• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.116-126
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• 2021

Ground Component Command (GCC) has been developing operational planning and execution systems to implement "Decisive Integrated Operations", which is the concept of ground operations execution, and achieved remarkable results. In particular, "Simultaneous Offense-Defense Integrated Operations" is developed mainly to neutralize enemies in deep areas and develop favorable conditions for the allies early by simultaneously attacking and defending from the beginning of the war. On the other hand, it is limited to providing scientific and reasonable support for the commander's decision-making process because analyzing the effects of the deep operation with existing M&S systems is impossible. This study developed a model for analyzing the effects of deep operations that can be used in the KJCCS. Previous research was conducted on the effects of surveillance, physical strike, and non-physical strike, which are components of deep operations to find the characteristics and limitations and suggest a research direction. A methodology for analyzing the effects of deep operations reflecting the interactions of components using data was then developed by the GCC, and input data for each field was calculated through combat experiments and a literature review. Finally, the Deep operations Effect CAlculating Model(DECAM) was developed and distributed to the GCC and Corps battle staff during the ROK-US Combined Exercise. Through this study, the effectiveness of the methodology and the developed model were confirmed and contribute to the development of the GCC and Corps' abilities to perform deep operations.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.1-7
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• 2017

The purpose of this paper is to examine how multi-cultural acceptability affects the perception of necessity of unification through structural equation model. The multi-cultural acceptability, familiarity with North Korean defectors, and awareness of unification were selected as the latent variables and the full / partial mediator models were built for structural equations. The observed variables for each latent variable were data that were collected through the National Survey on the Integration of North and South Korea conducted by the Korea Institute for National Unification in 2015. As a result, the acceptance of multiculturalism had a significant effect on the intimacy of the defectors, which had a positive effect on the recognition of the need for unification. The intimacy of the defectors was more influential as a parameter for full mediation than for partial mediation. Although the consciousness of unification gets weakened by postwar generations, that the phenomenon that changes into a multicultural society plays a part in recognizing the necessity of unification. In addition, the increase of North Korean defectors may ultimately become a factor in recognizing the need for unification. This study demonstrated that increasing the acceptance of multiculturalism can increase the need for unification, which means that more research fields can be derived.

• Korean Journal of Clinical Pharmacy
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• v.18 no.1
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• pp.38-44
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• 2008

Rebamipide, ($\pm$)-2-(4-chlorobenzoylamino)-3-[2(1H)-quinolinon-4-yl] propionic acid, is used for mucosal protection, healing of gastroduodenal ulcers, and treatment of gastritis. It works by enhancing mucosal defense, scavenging free radicals and temporarily activating genes encoding cyclooxygenase-2. The purpose of the present study was to evaluate the bioequivalence of two rebamipide tablets, $Mucosta^{(R)}$ (Korea Otsuca Pharmaceuticals Co., Ltd.) and Mustar (Korean Drug Co., Ltd.), according to the guidelines of the Korea Food and Drug Administration (KFDA). The release of rebamipide from the two rebamipide formulations in vitro was tested using KP VIII Apparatus II method with pH 6.8 dissolution medium. Twenty six healthy male subjects, $23.46{\pm}2.63$ years in age and $66.62{\pm}8.97\;kg$ in body weight, were divided into two groups and a randomized $2{\times}2$ cross-over study was employed. After a single tablet containing 100 mg as rebamipide was orally administered, blood samples were taken at predetermined time intervals and the concentrations of rebamipide in serum were determined using HPLC with fluorescence detector. The dissolution profiles of two formulations were similar in the tested dissolution medium. The pharmacokinetic parameters such as $AUC_t$, $C_{max}$ and $T_{max}$ were calculated, and ANOVA test was utilized for the statistical analysis of the parameters using logarithmically transformed $AUC_t$, $C_{max}$ and untransformed $T_{max}$. The results showed that the differences between two formulations based on the reference drug, $Mucosta^{(R)}$ were -5.08, 3.52 and -9.71 % for $AUC_t$, $C_{max}$ and $T_{max}$, respectively. There were no sequence effects between two formulations in these parameters. The 90% confidence intervals using logarithmically transformed data were within the acceptance range of log 0.8 to log 1.25 (e.g., log 0.84$\sim$log 1.07 and log 0.90$\sim$log 1.17 for $AUC_t$ and $C_{max}$, respectively). Thus, the criteria of the KFDA bioequivalence guideline were satisfied, indicating Mustar tablet was bioequivalent to $Mucosta^{(R)}$ tablet.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.143-150
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• 2021

It introduces the contents of establishing a geostationary satellite-based forest fire monitoring system that can monitor areas of the Korean Peninsula 24 hours a day for forest fire monitoring, and describes how to establish a forest fire monitoring system and use it in various ways. In order to establish a satellite-utilized forest fire monitoring system, we will describe and draw conclusions on literature research, technical principles, forest fire monitoring means, and satellite forest fire monitoring system. The satellite-utilized forest fire monitoring system can consist of one geostationary satellite equipped with infrared detection optical sensors and a ground processing station that processes data received from satellites to spread surveillance information. Forest fire monitoring satellites are located in the country's geostationary orbit and should be operated 24 hours a day, 365 days a day. Forest fire monitoring technology is an infrared detection technology that can be used in national public interests such as forest fire monitoring and national security. It should be operated 24 hours a day, and to satisfy this, it is efficient to establish a geostationary satellite-based forest fire monitoring satellite system.

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.475-483
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• 2019

Special chemical warfare agents are lethal gases that attack the human respiratory system. One of such gases are blood agents that react with the irons present in the electron transfer system of the human body. This reaction stops internal respiration and eventually causes death. The molecular sizes of these agents are smaller than the pores of an activated carbon, making chemical adsorption the only alternative method for removing them. In this study, we carried out a Computational Fluid Dynamics simulation by passing a blood agent: cyanogen chloride gas through an SG-1 gas mask canister developed by SG Safety Corporation. The adsorption bed consisted of a Silver-Zinc-Molybdenum-Triethylenediamine activated carbon impregnated with copper, silver, zinc and molybdenum ions. The kinetic analysis of the chemical adsorption was performed in accordance with the test procedure for the gas mask canister and was validated by the kinetic data obtained from experimental results. We predicted the dynamic behaviors of the main variables such as the pressure drop inside the canister and the amount of gas adsorbed by chemisorption. By using a granular packed bed instead of the Ergun equation that is used to model porous materials in Computational Fluid Dynamics, applicable results of the activated carbon were obtained. Dynamic simulations and flow analyses of the chemical adsorption with varying gas flow rates were also executed.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.157-171
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• 2022

Electrical resistivity tomography (ERT) is a traditional and representative geophysical method for determining the resistivity distributions of surrounding soil and rock volumes. Depth resolution profiles and sensitivity distribution sections of the resistivities with respect to various electrode configurations are calculated and investigated using numerical model data. Shallow vertical resolution decreases in the order of Wenner, Schlumberger, and dipole-dipole arrays. A high investigable depth in homogeneous medium is calculated to be 0.11-0.19 times the active electrode spacing, but is counterbalanced by a low vertical resolution. For the application of ERT depth resolution profiles and sensitivity distributions, we provide subsurface structure models for two types of land-creping failure (planar and curved), subvertical fracture, and weathered layer over felsic and mafic igneous rocks. The dipole-dipole configuration appears to be most effective for mapping land-creeping failure planes (especially for curved planes), whereas the Wenner array gives the best resolution of soil horizons and shallow structures in the weathered zone.

• Management & Information Systems Review
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• v.39 no.2
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• pp.39-60
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• 2020

Block chain technology is one of the core elements for realizing the 4^th industrial revolution, and many efforts have been made by government and companies to provide services based on block chain technology. In this study we analyzed the benefits of block chain technology for EVMS and designed EVMS block chain platform with increased data security and work efficiency for project management data, which are important assets in monitoring progress, foreseeing future events, and managing post-completion. We did the case studies on the benefits of block chain technology and then conducted the survey study on security, reliability, and efficiency of block chain technology, targeting 18 block chain experts and project developers. And then, we interviewed EVMS system operator on the compatibility between block chain technology and EVM Systems. The result of the case studies showed that block chain technology can be applied to financial, logistic, medical, and public services to simplify the insurance claim process and to improve reliability by distributing transaction data storage and applying security·encryption features. Also, our research on the characteristics and necessity of block chain technology in EVMS revealed the improvability of security, reliability, and efficiency of management and distribution of EVMS data. Finally, we designed a network model, a block structure, and a consensus algorithm model and combined them to construct a conceptual block chain model for EVM system. This study has the following contribution. First, we reviewed that the block chain technology is suitable for application in the defense sector and proposed a conceptual model. Second, the effect that can be obtained by applying block chain technology to EVMS was derived, and the possibility of improving the existing business process was derived.