• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1366-1381
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• 1997

Background : Uvulopalatopharyngoplasty(UPPP) has become the most common surgical treatment for obstructive sleep apnea syndrome(OSAS). However, the results of this therapeutic modality have been quite variable with successful results by several authors and poor results by others. Until recently, in Korea, there is only a few reports about the clinical efficacy of UPPP. A prospective study was undertaken to evaluate the effectiveness and complications of UPPP. Method : Twenty-six OSAS patients who had undergone UPPP with preoperative and postoperative polysomnographic studies were included in this study. Two definitions of surgical success were used. The responder was defined, using a conventional criteria, as a 50% or more reduction in apnea index(AI) or apneahypopnea index(AHI) after UPPP, or a postoperative AI of <10 or AHI of <20. The initial cure was defined, using our own criteria, as a postoperative AI of <5 or AHI of <10. Complications were categorized in two groups : early(disorders during the first 10 postoperative days) and late. Results : Eighteen patients(69.2%) were responders, and ten patients(38.5%) were considered as initial cure. On the other hand, in five patients (19.2%), postoperative polysomnographic data demonstrated deterioration compared with preoperative data. Reduction rate of AI or AHI following UPPP was not significantly related to the preoperative body mass index, AI or AHI. There was no significant change of sleep architecture before and after UPPP in responder and initial cure groups. Early complications such as pain, dyspnea, bleeding, nasal reflux, dysphagia or wound disruption were observed in all patients. Late complications such as nasal reflux, voice change, dysphagia, loss of taste, pharyngeal dryness or foreign body sensation were discovered in 22 patients (84.6%). However, all early and late complications were of minor importance. Conclusion : The response to UPPP was favorable in approximately 70% of OSAS patient. However, the initial Cure rate of UPPP was relatively low. We suggest that selection of more appropriate surgical candidates and adequate surgical protocol is necessary to obtain a more successful result with UPPP.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.499-504
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• 2023

본 연구에서는 민감한 개인정보의 유출과 남용 위험이 높아지고 있는 상황에서 정확한 개인정보 탐지 및 비식별화의 효율을 높이기 위해 개인정보 항목에 특화된 개체명 체계를 개발하였다. 개인정보 태그셋이 주석된 대화 데이터 4,981세트를 구축하고, 생성 AI 모델을 활용하여 개인정보 개체명 탐지 실험을 수행하였다. 실험을 위해 최적의 프롬프트를 설계하여 퓨샷러닝(few-shot learning)을 통해 탐지 결과를 평가하였다. 구축한 데이터셋과 영어 기반의 개인정보 주석 데이터셋을 비교 분석한 결과 고유식별번호 항목에 대해 본 연구에서 구축한 데이터셋에서 더 높은 탐지 성능이 나타났으며, 이를 통해 데이터셋의 필요성과 우수성을 입증하였다.

• The Mathematical Education
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• v.63 no.2
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• pp.351-368
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• 2024

One of the important factors for the effective implementation of artificial intelligence (AI) in mathematics education is the perceptions of the teachers who adopt it. This study surveyed 161 elementary school teachers and 157 secondary mathematics teachers on their perceptions of using AI in mathematics education, grouped into four categories: attitude toward using AI, AI for teaching mathematics, AI for learning mathematics, and AI for assessing mathematics. The findings showed that teachers were most positive about using AI for teaching and learning mathematics, whereas their attitudes towards using AI were less favorable. In addition, elementary school teachers demonstrated a higher positive response rate across all categories compared to secondary mathematics teachers, who exhibited more neutral perceptions. Based on the results, we discussed the pedagogical implications for teachers to effectively use AI in mathematics education.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.389-396
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• 2024

Generative AI has recently been utilized across all fields, achieving expert-level advancements in deep data analysis. However, identifying regional names in scientific literature remains a challenge due to insufficient training data and limited AI application. This study developed a standardized dataset for effectively classifying regional names using address data from Korean institution-affiliated authors listed in the Web of Science. It tested and evaluated the applicability of machine learning and deep learning models in real-world problems. The BERT model showed superior performance, with a precision of 98.41%, recall of 98.2%, and F1 score of 98.31% for metropolitan areas, and a precision of 91.79%, recall of 88.32%, and F1 score of 89.54% for city classifications. These findings offer a valuable data foundation for future research on regional R&D status, researcher mobility, collaboration status, and so on.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.151-159
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• 2018

This study focused on appreciative inquiry(AI) of salespeople who have to respond to various types of emotions according to the desires of individual customers at service contact points and the effect of emotional labor on adaptive selling behavior and customer satisfaction. Dyadic questionnaires were administerd to 115 automobile salespeople and 2 customers who received service from each salesperson, and the collected data was analyzed by using structural equation modeling. The results showed that AI had positive influences on deep acting and surface acting. Only deep acting was found to have positive relationship with adaptive selling behavior, but not to surface acting. Adaptive selling behavior had a positive effect on customer satisfaction. This study will contribute to identifying the need for AI access for salespersons and for activating adaptive selling behavior through emotional labor related to AI practice.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.71-86
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• 2022

The purpose of this study is to develop and validate a scale to measure the ethical awareness of users who accept artificial intelligence technology or service. To this end, the constructs and properties of AI ethics were identified through literature analysis on AI ethics. Reliability and validity were assessed through a preliminary survey(N=273), after conducting an open-type survey to men and women(N=133) in 10s to 70s nationwide, extracting the first questions, and reviewing them by experts. The results of an online survey conducted on men and women(N=500) were refined by confirmatory factor analysis. Finally, an AI technology ethics scale was developed. The AI technology ethics awareness scale was developed with 16 questions in total of 4 factors (transparency, safety, fairness, accountability) so that general awareness of ethics related to AI technology can be measured by detailed factors. In addition, through follow-up research, it will be possible to reveal the relationship with measurement variables in various fields by using the ethical awareness scale of artificial intelligence technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.370-372
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• 2021

According to the Clinical Research Center for Dementia, 840,000 Koreans aged 65 or older had dementia patients, with a prevalence rate of 10.39%. The prevalence rate is one in 10 elderly people, but difficult for families to take care of them all day. Judged that possible to manage the conditions and schedules of elderly people living alone by utilizing AI speaker system where schedule management is stored. This paper implements modules for AI schedulers in patients with dementia. Configured to link AWS, a remote IOT, inside the raspberry pi, and to output the schedule to speakers using a calendar from Google API. Through this study, judged that ease of scheduling will help manage and schedule dementia patients.

• Neonatal Medicine
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• v.18 no.2
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• pp.211-220
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• 2011

Purpose: Late-onset hypotension in preterm infants is not a rare condition. Late circulatory collapse due to adrenal insufficiency (AI) is one of the major causes of late-onset hypotension. We assessed the incidence and causes of late-onset hypotension. We also compared the clinical findings according to the presence of AI. Methods: In total, 244 preterm infants with a gestational age ${\leq}$32 weeks and who were admitted to the neonatal intensive care unit (NICU) of Seoul National University Boramae Hospital and Seoul National University Hospital from January 2009 to April 2011 were included. Clinical findings were analyzed retrospectively. Results: Forty-four infants (18%) suffered from late-onset hypotension. Hydrocortisone was administered to 30 infants (68.2%) and AI occurred in 16 infants (36.4%). Cesarean section, sepsis before hypotension, and gastrointestinal surgery were independently associated with late-onset hypotension. Intrauterine growth retardation (IUGR) was less frequent in the hydrocortisonetreated group than in infants not treated with hydrocortisone. The AI group had fewer IUGR infants, and the duration of hospitalization was shorter in the AI group than in infants who were not administered hydrocortisone. Blood pressure tended to normalize more quickly in the AI group, however, the difference was not significant. Conclusion: AI was a major cause of late-onset hypotension, and the use of hydrocortisone shortened the length of hospitalization.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.297-307
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• 2022

This study examined whether there was a difference in the attitude toward the recommended product and the effect on the choice deferral according to information sources. Experiment 1 examined the relationship between trust in information and product attitude, and between uncertainty and choice deferral according to information sources (AI chatbot vs. human). Experiment 2 examined the impact of social presence, perceived personalization, and choice deferral according to whether anthropomorphism of AI chatbots or not. The research results are as follows. First, consumers were found to have a more positive attitude toward products recommended by AI chatbots (vs. human). Second, consumers were more choice deferral whether to purchase products recommended by AI chatbots (vs. human). Third, it was found that consumers' selection of products recommended by anthropomorphic AI chatbots (vs. impersonated AI chatbots) increased. Also, the implications of this study and future research directions were discussed.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.69-76
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• 2022

In this paper, we presented the contents and methods of AI classes using AI platforms. First, we extracted the content elements of each stage of the AI class using the AI education platform from experts. Classes using the AI education platform were divided into 5 stages and 25 class elements were selected. We also conducted a survey of 82 teachers and analyzed the factors that they acted importantly at each stage of the AI platform class. As a result of the analysis, teachers regarded the following contents as important factors for each stage that are AI model preparation stage (the learning stage of the AI model), problem recognition stage (identification of problems and AI solution potential), data processing stage (understanding the types of data), AI modelingstage (AI value and ethics), and problem solvingstage (AI utilization in real life).