• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.211-218
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• 2021

This paper deals with the computational work to characterize the formation and pinching of a plasma in an X-pinch configuration. A resistive magnetohydrodynamic model of a single fluid and two temperature is adopted assuming a hollow conical structure in the (r,z) domain. The model includes the thermodynamic parameter of tungsten from the corrected Thomas-Fermi EOS(equation of state), determining the average ionization charge, pressure, and internal energy. The transport coefficients, resistivity and thermal conductivity, are obtained by the corrected Lee & More model and a simple radiation loss rate by recombination process is considered in the simulation. The simulation demonstrated the formation of a core-corona plasma and intense compression process near the central region which agrees with the experimental observation in the X-pinch device at Seoul National University. In addition, it confirmed the increase in radiation loss rate with the density and temperature of the core plasma.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.679-687
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• 2020

This study quantitatively analyzed the effects of self-efficacy in the workplace on job-stress and work-life balance (WLB) using a structural equation model (SEM) to seek ways to increase the WLB. Because the current government promotes the 52-hour weekly policy, WLB that refers to the balance between work and life that is used throughout society. In addition, self-efficacy, which was used mainly in the home and education system, has expanded its scope of application, and efforts to increase it in the workplace are working as demand for the times. The observation variables to be included in the SEM were collected from a questionnaire of 5,454 adults, and AMOS 21 was used for statistical analysis. As a result of the analysis, self-efficacy in the workplace has a negative correlation with stress, and a higher self-efficacy means a higher WLB. The results of this study did not show that the more workers are passionate about their work in the workplace due to work-oriented thinking and behavior rather than home had a lower WLB. In addition, these results can be used to analyze the WLB policy in the ROK Army.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.65-73
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• 2021

The maintenance of the guided missiles typically requires the efficient management of spare parts and maintenance time. This study analyzed the impact of the maintenance time on operational availability. This study classifies the maintenance team with consideration of the skill level of the Harpoon guided missile maintenance and the goal is to analyze the impact on the operational availability with the skill levels quantitatively. Based on the real maintenance data of Harpoon guided missiles, a simulation model is constructed and analyzed. The analysis of the simulation result shows the trade-off between the maintenance time and operational availability. It is expected that the simulation model can help the maintenance policies of guided missiles.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.87-101
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• 2021

Required Operational Capability(ROC), which means the performance of a weapon system, is determined when estimating the requirements of a new weapon system. It is very important to define the ROC as it has a decisive influence from acquisition of a weapon system to tactical operation. In this study, we propose a simulation methodology to verify the ROC of the Para-Observation Munition(POM), a newly developed weapon system. To this end, we propose a discrete-event simulation model that takes main performance of the weapon system constituting the ROC and environmental factors that affect performance of the weapon system as input values, and outputs operational effect as a result value. It describes various simulation logic required to implement a simulation model, and explains how to verify ROC using various simulation results such as sensitivity analysis. POM is a weapon system that does not have a similar one and that is difficult to directly utilize the military analysis model. This study can be used as a methodology to analyze the ROC and predict operational effects of weapon systems such as POM.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.97-109
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• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.347-357
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• 2021

Since the outbreak of Covid-19, many countries have tried to defense Covid-19 to protect their people and as an influential and reliable policy as of now, they have recommended vaccinating. Thus, this research explored what influences the intention to vaccinate against Covid-19 with three health locus of control from multi-dimension health locus of control (MHLC) and perceived susceptibility and severity from health belief model (HBM) through PLS path modeling. Consequently, chance locus of control (CHLC) influence indirectly intention to vaccinate against Covid-19 mediating with susceptibility perception. It implies that the more fatalistic people attitude toward Covid-19, the more susceptible they perceived to the disease, and then, the stronger intention to vaccinate they would have. Thus, the health promotion authorities should motivate to activate people's susceptibility perception toward the disease through utilizing a variety of policies and consider that the fatalistic tendency toward the disease of people could play an antecedent role in the process.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.1-7
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• 2023

Convolutional neural networks have already been applied to various fields beyond human visual processing capabilities in the image processing area. However, they are exposed to a severe risk of deteriorating model performance due to the appearance of adversarial attacks. In addition, defense technology to respond to adversarial attacks is effective against the attack but is vulnerable to other types of attacks. Therefore, to respond to an adversarial attack, it is necessary to analyze how the performance of the adversarial attack deteriorates through the process inside the convolutional neural network. In this study, the adversarial attack of the Alexnet and VGG11 models was analyzed using the population sparseness index, a measure of neuronal activity in neurophysiology. Through the research, it was observed in each layer that the population sparsity index for adversarial examples showed differences from that of benign examples.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.9-21
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• 2023

The recent conflict between Russia and Ukraine underscores the significant of military logistics support in modern warfare. Military logistics support is intricate and specialized, and traditionally centered on the mission-level operational analysis and functional models. Nevertheless, there is currently increasing demand for military logistics support even at the engagement level, especially for resupply using unmanned transport assets. In response to the demand, this study proposes a task model of the military logistics support for engagement-level analysis that relies on the logic of ammunition resupply below the battalion level. The model employs a decisions tree to establish the priority of resupply based on variables such as the enemy's level of threat and the remaining ammunition of the supported unit. The model's feasibility is demonstrated through a combat simulation using OneSAF.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.319-326
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• 2010

Effectiveness analysis of weapon system has been accomplished using engagement-level model alone. However, most previous works are prone to errors due to lack of behavioral information about the weapon systems. In order to overcome these limitations, this paper proposes an interoperation approach between the engagement- and engineering-level models. The proposed approach enables the engagement-level model to be supported by the engineering-level model representing the detailed behavior of weapon systems. Our methodology consider a limited combat situation including operational environments, dynamics and operational errors of weapons, and engagement orders. The paper describes a formalization of the system effectiveness analysis and defines an interface for interoperation between engagement- and engineering-level models. Then, we perform an anti-torpedo combat simulation as a case study.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.47-55
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• 2023

This paper presents a method for predicting the threat index of combat systems using Gradient Boosting Regressors and Support Vector Regressors among machine learning models. Currently, combat systems are software that emphasizes safety and reliability, so the application of AI technology that is not guaranteed to be reliable is restricted by policy, and as a result, the electrified domestic combat systems are not equipped with AI technology. However, in order to respond to the policy direction of the Ministry of National Defense, which aims to electrify AI, we conducted a study to secure the basic technology required for the application of machine learning in combat systems. After collecting the data required for threat index evaluation, the study determined the prediction accuracy of the trained model by processing and refining the data, selecting the machine learning model, and selecting the optimal hyper-parameters. As a result, the model score for the test data was over 99 points, confirming the applicability of machine learning models to combat systems.