenia syndrome were compared and analyzed in Korea and Japan for the past five years. Finally, in the case report, the cases of a patient diagnosed as gastrointestinal stromal tumors who received surgical treatment and chemotherapy were discussed, and the results of the judgment were presented.

• Korean Journal of Plant Resources
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• v.18 no.3
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• pp.512-517
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• 2005

To establish the economical cultivation method of Gastrodia elata Blume by controlling the shading rate and the mixing ratio of recycling spawn bed logs, a serial experiment was carried out. When G. elata was grown in the field with no shading, the yield of spawn tuber was higher than that of tuber of G. elata. The yield of G. elata was high in the rainproof green house covered with one layer of $95\%$ shading net, in the rainproof green house covered with two layers of $95\%$ shading net, and in the field with no shading, in that order. In the case of mixing ratio of recycling spawn bed logs, the yield was high in the fresh logs, in the mixing ratio of 2:1, and the ratio of 1:1, in that order. The income of the rainproof green house covered with one layer of $ 95\%$ shading net which brought the best yield was $81\%$ in the mixing ratio of 2:1 over the fresh logs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.45-55
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• 2015

In this paper, we consider curriculum mining as an application of process mining in the domain of education. The basic objective of the curriculum mining is to construct a registration pattern model by using logs of registration data. However, subject registration patterns of students are very unstructured and complicated, called a spaghetti model, because it has a lot of different cases and high diversity of behaviors. In general, it is typically difficult to develop and analyze registration patterns. In the literature, there was an effort to handle this issue by using clustering based on the features of students and behaviors. However, it is not easy to obtain them in general since they are private and qualitative. Therefore, in this paper, we propose a new framework of curriculum mining applying K-means clustering based on subject attributes to solve the problems caused by unstructured process model obtained. Specifically, we divide subject's attribute data into two parts : categorical and numerical data. Categorical attribute has subject name, class classification, and research field, while numerical attribute has ABEEK goal and semester information. In case of categorical attribute, we suggest a method to quantify them by using binarization. The number of clusters used for K-means clustering, we applied Elbow method using R-squared value representing the variance ratio that can be explained by the number of clusters. The performance of the suggested method was verified by using a log of student registration data from an 'A university' in terms of the simplicity and fitness, which are the typical performance measure of obtained process model in process mining.

• Journal of Gastric Cancer
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• v.21 no.4
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• pp.335-351
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• 2021

Purpose: An underlying factor for the failure of several clinical trials of anti-epidermal growth factor receptor (EGFR) therapies is the lack of an effective method to identify patients who overexpress EGFR protein. The quantitative dot blot method (QDB) was used to measure EGFR protein levels objectively, absolutely, and quantitatively. Its feasibility was evaluated for the prognosis of overall survival (OS) of patients with gastric cancer. Materials and Methods: Slices of 2×5 ㎛ from formalin-fixed paraffin-embedded gastric cancer specimens were used to extract total tissue lysates for QDB measurement. Absolutely quantitated EGFR protein levels were used for the Kaplan-Meier OS analysis. Results: EGFR protein levels ranged from 0 to 772.6 pmol/g (n=246) for all gastric cancer patients. A poor correlation was observed between quantitated EGFR levels and immunohistochemistry scores with ρ=0.024 and P=0.717 in Spearman's correlation analysis. EGFR was identified as an independent negative prognostic biomarker for gastric cancer patients only through absolute quantitation, with a hazard ratio of 1.92 (95% confidence interval, 1.05-3.53; P=0.034) in multivariate Cox regression OS analysis. A cutoff of 208 pmol/g was proposed to stratify patients with a 3-year survival probability of 44% for patients with EGFR levels above the cutoff versus 68% for those below the cutoff based on Kaplan-Meier OS analysis (log rank test, P=0.002). Conclusions: A QDB-based assay was developed for gastric cancer specimens to measure EGFR protein levels absolutely, quantitatively, and objectively. This assay should facilitate clinical trials aimed at evaluation of anti-EGFR therapies retrospectively and prospectively for gastric cancer.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.112-121
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• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.