• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.430-434
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• 2015

Safety education at the tertiary level prepares students to enter construction industry with adequate safety knowledge; then accidents can be prevented proactively. However, safety subject has not been paid adequate attention in universities and most institutional safety programs consider safety matters in isolation. Meanwhile, anatomical theory in the medicine field has been successfully adopted and proved potential advantageous in various scientific disciplines. With this regard, this study proposes a visualization based Building Anatomy Model (BAM) for construction safety education, which utilizes the anatomical theory in order to improve student's safety knowledge and practical skill. This BAM consists of two modules: 1) Knowledge Acquisition Module (KAM) aims to deliver safety knowledge to students through building anatomy models; 2) Practical Experience Module (PEM) where students safely perform construction activities by using the system to improve safety skill. The system trial is validated with virtual scenarios derived from real accidents cases. This study emphasizes the visualization based building anatomy model would be a powerful pedagogical method to provide effectively safety knowledge and practical skill for students, as a result, safety competence of students would be enhanced.

• 유통과학연구
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• 제22권6호
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• pp.33-44
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• 2024

Purpose: This study aims to measure how information quality, system quality, security, usefulness, and ease of use of Augmented Reality (VR) and Virtual Reality (AR) influence user satisfaction, motivating intelligent travel technology developers to improve VR/AR quality to meet customer requirements. Research design, data and methodology: This study investigates users interested in travelling in Ho Chi Minh City and Nha Trang City, Vietnam. The research model was implemented using an online questionnaire and face-to-face from 405 valid samples. To evaluate the scale's reliability, the study used the software SPSS 20. Test research hypotheses and evaluate measurement and structural models. This research uses AMOS 20 software. The proposed model is firmly grounded in the Information System Success model (ISS) and the Technology Acceptance Model (TAM), providing a solid theoretical foundation for our research. Results: Results show that consumer perceptions of information quality, system quality, security, usefulness, and ease of use have a positive impact on the perceived quality of VR/AR, thereby influencing tourists' travel intention. Conclusions: The results of this research enrich the theoretical understanding of consumer behaviour toward intelligent technology products in tourism, providing management implications for manufacturers to improve the quality of tourism products and satisfy user requirements in experience before considering choosing a destination.

• 한국자동차공학회논문집
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• 제12권3호
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• pp.44-50
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• 2004

The purpose of this study is to improve the prediction ability of the atomization and vaporization processes of GDI spray under high-pressure and high-temperature conditions. Several models have been introduced and compared. The atomization process was modeled using hybrid breakup model that is composed of Conical Sheet Disintegration (CSD) model and Aerodynamically Progressed TAB(APTAB) model. The vaporization process was modeled using Spalding model, modified Spalding model and Abramzon ＆ Sirignano model. Exciplex fluorescence method was used for comparing the calculated with the experimental results. The experiment and calculation were performed at the ambient pressure of 0.5 MPa and 1.0 MPa and the ambient temperature of 473k. Comparison of caldulated and experimental spray characteristics was carried out and Abramzon ＆ Sirignano model and modified Spalding model had the better prediction ability for vaporization process than Spalding model.

• 한국환경과학회지
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• 제24권8호
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• pp.1023-1036
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• 2015

A reliable streamflow forecasting is essential for flood disaster prevention, reservoir operation, water supply and water resources management. This study proposes a hybrid model for river stage forecasting and investigates its accuracy. The proposed model is the wavelet packet-based artificial neural network(WPANN). Wavelet packet transform(WPT) module in WPANN model is employed to decompose an input time series into approximation and detail components. The decomposed time series are then used as inputs of artificial neural network(ANN) module in WPANN model. Based on model performance indexes, WPANN models are found to produce better efficiency than ANN model. WPANN-sym10 model yields the best performance among all other models. It is found that WPT improves the accuracy of ANN model. The results obtained from this study indicate that the conjunction of WPT and ANN can improve the efficiency of ANN model and can be a potential tool for forecasting river stage more accurately.

• 지능정보연구
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• 제28권4호
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• pp.211-227
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• 2022

오늘날 온라인 도박 사이트를 통한 불법 도박이 큰 사회문제가 되고 있다. 인터넷 기술의 발전과 스마트폰 보급으로 시공간의 제약이 사라지고 불법 온라인 도박을 누구나 쉽게 접근할 수 있게 되었기 때문이다. 이를 막기 위해 국내에서는 자체 모니터 요원의 탐지, '누리캅스'와 같은 제보 시스템 등을 활용해 불법 사이트를 탐지하고 있지만 이러한 수동적인 프로세스로는 인력부족 같은 한계로 모든 불법 사이트를 탐지하기 어려운 실정이다. 이에 여러 학자들이 인공지능 기반의 자동 불법 도박 사이트 탐지 기술을 연구해왔다. Xu et al. (2019)은 가짜 사이트들의 HTML Tag 구조에는 차별적인 특징이 있다는 점을 발견하였다. 이는 HTML Tag 구조가 불법 사이트를 탐지하는데 주요한 특징정보가 될 수 있음을 시사하지만, 불법 사이트 탐지 모델에 HTML Tag 구조를 반영하여 모형의 성능을 제고하고자 하는 연구는 지금까지 거의 시도되지 않았다. 이러한 배경에서 본 연구는 HTML Tag 구조를 특징화하여 모형의 성능을 향상시키고자 하였고, HTML Tag 구조를 적절하게 벡터화하기 위한 방법론으로 Doc2Vec을 변형한 Tag2Vec을 제안한다. Tag2Vec 기반 모델의 효과를 검증하기 위해 '더 치트'의 유해 사이트 목록과 Google 검색을 통한 정상 사이트 목록을 데이터 세트로 활용하여 실증분석을 수행하였다. 그 결과 비교 모델로 설정된 URL 기반 탐지 모델보다 본 연구에서 제안하는 Tag2Vec 기반 탐지 모델이 분류 정확도, Recall, F1_Score에서 모두 향상된 성능을 보임을 확인할 수 있었다. 이러한 본 연구의 제안모델은 향후 지능형 기술을 통해 우리 사회의 건강도를 제고하는데 효과적으로 활용될 수 있을 것으로 기대된다.

• 대한간호학회지
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• 제45권6호
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• pp.900-909
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• 2015

Purpose: The purpose of this study was to identify the effect of predictive factors related to family strength and develop a structural equation model that explains family strength among married working women. Methods: A hypothesized model was developed based on literature reviews and predictors of family strength by Yoo. This constructed model was built of an eight pathway form. Two exogenous variables included in this model were ego-resilience and family support. Three endogenous variables included in this model were functional couple communication, family stress and family strength. Data were collected using a self-report questionnaire from 319 married working women who were 30~40 of age and lived in cities of Chungnam province in Korea. Data were analyzed with PASW/WIN 18.0 and AMOS 18.0 programs. Results: Family support had a positive direct, indirect and total effect on family strength. Family stress had a negative direct, indirect and total effect on family strength. Functional couple communication had a positive direct and total effect on family strength. These predictive variables of family strength explained 61.8% of model. Conclusion: The results of the study show a structural equation model for family strength of married working women and that predicting factors for family strength are family support, family stress, and functional couple communication. To improve family strength of married working women, the results of this study suggest nursing access and mediative programs to improve family support and functional couple communication, and reduce family stress.

• 제어로봇시스템학회논문지
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• 제16권9호
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• pp.827-832
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• 2010

Many researchers have tried to detect the falling and to reduce the injury associated with falling. Normally the method of detection of a loss of balance is more efficient than that of a compensatory motion in order to predict the falling. The detection algorithm of the loss of balance was composed of three main parts: parts of processing of measured data, construction of an internal model and detection of the loss of balance. The internal model represented a simple dynamic motion balancing with two rear legs of a four-legged chair and was a simplified model of a central nervous system of a person. The internal model was defined by the experimental data obtained within a fixed time interval, and was applied to the detecting algorithm to the end of the experiment without being changed. The balancing motion controlled by the human brain was improved in process of time because of the experience accruing to the brain from controlling sensory organs. In this study a reconstruction method of the internal model was used in order to improve the success rate and the detecting time of the algorithm and was changed with time the same as the brain did. When using the reconstruction method, the success rate and the detecting time were 95 % and 0.729 sec, respectively and those results were improved by about 7.6 % and 0.25 sec in comparison to the results of the paper of Ahmed and Ashton-Miller. The results showed that the proposed reconstruction method of the internal model was efficient to improve the detecting performance of the algorithm.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권9호
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• pp.718-731
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• 2009

소프트웨어 유지보수는 기존의 하자 유지보수 개념에서 운영관리 및 서비스의 향상을 위해 지속적인 개선이 요구되고 있다. 본 연구에서는 K사에서 수행중인 4개의 유지보수 프로젝트를 기반으로 소프트웨어 유지보수 성숙도 모델과 평가지표를 제안한다. 이를 위해 SMMM, ITSMM, ITIL을 기반하여 13개의 프로세스 영역과 64개의 평가지표를 도출하고, 도출된 64개의 평가지표를 5점 척도로 설문 평가하여 그 결과를 기반으로 성숙도 모델의 수준을 분류하여 K사의 성숙도 모델을 구축한다. 그리고 K사의 성숙도 모델을 검증 및 개선하기 위하여 K사의 설문평가 점수를 분석하여 평가지표의 개선방안을 제안하고, K사의 성숙도 모델이 소프트웨어 유지보수의 개선 방안을 어떻게 나타내는지를 확인하기 위하여 제안한 소프트웨어 유지보수 성숙도 모델을 K사의 4개의 프로젝트를 대상으로 하여 성숙도 평가를 수행하고, 그 결과를 기반으로 개선방안을 제시하였다.

• 한국지진공학회논문집
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• 제12권6호
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• pp.13-23
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• 2008

본 논문에서는 거더교 형식을 갖는 교량구조물의 격자 유한요소모델에 대한 모델개선을 위해 하이브리드 유전자 알고리즘에 기초한 유한요소 모델개선기법을 제안하였다. 하이브리드 유전자 알고리즘은 유전자 알고리즘과 심플렉스 최적화방법에 기초한 직접탐색기법으로 구성하였다. 제안된 기법에 적용할 수 있도록 고유진동수, 모드형상 및 정적 처짐에 대한 계측값과 유한요소해석 결과를 사용한 적합함수를 제시하고, 강성과 질량을 동시에 개선할 수 있도록 이들 세 가지 적합함수의 선형 조합 형태를 갖는 다중목적함수를 제시하였다. 제안된 방법은 2경간 연속 격자 유한요소모델의 수치예제와 단경간 플레이트 거더교에 대하여 검증하였다. 수치예제의 경우, 랜덤 노이즈를 고려한 계측오차의 영향을 수치해석적으로 평가하였다. 수치해석과 실험적 검증을 통해, 제안된 방법이 거더교 형식의 교량에 대한 유한요소 모델개선에 적합하고 효과적임을 검증하였다.

• 한국안전학회지
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• 제33권4호
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• pp.98-104
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• 2018

Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.