• Journal of Service Research and Studies
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• v.13 no.3
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• pp.147-159
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• 2023

This study is a study to develop a model for measurement and processing of experience data, which is emerging as a core value in quality management of medical services. In the theoretical background, a literature study was conducted on the importance of experience in medical service, measurement and processing of experience data, and realization of patient-centeredness. Based on these literature and theoretical background research results, operational definitions were performed for the following four research variables, and statistical tests were conducted. Hypothesis 1 is the effect of measuring experience data from the perspective of three factors on persona modeling, Hypothesis 2 is the effect of persona modeling on service blueprint visualization, Hypothesis 3 is the effect of service blueprint visualization on realization of patient-centeredness, and Hypothesis 4 is persona modeling This is the effect that modeling has on the realization of patient-centeredness. After data-based testing of factor analysis, reliability analysis, and correlation analysis, all four hypotheses were adopted as a result of verification using regression analysis. In conclusion, in an era where it is difficult to recognize the value of having only good medical staff and medical equipment in hospitals, it was possible to grasp the meaning that what kind of medical service experience is continuously obtained is more important to patients than the effectiveness of medical staff and medical equipment. In the era of the service economy, the core of hospital service competitiveness is providing attractive experiences, which is the real strength of hospitals, so the measurement and processing of experience data, which is the subject of this study, will have an important meaning in realizing patient-centeredness and realizing smart hospitals.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.30-43
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• 2023

Green infrastructure(GI) is considered a key strategy in establishing sustainable communities. However, research on GI from the perspective of urban system dynamics and resilience lacks depth, as does its integration with physical design. This research addresses two primary causes. First, there is a gap in methods between existing GI planning, which considers static variables, and urban modeling research, which addresses dynamic variables. Second, there is a gap in information between landscape design and urban modeling research. To address these issues, this study proposes an integrated modeling approach in consideration of design decision-making. By combining the LEAM model and MCDA model, this study evaluates the relationship between GI services and socioeconomic growth, while spatially forecasting the geographies of GI demand in 2050. The resulting information reveals a potential degradation in ecosystem services over the region due to Chicago's sub-urbanization. This indicates that there would be a spatial shift in GI demand, emphasizing the need for comprehensive, dynamic GI strategies. This study further discusses the applications of evidence-based design in a studio environment. This study aims to contribute to the GeoDesign literature in terms of the creation of a more resilient urban environment by facilitating efficient evidence-based decision-making.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.611-620
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• 2020

The purpose of the study is to find creativity factors of students in the process of small group modeling and relate them to the types of interactions among students. In order to capture students' detailed interactions, this study was conducted as an 'essential case study' through qualitative analysis. We have developed the modules of nine lessons about terraforming, and they were used in an actual classroom. In order to understand the creativity of the students in the process of modeling, students' discourses and interview data were analyzed using 19 creative factors or abilities. The findings are as follows. Frequently found creativity factors are Elaboration, Evaluation, Visualization, Resist premature closer, Originality, Analysis and Concentration. And students' interactions that affect students' creativity in the process of modeling can be classified into four categories: Suggestion, Agreement, Questioning, Refutation, and Conversion. Through each interaction, students demonstrated the process of expressing and modifying their own thoughts and ideas in the modeling process. The findings of the study suggest that it is important to the teachers to understand types of interactions among students and the relationship between the types of interaction and creativity factors for students' creative modeling in modeling-based learning.

• The Mathematical Education
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• v.63 no.3
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• pp.527-547
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• 2024

It is difficult for mathematics teachers to develop mathematical modeling tasks and implement mathematical modeling lessons for their students. These difficulties serve as a reason why mathematical modeling lessons are not implemented well in school mathematics. In this study, we aimed to examine how preservice mathematics teachers (PMTs) modify mathematical modeling tasks in mathematics textbooks as a way to develop mathematical modeling tasks and how they implement the mathematical modeling lesson. In particular, we focused on how the openness and reality reflected in the task and the mathematical modeling process change as PMTs modify the tasks. We collected data through PMTs' evaluation reports on analyzing textbook tasks, task modification, lesson plans and implementations, peer evaluation, and self-evaluation. Then, we analyzed these data according to the case analysis process. The findings revealed that when PMTs modified the textbook task, they focused on and improved the openness and the defining variables and the model stages of mathematical modeling process. However, when PMTs implemented lesson, the openness and the defining variables and the model stages of mathematical modeling process were restricted again. PMTs did not focus on other stages. Based on these results, the theoretical and practical implications of the study was discussed.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.119-125
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• 2015

This research has conducted high availability system modeling to assure the reliability of shipboard combat systems. Shipboard combat system is a way for efficient execution of duty and a crucial battlefield management system that determines the outcome of battle in the modern war. Especially in regard to a network-centric operational environment in the future, even 1% of malfunction can lead to fatal consequences for the outcome of war. So combat system should be designed by high availability system which is a "always-on" service. In this point of view, This work describes an architecture-based various high availability model and proposed alternative high available systems that can achieve more than 99.9999% accuracy at a minimum. This paper also provides an applicable model with which system engineers analyze out system failure and recovery process by employing computerized tools.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.85-92
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• 2013

An important source of noise from railways is rolling noise caused by wheel and rail vibrations induced by acoustic roughness at the wheel-rail contact. The main contributors to rolling noise are the sleepers, rail, and wheels. In order to analyze and predict rolling noise, it is necessary to understand the vibrating behaviors of railway tracks, as well as of the wheels. In the present paper, theoretical modeling methods for railway track are reviewed in terms of rolling noise; these methods are applied for the three representative types of domestic railway tracks operated: the conventional ballasted track, KTX ballasted track and KTX concrete track. The characteristics of waves propagating along rails are investigated and compared among the types of tracks. The tracks are modeled as discretely supported Timoshenko beams and are compared in terms of the averaged squared amplitude of velocity, which is directly related to the sound radiation from the rails.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.117-124
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• 2024

The objective of Value Engineering (VE) is to derive the optimal value at the most efficient life cycle cost, comprising three stages: Pre-Study, Study, and Post-Study. In this study, we propose a method for information collection and analysis during planned site visit surveys in the preparation stage of VE. The 3D spatial model, created using a drone, facilitated observation and analysis of the study area from various angles, both from the center and the outside. Additionally, through the utilization of drones, we conducted on-site investigations of the research area's 3D spatial model, enabling a macroscopic perspective previously only feasible through a microscopic viewpoint during planned site visits in the pre-study phase. Furthermore, the utilization of actual spatial data obtained from observations allowed for real-time information verification during Design VE workshops, enhancing the efficiency and reliability of the VE project.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.43-56
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• 2002

Most of works have been performed on representation of spatiotemporal objects from various points of view. Most of them represent spatiotemporal objects using approaches from GIS, temporal databases, object-oriented databases or data type. Spatiotemporal objects can be classified as objects whose position and shape changes discretely over time, objects whose position changes continuously and objects whose shape changes continuously as well as position. Previous works on spatiotemporal model have focused on only one of them. In this paper, we propose a spatiotemporal model that can represent three types of objects in Euclidean plan. For this purpose, we represent both discrete and continuous moving objects by defining temporal model extended from valid time and by defining relationship between two consecutive versions of objects. The proposed spatiotemporal object model is based on open GIS specification so that it has compatibility with existing spatial data model.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.283-283
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• 2021

혼합대는 지표수와 지하수의 수리적 교환이 일어나는 경계부로써 1) 수문학적 관점에서는 하도와 하상간의 물교환이 이루어지는 공간으로 다양한 물리적·화학적 작용이 발생, 2) 생지화학적인 관점에서는 하상 간극수 흐름에 의한 전이대(ecotone)를 형성하여 용존산소·영양물질·용존유기탄소의 이동뿐만이 아니라 지하수로부터 열에너지·무기염류의 공급을 유도하면서 높은 생지화학적 활동과 변환을 야기하는 산화·환원 반응구역, 3) 생태적인 관점에서는 저서생물과 지하 유기체종을 특징으로 하는 서식지이나 잠재적인 레퓨지움(refugium) 등의 관점에서 해석될 수 있다. 국내 하천환경의 생태학적 지속가능성을 위한 지표수-지하수 혼합대 관리에 대한 중요성이 점차 증대되고 있지만 우리나라는 여전히 지하수의 이용 및 보전과 지하수의 안정적인 수량·수질 확보를 목표로 관리를 추진하고 있다. 따라서, 실질적인 지표수-지하수 혼합대에서 발생하는 다양한 현상의 이해나 관리방안에 관한 연구는 아직 미비한 상황이다. 지표수-지하수 혼합대에 관한 보고서, 논문 등을 종합하여 혼합대의 영향인자를 살펴보면 1) 수리수문 특성에는 수리전도도·하천 수위·하천 유속·하천수 수온, 2) 수질 특성에는 유기오염물질·영양염류, 3) 수생태 특성에는 대형무척추동물 등으로 분류할 수 있다. 지금까지 단일 연구분야의 접근방법으로 다양한 현장측정기법 및 모델링을 통한 혼합대 연구가 수행되고 있지만, 혼합대가 가지는 환경적 중요성에 대한 이해와 인식이 부족하고, 혼합대 내부에서 발생하는 복합적인 프로세스로 인해 전문가들조차 연구에 어려움을 가질 것이다. 지표수-지하수 혼합대의 효율적인 관리를 위해서는 수리수문·수질·수생태 등 다양한 시각에서 접근하여 학제간 융합연구를 통해 기초 데이터를 상호교환하고, 기존의 혼합대 조사에 부족한 부분을 해결할 필요가 있다. 향후 하천 기저유출 및 혼합대 기초자료 구축, 혼합대 흐름 정량화, 하천복원사업에 의한 혼합대 영향 규명 등의 연구를 수행함으로써 혼합대를 체계적으로 관리할 수 있는 기술 방안을 제시할 필요가 있다.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.277-284
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• 2020

To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO₂ is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO₂. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO₂. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.