• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.3
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• pp.331-340
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• 2023

To estimate the biological reference points, suitable for fisheries management of sandfish Arctoscopus japonicas in the East Sea of Korea, we simulated the yield-per-recruit (Y/R) from age 0 to 6 (0-2,555 days). The stimulation was based on two instantaneous natural mortality conditions: size-dependent (M_t, d^-1) and constant (M_cons, d^-1); Subsequently, the biological reference points of the two mortality conditions was compared. M_t decreased from 0.0075 d^-1 to 0.0018 d^-1 depending on growth, and M_cons remained constant at 0.0011 d^-1 for all ages. Our Y/R model showed that the maximum yield of M_cons was 14 times higher than that of the M_t. The length at first capture to maximize the harvest at the F_0.1 points of the two natural mortality conditions was L_c,t=10.2 cm (TL) and L_c,cons=17 cm (TL). We concluded that M_t was more suitable for estimating M than M_cons; this is because L_c,t showed minimal difference from the current fishing regulations (11 cm, TL), and M_t reflected more biological characteristics than M_cons. We suggest that 10.2 cm and 0.8 as the suitable length at first capture and corresponding age, respectively for efficient fisheries management of sandfish.

• Annual Conference of KIPS
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• 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.