• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.

• Journal of Plant Biology
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• v.15 no.3
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• pp.1-8
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• 1972

A comparison between the productivity of the evergreen needle pine(Pinus densiflora) and of the deciduous broad leaved oak(Quercus mongolica) stands, which is located near Choon-Chun city, Kangwon dist. have been established. The pine stand had a stand density of 938 trees per ha and oak stand had of 638 trees per ha. The diameter at breast height (D) and the height of tree (H) of each tree were measured in sample plot of 800$m^2$. Twelve standard sample trees chose from the sample area felled down, and then weighed the stem, branches and leaves separately, according to both the stratified clip technique and the stem analysis. The vertical distribution of photosynthetic system was arranged effectively for high productivity in the productive structure of both trees. The allometric relation between D2H and dry weight of stem (Ws), branches (Wb) and leaves (Wl) of pine were approximated by log Ws=0.6212 log D2H-0.5383 log Wb=0.4681 log D2H-0.7236 log Wl=0.2582 log D2H-5.1567 and those of oak were approximated by log Ws=0.5125 log D2H＋0.0231 log Wb=0.5125 log D2H-0.3755 log Wl=0.8721 log D2H-2.9710 From the above, the standing crops of pine and oak in the sample area were estimated to be as much as 38.83ton and 48.11 ton of dry matter, above ground, per ha, respectively. Annual net production as the sum of the biomass newly formed during one year was appraised at 12.66ton/ha.yr in pine stand and at 8.74 ton/ha.yr in oak. The reason of high productivity of pine stand compared with oak might be resulted from much more about 4 times of the amount of the photosynthetic system, but less non-photosynthetic one of pine than those of oak. To increase the productivity of the forest stands investigated it was necessary to make densly a stand density, to be abundant in the inorganic nutrients and to preserve much water in soil to conserve the litters.

• Biomedical Science Letters
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• v.23 no.4
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• pp.333-338
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• 2017

This study was performed to assess microbial contamination of Aronia melanocarpa, blueberry, raspberry, and cranberry sold in several markets. We investigated total aerobic bacteria and detected foodborne bacteria by multiplex PCR from Aronia melanocarpa, blueberry, raspberry, and cranberry. Total aerobic bacteria of each sample showed mean 3.54 log CFU/g for Aronia melanocarpa, mean 1.90 log CFU/g for blueberry, and mean 1.40 log CFU/g for raspberry, but not detected in cranberry. Specially, Aronia melanocarpa contained high total aerobic bacteria contamination among various berries and contamination level reached 4.17 log CFU/g in sample 5. To evaluate the effect of distribution conditions, we also investigated total aerobic bacteria of various berries. Total aerobic bacteria showed mean 2.89 log CFU/g for berries in refrigerated distribution and 1.40 log CFU/g in frozen distribution, but not in dry distribution. For assessment of foodborne bacteria contamination, we conducted PCR with multiplex primers of E. coli O157, S. aureus, B. cereus, V. parahaemolyticus, L. monocytogenes, Y. enterocolitica, Salmonella spp., Shigella spp. Among these foodborne bacteria, B. cereus was amplified in Aronia melanocarpa in sample 4 and blueberry in sample 1, 2, 3, and 5. The result of quantitative analysis of B. cereus contamination showed 4.08 log CFU/g of Aronia melanocarpa in sample 4 and higher contamination rate 4.07 log CFU/g of blueberry in sample 3. These results suggest that strict food safety control in harvest and distribution of various berries is necessary to prevent foodborne disease and improve microbiological safety.

• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.148-155
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• 2009

The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

• Convergence Security Journal
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• v.17 no.1
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• pp.3-13
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• 2017

As security log plays important roles in various fields, the integrity of log data become more and more important. Especially, the stored log data is an immediate target of the intruder to erase his trace in the system penetrated. Several theoretical schemes to guarantee the forward secure integrity have been proposed, even though they cannot provide the integrity of the log data after the system is penetrated. Authentication tags of these methods are based on the linear-hash chain. In this case, it is difficult to run partial validation and to accelerate generating and validating authentication tags. In this paper, we propose a log authentication mechanism, based on Mekle Tree, which is easy to do partial validation and able to apply multi threading.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.81-88
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• 2004

Turbo code has been adopted in the 3GPP standard, since its performance is very close to the Shannon limit. However, the turbo decoder requires a lot of computations and the amount of the memory increases as the block size of turbo codes becomes larger. In order to reduce the complexity of the turbo decoder, the Log-MAP, the Max-Log-MAP and the sliding window algorithm have been proposed. In this paper, the performance of turbo codes adopted in the 3GPP standard is analyzed by using the floating point and the fixed point implementation. The efficient decoding method is also proposed. It is shown that the BER performance of the proposed method is close to that of the Log-MAP algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.23-33
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• 2014

The smart phone are changing the way people communicate. And, the mobile app marketplace is greatly fast-growing. The app store continues its rapid growth, there are already more than 900,000 mobile apps on AppStore. We anticipate to see gained momentum throughout the business. Mobile is also becoming popular for marketers. Therefore, specialized app analysis systems are becoming important to how marketers and app developers invest, analyze and market their apps. App analysis systems enable users to discover and analyze behavior through data observations and meaningful patterns. In this paper, we introduce app analysis system and CMS System Open API, NugaLog. The NugaLog acquires users data and engages with them in a variety of ways. It will be essential for us to understand how users interact with and move through the app. The NugaLog will be able to see the number of users, smart phone model, smart phone OS, resolution, page views, and app version.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.51-64
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• 2014

The purpose of operating the main homepage of University is to provide the related information about University resources to site visitors. In this study, we analyze website browsing patterns and extract characteristics of users in order to improve its utilization. The access log files to main homepage were used to analyze the browsing patterns and converted to process log files adaptable to a process mining tool, ProM. Finally we provide useful information about user friendly homepage design and suggest plans for improving its utilization to website operators.

• Water for future
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• v.26 no.4
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• pp.73-83
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• 1993

This study focuses on the separation effect analysis of rainfall data for 2-parameter log-normal, 3-parameter log-normal, type-extreme value, 2-parameter gamma, 3-parameter gamma, log-Pearson type-III, and general extreme value distribution functions. Difference in the relationship between the mean and standard deviation of skewness for historical data and relations derived from 7 distribution functions are analyzed suing the Monte Carlo experiment. The results show that rainfall data has the separation effect for 6 distribution functions except 3-parameter gamma distribution function.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.93-106
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• 2004

Recently, many data of various types is gained with development of computer in many fields. Especially, web log data generating in web site furnish beneficial information on an organization. The enterprise's destiny is swayed by according as how these information gaining from the web site utilize. In this paper, for the purpose of obtaining useful information, we present a tool is called WebBizi for web log analysis. This will be helpful to enterprise working the web site.