• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.349-377
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• 2023

With the recent advancements in artificial intelligence, the emergence of ChatGPT is expected to bring significant changes to various industries. In particular, there are active attempts to introduce ChatGPT in the education sector, and for librarians, utilizing ChatGPT is seen as an essential element for future learning tools. Against this background, this study aimed to examine librarians' perceptions of introducing ChatGPT in the school library through Focus Group Interviews (FGI). As a result, six themes were derived, including differences in perceptions of ChatGPT application in school libraries, teaching and learning activities utilizing ChatGPT, practical operation of ChatGPT, considerations for successful performance, librarians' required competencies and environment (infrastructure), and the development direction of ChatGPT utilization services in school libraries. Based on these findings, implications for the necessity of educational services utilizing ChatGPT were proposed. This study is significant as the first attempt to introduce ChatGPT in the school library field.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.329-332
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.229-232
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• 2022

Recently, production of offshore fisheries in Korea has been decreasing. Since production of offshore fisheries in 2016 fell below 1 million tons for the first time in 44 years, it has not recovered and has been decreasing. In order to cope with such a decrease in fishery resources, the TAC (total allowable catch) system is implemented internationally for fisheries resource management. Since 1999, South Korea has introduced the TAC system to perform resource management. In this paper, we propose an artificial intelligence-based fish classification and weight estimation system that can be used to investigate fishery resources of land observers essential for the implementation of the TAC system. The system consists of an app and a cloud server that automatically measures the body size and height of fish and takes photos using a terminal equipped with a lidar sensor. In the cloud server, fish classification is performed using a CNN-based efficientnet model and the weight of fish is predicted using automatically measured body length and body height information. Using this system, it is possible to improve the existing method in which the land observer manually writes after measuring the tape measure and weight in the stomach market.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.556-558
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• 2022

This paper proposes a CanSat system with a vehicle tracking function based on Jetson Nano, a high-performance small computer capable of operating artificial intelligence algorithms. The CanSat system consists of a CanSat and a ground station. The CanSat falls in the atmosphere and transmits the data obtained through the installed sensors to the ground station using wireless communication. The existing CanSat is limited to the mission of simply transmitting the collected information to the ground station, and there is a limit to efficiently performing the mission due to the limited fall time and bandwidth limitation of wireless communication. The Jetson Nano based CanSat proposed in this paper uses a pre-trained neural network model to detect the location of a vehicle in each image taken from the air in real time, and then uses a 2-axis motor to move the camera to track the vehicle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.304-305
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• 2022

Recently, as digital communication technology is widely applied to the maritime field, large amounts of maritime data are being accumulated. Accordingly, attempts to create new value by applying data science and Artificial Intelligence(AI) technologies are emerging. Typically, Ministry of Oceans and Fisheries has been providing korean e-Navigation service since 2021 based on LTE-Maritime communication network, as well as R&D for creating value-added service through analyzing huge-sized maritime traffic data is underway. By the way, to do any data-based research, legal system, as a research infra, that researchers can get the data whenever they need is essential. This paper looked at types of data in maritime fields, checked related legal system about scientific analysis and utilization. It is confirmed that there are some legal factors which restrict its scientific analysis and utilization, and suggested ways of improvement to boost R&D using maritime data as a conclusion.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.158-159
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• 2023

With the development and state-of-the-art of ocean satellites, wide-area management of the waters around Korea has become possible. In particular, in the field of ship operation, as autonomous navigation technology based on artificial intelligence and big data is being developed, there is a need for additional analysis and observation through ocean satellite data.. Researches that can combine ship operation with ocean satellite data include ship detection based on ocean satellites and ship navigation assistance using marine weather forecasting.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.3-4
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• 2021

Korea government has developed Korean e-Navigation service to assist ship's collision avoidance, and is providing it since Jan. 2021 to korean vessels to reduce marine accidents caused by human error which is regarded as main reason of marine accidents. It is a huge achievement itself because it is a real-time maritime safety information service based on digital communication, but still has room for improvement to provide customized information for each vessel, such as considering ship's characteristics. This research analyzes current status and requirement of collision avoidance assistance service. Lastly, it suggests direction of improvement of service such as using data science, artificial intelligence(AI).

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.214-214
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• 2022

Soluble starch synthases (SSs) elongate α-glucans from ADP-Glc to the glucan nonreducing ends and play a critical role in synthesizing resistant starch in the rice. A total of 10 SSs isoforms were reported in rice, including granules-bound starch synthase I (GBSSI), GBSSII, starch synthase I (SSI), SSIIa (SSII-3), SSIIb (SSII-2), SSIIc (SSII-1), SSIIIa (SSIII-2), SSIIIb (SSIII-1), SSIVa (SSIV-1), and SSIVb (SSIV-2). SSIII proteins are involved in forming the B chain and elongating cluster filling chains in amylopectin metabolism. The functions of SSIIIb (SSIII-1) are less clear as compared to SSs. Here, we sought to shed light on the genetic diversity profiling of the SSIII-1 gene in 374 rice accessions composed of 54 wild-type accessions and 320 bred cultivars (temperate japonica, indica, tropical japonica, aus, aromatic, and admixture). In total, 17 haplotypes were identified in the SSIII-1 coding region of 320 bred cultivars, while 44 haplotypes were detected from 54 wild-type accessions. The genetic diversity indices revealed the most negative Tajima's D value in the temperate-japonica, followed by the wild type, while Tajima's D values in other ecotypes were positive, indicating balancing selection. Nucleotide diversity in the SSIII-1 region was highest in the wild group (0.0047) while lowest in temperate-japonica. Lower nucleotide diversity in the temperate-japonica is evidenced by the negative Tajima's D and suggested purifying selection. The fixation index (F_ST) revealed a very high level of gene flow (low F_ST) between the tropical-japonica and admixture groups (F_ST=-0.21) followed by admixture and wild groups (-0.04), indica and admixture groups (0.02), while low gene flow with higher F_ST estimates between the temperate-japonica and aus groups (0.72), tropical-japonica and aromatic groups (0.71), and temperate-japonica and admixture groups (0.52). Taken together, our study offers insights into haplotype diversity and evolutionary fingerprints of SSIII-1. It provides genomic information to increase the resistant starch content of cooked rice.