• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.65-88
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• 2024

This pilot study explores a method of extracting metadata values and descriptions from records using named entity recognition (NER), a technique in natural language processing (NLP), a subfield of artificial intelligence. The study focuses on handwritten records from the Guro Industrial Complex, produced during the 1960s and 1970s, comprising approximately 1,200 pages and 80,000 words. After the preprocessing process of the records, which included digitization, the study employed a publicly available language API based on Google's Bidirectional Encoder Representations from Transformers (BERT) language model to recognize entity names within the text. As a result, 173 names of people and 314 of organizations and institutions were extracted from the Guro Industrial Complex's past records. These extracted entities are expected to serve as direct search terms for accessing the contents of the records. Furthermore, the study identified challenges that arose when applying the theoretical methodology of NLP to real-world records consisting of semistructured text. It also presents potential solutions and implications to consider when addressing these issues.

• Information Systems Review
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• v.24 no.3
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• pp.23-41
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• 2022

This case research investigates on how hearing aids, which is one of disability aids, is becoming a smart device, focusing on the case of Starkey Hearing Technologies(Starkey Inc.). Starkey, founded in 1967, has been a leader in innovating forms and functions of hearing aids, and has recently introduced the world's first hearing aid implemented with AI and biological sensors. In this study, history of disability aids, hearing aids(especially Starkey Inc.'s), smart wearable devices and smart earphones are compared. It has been found that recently, there has been a breakdown of boundaries between hearing aids and smart wearable devices in terms of their functions, since entertainment and life assistant functions are added to hearing aids. Based on this trend, the development model of disability aids and smart wearable devices are derived, and according social changes are discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.625-632
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• 2024

This paper analyzed the changes in the curriculum of computer and software-related majors that educate the core ICT technologies needed for the 4th Industrial Revolution, before and after the COVID-19 pandemic. According to the standard classification of university education units, 172 majors classified into Applied Software Engineering, Computer Science·Computer Engineering, and Artificial Intelligence Engineering were targeted, and the curricula of 2023 and 2019 were compared and analyzed. As a result of the analysis, the introduction of the related curriculum for each curriculum group increased by about 2.6%p before and after the COVID-19 pandemic (2023 84.2%, 2019 81.6%). and the 4th Industrial Revolution response index increased by 9.5 points (37.0 in 2023, 27.5 in 2019)

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.515-522
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• 2024

Energy consumption is steadily increasing, and buildings in particular account for more than 20% of the total energy consumption around the world. As an effort to cost-effectively manage the energy consumption of buildings, many research groups have recently focused on Smart Building Energy Management Systems (BEMS), which are deepening the research depth by applying artificial intelligence(AI). In this paper, we propose a reinforcement learning-based energy control method for smart energy buildings integrated with V2G station, which aims to reduce the total energy cost of the building. The results of performance evaluation based on the energy consumption data measured in the real-world building shows that the proposed method can gradually reduce the total energy costs of the building as the learning process progresses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.191-199
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• 2023

The purpose of this study is to examine the impact of ChatGpt's quality on users' satisfaction and intention to continuous use it. For this purpose, a survey was conducted targeting college students in the Busan and Gyeongnam regions, and responses from a total of 155 people were verified using the SPSS 28.0 program. As a result of the study, reliability and stability among ChatGPT quality factors were found to have a positive effect on satisfaction with use and intention to continuous use. Satisfaction with the use of ChatGPT was found to have a positive effect on intention to continuous use.. Satisfaction with use was found to have a positive mediating effect between the reliability and stability of ChatGPT quality and intention to continous use it. As a result of this study, we aim to contribute to suggesting educational and policy directions necessary to promote the use of ChatGPT by presenting factors that affect users' intention to continuous use ChatGPT among the qualities of ChatGPT.

• Convergence Security Journal
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• v.23 no.4
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• pp.61-70
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• 2023

Clustering is an unsupervised learning method that involves grouping data based on features such as distance metrics, using data without known labels or ground truth values. This method has the advantage of being applicable to various types of data, including images, text, and audio, without the need for labeling. Traditional clustering techniques involve applying dimensionality reduction methods or extracting specific features to perform clustering. However, with the advancement of deep learning models, research on deep clustering techniques using techniques such as autoencoders and generative adversarial networks, which represent input data as latent vectors, has emerged. In this study, we propose a deep clustering technique based on deep learning. In this approach, we use an autoencoder to transform the input data into latent vectors, and then construct a vector space according to the cluster structure and perform k-means clustering. We conducted experiments using the MNIST and Fashion-MNIST datasets in the PyTorch machine learning library as the experimental environment. The model used is a convolutional neural network-based autoencoder model. The experimental results show an accuracy of 89.42% for MNIST and 56.64% for Fashion-MNIST when k is set to 10.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.77-89
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• 2024

Knee osteoarthritis (OA) is a very common musculoskeletal disorder worldwide. The assessment of knee osteoarthritis, which requires a rapid and accurate initial diagnosis, is determined to be different depending on the currently dispersed classification system, and each classification system has different criteria. Also, because the medical staff directly sees and reads the X-ray pictures, it depends on the subjective opinion of the medical staff, and it takes time to establish an accurate diagnosis and a clear treatment plan. Therefore, in this study, we designed the stenosis length measurement algorithm and Osteophyte detection and length measurement algorithm, which are the criteria for determining the knee osteoarthritis grade, separately using CNN, which is a deep learning technique. In addition, we would like to create a grading system that integrates and complements the existing classification system and show results that match the judgments of actual medical staff. Based on publicly available OAI (Osteoarthritis Initiative) data, a total of 9,786 knee osteoarthritis data were used in this study, eventually achieving an Accuracy of 69.8% and an F1 score of 76.65%.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.574-581
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• 2024

This study explores the usability of extended reality (XR) content tailored for production process training, with a focus on user experience. Participants engaged with extended reality training modules, and qualitative data was subsequently collected through interviews. These interviews evaluated the hardware, user interface, and overall user satisfaction. The analysis utilized python packages for keyword extraction and word cloud visualization, offering insights into user perceptions. The findings revealed that although the hardware was deemed comfortable, concerns were raised regarding its weight and heat emission. The interactive interface, which relies on hand tracking, encountered issues with recognition rates, leading to suggestions for alternative input methods. Users acknowledged extended reality's potential impact on industries like healthcare and education, sharing both positive and negative views on the technology. This research enhances our understanding of user responses and guides the future enhancement of extended reality content for industrial applications, aiming to improve its quality and practical usability

• The Journal of Bigdata
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• v.9 no.1
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• pp.49-60
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• 2024

This study aims to provide insights for developing innovative products, based on reviews from females aged 30 to 70 who bought cosmetic cushions via TV home shopping. Analyzing 200,000 reviews with Selenium and NLP techniques, we found the main audience is in their 50s and 60s, prioritizing radiance, blemish and wrinkle coverage, and adherence. Notably, products with appealing designs were preferred, especially for gifting among relatives and friends. The proposed innovation is Korea's first AI-recommended cushion, utilizing NLP to match customer needs. Key ingredient recommendations include S.Acamella extract and AHA components, chosen for their perceived benefits and consumer preference. The research also highlights the importance of product aesthetics and gift potential, suggesting marketing strategies should emphasize these aspects to appeal to the target demographic. This approach aims to guide product development and marketing towards meeting consumer expectations in the cosmetic cushion industry, making products more personalized and gift-worthy.

• Journal of Embryo Transfer
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• v.17 no.2
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• pp.153-162
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• 2002

In order to develop the breeding techniques to increase Hanwoo (Bos taurus coreanae) population, the present study was performed 1) to establish the treatment protocol on reproductive disorders with GnRH or PGF／sub 2$\alpha$／, 2) to improve intraovarian PG $F_{2}$$\alpha$／ administration for reducing open period. Among total of 43 diagnosed, high percentage of cows (41.9％, 18 cows) were diagnosed as silent heat, followed by inactive ovaries (32.6％, 14 cows), ovarian cysts (9.3％, 4 cows), persistent corpus luteum (7.0％, 3 cows), endometriosis (4.7％, 2 cows), pyometra (2.3％, 1 cow) and luteal cysts (2.3％, 1 cow). To treat silent heat, 18 cows were administrated with 25 mg PGF／sub 2$\alpha$／, heat-detected, artificially inseminated and monitored pregnancy. All treated cows were heat-detected and 16 cows (88％) were successfully pregnant. With 200 $\mu\textrm{g}$ GnRH treatment, 7 cows (70％) with inactive ovaries and 3 cows (75％) with ovarian cysts were successfully pregnant. Administration with 25mg PGF／sub 2$\alpha$／, successfully treated 3 cows (100％) with persistent corpus luteum and 1 cow (100％) with luteal cysts, followed by 100％ pregnancy rate. With the combined treatment of 25 mg PG $F_{2}$$\alpha$／and antibiotics, 2 cows (100％) with endometriosis were effectively treated and got pregnant after. artificial insemination (AI). In order to reduce open period, 5 mg PGF／sub 2$\alpha$／ was administrated intraovarian to 20 days cows after delivery, heat-detected, artificially inseminated and monitored pregnancy. In the first experiment, in order to recover uterus, 5mg PGF／sub 2$\alpha$／were administrated, followed by administration of 5mg PGF／sub 2$\alpha$／ at the interval of 14 days. As results, 74％ (17／23 cows) of pregnancy rate after AI. In order to further reduce the open period, 5 mg PGF／sub 2$\alpha$／was administrated at the interval of 11 days without the period of uterus recovery, resulted in 94％ (16／17 cows) pregnancy rate. In conclusion, these results showed that PGF／sub 2$\alpha$／ and GnRH treatment were effective hormonal treatment resume in Hanwoo with various reproductive disorders. In addition, modified protocol of intraovarian PGF／sub 2$\alpha$／ administration could be the effective method for reducing the open period.