• Informatization Policy
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• v.30 no.4
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• pp.3-39
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• 2023

With the growing importance of information/information system, information security is emphasized, and the significance of information security audit as a tool for maintaining the proper security level is increasing as well. The objectives of the study are to identify the overall research trends and to propose future research areas by analyzing domestic and overseas research in the area. To achieve the objectives, 103 research papers were analyzed based on both general and subject-related criteria. The following are the major research results : In terms of research approach, more empirical studies are needed; For subject "Auditor," studies to develop a framework for related variables (e.g., capability) are needed; For subject "Audit Activities/Procedures," future research should focus on the process/results of detailed audit activities; Future domestic research for "Audit Areas" should look for the new technology/industry/security areas covered by foreign studies; For "Audit Objective/Impact," studies to define the variables (e.g., performance and quality) systematically and comprehensively are needed; For "Audit Standard/Guidelines," research on model/guideline needs to be continued.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1529-1539
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• 2023

The data from Geostationary Ocean Color Imager-II (GOCI-II), which observes the color of the sea to monitor marine environments, undergoes various correction processes in the ground station system, producing data from Raw to Level-2 (L2). Quality issues arising at each processing stage accumulate step by step, leading to an amplification of errors in the satellite data. To address this, improvements were made to the GOCI-II ground station system to measure potential optical quality and geolocation accuracy errors in the Level-1A/B (L1A/B) data. A newly established Radiometric and Geometric Performance Assessment Module (RGPAM) now measures five optical quality factors and four geolocation accuracy factors in near real-time. Testing with GOCI-II data has shown that RGPAM's functions, including data processing, display and download of measurement results, work well. The performance metrics obtained through RGPAM are expected to serve as foundational data for real-time radiometric correction model enhancements, assessment of L1 data quality consistency, and the development of reprocessing strategies to address identified issues related to the GOCI-II detector's sensitivity degradation.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Atmosphere
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• v.24 no.3
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• pp.303-315
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• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.6
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• pp.16-24
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• 2015

This study quantified storage and annual uptake of carbon for riparian greenspaces established in watersheds of four major rivers in South Korea and explored desirable strategies to improve carbon reduction effects of riparian greenspaces. Greenspace structure and planting technique in the 40 study sites sampled were represented by single-layered planting of small trees in low density, with stem diameter at breast height of $6.9{\pm}0.2cm$ and planting density of $10.4{\pm}0.8trees/100m^2$ on average. Storage and annual uptake of carbon per unit area by planted trees averaged $8.2{\pm}0.5t/ha$ and $1.7{\pm}0.1t/ha/yr$, respectively, increasing as planting density got higher. Mean organic matter and carbon storage in soils were $1.4{\pm}0.1%$ and $26.4{\pm}1.5t/ha$, respectively. Planted trees and soils per ha stored the amount of carbon emitted from gasoline consumption of about 61 kL, and the trees per ha annually offset carbon emissions from gasoline use of about 3 kL. These carbon reduction effects are associated with tree growth over five years to fewer than 10 years after planting, and predicted to become much greater as the planted trees grow. This study simulated changes in annual carbon uptake by tree growth over future 30 years for typical planting models selected as different from the planting technique in the study sites. The simulation revealed that cumulative annual carbon uptake for a multilayered and grouped ecological planting model with both larger tree size and higher planting density was approximately 1.9 times greater 10 years after planting and 1.5 times greater 30 years after than that in the study sites. Strategies to improve carbon reduction effects of riparian greenspaces suggest multilayered and grouped planting mixed with relatively large trees, middle/high density planting of native species mixed with fast-growing trees, and securing the soil environment favorable for normal growth of planting tree species. The research findings are expected to be useful as practical guidelines to improve the role of a carbon uptake source, in addition to water quality conservation and wildlife inhabitation, in implementing riparian greenspace projects under the beginning stage.

• 한국해양학회지
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• v.30 no.5
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• pp.403-412
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• 1995

The present study was performed to determine th growth and production of Mactra veneriformis on the Songdo tidal flat off Inchon. west coast of Korea. Monthly samples were collected from Marc 1989 to September 1990. The size distributions of shell length showed unimodal patterns from March to August 1989. The binodal pattern after September 1989 indicated a recruitment of young clams during this period. The density fluctuated irregularly, but showed a decreasing pattern over time on the whole. The density of the year class 1989 increased markedly after February 1990. The growth in shell length showed three phases during a year, a fast growth phase in spring, a slow growth phase in summer and autumn, and a lag phase in winter. The annual increment in shell length reduced with age. The flesh dry weight showed a peak in late spring just before the spawning period, and another peak in autumn. The length of annuli and the back-calculated flesh dry weight were used to describe the annual growth. The growth in shell length fitted to the von Bertalanffy model and the flesh dry weight to the Gompertz model. The absolute growth rate of the shell length reduced gradually with age. The year class 1985 had the highest L, and the yeat class 1986 the lowest L. The annual growth in weight showed a typical sigmoid curve. The growth rate was maximum at the age of 2 to 3. Year classes of 1984 and 1985 had higher values of W and higher absolute growth rates than those of 1986 and 1987. Maximum absolute growth rates of 1986 and 1987 year classes were recorded at younger ages than 1984 and 1985 year classes. The annual relative growth rates of length and weight decreased exponentially with age. Biomass in flesh dry weight increased till spring and thereafter decreased progressively. Maximum biomass was 134.6g m/SUP -2/ in August 1990. The biomass of 1989 yeat class occupied highest proportion in total biomass. Annual production in flesh dry weight from March 1989 to March 1990 was 67.9 g m/SUP -2/ year/SUP -1/. Cumulative production of 1989 year class was highest among all year classes, and that of year class 1984 was lowest. The production is high in spring and autumn, and very low in summer and winter.

• KSBB Journal
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• v.14 no.3
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• pp.328-336
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• 1999

A green microalga, Chlorella vulgaris UTX 259, was cultivated in a bench-scale raceway pond. During the culture, 15%(v/v) $CO_2$ was supplied and industrial wastewater discharged from a steel-making plant was used as a culture medium. In a small scale culture bottle, the microalga grew up to 1.8 g $dm^{-3}$ of cell concentration and ammonia was completely removed from the wastewater with an yield coefficient of 25.7 g dry cell weight $g^{-1}\;NH_3-N$. During the bottle-culture, microalga was dominant over heterotrophic microorganisms in the culture medium. Therefore, the amount of carbon dioxide fixation could be estimated from the change of dry cell weight. In a semi-continuous operation of raceway pond with intermittent lighting (12 h light and 12 h dark), increase of dilution rate resulted in increase of the ammonia removal rate as well as the $CO_2$ fixation rate but the ammonia removal efficiency decreased. Ammonia was not completely removed from the medium (wastewater) of raceway pond which was operated in a batch mode under a light intensity up to 20 klux. The incomplete removal of ammonia was believed due to insufficient light supply. A mathematical model, capable of predicting experimental data, was developed in order to simulate the performance of the raceway pond under the light intensity of sun during a bright daytime. Simulation results showed that the rates of $CO_2$ fixation and ammonia removal could be enhanced by increasing light intensity. According to the simulation, 80 mg $dm^{-3}$ of ammonia in the medium could be completely removed if the light intensity was over 60 klux with a continuous lighting. Under the optimal operating condition determined by the simulation, the rates of carbon dioxide fixation and ammonia removal in the outdoor operation of raceway pond were estimated as high as $24.7 g m^{-2} day^{-1}$ and $0.52 g NH_3-N m^{-2} day^{-1}$, respectively.

• Journal of Korean Society of Forest Science
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• v.82 no.4
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• pp.420-430
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• 1993

This study was conducted to investigate the effect of the forest environmental factors(5 items) and physico-chemical properties of soil(13 items) on the growth of Pinus thunbergii stands. The 218 plots were sampled over the coastal district of the whole country. In statistical analysis, the explanatory variables were soil and environmental factors(18 items), and the response variable was the site index of Pinus thunbergii stands. Data computation was processed in order of preparation of original data, computation of inner correlation matrix table by correlation analysis, calculation of partial correlation coefficients and coefficients of determination, estimation of regression equation by stepwise begression analysis, and stepwise regression analysis by factor score of factor analysis. The main results obtained were summarized as follows ; 1. The site index in Pinus thunbergii stands way highly correlated with effective soil depth(r=0.8668), slope percentage, organic matter, and total nitrogen. 2. According to the coefficients by partial correlation analysis, effective soil depth(r=0.6270), slope percentage (r=-0.5423) and base saturation(r=0.3278) among environmental factors had a great effect on tree growth. 3. With stepwise regression analysis, the factors effecting on the Pinus thunbergii stands growth were effective soil depth, slope percentage, organic matter, base saturation, soil pH, content of silt, exchangeable Ca, and etc. 4. Estimation equation for the site index of Pinus thunbergii stands was given by $Y=13.2691+0.0242\;X_2-1.2244\;X_4+0.6142\;X_5-0.3472\;X_{11}+0.0355\;X_{13}+0.1552\;X_{15}-0.1002\;X_{17}$. The coefficient of determination for the estimation model was 0.77, which was significant at the 1 percent level. 5. In result of factor analysis by the environmental factors, principal components were 6 factors, and communality contribution percentage was 71.1 percent. 6. By stepwise regression analysis between factor score and site index of Pinus thunbergii stands, the factor group effecting on site index was 5 principal components. The coefficients of determination was 85 percent, which was significant at the 1 percent level. In conclusion, on the occasion of analizing which factors to effect on the tree height growth in Pinus thunbergii stands the stepwise regression analysis proved to be greatly significant. Also the management of Pinus thunbergii stands should be working by the above selected growth factors.

• Clinical and Experimental Pediatrics
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• v.48 no.2
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• pp.197-203
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• 2005

Purpose : Changes in metalloproteinases(MMP) activity have been demonstrated in several disease states, including rheumatoid arthritis and tumor metastasis. More importantly, increased myocardial MMP activity has been reported to occur in both clinical and experimental forms of dilated cardiomyopathy. There was no report about MMP in adriamycin(ADR)-induced cardiomyopathy. The purpose of this study was to investigate gene expression of MMP and tissue inhibitor of metalloproteinases(TIMP) in ADR-induced cardiomyopathy and clarify the relationship between MMP and cytokines. Methods : Male Sprague-Dawley rats were divided into two groups. The first group was control. The second group was given intraperitoneal injections of ADR(5 mg/kg) twice a week over two weeks. Serum concentrations of MMP, TIMP, interleukin(IL)-6 and tumor necrosis factor(TNF)-${\alpha}$ were measured. RNA extraction was performed from frozen rat hearts. Reverse transcription polymerase chain reaction(RT-PCR) was employed. cDNA Microarray analysis was performed by using a set of 5,184 sequence-verified rat cDNA clones. Results : Serum MMP and TIMP levels were not significantly different between the two groups. IL-6 was $36.8{\pm}2.8pg/mL$ and TNF-${\alpha}$ $2.2{\pm}2.7pg/mL$ in the ADR group. They were significantly higher than in the control group. Serum MMP correlated significantly with TNF-${\alpha}$(r=0.41, P<0.05). There was no gene expression of MMP, IL-6 or TNF-${\alpha}$ in the hearts of both groups. Gene expression of TIMP was significantly depressed in the hearts of the ADR group. Conclusion : These results suggested a potential role for TNF-${\alpha}$ in the regulation of extracellular matrix remodeling in ADR induced cardiomyopathy. Rapid screening of multiple decreased gene expression by DNA chip may be a useful diagnostic test to detect early cardiac injury before developing ADR induced cardiomyopathy.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.