• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.132-133
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• 2023

The safe evacuation of people during disasters is of utmost importance. Various life safety evacuation simulation tools have been developed and implemented, with most relying on algorithms that analyze maps to extract the shortest path and guide agents along predetermined routes. While effective in predicting evacuation routes in stable disaster conditions and short timeframes, this approach falls short in dynamic situations where disaster scenarios constantly change. Existing algorithms struggle to respond to such scenarios, prompting the need for a more adaptive evacuation route algorithm that can respond to changing disasters. Artificial intelligence technology based on reinforcement learning holds the potential to develop such an algorithm. As a fundamental step in algorithm development, this study aims to evaluate whether an evacuation algorithm developed by reinforcement learning satisfies the performance conditions of the evacuation simulation tool required by IMO MSC.1/Circ1533.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.497-516
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• 2023

The purpose of this study is to explore the possibility of enhancing teachers' pedagogical design capacity using ChatGPT. For this purpose, a survey was conducted to investigate preservice teachers' perceptions of ChatGPT, and lesson plans created using ChatGPT were analyzed from the perspectives of design elements, conversations with ChatGPT, and information transforming. The results showed that pre-service teachers have a rather passive attitude toward the use of ChatGPT, and that teacher moderation and ChatGPT characteristics affect pre-service teachers' perceptions of the use of ChatGPT. In addition, pre-service teachers mainly used ChatGPT for motivational activities and play activities, and there were significant differences in the level of utilization of ChatGPT among individuals, i.e., how they interacted with ChatGPT and how they transformed information. Based on these findings, we explored the possibility of using ChatGPT for teacher professional development and teacher education.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.629-634
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• 2023

In this paper, the design of a miniaturized wideband tapered slot antenna using slots combining various types of fan-shaped structures was studied. To miniaturize the tapered slot antenna and make it operate at low frequencies, slots combining fan-shaped structures were added to the ground plane of the tapered slot antenna. The miniaturization design process of the final proposed antenna was systematically explained by comparing the input reflection coefficient and gain variations when each fan-shaped structure was appended, compared to when there was no slot. The proposed miniaturized wideband tapered slot antenna using slots combining the fan-shaped structures was fabricated on an RF-35 substrate and its measured characteristics were compared with the simulation results. Experiment results show that the frequency band with a voltage standing wave ratio (VSWR) less than 2 was 2.59-11.39 GHz, and gain within the band was measured to be 3.3-7.0 dBi. The proposed miniaturized wideband tapered slot antenna can be reduced in size by 36.9%, compared to when there are no slots in the ground plane.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.510-515
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• 2022

In this paper, a microstrip patch sensor antenna (MPSA) for detecting the concentration of an ethanol-water solution in a microliter volume is proposed. A rectangular slot was added at the radiating edge of the patch to increase the sensitivity to the relative permittivity change. To improve a low input resistance caused by placing an ethanol-water solution, which is a polar liquid with high dielectric constant and high loss tangent, on the patch, a quarter-wave impedance transformer was added between the 50-ohm feedline and the patch, and the MPSA was fabricated on a 0.76 mm-thick RF-35 substrate. A cylindrical container was made of acryl, and 15 microliters of the ethanol-water solution was tested from 0% to 100% of ethanol concentration at 20% intervals. Experiment results show that the resonant frequency increased from 1.947 GHz to 2.509 GHz when the ethanol concentration of the ethanol-water solution was increased from 0% to 100%, demonstrating the performance as a concentration detecting sensor.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.516-521
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• 2022

In this paper, a compact 4-bit chipless RFID(radio frequency identification) tag using a modified ELC(electric field-coupled inductive-capacitive) resonator and multiple slot resonators is proposed. The modified ELC resonator uses an interdigital-capacitor structure in the conventional ELC resonator to lower the resonance peak frequency of the RCS. The multiple slot resonators are designed by etching three slots with different lengths into an inverted U-shaped conductor. The resonant peak frequency of the RCS for the modified ELC resonator is 3.216 GHz, whereas those of the multiple slot resonators are set at 4.122 GHz, 4.64 GHz, and 5.304 GHz, respectively. The proposed compact four-bit tag is fabricated on an RF-301 substrate with dimensions of 50 mm×20 mm and a thickness of 0.8 mm. Experiment results show that the resonant peak frequencies of the fabricated four-bit chipless RFID tag are 3.285 GHz, 4.09 GHz, 4.63 GHz, and 5.31 GHz, respectively, which is similar to the simulation results with errors in the range between 0.78% and 2.16%.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.125-134
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• 2023

The purpose of this paper is to propose a method to improve the performance of the previous research is characterized by recognizing facial gestures from the 3D coordinates of seven landmarks selected from the MediaPipe Face Mesh model, generating corresponding user events, and executing corresponding commands. The proposed method applied adaptive moving average processing to the cursor positions in the process to stabilize the cursor by alleviating microtremor, and improved performance by blocking temporary opening/closing discrepancies between both eyes when opening and closing both eyes simultaneously. As a result of the usability evaluation of the proposed facial gesture interface, it was confirmed that the average recognition rate of facial gestures was increased to 98.7% compared to 95.8% in the previous research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.659-665
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• 2023

The exciter of a ship generator adjusts the magnetic flux through excitation current control to maintain the output terminal voltage constant. The voltage controller inside the exciter typically uses a proportional integral control method. however, the response characteristics determined by the gain and time constant produce unwanted output owing to an inappropriate setting value that can reduce the quality and stability of power within the ship. In this study, a neural network circuit is learned using stable input/output data that can be obtained through the AC4A type exciter model provided by IEEE, and the simulation is performed by replacing the existing proportional integral control type voltage controller with the learned neural network circuit controller. Consequently, overshooting was improved by up to 9.63% compared with that of the previous model, and excellence in stable response characteristics was confirmed.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.310-316
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• 2023

This study aims to predict uncertain future scenarios that may unfold in South Korea in the near future, utilizing the theory of extreme events(X-events). A group of 32 experts, consisting of government emergency planning officers, was selected as the focus group to achieve this objective. Using the Focus Group Interview (FGI) technique, opinions were gathered from this focus group regarding potential X-events that may occur within the advanced science and technology domains over the next 10 years. The analysis of these opinions revealed that government emergency planning officers regarded the "Obsolescence of current technology and systems," particularly in the context of cyber network paralysis as the most plausible X-event within science and technology. They also put forth challenging and intricate opinions, including the emergence of new weapon systems and ethical concerns associated with artificial intelligence (AI). Given that X-events are more likely to emerge in unanticipated areas rather than those that are widely predicted, the results obtained from this study carry significant importance. However, it's important to note that this study is grounded in a limited group of experts, highlighting the necessity for subsequent research involving a more extensive group of experts. This research seeks to stimulate studies on extreme events at a national level and contribute to the preparation for future X-event predictions and strategies for addressing them.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.