• International Area Studies Review
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• v.14 no.2
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• pp.61-78
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• 2010

The paper is basically attempted to reveal a possibility of monetary unification and setting an anchor currency in North East Asian economies such as South Korea, China, and Japan. The Cobb-Douglas utility function is tentatively built by a Walrasian economic framework. Korean Won(KRW) is represented for a numeraire in a structural model, and the estimation of a parameter is performed by 2SLS and GARCH-M models. Empirical evidence is found that not only monetary unification itself in this regime seems not to be practicable, but also setting an anchor currency by Chinese Yuan(CNY) or Japanese Yen(JPY) is also inappropriated due to the fact that the estimated parameter is not converged to a unity. Walrasian equilibria are enhanced by the convergence to a unity in the model. It also has to be mentioned that a number of necessary and sufficient conditions should be fulfilled prior to discuss a monetary unification in North East Asian economies. Instead, Asia currency unit(ACU) is more feasible in reality.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.482-491
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• 2020

This study proposed a research model based on self-determination theory and unified theory of acceptance and use of technology to explain the factors influencing intention to use sharing economy services. A total of 392 responses were collected, and structural equation analysis was performed with AMOS 22.0. The results are summarized as follows. First, self-technological aptness and trust had a positive effect on intention to use sharing economy services. Second, access bigger market and environmental friendliness had a positive effect on intention to use sharing economy services. Third, intention to use sharing economy services had a positive effect on actual usage of sharing economy services. Finally, benefits was found to strengthen the relationship between intention to use sharing economy services and actual usage of sharing economy services. The findings of this study would provide a theoretical framework for sharing economy services and important information for understanding individuals using the sharing economy services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.726-741
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• 2022

The purpose of this study is to provide instructive theoretical models for art (music) education institutions especially when unpredictable risks, such as pandemics, occur again. Based on the customer behavior theory of the business-to-business-to-customer (B2B2C) platform, and in combination with the technology acceptance model (TAM) and expectation confirmation model (ECM), this study proposes an online education model from the perspective of art education. The framework is based on the three decision-making processes of the customer, and includes the product owner, content owner, and customer area. This paper highlights the factors that influence customers in making decisions when art education institutions are product owners. Regression analysis was introduced to study the factors influencing the expectation confirmation, and the overall fitting testing and six hypotheses testing of 385 effective samples were performed using the structural equation modeling (SEM). The results show that the course-design and after-service positively influenced the expectation confirmation, and the domain image positively influenced the continuance behavior. Negative emotions skipped the mediator (expectation confirmation) and directly exerted a significant negative impact on customers' willingness to continue system usage (continuance behavior). In addition, expectation confirmation positively influenced continuance behavior. The paths of detailed items comprising course-design, after-service, and negative emotion were also analyzed and discussed. In this path analysis, ordinary art learners did not believe that AI partners can play a very good auxiliary role. The findings contribute to the scope of information systems acting as an art education platform academically, and provide effective and theoretical support for the actual operation of art education institutions.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.1-9
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• 2022

Ship detection in synthetic aperture radar (SAR) images is an important application in marine monitoring for the military and civilian domains. Over the past decade, object detection has achieved significant progress with the development of convolutional neural networks (CNNs) and lot of labeled databases. However, due to difficulty in collecting and labeling SAR images, it is still a challenging task to solve SAR ship detection CNNs. To overcome the problem, some methods have employed conventional data augmentation techniques such as flipping, cropping, and affine transformation, but it is insufficient to achieve robust performance to handle a wide variety of types of ships. In this paper, we present a novel and effective approach for deep SAR ship detection, that exploits label-rich Electro-Optical (EO) images. The proposed method consists of two components: a data augmentation network and a ship detection network. First, we train the data augmentation network based on conditional generative adversarial network (cGAN), which aims to generate additional SAR images from EO images. Since it is trained using unpaired EO and SAR images, we impose the cycle-consistency loss to preserve the structural information while translating the characteristics of the images. After training the data augmentation network, we leverage the augmented dataset constituted with real and translated SAR images to train the ship detection network. The experimental results include qualitative evaluation of the translated SAR images and the comparison of detection performance of the networks, trained with non-augmented and augmented dataset, which demonstrates the effectiveness of the proposed framework.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.224-239
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• 2022

Despite an impressive growth of online sales, the bricks-and-mortar bandwagon still remain high-profile in the realm of consumer channel switching behavior. Different from the existing research exploring the consumer switching behavior from the offline to the online retailer, this study is an effort to investigate why and when do consumers switch from the online to the offline channel by applying the push-pull-mooring framework. Thus, structural equation modeling and SPSS were used to test the established hypotheses. The results, as expected, show that both push factors (i.e., perceived risk and dissatisfaction) and pull factors (alternative attractiveness and perceived ownership) are positively related to a consumer's intention to switch from the online to the offline channel. Moreover, all of expected interactions between push factors and mooring factors (i.e., switching costs, variety seeking, and subjective norms), and between pull factors and mooring factors are supported, except for the interactions between push factors and switching costs as well as between pull factors and subjective norms. Finally, implications and limitations are discussed.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.331-336
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• 2021

This study first examined the social meanings of typicality found in the prison, (solitary) confinement, and conduit(passage) in Peter Halley's works, in which both the prison and (solitary) confinement represent a suppressed structural framework. The former has freedom and escape excluded from it, and the latter allows for mutual regulation and connection as a space of positive mediation. Conduits are interpreted to be flexible and have the potential of creating something new through connection and communication with the outside world. The study then compared and analyzed the meanings of typicality in Halley's works and the concept of segments proposed by Gilles Deleuze and Félix Guattari as social justice in that both of them were in the same context. The findings lead to a conclusion that Halley's prison, (solitary) confinement, and conduit(passage) can be connected to a solid, flexible, and escape segment, respectively, by Deleuze and Guattari.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.347-357
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• 2021

This study analyzed the effects of optimism and innovativeness, the two drivers of a consumer's technological readiness to use an augmented reality(AR) fashion shopping service within the framework of the Technology Acceptance Model (TAM). The survey was conducted on 249 people (males = 58; females = 191) in their 20s who were willing to participate in the AR experience. Data were analyzed using confirmatory factor analysis (CFA) and structural equation modeling by AMOS 22.0. The results indicated that a greater level of perceived optimism had a positive influence on the ease of use and usefulness of the technology. The findings also show that consumers with a high degree of innovativeness tend to have a higher level of playfulness toward AR fashion shopping. Regarding the effects of user beliefs, ease of use had a positive effect on the perception of usefulness and playfulness with higher levels implying a higher consumer intention to adopt an AR fashion shopping service. In addition, this study reveals the moderating effect of consumers with high-fashion versus those with low-fashion innovativeness. For the latter, technological innovation had an insignificant effect on playfulness, thus indicating that consumers with low interest in fashion did not enjoy AR fashion shopping even if the technology was highly innovative. Nevertheless, the analysis confirms the possibility that experiencing a fashion product through AR technology could replace the actual experience of wearing the products.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.645-655
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• 2021

Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• Journal of Korean Academy of Nursing
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• v.52 no.2
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• pp.157-172
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• 2022

Purpose: This study aimed to construct and test a hypothetical model to explain the predictive factors and causal pathways for exercise levels in patients with ankylosing spondylitis based on the self-determination theory. A conceptual framework was constructed assuming that autonomy support by health care providers would satisfy the three basic psychological needs of patients, which would increase their autonomous motivation for exercise, resulting in its initiation and continuation. Methods: This cross-sectional study included 221 patients with ankylosing spondylitis who were visiting rheumatology clinics in two tertiary hospitals. Health Care Climate Questionnaire-exercise regularly, Basic Psychological Needs Satisfaction scale, Behavior Regulation in Exercise Questionnaire-2, and exercise level were used to collect data. Results: The fitness of the hypothetical model met the recommended level (𝛘²/df ≤ 3, SRMR ≤ .08, RMSEA ≤ .08, GFI ≥ .90, AGFI ≥ .85, NFI ≥ .90, TLI ≥ .90, CFI ≥ .90). The model effect analysis revealed that autonomy support by health care providers had a positive effect on patients' autonomy, competence, relatedness, autonomous motivation, and exercise level. Competence and relatedness had positive effects on autonomous motivation and exercise level, respectively. Autonomous motivation had a positive effect on exercise level. Conclusion: The predictive factors of exercise level in patients with ankylosing spondylitis were autonomous motivation, health care providers' autonomy support, competence, and relatedness. Considering these factors, we recommend the development of an effective program for improving exercise levels in these patients.