• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.3-16
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• 2024

The government announced the Housing Welfare Roadmap (November 2017), to expand the supply of public rental housing by reconstructing aged long-term public rental complexes. Also, remodeling projects for complexes with low business feasibility of reconstruction projects are recognized as an alternative to supplying public rental housing in urban area. This study analyzed influence factors by dividing them into project feasibility, architectural plan, urban & residential environment plan, and legal system groups in order to establish a plan for long-term public rental housing remodeling project. Futhermore, this work conducted the principal component analysis to get the principal component factors among the influence factors of each group, and the weight analysis to calculate weighting of them. In addition, major influence factors were derived by calculating the relative importance score (RIS) of each factor. Lastly this paper validated the major influence factors and applicability of the procedure to select 3 complexes that can be reviewed for remolding project among 33 long-term public rental housing complexes located in Seoul. The results of this study are expected to be useful when establishing a remodeling project plan for long-term public rental housing.

• 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.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.123-150
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• 2023

The National Library for the Disabled was upgraded to a primary affiliated organization of the Ministry of Culture, Sports and Tourism on June 4, 2020, in accordance with Article 24 (1) of the Library Act (Law No. 16685). The National Library for the Disabled is currently preparing to build an independent library building. Now that the National Library for the Disabled has secured its independent legal status, it must become a specialized national library by comprehensively collecting not only alternative materials for the disabled, but also domestic and foreign materials useful to researchers related to the disabled. Accordingly, the purpose of this study is to conduct basic research for comprehensive and strategic collection of library materials for people with disabilities, which is an essential part of the statutory work of the National Library for the Disabled. To this end, the concept and category of library materials for the disabled that are expected to be useful for satisfying the intellectual needs of the disabled and for education and research related to the disabled were established targeting knowledge information resources produced and distributed domestically and internationally. Next, based on the current collection development policy of the National Library for the Disabled, an implementation strategy and mid to long term roadmap for comprehensively collecting library materials were presented.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.5
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• pp.261-269
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• 2023

In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.69-97
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• 2024

It is important to plan and operate various training programs at the national level to develop librarians' job performance expertise and future-oriented capabilities. The purpose of this study was to examine the possibility of introducing a librarian learning community as an training program at a professional education and training institution and to suggest an appropriate operation method. To this end, research was conducted using the following contents and methods: 1) theoretical discussion on program operation such as the concept, operation stages, and types of a librarian learning community through a review of related literature; 2) exploring the possibility of operating a librarian learning community through pilot operation and derivation of implications, 3) proposal of a librarian learning community operation model. This study reviewed the librarian learning community operating model through participant observation and participant opinion collection during the pilot operation process to minimize confusion in the early stages of implementation, and also presented an operational roadmap and support system for the successful establishment of the program in the future. There is a need to further develop the librarian learning community operating model presented in this study through implementation and empirical analysis over the next several years. However, the results of this study will also be useful as an initial operating model for a learning community for professional education and training in other fields.