• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.2
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• pp.252-263
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• 1997

Steady-state two-dimensional natural convective heat transfer in horizontal cylindrical annuli was studied by solving the governing equations based on the primitive variables. Emphasis was put on the occurrence of the multiple solutions at a given set of parameter values, and on the determination of the bifurcation points at which those multiple solutions begin to branch out. The multicellular flow pattern from the results of melting process in an isothermally heated horizontal cylinder for high Rayleigh numbers, was used as initial guesses for the field variables. This was succeeded in new bifurcation point to tetracellular solutions for an identical set of parameter variables of previous works. The close examination of flow pattern transition around bifurcation point was also conducted. It was found that the mechanisms of flow transition are different depending on the critical Rayleigh number of bifurcation point.

• BMB Reports
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• v.39 no.3
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• pp.240-246
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• 2006

The base compositional correlations that hold among various coding and noncoding regions of the canine genome have been analysed. The distribution pattern of genes, on the basis of $GC_3$ composition, shows a wide range similar to that observed in human. However the occurrence of maximum number of genes was observed in the range of 65-75% of $GC_3$ composition. The correlation between the coding DNA sequences of canine with the different noncoding regions (introns and flanking regions) is found to be significant and in many cases the degree of correlation show similarity to human genome. We found that these correlations are not limited to the GC content alone, but is holding at the level of the frequency of individual bases as well. The present study suggests that canines ideally belong to the predicted 'general mammalian pattern' of genome composition along with human beings.

• Journal of Oral Medicine and Pain
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• v.15 no.1
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• pp.117-124
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• 1991

The purpose of his study was to investigate the variations of occlusal contact pattern according to chewing side preference. The author selected 59 dental students (mean age 23.6 years) who had no signs and symptoms of masticatory disorders and divided into two groups, that is, bilateral chewing side group and unilateral chewing side group, respectively. For recording, T-Scan System(Teksan Inc., USA) was used and the recorded occlusal contacts were examined as to the number of occlusal contacts, points distribution in dental arch, time sequence and force snapshot. The obtained results were as follow s: 1. Total number of occlusal contacts were more in unilateral chewing side group and there were significant difference in number between right and left side or between chewing and less-chewing side in all two groups. 2. All items related to time sequence showed no statistical significant difference between two groups in any case. 3. Unilateral chewing side group had more occlusal contact force than bilateral group, especially in chewing side. From the above finding, the author considered that there was occlusal unbalance in unilateral chewing side group. 4. Chewing side preference would possibly have more effects on the occurrence rate of anterior tooth contact that the rate of prolonged their contact but proved.

• Journal of KIISE
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• v.43 no.6
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• pp.718-723
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• 2016

In streaming data analysis, detecting concept drift accurately is important to maintain the performance of classification model. Error rates are usually used for concept drift detection. However, by describing prediction results with only binary values of 0 or 1, useful information about a behavior pattern of a classifier can be lost. In this paper, we propose an effective concept drift detection method which describes performance pattern of a classifier by utilizing probability estimates for class prediction and detects a significant change in a classifier behavior. Experimental results on synthetic and real streaming data show the efficiency of the proposed method for detecting the occurrence of concept drift.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.117-125
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• 2016

Software reliability in the software development process is an important issue. In infinite failure non-homogeneous Poisson process software reliability models, the failure occurrence rates per fault. can be presented constant, monotonic increasing or monotonic decreasing pattern. In this paper, the reliability software cost model considering decreasing intensity function was studied in the software product testing process. The decreasing intensity function that can be widely used in the field of reliability using power law process, log-linear processes and Musal-Okumoto process were studied and the parameter estimation method was used for maximum likelihood estimation. In this paper, from the software model analysis, we was compared by applying a software failure interval failure data considering the decreasing intensity function The decreasing intensity function model is also efficient in terms of reliability in the arena of the conservative model can be used as an alternating model can be established. From this paper, the software developers have to consider life distribution by preceding information of the software to classify failure modes which can be gifted to support.

• Research in Plant Disease
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• v.10 no.2
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• pp.150-153
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• 2004

This study was conducted to investigate the sap transmission pattern of CGMMV and to select the disinfectant of sap transmission on watermelon cultivation. Being investigated CGMMV occurrence change after transplanting two diseased plants among 47 plants on the watermelon house, disease spread rapidly from early growth stage of 4 % to late growth stage of 83 %. When the grafting knife and topping scissor was dipped onto the several disinfectants before grafting or topping, disease suppressed 87-95 % on whole milk, skim milk, tri-sodium phosphate, and sodium hypo-chloride solution. Disinfection effects of 88.2 % and 91.2 % on whole milk and skim milk were showed when the hand dipped on the disinfectants.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.71-80
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• 2017

Software reliability is one of the most elementary and important problems in software development In order to find the software failure occurrence, the instantaneous failure rate function in the Poisson process can have a constant, incremental or decreasing tendency independently of the failure time. In this study, we compared the reliability performance of the software reliability model using the parameters of Pareto life distribution with the intensity decreasing pattern and the shape parameter of Erlang life distribution with the intensity increasing and decreasing pattern in the software product testing. In order to identify the software failure environment, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, we compare and evaluate software reliability by applying software failure time data. The reliability of the Erlang and Pareto life models is shown to be higher than that of the Pareto lifetime distribution model when the shape parameter is higher and the Erlang model is more reliable when the shape parameter is higher. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing basic knowledge using software failure analysis.

• Environmental Analysis Health and Toxicology
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• v.26
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• pp.1.1-1.6
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• 2011

Plasmodium vivax malaria has occurred annually in the Republic of Korea (ROK) since its re-emergence in 1993. P. vivax malaria in ROK has been strongly influenced by infected mosquitoes originating from the Democratic People's Republic of Korea. Korean P. vivax malaria has shown typical characteristics of unstable malaria transmitted only during the summer season, and displays short and long incubation periods. The changing pattern of the transmission period can be predicted by analyzing the seasonal characteristics of early primary attack cases with a short incubation period. Such cases began to gradually occur earlier in the 1990s after the re-emergence. Most of the malaria cases after mid-August are presumed to be early primary attack, short incubation period cases. Only primary transmission was possible until the early 2000s, whereas up to fourth or fifth transmission occurred in the mid-2000s. The results indicate that the length of transmission period has been gradually extending, which may be ascribed to a climate change-mediated temperature rise. Malaria and climate data should be integrated to analyze and predict the influence of climate change on malaria occurrence in ROK.

• Korean Journal of Veterinary Research
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• v.42 no.1
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• pp.115-121
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• 2002

The present study was conducted to investigate the pattern of fracture of 50 Thoroughbred foals in Jeju from January 1997 to August 2001. A total 50 Thoroughbred foals were investigated to figure out the relationship between breeding condition and fracture. The fracture was diagnosed by physical and radiological examinations after lameness test. Most sites of fracture were limb, skull and vertebrae. Age analyzed that the most popular is the 1-year-old foals. Most places of the occurrence of the fracture were pasture, paddock, track and stable. Main cause of the fracture were play, training and foal's dam. These results suggest that there were the 1-year-old foals have a lot of fracture during play at pasture in winter.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.