• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.457-467
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• 2016

Understanding professional baseball fans' expenditure is expected to provide fundamental marketing information that help increase each team's marketing profits and values and produce a better economic impact on its community. In this regard, this study employed a survey method with a total of 372 residents located in Changwon. A questionnaire included factors such as demographics, consumption patterns and perceived socio-psychic effect(PSE), all of which were derived from literature review. A binary logistic regression was modeled with a dichotomous dependent variable, expenditure(30,000 won more or less). The following were input in the model as the independent variables in order to see the relationships; gender, marriage, education, occupation, income, location, age, leisure type, distance, companion, transportation, interest, and PSE. The results of the logistic regression analysis are as follows. Overall, the model was statistically significant, χ²(21, N=372)=59.159, p=.000. Cox and Snell R² was reported as .147 and .200 respectively. So, the model accounted for between 14.7% and 20.0% of the variation in expenditure. Among the independent variables, income, location, companion, and PSE were found to be the significant factors to expenditure. For income, subjects with 2 million won less of income, compared to those with 4 million won more, were .38 times less likely to pay the money of 30,000 won more. For location, subjects in Masan, compared to those in Jinhae, were 3.49 times more likely to pay 30,000 won more. Subjects in Changwon, compared to those in Jinhae, were 3.05 times more likely to pay 30,000 won more. For companion, people visiting the stadium alone, compared to those with friends/colleague, were .36 times less likely to pay 30,000 won more. For PSE, the odds of 30,000 won more paid increased by 1.37 times with one-unit increase in PSE.

• Industry Promotion Research
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• v.8 no.3
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• pp.181-199
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• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.207-234
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• 2023

Since the advent of the Fourth Industrial Revolution, related studies have been conducted in various fields including industrial fields. In this study, to analyze domestic research trends on the Fourth Industrial Revolution, a keyword analysis and topic modeling analysis based on the LDA algorithm were conducted on 2,115 papers included in the KCI from January 2016 to August 2023. As a result of this study, first, the journals in which more than 30 academic papers related to the Fourth Industrial Revolution were published were digital convergence research, humanities society 21, e-business research, and learner-centered subject education research. Second, as a result of the topic modeling analysis, seven topics were selected: "human and artificial intelligence," "data and personal information management," "curriculum change and innovation," "corporate change and innovation," "education change and jobs," "culture and arts and content," and "information and corporate policies and responses." Third, common research topics related to the Fourth Industrial Revolution are "change in the curriculum," "human and artificial intelligence," and "culture arts and content," and common keywords include "company," "information," "protection," "smart," and "system." Fourth, in the first half of the research period (2016-2019), topics in the field of education appeared at the top, but in the second half (2020-2023), topics related to corporate, smart, digital, and service innovation appeared at the top. Fifth, research topics tended to become more specific or subdivided in the second half of the study. This trend is interpreted as a result of socioeconomic changes that occur as core technologies in the fourth industrial revolution are applied and utilized in various industrial fields after the corona pandemic. The results of this study are expected to provide useful information for identifying research trends in the field of the Fourth Industrial Revolution, establishing strategies, and subsequent research.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.89-102
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• 2024

The recent advancements in Smart City and Digital Twin technologies have highlighted the critical role of integrating GIS and BIM in urban planning and construction projects. This integration ensures the consistency and accuracy of information, facilitating smooth information exchange. However, achieving interoperability requires standardization and effective project integration management strategies. This study proposes interoperability solutions for the integration of GIS and BIM for managing various projects. The research involves an in-depth analysis of the IFC schema and data structures based on the latest IFC4 version and proposes methods to ensure the consistency of reference point coordinates and coordinate systems. The study was conducted by setting the EPSG:5186 coordinate system, used by the National Geographic Information Institute's digital topographic map, and applying virtual shift origin coordinates. Through BIMvision, the results of the shape and error check coordinates' movement in the BIM model were reviewed, confirming that the error check coordinates moved consistently with the reference point coordinates. Additionally, it was verified that even when the coordinate system was changed to EPSG:5179 used by Naver Map and road name addresses, or EPSG:5181 used by Kakao Map, the BIM model's shape and coordinates remained consistently unchanged. Notably, by inputting the EPSG code information into the IFC file, the potential for coordinate system interoperability between projects was confirmed. Therefore, this study presents an integrated and systematic management approach for information sharing, automation processes, enhanced collaboration, and sustainable development of GIS and BIM. This is expected to improve compatibility across various software platforms, enhancing information consistency and efficiency across multiple projects.

• Journal of the Korean Society of Radiology
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• v.81 no.1
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• pp.21-40
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• 2020

Magnetic resonance imaging (MRI) is an essential modality for the diagnosis of musculoskeletal system defects because of its higher soft-tissue contrast and spatial resolution. With the recent development of MRI-related technology, faster imaging and various image plane reconstructions are possible, enabling better assessment of three-dimensional musculoskeletal anatomy and lesions. Furthermore, the image quality, diagnostic accuracy, and acquisition time depend on the MRI protocol used. Moreover, the protocol affects the efficiency of the MRI scanner. Therefore, it is important for a radiologist to optimize the MRI protocol. In this review, we will provide guidance on patient positioning; selection of the radiofrequency coil, pulse sequences, and imaging planes; and control of MRI parameters to help optimize the MRI protocol for the six major joints of the musculoskeletal system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.37-42
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• 2024

This paper suggests polynomial time algorithm for cutwidth minimization problem that classified as NP-complete because the polynomial time algorithm to find the optimal solution has been unknown yet. To find the minimum cutwidth CW_f(G)=max_𝜈∈_VCW_f(𝜈)for given graph G=(V,E),m=｜V｜, n=｜E｜, the proposed algorithm divides neighborhood N_G[𝜈_i] of the maximum degree vertex 𝜈_i in graph G into left and right and decides the vertical cut plane with minimum number of edges pass through the vertex 𝜈_i firstly. Then, we split the left and right N_G[𝜈_i] into horizontal sections with minimum pass through edges. Secondly, the inner-section vertices are connected into line graph and the inter-section lines are connected by one line layout. Finally, we perform the optimization process in order to obtain the minimum cutwidth using vertex moving method. Though the proposed algorithm requires O(n²) time complexity, that can be obtains the optimal solutions for all of various experimental data

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.267-275
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• 2023

To obtain better esthetic results when immediately placing a dental implant, the soft tissue surrounding the implant must be conditioned during healing of the extraction socket. To this end, the emergence profile can be customized through immediate restoration of the provisional prosthesis, and good clinical results can be obtained at the time of definitive restoration in the future, resulting in high patient satisfaction. In this case, horizontal root fracture occurred after trauma to both maxillary central incisors. Immediate implant placement and loading was planned considering aesthetics and alveolar bone condition. By taking an impression using a digital intraoral scanner, a digital diagnostic wax-up was performed to make a more aesthetic prosthesis without applying external force to the traumatized teeth. Based on this, the ideal placement location was determined and immediate implant placement was performed using a 3D printed surgical guide. The provisional prosthesis was restored 5 days after placement, and the definitive zirconia crown was restored through soft tissue conditioning and customization using the shape of the provisional prosthesis for 3 months.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Horticultural Science & Technology
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• v.28 no.4
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• pp.567-573
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• 2010

Research was initiated to investigate early establishment characteristics and germination pattern of fine-textured fescues (FF). Six varieties from Chewings fescue ($Festuca$ $rubra$ L. ssp. $commutata$ Gaud., CF), creeping red fescue ($F.$ $rubra$ L. ssp. $rubra$ Gaud., CRF), hard fescue ($F.$ $ovina$ ssp. $longifolia$ Thuill., HF) and sheep fescue ($F.$ $ovina$ L., SF) were evaluated in the study. An alternative environmental condition requiring a FF germination test by International Seed Testing Association (ISTA) was applied in the experiment, consisting of 8-hr light at $25^{\circ}C$ and 16-hr dark at $15^{\circ}C$ (ISTA conditions). Daily and cumulative germination patterns were measured and analyzed on a daily basis. Significant differences were observed in germination pattern, days to the first germination, days to 50% germination, days to 60% germination, and germination rate. The final germination percentage was variable with species and varieties, being 40.25 to 82.00% at the end of study. There were considerable variations in early germination characteristics and germination pattern among FF species. The first germination in all entries except HF was initiated between 5 and 6 DAS (days after seeding) under ISTA conditions, while HF between 6 and 7 DAS, being 1 day later. It was 8 to 10 DAS in days to the 50% germination, which was 2 to 4 days after the first germination date. Days to the 60% germination were 9.10 to 14.80 DAS under ISTA conditions, being 5.70 days in differences among the entries. CF 'Jamestown II' and 'Shadow II' and HF 'Aurora Gold' were the fast varieties. The slowest one was HF 'Rescue 911'. Among FF species, turf establishment speed was becoming faster in CRF, SF, HF and CF in this order. Information on differences in germination characteristics and pattern from this study would be usefully applied for golf course design and construction, when established with FF.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.