본 연구는 한국어교육 분야의 기존 메타버스 관련 개별 연구를 혼합연 구의 방법으로 종합적으로 분석하고 수업 모형 개발을 통해 구체적인 교 육 방안을 제시하는 데 목적이 있다. 이를 위해 먼저 일차 선정된 한국 어교육 분야의 학술지 논문 및 학위논문 52편을 대상으로 통합 요소를 도출하고, 양적·질적·혼합적 방법으로 결과를 통합하였다. 먼저 양적 통 합 결과 교육 분야에서 많이 활용되는 플랫폼, 학습자 대상 및 숙달도 수준의 경향성을 확인할 수 있었다. 다음으로 혼합적 통합 결과 메타버 스 활용 수업에 대한 인식과 기대, 몰입감 및 실재감과 관련된 의견을 통합할 수 있었다. 마지막으로 질적 통합 결과 기존 연구에서 제안한 수 업 모형 사례를 분석하고 교육 방안과 방향성 내용을 통합하였다. 이를 바탕으로 본 연구에서는 메타버스 활용 모듈식 한국어 수업 모형을 제안 하였다. 이 모형은 지식 중심, 상호작용 중심, 수행 중심 모듈로 구분되 며 수업 환경이나 학습자에 따라 적용할 수 있도록 구성되어 효용성이 높다는 점에서 의의가 있다.

목적 : 본 연구의 목적은 Coronavirys Disease(COVID-19) 팬데믹을 거친 고령자의 사회적 건강의 수준의 변화궤적에 대한 잠재계층을 분류하고 잠재 계층별 특성을 분석함에 있다. 또한 이러한 사회적 건강에 영향을 미치는 예측요인을 파악하여 고령자의 사회적 건강을 증진을 위한 기초자료를 마련하고자 한다. 연구방법 : 국내 고령자의 사회적 친밀도에 따른 사회적 건강 유형을 파악하기 위해서 한국복지패널의 3 년차 종단자료를 토대로 분석하였으며, 연구대상자는 세 시점 모두를 응답한 2845명의 고령자를 대상으 로 하였다. 대상자중심접근인 성장혼합모형(Growth Mixture Model; GMM)을 적용하여 변화궤적에 따 른 잠재계층을 분석 하였고, 도출된 각 잠재유형별 특성을 파악하기 위해 χ2 분석, 분산분석을 실시하 였으며, 계층 간 차이를 유발하는 요인을 파악하기 위해 다항로지스틱 회귀분석을 실시하였다. 결과 : GMM 적용결과, 사회적 건강의 변화궤적에 대한 잠재계층은 최종 4개의 집단으로 저수준 감소-증 가 집단, 중수준 유지-증가 집단, 고수준-감소 집단, 고수준 유지’집단으로 분류되었다. 또한 사회적 건강 수준에 따라 여가만족도에서 차이가 나타나는 것으로 드러났으며, 그 외에도 연령 차이가 존재하였 다. 잠재계층분류에 영향을 미치는 영향변인을 검증한 결과, 특히 여성일수록, 종교를 가지고 있을수록, 여가만족도와 전반적 만족도가 모두 높을수록 고수준 유지 집단에 속할 확률이 높은 것으로 나타났다. 결론 : 국내 고령자의 사회적 건강은 시간이 지남에 따라 감소하는 궤적을 보이는 것으로 나타났다. 변화 궤적에 따라 4개의 집단으로 구분 지을 수 있으며, 각 잠재 유형별 연령과 여가 만족도 부분에서 집단별 차이가 드러났다.

Corrosion of copper (Cu) canisters is one of the important factors to ensure the safety of a deep geological repository site. This is because the corrosion of a canister may induce failure of the canister which can lead to a release of radionuclides into the environment. Corrosion of canisters for highlevel wastes is affected by the following multiphysics: thermal-hydraulics, transportation of chemical species, chemical reactions, and interface reactions. This research aimed to develop a multiphysics numerical model for the corrosion of spent nuclear fuel canisters for a deep geological repository in South Korea. The multiphysics model is based on MOOSE (Multiphysics Object-Oriented Simulation Environment) which uses a finite element method. In the multiphysics model, the following multiphysics are coupled and solved together for a deep geological repository design of South Korea: interface redox reactions, porous flow, and heat transport in porous flow. The proposed model was validated with experimental data before being applied to a KAERI reference disposal unit. It was found that the corrosion potential of a Cu canister shows an uneven distribution of corrosion potential along with the surface. In addition, top, bottom, and side surfaces of the canisters show a different lifetime and corrosion potential. Important redox reactions for corrosion are changed along with time from a reduction of O2 and anodic dissolution of Cu by Cl− to sulfidation of Cu and reduction of water. The proposed model will be coupled with some important chemical reactions in engineering buffers and will be the base for the understanding of the behavior of Cu canisters in the KAERI reference disposal unit.

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation’s characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles’ route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

The purpose of this study is to investigate the influence of social factors on the use of honorific language by discourse completion test. Participants complete a short discourse by filling in their responses in conversations that may occur in families, schools, and workplaces where the social status and solidarity of the listener is predetermined. Honorific styles of sentence endings of their responses are analyzed by the generalized linear mixed model. The results show that social status and solidarity are statistically significant factors in the use of honorific styles, but their effects are dependent on the discourse situation. The ratio of using honorific styles gradually increases as the formality of situation increases (i.e., family < school < workplace). Interestingly, when the solidarity is low at the workplace, the ratio of using honorific styles is consistently high regardless of the social status of the listener. These results show that the use of Korean honorific styles is pragmatically changing according to the discourse situation.

The objective of this study was to select a model showing high-levels of interpretability which is high in R-squared value in terms of predicting the yield in the mixed pasture using the factors of fertilization, seeding rate and years after pasture establishment in steps, as well as the climate as a basic factor. The processes of constructing the yield prediction model for the mixed pasture were performed in the sequence of data collection (forage and climatic data), preparation, analysis, and model construction. Through this process, six models were constructed after considering climatic variables, fertilization management, seeding rates, and periods after pasture establishment years in steps, thereafter the optimum model was selected through considering the coincidence of the models to the forage production theories. As a result, Model VI (R squared = 53.8%) including climatic variables, fertilization amount, seeding rates, and periods after pasture establishment was considered as the optimum yield prediction model for mixed pastures in South Korea. The interpretability of independent variables in the model were decreased in the sequence of climatic variables(24.5%), fertilization amount(17.8%), seeding rates(10.7%), and periods after pasture establishment(0.8%). However, it is necessary to investigate the reasons of positive correlation between dry matter yield and days of summer depression (DSD) by considering cultivated locations and using other cumulative temperature related variables instead of DSD. Meanwhile the another research about the optimum levels of fertilization amounts and seeding rates is required using the quadratic term due to the certain value-centered distribution of these two variables

Previous researches have focused on the efficiency of project execution and the satisfaction of internal customers in view of the fact that a project is successful if any defects are not found in the short-term performance test of the project final outcom

The paper reviews gauge R&R studies by two-factor mixed models including random and fixed factors. The two-factor mixed models include restricted models and unrestricted models considering the interaction of two factors. This study also classifies the models according to the number of factors, and the combination of various factors such as random factor, fixed factor, block factor and repetition type.

This paper considers the sequencing of products in mixed model assembly lines. The sequence which minimizes overall utility work in car assembly lines reduce the cycle time, the number of utility workers, and the risk of conveyor stopping. The sequencing problem is solved using Tabu Search. Tabu Search is a heuristic method which can provide a near optimal solution in real time. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

This paper considers the sequencing of products in mixed model assembly lines under Just-In-Time (JIT) systems. Under JIT systems, the most important goal for the sequencing problem is to keep a constant rate of usage every part used by the systems. The sequencing problem is solved using Genetic Algorithm Genetic Algorithm is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problems are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed-model production lines, the two problems have been considered separately. A genetic algorithm for balancing and sequencing in mixed-model U line is proposed. A presentation method and genetic operators are proposed. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that the proposed algorithm is promising in solution quality.

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

본 논문에서는 혼합모우드형의 공학적 파괴역학을 위한 두가지 방법의 p-version유한요소모델을 사용한 응력확대계수 산정을 목적으로 연구되었다. 두 가지 방법은 COD와 CSD방법에 의한 변위외삽법과 분해법에 기초한 J-적분법이다. 즉, p-version 유한요소해석을 통해 얻어지는 변위장을 균열선에 대해 대칭 및 역대칭 변위로 분리함으로써, 앞에서 언급된 두가지 방법에 의해 모우드-I과 모우드-II 응력확대계수를 결정할 수 있다. 제안된 방법들의 검증을 위한 예제는 인장력을 받는 중앙균열판과 중앙 경사균열판 문제이다. 균열판의 경사각의 변화와 균열길이와 평판 폭의 비에 따른 수치해석결과는 기존 문헌에 있는 이론값과 경험식에 의한 결과와 비교되어 높은 정도를 보여주고 있다 .