• Development and Reproduction
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• v.23 no.2
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• pp.79-92
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• 2019

Humanized mice, containing engrafted human cells and tissues, are emerging as an important in vivo platform for studying human diseases. Since the development of Nod scid gamma (NSG) mice bearing mutations in the IL-2 receptor gamma chain, many investigators have used NSG mice engrafted with human hematopoietic stem cells (HSCs) to generate functional human immune systems in vivo, results in high efficacy of human cell engraftment. The development of NSG mice has allowed significant advances to be made in studies on several human diseases, including cancer and graft-versus-host-disease (GVHD), and in regenerative medicine. Based on the human HSC transplantation, organ transplantation including thymus and liver in the renal capsule has been performed. Also, immune reconstruction of cells, of the lymphoid as well as myeloid lineages, has been partly accomplished. However, crosstalk between pluripotent stem cell derived therapeutic cells with human leukocyte antigen (HLA) mis/matched types and immune CD3 T cells have not been fully addressed. To overcome this hurdle, human major histocompatibility complex (MHC) molecules, not mouse MHC molecules, are required to generate functional T cells in a humanized mouse model. Here, we briefly summarize characteristics of the humanized mouse model, focusing on development of CD3 T cells with MHC molecules. We also highlight the necessity of the humanized mouse model for the treatment of various human diseases.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.111-118
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• 2014

This study sought to describe the relationships among physical environment, self-congruity, positive emotion, and revisit intentions in the coffeehouse setting. This study adopted second-order factor of physical environment in a structural equation model, imploying trend(fashion), cleanliness, reliability, spatial, convenience, and appropriacy as the second-order factors. The conceptual model in this study used responses from 338 college students who visited coffeehouse at least once in the past month. The proposed relationships were analyzed using SPSS 20.0 and AMOS 6.0. The results of data analysis indicated that the six secondorder factors of physical environment significantly affected coffeehouse visitor's self-congruity and positive emotion, and self-congruity as well as positive emotion significantly influenced revisit intentions. Further discussion and theoretical/practical implications of the findings along with directions for future studies are provided. In essence, the findings highlight significant role of coffeehouse's physical environment toward self-congruity and positive emotion in the formation of customer's revisit intentions in the coffeehouse context.

• Journal of Fisheries and Marine Sciences Education
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• v.13 no.2
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• pp.132-145
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• 2001

The cold discharge from LNG(liquefied natural gas) terminal makes the water temperature around the terminal fall down. This temperature reduction may result in serious changes on marine ecosystem of the coastal area. The numerical model experiments of material transport and tidal circulation in the inner bay, Chinhae Bay are investigated in the dispersion of cold discharge from LNG terminal. The condition of ambient water is exposed to tide, tidal current and cold discharge temperature. Simple numerical model experiments highlight the importance of tidal circulation and cold discharge at each case and some results are discussed. The results of this study can be used as the guideline for the site selection of LNG terminals and long-term marine environmental impact assessment.

• Interaction and multiscale mechanics
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• v.6 no.1
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• pp.51-81
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• 2013

A wide literature review on Static Soil-Structure-Interaction (SSI) is done to highlight the key impacts of soil complexity on structural members of framed structures. Attention is paid to the developed approaches, i.e., conventional and Finite Element Method (FEM), to emphasize on deficiencies and merits of the proposed methods according to their applicability, accuracy and power to model and idealization of the superstructures as well as the soil continuum. Proposed hypothesis are much deeply discussed herein for better understanding which is normally neglected in literature review papers due to the large number of references and limit of space.

• Ocean Systems Engineering
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• v.8 no.3
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• pp.281-312
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• 2018

Characteristics of a turbulence wind model control the magnitude and frequency distribution of wind loading on floating offshore wind turbines (FOWTs), and an in-depth understanding of how wind spectral characteristics affect the responses, and ultimately the design cost of system components, is in shortage in the offshore wind industry. Wind spectrum models as well as turbulence intensity curves recommended by the International Electrotechnical Commission (IEC) have characteristics derived from land-based sites, and have been widely adopted in offshore wind projects (in the absence of site-specific offshore data) without sufficient assessment of design implications. In this paper, effects of wind spectra and turbulence intensities on the strength or extreme responses of a 5 MW floating offshore wind turbine are investigated. The impact of different wind spectral parameters on the extreme blade loads, nacelle accelerations, towertop motions, towerbase loads, platform motions and accelerations, and mooring line tensions are presented and discussed. Results highlight the need to consider the appropriateness of a wind spectral model implemented in the strength design of FOWT structures.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.229-244
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• 2012

The purpose of this study is to highlight the effects of the two leadership styles, namely: transformational leadership and transactional leadership, on the different types of followership through analyzing their impact in the productivity and competitiveness of human resources in IT SMEs. The paper focuses on determining whether transformational leadership or transactional leadership is more effective as shown by the levels of empowerment derived from these two types of leadership under study. From this study, alien, role model and passive types of followership, transformational leadership appears to be more influential for personal empowerment. As for group level of empowerment, the transformational type of leadership shows higher effectiveness in alien, role model, passive, and practical types of followership. On the other hand, transactional leadership yields positive impact on practical and conformist types of followership. In summary, personal empowerment plays a direct impact on group empowerment. Thus, with the exception of conformist type of followership, transformational leadership has more impact in human resources of IT SMEs.

• Journal of Korean Society for Quality Management
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• v.40 no.2
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• pp.106-116
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• 2012

This paper aims to develop the adequate quality cost model at a company which delivers ICT(information communication technology) services. One particular business unit was in the first instance selected and quality costs were then analysed at an organization level, for a department and for specific processes. Some areas were determined for quality improvement at each level and their causes were also investigated. However, the existing PAF(prevention, appraisal and failure) models reveled some limitations because the ICT services company included the different number of large and complicated business processes. The PAF model did not sufficiently highlight the detailed causes of failure costs. It did not also stimulate the relevant department's strong responsibility to improve such problems. Both micro PAF and process cost models were proposed in order to cope with this. In final, it explains the relationship between six sigma and quality costing, suggesting how to use the quality costing results as a means of promoting either continuous improvement or innovation in a case company.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.151-162
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• 2014

This study proposes an optimization model to plan the patient distribution and medical resource allocation considering the diverse characteristics of disaster. For reflecting the particularity of disaster response, we configured a few scenarios such as availability of emergency surgery of non-major medical staff and the change in number of patients estimated reflecting the uncertainty, urgency and convergence of disaster. And we finally tested the effects of the scenarios' combination on the objective function defined as maximum number of survival patients. Our experimental results are expected to highlight the significance of the proposed model as well as the applicability of scenarios under disaster response.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.143-160
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• 1998

This article is concerned with the selection of subsets of predictor variables to be included in bulding the binary response logistic regression model. It is based on a Bayesian aproach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the logistic regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. It is done by use of the fact that cdf of logistic distribution is a, pp.oximately equivalent to that of $t_{(8)}$/.634 distribution. The a, pp.opriate posterior probability of each subset of predictor variables is obtained by the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as that with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

• Computers and Concrete
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• v.24 no.5
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• pp.469-488
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• 2019

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.