• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.667-677
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• 2013

As the firewall is a typical network security equipment, it is usually installed at most of internal/external networks and makes many packet data in/out. So analyzing the its logs stored in it can provide important and fundamental data on the network security research. However, along with development of communications technology, the speed of internet network is improved and then the amount of log data is becoming 'Massive Data' or 'BigData'. In this trend, there are limits to analyze log data using the traditional database model RDBMS. In this paper, through our Method of Analyzing Firewall log data using MapReduce based on NoSQL, we have discovered that the introducing NoSQL data base model can more effectively analyze the massive log data than the traditional one. We have demonstrated execellent performance of the NoSQL by comparing the performance of data processing with existing RDBMS. Also the proposed method is evaluated by experiments that detect the three attack patterns and shown that it is highly effective.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.453-469
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• 2022

The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.593-600
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• 2018

Owing to the advancement of Internet and smart devices, access to various media such as social media became easy; thus, a large amount of big data is being produced. Particularly, the companies that provide various Internet services are analyzing the big data by using the MapReduce-based big data analysis techniques to investigate the customer preferences and patterns and strengthen the security. However, with MapReduce, when the big data is analyzed by defining the number of reducer objects generated in the reduce stage as one, the processing rate of big data analysis decreases. Therefore, in this paper, a MapReduce-based split big data analysis method is proposed to improve the log analysis processing rate. The proposed method separates the reducer partitioning stage and the analysis result combining stage and improves the big data processing rate by decreasing the bottleneck phenomenon by generating the number of reducer objects dynamically.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.541-542
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• 2017

In this paper, we intend to develop an integrated management solution that can be easily operated by integrating complex and various cloud environments. This has the advantage that users and administrators can conveniently solve problems by collecting and analyzing fixed log data and unstructured log data based on big data and realizing integrated monitoring in real time. Hypervisor log pattern analysis technology will be able to manage existing complex and various cloud environment more efficiently.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.185-194
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• 2007

The information of covariates are available to do fully efficient fractional imputation(FEFI). The new method, FEFI with logistic regression is proposed to construct complete contingency tables. Jackknife method is used to get a standard errors of log-odds ratio from the completed table by the new method. Simulation results, when covariates have more information about categorical variables, reveal that the new method provides more efficient estimates of log-odds ratio than either multiple imputation(MI) based on data augmentation or complete case analysis.

• Convergence Security Journal
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• v.17 no.5
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• pp.35-40
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• 2017

The control system can have such threats as information leakage and falsification through various routes due to communications network fusion with public network. As the issues about security and the infringe cases by new attack methods are diversified recently, with the security system that makes information data database by simply blocking and checking it is difficult to cope with new types of threats. It is also difficult to respond security threats by insiders who have security access authority with the existing security equipment. To respond the threats by insiders, it is necessary to collect and analyze Event Log occurring in the internal system realtime. Therefore, this study could find out whether there is correlation of the elements among Event Logs through correlation analysis based on Event Logs that occur real time in the control system, and based on the analysis result, the study is expected to contribute to studies in this field.

• Geosciences Journal
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• v.22 no.6
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• pp.1015-1026
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• 2018

This paper aims to investigate the good reservoir quality and hydrocarbon potentiality of the Khatatba Formation, Qasr Field in the Shoushan Basin of the North Western Desert, Egypt by combining results from log-based petrophysical analysis, petrographic description and images from scanning electron microscope (SEM). Promising reservoir units are initially identified and evaluated through well log analysis of three wells in the field of study. Petrophysical results are then compared with petrographic and SEM images from rock samples to identify features that characterize the reservoir quality. Well log results show that Khatatba Formation in the study area has good sandstone reservoir intervals from depths ranging from 12848 ft to 13900 ft, with good effective porosity records of 13-15% and hydrocarbon saturations of greater than 83%. Petrographic analysis of these sandstone reservoir units indicate high concentrations of vacant pore spaces with good permeability that can be easily occupied by hydrocarbon. The availability of these pore spaces are attributed to pore-enhancing diagenetic features, mainly in the form of good primary porosity and dissolution. SEM images and EDX analysis confirmed the presence of hydrocarbon, therefore indicating a good hydrocarbon-storing potential for the Khatatba Formation sandstones.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.88-91
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• 2001

The reliability data analysis for components of CNC machining center is studied in this paper. The failure data of mechanical part is analyzed by Exponetial, Weibull, and Log-normal distributions. And then, the optimum failure distribution model is selected by goodness of fit test. The reliability data analysis program is developed using ASP language. The failure rate, MTBF, life, and failure mode of mechanical parts are estimated and searched by this program. The failure data and analysis results are stored in the database.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.218-225
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• 1995

In this paper, a mechanical analysis model for steep-slope log-skidding operations of a rubber-tired tractor is discussed and the applicability of the model is investigated. The model largely consists of mathematical analysis models for log drag, dynamic vehicle weight distributions and soil-vehicle traction. For the case study, a theoretical data set for log skidding operations is used in investigating the effect of the factors influencing the results of mechanical analysis or the productivity of skidding operations. The analyses include 1) the effect of log choking methods on tangential log-skidding force, 2) the effects of the change in travel speed and log load on the required input power to the wheels and 3) the log skidding performance of a two-wheel drive compared with that of a four-wheel drive.

• The Journal of Information Systems
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• v.23 no.1
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• pp.185-202
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• 2014

ERP, a typical enterprise application, helps companies to increase their productivity and to support their decision makings. ERP is composed of diverse functions that are optimized under PC environment, whereas the ERP applications on a mobile platform have many constraints such as a small screen, limited resolution, and computing power. Because all the functions of a ERP legacy system are not required for ERP on a mobile device, the core functions of the ERP system should be selected to increase system efficiency. In this study, two main methods were used; interviews and log analyses. The end users using a ERP system were interviewed for their perceptions, and log data analyses were made for the hitting number of specific ERP functions. The differences between the actual usage based on log data and users' cognitive preferences about ERP functions were analysed. Finally, the functional differences between users' perception and actual usage were suggested for some practical implications.