• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.541-554
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• 2023

The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.140-147
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• 2024

In order to increase the utilization of biomass, an electrochemical performance was considered after manufacturing a carbon anode material (SV-C) for a Setaria viridis-based lithium ion secondary battery through a heat treatment process. When the heat treatment temperature of the Setaria viridis is as low as 750 ℃, the capacitance (1003.3 mAh/g, at 0.1 C) is high due to the negative (-) charge of oxygen present on the surface attracting lithium, along with the low crystallinity and high specific surface area (126 m²/g), but the capacity retention rate is believed to be as low as 61.0% (at 500 cycles and 1 C). In addition, it was confirmed that when the heat treatment temperature increased to 1150 ℃, the carbon layer was condensed to be excellent in arrangement, and the structural defects were reduced, resulting in a significant reduction in the specific surface area (32 m²/g) of the pores. Furthermore, when the surface defects of the anode material are reduced and the crystallinity is increased, the capacity retention rate is as high as 89.7% (at 500 cycles and 1 C), but the degree of defects is small, the active point is reduced, and the specific capacity is considered to be very low at 471.7 mAh/g. In the scope of this study, it was found that in the case of the Setaria viridis-based carbon anode material manufactured according to the heat treatment temperature, the surface oxygen content and crystallinity have higher reliability on the electrochemical properties of the anode material than the specific surface area.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• Industry Promotion Research
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• v.9 no.1
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• pp.21-29
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• 2024

In the rapidly advancing information society, electronic devices, including smartphones and tablets, are increasingly digitized and equipped with high-performance features such as flexible displays. This study focused on optimizing the manufacturing process for Transparent Conductive Films (TCF) by using the cost-effective conductive polymer PEDOT and transparent substrate PET as alternatives to expensive materials in flexible display technology. The variables considered are production speed (m/min), coating maximum temperature (℃), and PEDOT supply speed (rpm), with surface resistivity (Ω/□) as the response parameter, using Response Surface Methodology (RSM). Optimization results indicate the ideal conditions for production: a speed of 22.16 m/min, coating temperature of 125.28℃, and PEDOT supply at 522.79 rpm. Statistical analysis validates the reliability of the results (F value: 18.37, P-value: < 0.0001, R²: 0.9430). Under optimal conditions, the predicted surface resistivity is 145.75 Ω/□, closely aligned with the experimental value of 142.97 Ω/□. Applying these findings to mass production processes is expected to enhance production yields and decrease defect rates compared to current practices. This research provides valuable insights for the advancement of flexible display manufacturing.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.147-156
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• 2023

Because the behavior of cable bridges is dominated by dynamic response and is relatively complex, short- and long-term field monitoring are often required to evaluate the bridge condition. If a permanent SHMS (Structural Health Monitoring System) is not installed, a portable monitoring system is needed for the checking of bridge condition. In this case, it can be difficult to operate the portable monitoring system due to limited conditions such as power and communication according to the location and type of the bridge. In this study, the portable-based smart structural response monitoring system is developed that can be effectively used for short- and long-term monitoring of cable bridges in Korea and Southeast Asia. The developed system is a multi-channel portable data acquisition and analyzer that can be operated for a long time in the field using its own power supply system, and is included with the automated analysis algorithm for the dynamic characteristics of cable bridges using real-time data. In order to evaluate the field applicability of the developed system, field demonstration was conducted on cable bridges in Korea and Vietnam. Through the demonstration, the reliability and efficiency of field operation of the developed system were confirmed, and additionally, the possibility of application to overseas markets was confirmed in cable bridge monitoring field.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.31-41
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• 2024

Deep learning models show excellent performance in tasks such as image classification and object detection in the field of computer vision, and are used in various ways in actual industrial sites. Recently, research on improving robustness has been actively conducted, along with pointing out that this deep learning model is vulnerable to hostile examples. A hostile example is an image in which small noise is added to induce misclassification, and can pose a significant threat when applying a deep learning model to a real environment. In this paper, we tried to confirm the robustness of the edge-learning classification model and the performance of the adversarial example detection model using it for adversarial examples of various algorithms. As a result of robustness experiments, the basic classification model showed about 17% accuracy for the FGSM algorithm, while the edge-learning models maintained accuracy in the 60-70% range, and the basic classification model showed accuracy in the 0-1% range for the PGD/DeepFool/CW algorithm, while the edge-learning models maintained accuracy in 80-90%. As a result of the adversarial example detection experiment, a high detection rate of 91-95% was confirmed for all algorithms of FGSM/PGD/DeepFool/CW. By presenting the possibility of defending against various hostile algorithms through this study, it is expected to improve the safety and reliability of deep learning models in various industries using computer vision.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.49-55
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• 2006

Measurement of impact sound insulation of floor, by current Korean Standard KS F 2810-2. is to be made with peak levels over 4 point in a receiving room. But it is often the case that there is inconsistency in results at various receiving points in the receiving room. Such variations obviously have effects on the repeatability and reproducibility of measured data. The result shows that there are even 10 dB deviations in 63Hz octave band frequency range and relatively less variations are occurred in other low frequency ranges. Such variations seems to be coming from modal overlaps of the receiving room. According to current rating method of floor impact sound. KS F 2863-2, that may affect on the single number latins scheme. From the result of tests in this study, there are 2dB to 6dB differences in the sin91e number with the combination of measurement points. This means that the reduction of measurement variations from the microphone positions is needed for a better credibility of measurement results.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.289-295
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• 2024

This study analyzes the correlation between the accracy of rifle and the result of engagement. And estimates the improvement cost of the rifle accordingly. For this experiment, an engagement class simulation model(AWAM: Army Weapon Effectiveness Analysis Model) was used. We also selected the rifle, which is a portable weapon for the experiment. Prior to this experiment, we conducted a reliability test(VV&A: Verification, Validation and Accreditation) on the model. The VV&A process is mainly done during the development of the DM&S model, which is also necessary for the operation of the M&S. We confirmed the need for VV&A during the experiment and obtained reliable experimental results using the corrected values. In the Accuracy Experiment we found that the 20% improvement is the most effective. And we were able to estimate the cost of acquiring a rifle with a 20% higher accuracy. The cost was estimated by simple regression analysis based on the price of the current rifle. Through this study, we could know the impact of the accuracy of rifle on the experimental results and estimate the cost of improved rifle.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.585-590
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• 2024

In this study, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of engineers and simple measuring tools. With the recent enactment of the Track Diagnosis Act, a large budget has been invested and the volume of rail diagnosis is rapidly increasing, but it is difficult to secure the reliability of diagnosis results using labor-intensive visual inspection techniques. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the rail internal crack characteristics due to rail surface damage were studied. In field measurements, rail surface damage locations were selected, samples of various damage types were collected, and the rail surface damage status was evaluated. In indoor testing, we intend to analyze the correlation between rail surface defects and internal defects using a electron scanning microscope (SEM). To determine the crack growth rate of urban railway rails currently in use, the Gaussian probability density function was applied and analyzed.