민속문화는 중요한 관광자원으로서 지역의 경제발전을 효과 적으로 촉진하고 민속문화를 보호하여 홍보하며 지역의 관광 경쟁력을 높일 수 있다. 그러나 현실적으로 민속관광 개발은 민속문화에 부정적인 영향을 미칠 수 있다. 예를 들면, 외래문 화가 관광지 문화에 미치는 문화적 충격, 과도한 개발로 인한 민속유산 훼손, 민속풍토의 동화, 민속문화의 저속화 등의 문제 가 생긴다. 본 논문은 중국 민속관광의 발전과 민속문화의 보 호를 위하여 네 가지 요구 사항을 제시한다. 즉, 개발과 보호, 전승과 발전 간의 관계를 올바르게 처리하고, 지역 실정에 따 라 관광자원을 개발하고, 정책적인 지도를 강화하여 지역사회 에서 민속문화 보호에 대한 인식을 높임이다. 아울러 전문 인 재를 양성하여 민속문화에 대한 연구와 전승을 확대해야 한다 는 결론을 도출하였다.

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.

An “online respiratory infectious disease nursing simulation course” was developed to strengthen the nursing competency in respiratory infectious disease. Methods: In this methodological study, an “online respiratory infectious disease nursing simulation course” was developed using the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model and evaluated using a one-group pre-post quasi-experimental design to ascertain the respiratory infectious disease knowledge, performance confidence, and clinical performance of 37 nursing students. Results: The online course comprised 17 sessions categorized as follows: seven theory, five at-home laboratory training, two case study, and three simulation sessions. All the nursing students engaged in the course successfully fulfilled its requirements by attending all 17 sessions and passing the clinical performance examination. The knowledge, confidence, and clinical performance (t=-6.60, -10.62, and –6.36, respectively; p<.001 for all) pertaining to respiratory infectious disease significantly increased among participants after the concluding simulation session, compared with their pre-scores obtained prior to the course participation. Conclusion: The “online respiratory infectious disease nursing simulation course” significantly improved the nursing knowledge, performance confidence, and clinical performance ability of nursing students in managing respiratory infectious diseases.

본 연구는 제5차 국가산림자원조사(2006-2010)에서 조사된 편백을 대상으로 흉고직경에 따른 수고 생장곡선식과 초기 수고생장 모델을 개발하여 편백의 초기 생장특성을 고려한 합리적인 산림경영계획 수립에 필요한 기초자료를 제공할 목적으로 실시하였다. 연구자료는 제5차 국가산림자원조사 자료 중 편백 표준목 353본에 대한 수고, 흉고직경, 연륜생장 자료를 이용하였다. 흉고직경에 따른 수고 생장곡선식은 Petterson 식, Log 식, Michailow 식을 이용하여 개발하였으며, 연령에 따른 초기 수고생장 모델은 Chapman-Richards 식, Gompertz 식, Schumacher 식을 이용하여 개발하였다. 본 연구 결과, 모델 검정을 통하여 흉고직경에 따른 수고 생장곡선식은 Petterson 식이 가장 적합한 것으로 나타났으며, 초기 수고생장 모델은 Gompertz 식이 가장 적합한 것으로 나타났다. 본 연구에서 개발한 초기 수고생장 모델을 그래프로 나타낸 결과 편백은 13년생일 때 연간 수고생장량이 0.54m로 가장 많은 것으로 나타났다. 본 연구 결과는 편백의 생장 특성 관련 연구에 활용할 수 있을 뿐 아니라 초기의 편백 조림지에 대하여 합리적인 산림경영계획 수립에 유용한 기초자료가 될 것으로 기대된다.

This study aimed to develop virtual reality (VR)-based content on surgical aseptic techniques for nursing students and evaluate its effectiveness. Methods: The content was developed following the system development life cycle, involving analysis, design, implementation, and evaluation. Experts and fourth-year nursing students validated the content for its validity and usability of the content. The study was conducted from December 2022 to April 2023. Results: The VR content was developed using Keller's ARCS motivational design model (attention, relevance, confidence, and satisfaction) as the fundamental strategy. Upon applying the VR content developed in this study, the research participants confirmed the values of the following sub-factors: confidence (3.86 out of 5), relevance (3.74 out of 5), attention (3.68 out of 5), and satisfaction (3.65 out of 5). Conclusion: VR-based surgical content on aseptic techniques demonstrates potential benefits for nursing students. Therefore, through systematic development and utilizing of diverse nursing skill content, we can enhance the core competencies of nursing students, providing them with high-quality practical education.

This study aimed to develop virtual reality (VR)-based content on surgical aseptic techniques for nursing students and evaluate its effectiveness. Methods: The content was developed following the system development life cycle, involving analysis, design, implementation, and evaluation. Experts and fourth-year nursing students validated the content for its validity and usability of the content. The study was conducted from December 2022 to April 2023. Results: The VR content was developed using Keller's ARCS motivational design model (attention, relevance, confidence, and satisfaction) as the fundamental strategy. Upon applying the VR content developed in this study, the research participants confirmed the values of the following sub-factors: confidence (3.86 out of 5), relevance (3.74 out of 5), attention (3.68 out of 5), and satisfaction (3.65 out of 5). Conclusion: VR-based surgical content on aseptic techniques demonstrates potential benefits for nursing students. Therefore, through systematic development and utilizing of diverse nursing skill content, we can enhance the core competencies of nursing students, providing them with high-quality practical education.

The study aim was to develop and test the effects of integrated simulation pertaining to patients with schizophrenia using a hypertensive crisis module for nursing students. Methods: This pilot study with seven undergraduate nursing students used a single group, pre-post test design. Integrated simulation pertaining to patients with schizophrenia using a hypertensive crisis module was developed based on the ADDIE model (i.e., Analysis, Design, Development, Implementation, and Evaluation), expert meetings with subject professors, a literature review, a preliminary survey, and focus group interviews. Data were collected and measured for general characteristics of the study participants, critical thinking disposition, problem-solving, clinical judgment, self-efficacy, simulation design, and simulation effectiveness. Qualitative contents were analyzed through focus group interviews. Results: No statistically significant differences were found in class design, critical thinking disposition, problem-solving, clinical judgment, and self-efficacy after applying the integrated simulation module. Based on the data obtained from the focus group interviews of study participants, the following four categories were established: “Integrating knowledge and applying it to practice,” “Nursing in unexpected situations,” “Challenged to be an expert,” and “Ensuring receptive and psychological safety in simulation practice.” Conclusion: An integrated simulation module was developed to integrate the nursing problems associated with individual subjects beyond the scope of one subject, and the effect was verified by applying it

이 연구는 초분광 영상으로 두 품종의 콩(청자 3호, 대찬)의 들불병을 진단할 수 있는 모델과 다중분광 영상센서를 개발하기 위해 수행되었다. 무처리구와 들불병 처리구에서 5 nm full width at half maximum (FWHM)으로 구성된 원시 초분광 중심파장들의 콩 식물 영역 반사율들을 추출하여 10 nm FWHM으로 병합한 후, t-test로 차이가 나타난 blue, green, red, red edge, NIR1 및 NIR2 각 영역에서 선정된 대표 밴드로 121개의 식생지수를 계산하였다. 식생지수를 입력변수로 support vector machine (SVM), random forest (RF), extra tree (EXT), extreme gradient boosting (XGB)의 머신러닝 기법과 shapley additive explanation 변수 선택 기법을 적용하여 들불병 진단에 가장 적절한 모델을 선정하고 사용된 식생지수와 파라미터를 나타내었다. T-test 결과 품종에 상관없이 blue 1개(420 nm), green 2개(500, 540 nm), red 1개(600 nm), red edge 2개(680, 700 nm), NIR1 2개(780, 840 nm), NIR2 1개(920 nm)의 총 9개 대표 밴드들이 선택되었고, 성능 평가를 통해 선정된 모델에 청자 3호의 경우 SVM모델(OA=0.86, KC=0.72, 10 VIs)이 선정되었으나 혼동행렬 분석 결과 정상오분류가 적은 RF모델이 선택되었다. RF모델(식 생지수 : RE/Blue, NSI, GDVI, Green/Blue, 파라미터 : max_depth=6, n_estimators=100)은 OA=0.81, KC=0.60, precision=0.86, recall=0.81, F1 score=0.80의 성능을 나타내었다. 대찬은 EXT모델(식생지수 : YVI, RE/Green, 2YVI, 파라미터 : max_depth=8, n_estimators=10)이 선정되 었고, OA=0.86, KC=0.72, precision=0.86, recall=0.86, F1 score=0.86의 성능을 나타내었다.

This study reports an analytical investigation on the development of SB4-grade separated concrete median barriers. The proposed barrier sections comprise three designs, with heights of 810, 1000, and 1270 mm and upper widths of 90, 120, and 120 mm, respectively. Before conducting collision analyses on the proposed sections, the considered collision analysis model was validated using real collision test results; the model was found to accurately predict the real collision test results. The proposed cross-sections were modeled to perform collision analysis according to SB4-grade collision conditions. Results indicated that increasing the cross-section height increased the damaged area and decreased the strength, while the occupant protection performance remained mostly unaffected. Furthermore, the proposed cross-sections met the strength and occupant protection performance criteria specified in domestic guidelines, suggesting their suitability as a separated concrete median barrier for bridges.

행복은 개인들이 추구하는 삶의 가장 중요한 목적이라고 할 수 있다. 본 연구에서는 행복 증진을 위해서 개인들이 스스로 자신의 웰니스를 점검하고 관리하는 것이 필요하다고 보고, 셀프 라이프코칭 앱의 웰니스 증진 효과에 대한 예비 연구를 진행하였다. 이를 위해, 총 36명의 참여자를 실험집단(1·2)과 통제집단에 무선배정하고, 실험집단에는 연구용 앱을 활용해 4주간 셀프 라이프코칭을 수행하도록 하였다. 실험처치 중 주간 피드백을 실험집단1에는 제공하 고, 실험집단2에는 제공하지 않았다. 종속변인으로 노동자를 위한 웰니스 지수(WIW)와 한국형 웰니스 척도(KWS) 를 사용하였다. 실험결과, 사전, 사후, 추후의 시점과 집단 간의 상호작용 효과는 통계적으로 유의미하지 않았으나, 효과의 경향성을 확인하였다. 주간 피드백 유무에 따른 실험처치 효과 차이는 확인되지 않았다. 시간에 따른 웰니스 증진 효과가 통계적으로 유의미했으며, 실험처치가 웰니스에 미치는 효과가 선형적임을 확인하였다. 참여의견 조사 결과, 참여자의 84.2%가 이번 활동이 도움이 된다고 하였으며, 78.9%가 상용화된 앱이 있다면 1주 또는 2주에 한번 사용하겠다고 응답하였다. 본 연구는 누구나 스스로 자신의 웰니스 증진에 활용할 수 있는 방법론을 제시하였으며, 그 효과를 일정 부분 확인하였다는 점에서 의의가 있다.

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 paper, we present a case study of developing MVIS (Machine Vision Inspection System) designed for exterior quality inspection of stamping dies used in the production of automotive exterior components in a small to medium-sized factory. While the primary processes within the factory, including machining, transportation, and loading, have been automated using PLCs, CNC machines, and robots, the final quality inspection process still relies on manual labor. We implement the MVIS with general- purpose industrial cameras and Python-based open-source libraries and frameworks for rapid and low-cost development. The MVIS can play a major role on improving throughput and lead time of stamping dies. Furthermore, the processed inspection images can be leveraged for future process monitoring and improvement by applying deep learning techniques.

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.

Approximately 40,000 elevators are installed every year in Korea, and they are used as a convenient means of transportation in daily life. However, the continuous increase in elevators has a social problem of increased safety accidents behind the functional aspect of convenience. There is an emerging need to induce preemptive and active elevator safety management by elevator management entities by strengthening the management of poorly managed elevators. Therefore, this study examines domestic research cases related to the evaluation items of the elevator safety quality rating system conducted in previous studies, and develops a statistical model that can examine the effect of elevator maintenance quality as a result of the safety management of the elevator management entity. We review two types: odds ratio analysis and logistic regression analysis models.

가상의 공간에서 함께 즐기는 콘텐츠에 대해 관심이 늘어나고 있다. 더불어 가상공간에서 나만의 아바타도 꾸미고 게임 콘텐츠 역시 즐기고 있다. 이러한 가상의 공간을 메타버스라고 하며 대표적인 플랫폼으로는 제 페토와 로블록스가 있다. 메타버스 플랫폼은 플랫폼의 취지에 맞게 유저가 직접 제작하기 편리한 컨텐츠 제 작 도구를 지원한다. 그러나 일반 유저가 제작한 콘텐츠는 메타버스에서 활동하고 있는 다양한 유저의 관심 과 흥미를 지속적으로 유발하기에는 부족한 부분이 있어 꾸준한 흥행이 어렵다. 본 논문은 기존 게임 엔진을 활용해서 콘텐츠를 제작하는 콘텐츠 개발자로서 메타버스 플랫폼이 제공하는 제작 도구의 효용성을 검증하 고자 게임 엔진의 선택 기준을 참고하여 인터페이스, 개발 언어, 개발 공정의 기준으로 대표하는 플랫폼의 제작 도구를 비교하였다.

본 연구는 환경교육용 보드게임 개발에 관한 연구다. 이를 위해 문헌 고찰과 전문가 인터뷰를 실시하여 핵심 메커니즘과 용어를 도출하였다. 또한, 타당도와 신뢰도 검증을 위하여 델파이 조사를 진행하였다. 연구 결과 9개 항목에 대하여 합의가 이뤄졌으며, 이를 기반으로 ‘수풀로 메이커’ 프로토타입을 제작하고 플레이테스트 를 진행하였다. 그 결과, 환경에 대한 관심, 생태복원의 개념, 탄소 중립에 대한 이해를 보여, 연구의 초기 목 적을 달성한 것으로 나타났다. 본 연구로 인해 개발된‘수풀로 메이커’는 아동과 청소년의 환경교육 교재의 역할 뿐만 아니라, 환경에 대한 깊이 있는 이해를 견인하고, 더 나아가 실천양식 변화의 잠재성을 키우는 역 할에 기여할 수 있을 것으로 기대한다.

In this study, project information of government-funded research institute in the food field was collected and analyzed to systematically identify the factors affecting the process of transferring technological achievements of public research institute to the private sector. This study hypothesized that human resources, financial resources, and technological characteristics as input factors of R&D projects affect output factors, such as research papers or patents produced by R&D projects. Moreover, these outputs would serve as drivers of the technology transfer as one of the R&D outcomes. Linear Regression Analysis and Poisson Regression Analysis were conducted to empirically and sequentially investigate the relationship between input factors and output and outcome of R&D projects and the results are as follows: First, the principle investigator's career and participating researcher's size as human resource factors have an influence on both the number of SCI (science citation index) papers and patent registration. Second, the research duration and research expenses for the current year have an influence on the number of SCI papers and patent registrations, which are the main outputs of R&D projects. Third, the technology life cycle affects the number of SCI papers and patent registrations. Lastly, the higher the number of SCI papers and patent registrations, the more it affected the number of technology transfers and the amount of technology transfer contract.