This study aimed to explore nursing students' experience of learning cardiopulmonary resuscitation (CPR) in a web-based virtual simulation (vSim) through analysis of the reflection journals. Method: From June to July 2020, data were collected from 48 fourth-year nursing students who performed the simulation by reviewing prompt feedback on their CPR performance. The contents of the reflection journals were analyzed using NVivo qualitative data analysis software. Results: Nursing students experienced unfamiliarity with the English-based virtual environment as well as psychological pressure and anxiety about emergencies. Incorrect interventions were identified in the following order of frequency: violation of defibrillator guidelines, missing fundamental nursing care, error in applying an electrocardiogram monitor, inadequate initial response to cardiac arrest, insufficient chest compression, and inadequate ventilation. Lastly, the participants learned the importance of embodied knowledge, for knowing and acting accurately and reacting immediately, and their attitudes as nurses, such as responsibility, calmness, and attentiveness. Learning strategies included memory retention through repetition, real-time feedback analysis, pre-learning, and imagining action sequences in advance. The level of achievement, time required, CPR quality, and confidence improved with behavior-modification strategies developed through self-reflection. Conclusion: Educational interventions that are based on understanding accurate algorithms can strengthen selfawareness of mistakes to improve efficient imparting of CPR education.

Purpose: Even today, cancer remains a challenge to overcome. The purpose of this study is to understand the current status of lip-oral-pharyngeal cancer in Koreans by identifying the survival rate of lip-oral-pharyngeal cancer in Koreans through long-term big data. Material and Method: This study utilized 2023 KOSIS (Cancer Registration Statistics, Ministry of Health and Welfare) academically. The 5-year relative survival rates of lip-oral-pharyngeal cancer from 1996 to 2020 were compared and analyzed at 5-year intervals. Results: The 5-year relative survival rate for lip-oral-pharyngeal cancer was 47.4% from 1996 to 2000, 54.5% from 2001 to 2005, 61.1% from 2006 to 2010, 65.5% from 2011 to 2015, and 69.7% from 2016 to 2020. From 1996 to 2005, the 5-year relative survival rate for lip-oral-pharyngeal cancer was higher than the 5-year relative survival rate for all cancers. However, in the recent 15 years from 2006 to 2020, the 5-year relative survival rate for lip-oral-pharyngeal cancer was lower than for all cancers. Conclusions: In conclusion, this long-term big data showed that the 5-year relative survival rate of lip-oral-pharyngeal cancer in Koreans has increased further in modern times. However, in order to increase the overall survival rate of all human cancers, continuous efforts to improve the survival rate of lip-oral-pharyngeal cancer are needed in the future.

PURPOSES : Construction cost estimates are important information for business feasibility analysis in the planning stage of road construction projects. The quality of current construction cost estimates are highly dependent on the expert's personal experience and skills to estimate the arithmetic average construction cost based on past cases, which makes construction cost estimates subjective and unreliable. An objective approach in construction cost estimation shall be developed with the use of machine learning. In this study, past cases of road projects were analyzed and a machine learning model was developed to produce a more accurate and time-efficient construction cost estimate in teh planning stage. METHODS : After conducting case analysis of 100 road construction, a database was constructed including the road construction's details, drawings, and completion reports. To improve the construction cost estimation, Mallow's Cp. BIC, Adjusted R methodology was applied to find the optimal variables. Consequently, a plannigs-stage road construction cost estimation model was developed by applying multiple regression analysis, regression tree, case-based inference model, and artificial neural network (ANN, DNN). RESULTS : The construction cost estimation model showed excellent prediction performance despite an insufficient amount of learning data. Ten cases were randomly selected from the data base and each developed machine learning model was applied to the selected cases to calculate for the error rate, which should be less than 30% to be considered as acceptable according to American Estimating Association. As a result of the analysis, the error rates of all developed machine learning models were found to be acceptable with values rangine from 17.3% to 26.0%. Among the developed models, the ANN model yielded the least error rate. CONCLUSIONS : The results of this study can help raise awareness of the importance of building a systematic database in the construction industry, which is disadvantageous in machine learning and artificial intelligence development. In addition, it is believed that it can provide basic data for research to determine the feasibility of construction projects that require a large budget, such as road projects.

In this study, complaints from visitors in the science museum satisfaction survey were categorized into four primary factors and ten sub-factors. This categorization aimed to provide recommendations for enhancing the Geochang Wolseong Space Creative Science Museum as an illustrative case study. Futhermore, the study examimed the relative importance of each factor by surveying 90 science museum visitors. The following results are obtained. Firstly, it was evident that the Geochang Wolseong Space Creative Science Museum requires urgent improvement. Certainly, in the primary factors, issues related to the utilization environment emerged as the most significant sources of dissatisfaction, while in the sub-factors, the adequacy of fees was identified as the most prominent concern. Secondly, through the result of the IPA (Importance-Performance Analysis) of the complaint factors, four primary issues were identified as top priorities for consideration: fare adequacy, lack of convenient facilities, in sufficient publicity, and a lack of distinctiveness compared to similar facilities. Lastly, when analyzing the relationship between complaints and overall satisfaction, factors related to human service, environment, and educational content had negative effects. In contrast, factors associated with science museum operation exhibited a different trend, suggestinga structural impact relationship with the overall impact of complaints.

This study aims to verify the impact of a metaverse-based safety education program on the fire safety awareness of elementary school students. Utilizing the National Fire Agency's 119 metaverse program, an educational program was implemented for two months, and the experimental group was examined using paired-sample t-tests, while comparisons with the control group were made using independent-sample t-tests. The results revealed statistically significant differences between the experimental and control groups in the area of fire prevention. Although no statistically significant differences were observed over time within each group, the overall average scores for the entire class improved across all areas. Based on these findings, the effectiveness of metaverse-based safety education is suggested; however, a significant difference compared to traditional education was not detected. The study concludes by exploring implications for considerations in the implementation of metaverse safety education in the future.

Based on my attendance at the CIPA International Symposium(CIPA2023) organized by the International Scientific Committee on Heritage Documentation(ICOMOS), this paper explored research cases applying digital technologies, including BIM, to architectural heritage. The researches presented at this symposium were categorized into specific areas: data acquisition, data management, data sharing&experience. Through this classification, an analysis of research cases in architectural heritage utilizing digital technology was conducted. By categorizing the 43 academic papers from the CIPA2023 based on research themes, trends in the digital architecture field were analyzed, providing insights into future research directions for the digital acquisition, management, sharing, and experiential aspects of Korean architectural heritage. In conclusion, it is deemed necessary to reference and supplement the methodologies, including algorithms, workflows, and approaches developed in each study, to effectively apply methodologies suitable for the characteristics of Korean architectural heritage and its data.

본 연구는 어촌다운 어촌 조성과 추후 어촌 개발 사업의 근거 및 방향을 제시하는 것을 목적으로 ‘어촌 다움’을 키워드로 텍스트마이닝 분석을 진행하였다. 텍스트마이닝은 온라인상의 비정형 데이터를 분 석하는 방법으로 키워드의 등장 횟수를 나타내는 키워드 빈도분석, 키워드 간의 관계를 시각화하여 나 타내는 N-gram 분석, 텍스트에 나타나는 사람들의 의견이나 성향을 분석하는 감성분석을 통해 다음과 같은 결론을 내렸다. 첫째, ‘어촌다움’ 키워드는 어촌뿐만 아니라 농촌, 산촌 등 타 촌락과의 연관성이 있으며, 상호 관계와 고유한 조건 속에서 특성이 나타나고 있음을 알 수 있었다. 둘째, ‘어촌다움은’ 크게 자연·역사 경관의 보전 및 회복과 주민들의 정주여건 및 환경개선 총 두 가지 방향으로 구분할 수 있었 다. 셋째, ‘어촌다움’ 키워드에 가장 연관이 있었던 어촌 개발 사업인 어촌뉴딜 사업은 감성분석 결과 긍정적인 역할을 했으나 ‘어촌다움’의 일부인 어촌 주민의 정주여건 개선 및 정주기반 구축은 아직 미 비하며, 개선이 필요함을 알 수 있었다. 본 연구는 ‘어촌다움’과 유사한 키워드인 ‘어촌스러움’, ‘어촌다 운’ 등의 키워드를 함께 분석하지 못한 한계점이 있으며, 향후 이러한 키워드와의 종합적인 분석과 어 촌지역 정주기반에 대한 세부적인 방향 제시가 필요할 것으로 판단한다.

The asphalt concrete industry, accounting for >90% of road pavement, is a crucial contributor to construction waste. This study focuses on the recycling of asphalt concrete recycled aggregates, which currently exhibits a low rate. We investigated the application of these aggregates, combined with hardener and mixing water, in the development of ecofriendly road base materials using circular aggregates. Results revealed that the 13-mm asphalt concrete recycled aggregates met all quality standards. However, the 25-mm aggregates did not conform to the reclaimed asphalt content standard; however, they met other quality standards. Moreover, the experimental results for the hardener and mixing water indicated compliance with all quality standards.

본고는 BCC 코퍼스를 활용한 중국어 미각어 용례 연구로 미각어 ‘甜’과 ‘苦’에 후 행하는 품사를 중심으로 살펴보고자 한다. 이에 BCC 코퍼스를 활용한 미각어 ‘甜’과 ‘苦’ 각각의 연구 방법과 비교 분석을 통해 연구하고자 한다. 본고는 기존 미각어 연 구에서 볼 수 없었던 방대한 데이터를 활용하여 BCC 코퍼스 내의 코퍼스 분석 도구 를 활용하여 보다 객관적이고 과학적으로 양적인 면에서의 미각어 ‘甜’과 ‘苦’에 후행 하는 용례를 고찰하고자 한다.

본 연구는 화재, 구조, 구급 등 재난 대응 최일선에서 근무하는 119상황관리사의 직무 역량이 무엇인지 도출하고 델파이 연구로 타당성을 검증하여 해당 직무의 전문성 향상을 위해 발전된 교육훈련 기초자료 를 마련하고자 수행되었다. 이에 국내외 선행연구 및 직무매뉴얼을 분석하여 119상황관리사 직무역량 후 보군을 구성한 후 초점집단면접을 통해 직무역량 개발에 대한 의견을 수렴하는 과정을 거쳐 119상황관리 사 직무역량의 정의를 규명하였다. 마지막으로 2차에 걸친 전문가 패널을 대상으로 델파이조사를 실시하 여 검증한 후 타당성을 확보하였다. 이러한 연구결과 분석을 통해 다음과 같은 결론이 도출되었다. 첫째, 최종 확정된 119상황관리사 직무역량은 8개의 책무영역과 70개의 직무역량으로 구성되었다. 특히 119상 황관리사 직무역량에서 화재, 구급, 구조신고 상황관리 역량이 가장 큰 부분을 차지하는 것으로 나타났다. 둘째, 119상황실에 따라 제대로 다루지 못한 스트레스 관리 역량이나 중요한 공통 직무역량의 구체적 내 용을 도출하였다. 셋째, 119상황관리사의 실제 현장 경험이 풍부한 전문가 패널들로부터 현업에 기반을 둔 직무 역량으로 타당성을 확보하였다. 이를 기반으로 119상황실의 지역에 따른 편차를 줄이고, 직무 수 행 수준 향상을 위한 교육과 훈련의 기초자료로 활용될 수 있다는 점에서 몇 가지 시사점을 제안하였다.

This research aims to understand the specific aspects of the utilization of the pavilion by a group of governors in the mobile office system of the early Joseon Dynasty through two diaries written in the 16th century. Miam Diary by Yu Hee-chun, a governor of Jeolla Province, and Jaeyeongnam Diary by Hwang Sa-woo, a chief aide of Gyeongsang Province, are important historical materials that reveal the utilization patterns of the pavilion by the governor, who was the decision maker and main user of governmental pavilions. As a result of analyzing the two diaries, the utilization of governmental pavilions was concentrated in the hot summer season, May to July, which is closely related to the perception of temperature and humidity. While pavilions are mostly used as office and banquet places, some notable usage patterns have been identified. When there were several governmental pavilions in a town, the order of appreciation was determined by considering the location and scenery, and the pavilions were also used as a place to encourage learning as governors taught Confucian scholars well. Governmental pavilions functioned as a device to visualize hierarchy through seating and accommodation arrangements. The authors of the diaries left comments on the famous pavilions and sometimes went to see the pavilions after asking for permission from the superior. This research is meaningful in that it reconstructed the relationship network and phases of the times of governmental pavilions scattered across the country through institutions and daily life.

해사영어는 선박 운항, 해양 안전, 선내 의사소통 및 선외 교신을 위해 설계된 특수한 영어 언어체계이다. 국제해사기구 STCW(선원의 훈련, 자격증명 및 당직근무의 기준에 관한 국제협약)에 따르면 국제항해에 종사하는 항해사가 되기 위해서는 SMCP를 포함한 해사영어 대한 충분한 이해가 수반되어야 한다. 본 연구는 음성인식, 번역, 단어 기입 등 유형의 해사영어시험을 통하여 학생들 의 해사영어 활용 능력을 측정하고 플랫폼 사용에 따른 시험 점수 향상 정도, 나아가 초임항해사로 나가기 위하여 요구되는 해사영어 시험 플랫폼 활용 시간 등을 조사하고자 하였다. 실험은 먼저 초기 시험을 통해 학생들의 일반영어능력과 SMCP 활용 능력에 대한 연 관성을 조사한 후, 중간 시험 및 최종 시험을 통해 플랫폼 활용에 대한 점수 향상 정도, 응시시간 변화 등 요인을 측정하였다. 초기 시 험을 통해 개인 요인(예: 토익 점수, 본인 스스로에 대한 영어능력 평가)에 따른 그룹 간 해사영어시험 점수에 유의한 차이가 있음을 확인하였으며, 중간시험 및 최종시험을 통해 플랫폼 활용이 유의한 시험점수 향상으로 이어졌음을 확인하였다. 해당 연구는 해사 교육 분야에 다양하게 적용할 수 있는 학습 플랫폼 활용 효능을 조사하였으며 향후 해사영어 교육 외 그 범위를 넓혀 활용될 수 있을 것으 로 사료된다.

This study analyzes the body shapes of lower-body obese female adolescents and proposes a slacks pattern suitable for their body type. Lower-body obesity is a prevalent type of teenage obesity, and our proposals aim to improve consumer satisfaction in ready-to-wear clothes across this demographic. We first observe characteristics of obese lower bodies, noting significantly above-average thigh and hip circumference. These figures indicate a high degree of curvature in obese lower bodies, along with a large drop value. Leveraging this data, we develop a novel slacks pattern using 3D avatars in a virtual simulation system. The formulas for the main areas of the pattern are as follows: front waist girth W/4+0.75cm+0.5cm, back waist girth W/4+0.5cm– 0.5cm, front hip girth H/4+1.25cm–0.5cm, back hip girth H/4+2cm+0.5cm, front crotch extension H/16+0.5cm, back crotch extension H/8+1cm. Results from appearance evaluations show that this pattern minimizes strain rate on the waist and hips, and its average score is significantly higher than that of an alternative pattern that was also evaluated. The minimized strain rate and high average score indicate that our pattern assigns a sufficient amount of space to the appropriate areas. Based on these results, we expect our research to inform slacks pattern development and production for obese consumers of all types.

This study aims to merge Picasso’s expressive elements and deconstructive fashion’s formative traits, proposing an upcycle fashion design that fuses artistic and philosophical aspects. The analysis of Picasso’s Cubism identified qualities like liberating revolution, fluidity of vision, geometric reducibility, complex symbolism, and creative imitation. The analysis of Derrida’s deconstructionism revealed expressive traits: uncertainty, intertextuality, différance, and dis-de phenomenon. An upscale fashion design was developed based on six Picasso works featuring women. The design was created using the fashion design software CLO 3D and integrated clothing waste and scrap fabrics as materials.The results are as follows. First, upcycle fashion was viewed from a new perspective based on Picasso and Derrida’s values. This perspective suggested creating better ethical values by upholding environmental protection in novel ways that overcome limitations rather than destroy existing values indiscriminately. Second, upcycle fashion design methodologies were derived from various perspectives utilizing formative features of Picasso’s works and specific expressive features of deconstructed fashion. Third, the direction of mitigating waste and pollution from clothing production and transportation was revealed by making clothes in a virtual space using the CLO 3D program. This study contributed to obtaining various methods for developing upcycle fashion designs using own methods of Picasso and Derrida to diversify the approaches of upcycling, which is relatively stagnant in disassembling.

In this study, the evaluation items related to the effectiveness evaluation of the LVC (Live, Virtual, Constructive) training system of the Air Force were derived and the weights of each item were analyzed. The LVC training system evaluation items for AHP (Analytic Hierarchy Process) analysis were divided into three layers, and according to the level, 3 items were derived at level 1, 11 items at level 2, and 33 items at level 3. For weight analysis of evaluation items, an AHP-based pairwise comparison questionnaire was conducted for Air Force experts related to the LVC training system. As a result of the survey, related items such as (1) Achievement of education and training goals (53.8%), (1.2) Large-scale mission and operational performance (25.5%), and (1.2.1) Teamwork among training participants (19.4%) was highly rated. Also, it was confirmed that the weights of evaluation items were not different for each expert group, that is, the priority for importance was evaluated in the same order between the policy department and the working department. Through these analysis results, it will be possible to use them as evaluation criteria for new LVC-related projects of the Air Force and selection of introduction systems.

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

본 논문에서는 대규모 실시간 매칭의 생존 게임에서 플레이를 위한 유저들의 소셜 관계에 대해 연구한다. 특 히 “사전 팀 구성”을 통한 자의적인 팀 구성이 어떤 방식으로 유저들을 연결하는 지 연구하고자 한다. 다수 의 사람 간 집단 역학에서 나타나는 특성이나 패턴에 대한 조사를 중심으로 하였으며, 개인의 특성은 보조적 인 수단으로만 사용된다. 이번 연구에서는 게임을 플레이하는 유저들의 익명화 된 대규모 데이터를 활용하며 이에 대한 간소화된 집계 방법을 제안한다. 데이터 세트에는 사전 팀 구성에 관한 11,259만 줄의 속성이 포 함되어 있으며, 데이터에서 우리는 250만개의 노드와 1,182만개의 무방향 에지가 있는 협업 네트워크를 구성 하여 대규모 게임 내 협동 네트워크를 만듭니다. 연결 정도, 경로 길이, 클러스터링 및 소속 하위 컴포넌트의 크기 등 네트워크에 관한 수치를 통해 게임내 소셜 활동에 대한 이해를 높이고자 한다. 본 논문에서는 다음 의 두가지 특성을 중심으로 결론을 제시한다. 첫째, 네트워크 내에는 대규모로 연결된 2개(전체의 44% 및 2%)와 나머지의 파편화된 하위 컴포넌트로 구성 되어있다. 이 대규모 컴포넌트 중 작은 쪽은 한국 유저로만 구성되어 있다. 둘째, 컴포넌트 크기 별 평균 연결 거리와 군집화 계수, k-core를 확인함으로써 기타 다른 네 트워크 대비 이웃 간 연결이 강하면서 전체적으로는 비교적 멀리 떨어져 있음을 확인한다.

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

디지털 기술은 단순한 정보 전달 수단을 넘어서, 서사를 생성하고 소비하는 방식을 재정의하는 새로운 형태 의 패러다임이다. 디지털 기술의 발전과 함께, 디지털 매체는 강력한 스토리텔링 도구로서 현대 교육 분야에 자리 잡고 있으며, 이는 전통적인 교육 방식과 비교했을 때 학습자의 상호작용이 강조된다는 차이가 있다. 본 연구는 이러한 디지털 스토리텔링 환경에서 시·청각이 결합된 정보를 학습자에게 제공하고, 스토리텔링 과정에 선택지를 제공함으로써 상호작용성과 게임 요소를 더해 학습자 스스로 스토리텔링을 통해 학습하는 방법을 제안하였다. 그리고 연구의 타당성 검증을 위해 전문가 인터뷰를 실시하였다. 전문가 검증결과, 학습 자 스스로 스토리텔링을 통해 학습하는 과정은 이해도와 몰입도 측면에서 매우 효과적일 것이라는 긍정적인 답변을 얻을 수 있었다.