• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.23-38
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• 2007

Since the players in online games seek fun, emotional aspects may be important factors in the pleasure-oriented information systems. This study attempted to verify the effects of characteristic factors of games (fun, challenge, compensation, and diversity) on emotion and customer satisfaction in game portal sites. The study established the research model on the foundation of precedent researches related to online games, emotion, and customer satisfaction. The study conducted online and offline survey on individuals with experiences in using online game portal sites. 206 samples were used to test the research hypotheses. By using Structural Equation Modeling, The study found the following results. First, it was revealed that characteristics of games had positive effects on emotion in game portal sites and indirect effects on user satisfaction. Second, the study analyzed the difference between low user group and high user group. It was revealed that the characteristics of games had positive effects on emotion in the low user group, but only challenge factor influenced on emotion in the high user group.

• Parasites, Hosts and Diseases
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• v.45 no.4
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• pp.255-266
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• 2007

The protective effect of the Synadenium carinatum latex lectin (ScLL), and the possibility of using it as an adjuvant in murine model of vaccination against American cutaneous leishmaniasis, were evaluated. BALB/c mice were immunized with the lectin ScLL (10, 50, 100$[\mu}g$/animal) separately or in association with the soluble Leishmania amazonensis antigen (SLA). After a challenge infection with $10^6$ promastigotes, the injury progression was monitored weekly by measuring the footpad swelling for 10 weeks. ScLL appeared to be capable of conferring partial protection to the animals, being most evident when ScLL was used in concentrations of 50 and 100${\mu}g$/animal. Also the parasite load in the interior of macrophages showed significant reduction (61.7%) when compared to the control group. With regard to the cellular response, ScLL 50 and 100 ${\mu}g$/animal stimulated the delayed-type hypersensitivity (DTH) reaction significantly (P < 0.05) higher than SLA or SLA plus ScLL 10 weeks after the challenge infection. The detection of high levels of IgG2a and the expression of mRNA cytokines, such as IFN-$\gamma$, IL-12, and TNF-$\alpha$ (Th1 profiles), corroborated the protective role of this lectin against cutaneous leishmaniasis. This is the first report of the ScLL effect on leishmaniasis and shows a promising role for ScLL to be explored in other experimental models for treatment of leishmaniasis.

• Journal of Microbiology and Biotechnology
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• v.29 no.3
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• pp.489-499
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• 2019

Subunit vaccines are safer and more stable than live vaccines although they have the disadvantage of eliciting poor immune response. To develop a subunit vaccine, an effective delivery system targeting the key elements of the protective immune response is a prerequisite. In this study, oxidized carbon nanospheres (OCNs) were used as a subunit vaccine delivery system and tuberculosis (TB) was chosen as a model disease. TB is among the deadliest infectious diseases worldwide and an effective vaccine is urgently needed. The ability of OCNs to deliver recombinant Mycobacterium tuberculosis (Mtb) proteins, Ag85B and HspX, into bone marrow derived macrophages (BMDMs) and dendritic cells (BMDCs) was investigated. For immunization, OCNs were mixed with the two TB antigens as well as the adjuvant monophosphoryl lipid A (MPL). The protective efficacy was analyzed in vaccinated mice by aerosol Mtb challenge with a virulent strain of Mtb and the bacterial burdens were measured. The results showed that OCNs are highly effective in delivering Mtb proteins into the cytosol of BMDMs and BMDCs. Upon immunization, this vaccine formula induced robust Th1 immune response characterized by cytokine profiles from restimulated splenocytes and specific antibody titer. More importantly, enhanced cytotoxic $CD8^+$ T cell activation was observed. However, it did not reduce the bacteria burden in the lung and spleen from the aerosol Mtb challenge. Taken together, OCNs are highly effective in delivering subunit protein vaccine and induce robust Th1 and $CD8^+$ T cell response. This vaccine delivery system is suitable for application in settings where cell-mediated immune response is needed.

• 한국정책학회보
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• v.21 no.1
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• pp.337-361
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• 2012

This study is conducted to provide empirical evidences which support that the problems of social isolation and loneliness of elderly can be alleviated by intervening the inter-generational relationship of the elderly by means of active ageing policy. The major empirical challenge to address this question is the possibility of selection bias caused by reversed causal relationship. To address this challenge, I constructed comparison group with 'Eligible Non-Participants' (ENP), and used instrumental variable method to estimate the empirical model. My findings indicate that inter-generational relationship, both in the aspects of economical solidarity and associational solidarity, is significantly improved as time use pattern of the elderly becomes more active. The improvement effect is intensively observed for the group of elderly who do not live with their adult children. The important policy implication of these findings is that the improvement of inter-generational relationship can be added as a new benefit of active ageing policy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1075-1084
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• 2022

The use of Hi-Tech in cultural heritage preservation and the promotion of cultural heritage values in general, particularly artifacts, opens new opportunities for attracting tourists while also posing a challenge due to the need to reward high-quality excursions to visitors historical and cultural values. Building Information Modeling (BIM) and Hi-Tech in new building management have been widely adopted in the construction industry; however, Historic Building Information Modeling (HBIM) is an exciting challenge in 3D modeling and building management. For those reasons, the Scan-to-HBIM approach involves generating an HBIM model for existing buildings from the point cloud data collected by Terrestrial 3D Laser Scanner integrated with Virtual Reality (VR), Augmented Reality (AR), contributes to spatial historic sites simulation for virtual experiences. Therefore, this study aims to (1) generate the application of Virtual Reality, Augmented Reality to Historic Building Information Modeling - based workflows in a case study which is a monument in the city; (2) evaluate the application of these technologies to improve awareness of visitors related to the promotion of historical values by surveying the experience before and after using this application. The findings shed light on the barriers that prevent users from utilizing technologies and problem-solving solutions. According to the survey results, after experiencing virtual tours through applications and video explanations, participant's perception of the case study improved. When combined with emerging Hi-Tech and immersive interactive games, the Historic Building Information Modeling helps increase information transmission to improve visitor awareness and promote heritage values.

• Wind and Structures
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• v.39 no.1
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.139-149
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• 2017

Artificial intelligence education is very important in the 21st century knowledge information society. Even if it is very important to understand artificial intelligence and practice computer programming in computer education in the fourth industrial revolution, but there is no teaching and learning model to understand artificial intelligence and computer programming education. In this paper, the proposed model consists of problem understanding step, data organizing step, artificial intelligence model setting step, programming step, and report writing step. At the program step, students can choose to copy, transform, create, and challenge steps to their level. In this study, the validity of the model was proved by the Delphi evaluation of elementary school teachers. The results of this study provide a good opportunity for elementary school students to practice artificial intelligence programs.

• Advances in Computational Design
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• v.3 no.4
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• pp.367-384
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• 2018

The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.16-37
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• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1382-1399
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• 2023

Pressure relief valve (PRV) is one of the important control valves used in nuclear power plants, and its sealing performance is crucial to ensure the safety and function of the entire pressure system. For the sealing performance improving purpose, an explicit function that accounts for all design parameters and can accurately describe the relationship between the multi-design parameters and the seal performance is essential, which is also the challenge of the valve seal design and/or optimization work. On this basis, a surrogate model-based design optimization is carried out in this paper. To obtain the basic data required by the surrogate model, both the Finite Element Model (FEM) and the Computational Fluid Dynamics (CFD) based numerical models were successively established, and thereby both the contact stresses of valve static sealing and dynamic impact (between valve disk and nozzle) could be predicted. With these basic data, the polynomial chaos expansion (PCE) surrogate model which can not only be used for inputs-outputs relationship construction, but also produce the sensitivity of different design parameters were developed. Based on the PCE surrogate model, a new design scheme was obtained after optimization, in which the valve sealing stress is increased by 24.42% while keeping the maximum impact stress lower than 90% of the material allowable stress. The result confirms the ability and feasibility of the method proposed in this paper, and should also be suitable for performance design optimizations of control valves with similar structures.