• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.546-549
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• 2022

The installation rate of AMI (advanced metering infrastructure) capable of automatic electricity measurement is less than 43% nationwide and 10.5% in rural areas, which is very poor. Therefore, for the smart grid, automatic information recording of the watt-hour meter is required. For this purpose, it is necessary to develop a system capable of remote meter reading and use control by improving the existing watt-hour meter. In this paper, in order to enable the AMI function of the existing electricity meter, the remote meter reading and control technology of the existing electricity meter for AMI, the core of the smart grid, was developed using IoT and AI. The main research content was to recognize numbers using Tensorflow and Open-cv to convert it into a power meter sensing device for SG. We confirmed and checked the performance using the protyope system.

• Korean Journal of Social Welfare Studies
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• v.42 no.2
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• pp.41-70
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• 2011

This research is to study the interaction of multiculture parents in law between. daughter in law. We approached hermeneutical grounded theory and six of multiculture family's parent's in law participated this research. Data were collected by the depth interview and various written records and we could construct 9 hermeutical theme by analyzing and categorizing 83 meaning units, 22 categories. We descripted the process of acculturation between parent's in law and daughter in law. The result as follows : ① sticking self dimensions → ② strategic acceptomce → ③ making shade of co-existence → ④ self dismantling and reconstruction. Finally we proposed the 「joint program of parent's in law and daughter in law for reinforcing culture unpetence」.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.59-67
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• 2023

Private blockchains can apply enhanced security policies that allow only authorized users to participate in the blockchain network. In addition, when used in a career management system where the validity of an individual's career is important, it has the suitable characteristics in terms of information integrity. However, due to the excessive performance requirements of blockchain technology, identifying performance characteristics through simulation can be helpful in stable operation of the system. This paper presents research results that utilized performance evaluation results while constructing a career management system based on the Ethereum blockchain. The service not only serves as a portfolio that records personal career development activities, certification acquisition, and award results, but also provides a community function for career planning to strengthen employment competitiveness. In addition, we present how a compensation policy can be executed to encourage users to participate in career development through community activities. In particular, an appropriate compensation policy was derived by reviewing changes in performance characteristics in accordance with the transaction volume on Geth nodes.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.1-8
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• 2024

In the API gateway, API composition is an essential function that can reduce the number of client calls and prevent over-fetching and under-fetching. API composition that operate with IMJ (In-Memory Join) consume a lot of resources, putting a burden on the performance of the API gateway. In this paper, to improve the problem of IMJ-style API composition, we propose SAPIC (Stream-based API Composition), which delivers the data to be composed to the client by streaming. SAPIC calls each MSA API that makes up the client response data and immediately streams the received response data to the client, reducing the resource consumption of the API gateway and providing faster response time compared to IMJ. As a result of a comparison experiment with GraphQL, a representative API combination technology, SAPIC recorded a maximum CPU occupancy rate of approximately 21 to 70 % lower, a maximum heap usage rate of approximately 16 to 74 % lower, and a throughput rate that was 1 to 2.3 times higher than GraphQL.

• Convergence Security Journal
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• v.24 no.2
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• pp.201-207
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• 2024

Voice is a critical element of human communication, and the development of speech recognition models is one of the significant achievements in artificial intelligence, which has recently been applied in various aspects of human life. The application of speech recognition models in the military field is also inevitable. However, before artificial intelligence models can be applied in the military, it is necessary to research their vulnerabilities. In this study, we evaluates the military applicability of the multilingual speech recognition model "Whisper" by examining its vulnerabilities to battlefield noise, white noise, and adversarial attacks. In experiments involving battlefield noise, Whisper showed significant performance degradation with an average Character Error Rate (CER) of 72.4%, indicating difficulties in military applications. In experiments with white noise, Whisper was robust to low-intensity noise but showed performance degradation under high-intensity noise. Adversarial attack experiments revealed vulnerabilities at specific epsilon values. Therefore, the Whisper model requires improvements through fine-tuning, adversarial training, and other methods.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.1
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• pp.82-94
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• 2024

This is a case report of complete mouth rehabilitation in a patient with generalized attrition and loss of posterior support. After analyzing the condition of the temporomandibular joint, multiple implants were placed to restore collapsed occlusion. Fixture/abutment level intraoral scanning was done instead of using conventional impression materials which entail multiple bite registration for cross-mounting. A 'jaw motion tracking'device, 'digital face-bow transfer', and 'double scan technique' which enables duplicating temporary restoration to definitive restoration were used to fabricate definitive prostheses. By using various digital techniques, complete mouth rehabilitation was done with minimal chair time in a patient with unstable occlusion.

• Korean Journal of Ichthyology
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• v.36 no.2
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• pp.199-206
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• 2024

A single specimen belonging to the family Carangidae was first collected by angling in Seogwi-dong, Seogwipo-si, Jeju-do on 16 October 2023. This individual was identified as Caranx papuensis Alleyne & MacLeay based on morphological traits as following: lateral line gently curving below the first dorsal fin, presence of scaleless area on the thorax, and gill rakers 26. A total of 619 base pairs sequences of the mitochondrial DNA cytochrome c oxidase subunit I region was analyzed, and we found it closely matched to the Japanese C. papuensis (K2P distance=0.54%). We propose its new Korean name "Hwang-jul-jeon-gang-i" based on a yellow band along the lateral line.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.128-137
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• 2024

Purpose: This study was conducted to investigate, through experimental methods, the efficiency of passenger movement and evacuation in the event of an emergency situation on an aircraft. Method: The experiment was conducted a total of 4 times, including 3 scenarios. The three situations were evacuation without luggage, evacuation with carry-on baggage, and evacuation with carry-on baggage and carrier. In the experiment, time was measured based on recorded video. Result: The total evacuation time was found to be approximately 1.5 times higher for the evacuation with luggage, and approximately 3.5 times higher for the evacuation with luggage and 3 carriers compared to the evacuation result in a situation where nothing was carried. As a result of applying the evacuation simulation, it was found that there was a difference from the experimental results. In particular, consideration of complex situations such as carrying out and moving carriers is considered to be a situation that requires more technical research. Conclusion: Quantitive data was obtained to determine how carry-on luggage and carrier affect evacuation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.77-93
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• 2024

The recent development of data collection technology, which conveys various travel data in real-world such as mobile data and probe vehicle data, facilitates transportation planners identifying specified spatio-temporal travel patterns. In this study, an easily implementable travel mode classification methodology was proposed to classify inter-regional trip-modes without modeling by superimposing trajectories generated from mobile phone signaling and transportation infrastructure points into a polygon scale of a shapefile in a GIS system. Each regional mode trip was classified according to the rules such as the presence of transportation infrastructure in the trip trajectory, travel time, and the presence of access trips. An accuracy test generates Type I and Type II error results table to verify the proposed methodology. As a result, it was found that the methodology developed showed the F1-Score of the air mode 1.00, rail mode 0.95, bus mode 0.73.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.105-111
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• 2024

In this paper, we propose methods for the named entity normalization of traditional herbal formula found in medical texts. Specifically, we developed methodologies to determine whether mentions, such as full names of herbal formula and their abbreviations, refer to the same concept. Two different approaches were attempted. First, we built a supervised classification model that uses BERT-based contextual vectors and character similarity features of herbal formula mentions in medical texts to determine whether two mentions are identical. Second, we applied a prompt-based querying method using GPT-4o mini and GPT-4o to perform the same task. Both methods achieved over 0.9 in Precision, Recall, and F1-score, with the GPT-4o-based approach demonstrating the highest Precision and F1-Score. The results of this study demonstrate the effectiveness of machine learning-based approaches for named entity normalization in traditional medicine texts, with the GPT-4o-based method showing superior performance. This suggests its potential as a valuable foundation for the development of intelligent information extraction systems in the traditional medicine domain.