• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.617-627
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• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1273-1300
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• 2024

In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

• Convergence Security Journal
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• v.23 no.4
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• pp.81-92
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• 2023

In recent years, the ROK military is promoting Defense Innovation 4.0 with the goal of fostering strong military based on science and technology equipped with artificial intelligence(AI) to prepare for the upcoming population cliff. In particular, at the present time of increased threats of North Korea, the South Korean military is seeking to deal with a decrease in military service resources through the introduction of a Scientific Guard System using advanced technology. TICN which is a core basic communication system to ensure the integrated combat capability of the ROK military is, however, limited to use as a based network for the emerging Scientific Guard System due to the narrow transmission bandwidth with widely spread poor reception area. To deal with this problem, this paper proposes TVWS-based Scientific Guard Systems with TVWS-based wireless network construction technology that has been available for free in Korea since 2017. The TVWS-based Scientific Guard System proposed in this paper, when compared to the existing wired network-based Scientific Guard Systems, has various advantages in terms of minimizing operational gaps, reducing construction costs, and flexibility in installation and operation.

• The Korea Journal of Herbology
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• v.22 no.2
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• pp.51-63
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• 2007

Objectives : For the congenital feeble, the Gongjindan is useful medicine. The experiment is to estimate the value of the Gongjindan as therapeutic agent preventing against aging with an analysis of the ingredients and the bio-activating effects by enzymologic methods. Methods : General ingredients' of the Gongjindan's extract were analyzed first and the quantitative analysis of a reducing sugar, a soluble protein, an amino acid and minerals was made. The Gongjindan, which is extracted, concentrated, and freeze drying with water, ethanol and chloroform, have got applied for the experiment. The effects on electronic donating ability, SOD-like activity, nitric oxide inhibition, xanthine oxidase inhibition, whitening effect have been investigated in the physiological activity measurement of function experiment. Results : The contained amino acid, in order of high amount, is Arginine, Alanine, Glutamic acid, Proline and the contained free amino acid is Glutamic acid, Leucine, Lysine, Phenylalanine. The derivative of free amino acid is ${\gamma}-Aminoisobutyric$ acid, Phosphoserine, Taurine. And the Gongjindan is containing 13 species of minerals in order of Ca>K>Na>Mg>Fe>AI>Mn. Then, to assure of the Gongjindan's capability of anti-oxidation, these following subjects-polyphenol, electronic donating ability, SOD-like activity, nitric oxide inhibition, xanthine oxidase inhibition, tyrosinase inhibition- are analyzed and show high activity especially the most in ethanol extracts. Conclusion : With this analysis of ingredients, the Gongjindan is containing many materials functioning as anti-oxidation, anti-aging, anti-fatigue, neurotransmitter and immune agent. Moreover, In every water, ethanol, chloroform extracts, the Gongjindan's capability of anti-oxidation is confirmed so that we can apply to patients' treatment clinically.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.45-50
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• 2023

In software development, the elicitation and analysis of requirements is a crucial phase, and it involves considerable time and effort due to the involvement of various stakeholders. ChatGPT, having been trained on a diverse array of documents, is a large language model that possesses not only the ability to generate code and perform debugging but also the capability to be utilized in the domain of software analysis and design. This paper proposes a method of requirements engineering that leverages ChatGPT's capabilities for eliciting software requirements, analyzing them to align with system goals, and documenting them in the form of use cases. In software requirements engineering, it suggests that stakeholders, analysts, and ChatGPT should engage in a collaborative model. The process should involve using the outputs of ChatGPT as initial requirements, which are then reviewed and augmented by analysts and stakeholders. As ChatGPT's capability improves, it is anticipated that the accuracy of requirements elicitation and analysis will increase, leading to time and cost savings in the field of software requirements engineering.

• Korean Journal of Poultry Science
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• v.32 no.2
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• pp.113-123
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• 2005

Avian influenza (AI) virus (AIV) is distributed worldwide and it has been isolated from various species of wild and domestic birds. AI transfers with high speed and shows diverse pathogenicity syndroms. In Korea, several low Pathogenic AIV, H9N2, have been isolated from the commercial farms with severe decrease of egg production and mortality resulted in severe economic loss since 1996. Therefore, it has been requested to develop AI vaccines to prevent clinical signs and economic losses from the field infection of AIV. To develop a killed vaccine that efficiently prevents low pathogenic AIV (H9N2), evaluation on the pathogenicity and selection of an inactivator for H9N2 is taking place and is being tested safety and immunogenicity of vaccine produced. Based on the pathogenicity test and viral reisolation test, the ADL0401 isolate is the characteristic low pathogenic AIVs and has fairly similar biologic functions compared with MS96 which is the official low pathogenic AIV (H9N2) and one of the predominant AIV isolated from poultry farms in Korea. In antigenicity tests, the ADL0401 and MS96 virus have no significant antigenic difference. In inactivation tests, the ADL0401 isolates can be easily inactivated with $0.1\%$ Formalin at $37^{\circ}C$ within 1 hour with a little decrease of HA titer. The vaccine developed in the present report has no harmful effect on bird and forms good immune capability. Therefore, the isolates, ADL0401 can be used for a killed vaccine which can reduce the clinical signs and viral shedding in the birds infected with H9N2 low pathogenic AIVs.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.5
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• pp.285-295
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• 1999

Electroluminescent(EL) devices based on organic materials have been of great interest due to their possible applications for large-area flat-panel displays. They are attractive because of their capability of multi-color emission, and low operation voltage. An approach to realize such device characteristics is to use active layers of lanthanide complexes with their inherent extremely sharp emission bands in stead of commonly known organic dyes. In general, organic molecular compounds show emission due to their $\pi$-$\pi*$ transitions resulting in luminescence bandwidths of about 80 to 100nm. Spin statistic estimations lead to an internal quantum efficiency of dye-based EL devices limited to 25%. On the contrary, the fluorescence of lanthanide complexes is based on an intramolecular energy transfer from the triplet of the organic ligand to the 4f energy states of the ion. Therefore, theoretical internal quantum efficiency is principally not limited. In this study, Powders of TPD, $Eu(TTA)_3(phen) and AlQ_3$ in a boat were subsequently heated to their sublimation temperatures to obtain the growth rates of 0.2~0.3nm/s. Organic electrolumnescent devices(OELD) with a structure of $glass substrate/ITO/Eu(TTA)_3(phen)/AI, glass substrate/ITO/TPD/Eu(TTA)_3(phen)/AI and glass substrate/ITO/TPD/Eu(TTA)_3(phen)/AIQ_3AI$ structures were fabricated by vacuum evaporation method, where aromatic diamine(TPD) was used as a hole transporting material, $Eu(TTA)_3(phen)$ as an emitting material, and Tris(8-hydroxyquinoline)Aluminum$(AlQ_3)$ as an electron transporting layer. Electroluminescent(EL) and current density-voltage(J-V) characteristics of these OELDs with various thickness of $Eu(TTA)_3(phen)$ layer were investigated. The triple-layer structure devices show the red EL spectrum at the wavelength of 613nm, which is almost the same as the photoluminescent(PL) spectrum of $Eu(TTA)_3(phen)$.It was found from the J-V characteristics of these devices that the current density is not dependent on the applied field, but on the electric field.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.198-200
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• 2006

This paper presents a development of an educational simulator of particle swarm optimization (PSO) and application for solving the test functions and economic dispatch (ED) problems with nonsmooth cost functions. A particle swarm optimization is one of the most powerful methods for solving global optimization problems. It is a population-based search algorithm and searches in parallel using a group of particles similar to other AI-based heuristic optimization techniques. In developed simulator, lecturers and students can select the functions for simulation and set the parameters that have an influence on PSO performance. To improve searching capability for ED problems, a crossover operation is proposed to the position update of each individual (CR-PSO). To verify the feasibility of CR-PSO method, numerical studies have been performed for two different sample systems. The proposed CR-PSO method outperforms other algorithms in solving ED problems.