• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.177-191
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• 2021

Due to the development of mobile devices and streaming technology, many changes in consumption patterns have appeared. In addition, social impact is becoming an era of non-face-to-face consumption due to the panthermic environment of COVID-19. Accordingly, in line with the non-face-to-face consumption trend, we focused on the importance of live commerce, which is emerging as a new distribution channel, and tried to investigate the causal relationship that the characteristics of live commerce and show hosts have on purchase intention. The respondents of this study were 235 general adults of live commerce users. Interaction, economics, entertainment as the characteristics of live commerce and attractiveness, professionality, and awareness as the characteristics of show hosts were set as independent variables. Purchase intention was set as the dependent variable, and content flow was set as the mediating variable. As a result of the study, it was found that the characteristics of live commerce such as Interaction, economics, entertainment, and the characteristics of show hosts such as attractiveness, professionality, and awareness all had a positive (+) significant effect on purchase intention. The impact was shown in the following order: entertainment of live commerce, awareness, attractiveness, professionality of show hosts, economics, interaction of live commerce. In addition, the results of the mediating effect of content flow on purchase intention are as follows. Content flow was found to play a mediating role between interaction, entertainment, attractiveness, professionality, awareness and purchase intention. On the other hand, economics was analyzed to have no mediating effect. The implications of this study are as follows. Companies and show hosts that sell products in live commerce should sell products that can inspire consumers rather than simply sell products. In addition, it is considered that content that provides entertainment and attractions gives pleasure to consumers. If not only a well-recognized show host, but also people with high recognition in various fields such as influencers and creators, become show hosts, consumers' content flow and purchase intentions will increase. And vendors must offer interesting content development and reasonable prices. Show hosts need to focus on active communication with consumers.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.268-276
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• 2021

As wireless communication devices become more common, interests in how to control the electromagnetic waves generated from the devices are increasing. One of the most commonly used electromagnetic wave control materials is magnetic one, but due to the features that make the product heavy and thick when applied to the product, it is difficult to use them in curved electronic devices. Therefore, a polymer flexible meta electronic device has been presented to sort out the problem, which is thin and can have various curvatures. However, it requires an additional evaluation of curvature reliability. In this study, we developed a method to predict electromagnetic wave control characteristics through the resistance/length of the conductive ink line patterns of polymer flexible meta electronic devices, which is inversely proportional to the electromagnetic wave control characteristics. As the radius of curvature decreased, the resistance/length increased, and there was little variations with the duration times of curvature. We also found that both permanent and recoverable changes along with the removal of curvature were occurred when the curvature was applied, and that the cause of these changes was newly created vertical cracks in the conductive ink line pattern due to the tensile stress applied by applying curvature.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.391-409
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• 2022

In this study, class demonstrations conducted integrating science education and 'Education for Sustainable Development (ESD)' by pre-service science teachers were analyzed, focusing on the concept of 'sustainable happiness' and the main elements of 'complexity theory'. In addition, changes before and after participating in such education implementation were analyzed from various angles. Through this, pre-service science teachers tried to derive implications for developing multidimensional teacher professionalism in ESD. The main findings are as follows. First, as a result of peer evaluation of class materials and class demonstrations designed by pre-service science teachers, the average of the integration for 'sustainable happiness' was relatively high. Next, it was analyzed that the elements of 'sustainable happiness' and 'complexity theory' generally had a positive correlation with ESD. In addition, after participating in the study, pre-service science teachers considered individual and social behavioral patterns as important in the sense of ESD. Regarding the need to integrate science education and ESD, pre-service science teachers thought it was necessary to deal with the concept of 'sustainable happiness' in science education to understand a sustainable way of life. It was analyzed that the elements of 'sustainable happiness' and 'complexity theory' generally had a positive correlation with ESD. It was found that pre-service science teachers' confidence in incorporating ESD in science classes was significantly higher after participation in the study. In addition, it was analyzed that pre-service science teachers have come to think more about the role of teachers who can communicate with students and think about happy lives together than before. Overall, it is thought that pre-service science teachers have come to think of multidimensional science teacher professionalism by applying the perspective of the teaching and learning strategy of the new ESD, which integrates the concept of 'sustainable happiness' and elements of 'complexity theory'.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.4
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• pp.15-31
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• 2022

This study interpreted the logical validity of the landscape restoration and maintenance patterns of Changgyeonggung Palace, where modern landscapes coexist. The results of the study are as follows; First, the changes in the landscape restoration and maintenance attitude concerning the Changgyeonggung management organization were identified. With the establishment of the Office of the Imperial Garden, an imperial property was nationalized. The Cultural Heritage Managing Department was opened in 1961, and Changgyeonggung Palace were preserved as designated as historical sites in 1963. An environmental purification was implemented by the Changgyeonggung Office as a follow-up measure for restoration in 1983. As the Cultural Heritage Administration promoted in 1999 and the Royal Palaces and Tombs Center was established in 2019, the palace has been managed professionally as a palace landscape to provide a viewing environment. Second, In the 'Purification Period of Changgyeongwon(1954~1977)', environmental purification was carried out to restore amusement facilities, install facilities for cherry blossom viewing, and develop the place into a national zoo. In the 'Reconstruction Period of Changgyeonggung(1983~1986)', restoring function as an urban park, reserving green areas, the outside space was recreated in the traditional feel, and the forest area was generally maintained. In the 'Supplementation Period of Traditional Landscape Architecture Space(1987~2009)', a uniform green landscape was created with pine trees and various vegetation landscapes centered on the flower beds. In the 'Improvement and Maintenance Period of Viewing Environment(2010~2022), a master plan was reestablished on the premise of utilization, but maintenance has been carried out in a small scale centering on unit space. Third, regarding the validity of the landscape restoration and maintenance, It was found in terms of 'originality' that the recovery of the palace system has not been expanded for over 40 years in existing areas. The 'characteristics of the times', which shows whether multi-layered history was taken into account, Changgyeongwon was excluded from the discussion in the process of setting the base year twice. In terms of 'integrity,' the area of the Grand Greenhouse where the historic states coexists needs a maintenance policy that binds the greenhouse, carpet flower bed, and Chundangji Pond. The 'utility' identified as the utilization of spaces suggests the establishment of a sense of place in the Grand Greenhouse area, which is concentrated with programs different from other areas.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.667-685
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• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of the Daesoon Academy of Sciences
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• v.33
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• pp.257-286
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• 2019

This study aims to explain theodicy in Daesoon Jinrihoe using established theodicies. Theodicy in Daesoon Jinrihoe can be described as follows: within the worldview of Daesoon Jinrihoe, the problems of evil and suffering are better addressed by analyzing the problem of mutual contention. Accordingly, theodicy in Daesoon Jinrihoe is a matter which should be discussed only in regards to the time period known as the Former World and the transition period after the Reordering Works that leads up to the Later World. The Later World does not operate under patterns of mutual contention. Consequently, there will be no suffering. Therefore, issues of theodicy are irrelevant in the Later World. Theodicy should be dealt differently as it pertains to the Former World and the previously mentioned transition period. Daesoon Thought posits that there is an underlying principle presides over the cosmos, and the divine beings act in accordance with it and perform specific duties in their own subdivisions. The cosmic principle is able to contain cycles of both Sanggeuk ('mutual destruction' in general usage, but 'mutual contention' in Daesoon Thought related to the Former World) and sangsaeng ('mutual generation' in general usage and 'mutual beneficence' in Daesoon Thought related to the Later World). Suffering came into being due to mutual contention. However, mutual contention was not set into motion maliciously, but was arranged instead to facilitate the realization of greater values such as growth and development. In other words, mutual contention are not products of a moral value the nature of which is bad or wrong. Yet, since the world has operated under mutual contention from time immemorial, a nearly incalculably vast multitude of grievances have accumulated. In addition, the divine beings who had operated under mutual contention often made mistakes and spread confusion. This extreme situation resulted in tremendous disasters breaking out all over the world. Perhaps this particular theodicy could be named "Dualistic Sanggeuk Theology (Dualistic Theodicy of Mutual Contention)." After the divine beings reported to the Supreme God that the world had fallen into a serious crisis, the Supreme God penetratingly examined the circumstances of the world and then descended to Earth as a human being named Jeungsan. As Jeungsan practiced the Reordering Works of Heaven and Earth, the Great Opening was preordained by Him. As a result, the transition period started, and from that point onward, theodicy should be described differently. It is presumed that all creatures will be judged at the time of the Great Opening. This will result in the annihilation of all wicked beings including both divine beings and humans. There will also be the establishment of an earthly paradise as well as grievance resolution for all beings prior the Great Opening. This can also be called "The Eschatological Theodicy of the Resolution of Grievances." Theodicy in Daesoon Jinrihoe adopts the two theodicies mentioned above. In addition to that, various theodicies from other traditions such as Irenaean ("soul-making") Theodicy, Free Will Theodicy, Recompense Theodicy, Afterlife Theodicy, Karma Samsara Theodicy, theodicy of participation, and Communion Theodicy can all potentially be applied on a case by case basis.