Journal of the Korean Society for information Management
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v.39
no.4
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pp.215-239
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2022
Human networks can be an important means of solving various information problems including tacit knowledge, as an essential channel of knowledge sharing. Particularly, in the case of a teacher librarian(or librarian) of a school library composed of one person in the organization, the human networks for work can be more effective with people outside the organization who are in charge of the same duties than with members inside the organization. Thus, this study aims at exploring the characteristics of the personal networks related to the work of teacher librarians and understanding the effect of these network characteristics on job satisfaction and role ambiguity resolution. A survey was conducted on one of the teacher librarian associations in Seoul, and the collected data were analyzed using social network analysis(SNA) method. As a result, it was found that personal networking of teacher librarians is active in experienced teacher librarians, while those with shorter career have fewer channels of help-seeking. Also, the characteristics of personal networking do not affect job satisfaction and the resolution of role ambiguity. Based on these results, this study proposes the expansion of collaborating and networking among teacher librarians to solve information problems in a single-person workplace.
Lee, Kwang Ho;Kim, Chang Hoon;Kim, Do Sam;Yeh, Harry;Hwang, Young Tae
KSCE Journal of Civil and Environmental Engineering Research
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v.29
no.3B
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pp.289-301
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2009
In this work, wave run-up heights and resultant wave forces on a vertical revetment due to tsunami (solitary wave) are investigated numerically using a numerical wave tank model called CADMAS-SURF (CDIT, 2001. Research and Development of Numerical Wave Channel (CADMAS-SURF). CDIT library, No. 12, Japan.), which is based on a 2-D Navier-Stokes solver, coupled to a volume of fluid (VOF) method. The third order approximate solution (Fenton, 1972. A ninth-order solution for the solitary wave. J. of Fluid Mech., Vol. 53, No.2, pp.257-271) is used to generate solitary waves and implemented in original CADMAS-SURF code. Numerical results of the wave profiles and forces are in good agreements with available experimental data. Using the numerical results, the regression curves determined from the least-square analysis are proposed, which can be used to determine the maximum wave run-up height and force on a vertical revetment due to tsunami. In addition, the capability of CADMAS-SURF is demonstrated for tsunami wave forces acting on an onshore structure using various configuration computations including the variations of the crown heights of the vertical wall and the position of the onshore structure. Based on the numerical results such as water level, velocity field and wave force, the direct effects of tsunami on an onshore structure are discussed.
Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.
Kyung Jun Ser;Jong Chan Choi;Min Jun Ji;Do Young Kwon;Jae Eun Yang;Ji Hyang Gu;Eun Jung Lee;Min Seok Oh
Journal of Korean Medicine Rehabilitation
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v.34
no.2
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pp.29-49
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2024
Objectives The purpose of this study is to systemically review the recent studies in the Korean medicine treatments for torticollis. Methods We search the clinical studies from January 1, 2018 to December 31, 2023. The studies were searched through 10 databases (Oriental Medicine Advanced Searching Integrated System, Korean studies Information Service System, Research Information Sharing Service, Korean Medical Database, ScienceON, PubMed, Cochrane Library, Embase, Wanfang Data, China National Knowledge Infrastructure). Results A total of 19 studies were included in the study. 12 studies were case report studies, 5 studies were randomized controlled trials, 2 studies were non-randomized controlled trials. Of the 19 interventions, Chuna was the most used in this study and of the 28 evaluation tools, Sternocleidomastoid thickness was the most used in this study except efficiency rate. All 19 studies had improvements after treatment, and 8 studies had statistically significant improvements. As a result of the study, we found that Chuna, GB, GB20, BL10, Glycyrrhiza uralensis were commonly used Korean medicine treatments for torticollis. Conclusions We analyzed the Korean medicine treatments for torticollis. Through this study, we found that the Korean medicine was effective for torticollis. However, more research is needed to confirm the more detailed effect.
Objectives : Gastric cancer is a malignant tumor of the digestive tract that not only has a high mortality rate, but also affects quality of life. In Traditional Korean Medicine, acupuncture and herbal medicines can increase the survival rate for Gastric cancer and improve the quality of life. Traditional Korean Medicine treatment played an important role when used alone or in combination with chemotherapy. However, there is still insufficient evidence to support the efficacy and safety of Traditional Korean Medicine in patients undergoing chemotherapy after surgery. Therefore, the purpose of this study is to systematically evaluate the effect of oriental medicine treatment on patients as a complementary therapy for Gastric cancer. Methods : 2 researchers will search using EMBASE, Pubmed, CNKI, Cochrane Library, CiNii, KMBASE, KISS, OASIS, RISS, ScienceON. The search period of the database is from inception until June 2022. This study will include a randomized controlled trial of GC for acupuncture and herbal treatment. Primary outcomes include anti-cancer effects. Secondary outcomes evaluate survival rates and improvements in quality of life. The data uses Review Manager Software 5.4. Results : This study will provide a systematic evaluation by synthesizing the anti-cancer effect, survival rate and quality of life of Gastric cancer when Traditional Korean Medicine is combined with chemotherapy. Conclusion : The conclusion of this study will provide a basis for determining whether Traditional Korean Medicine treatment for Gastric cancer treatment is an effective and safe treatment method in clinical practice.
Journal of the Korean Association of Geographic Information Studies
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v.27
no.1
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pp.29-40
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2024
Recently, the technology of autonomous driving, one of the core of the fourth industrial revolution, is developing, but sensor-based autonomous driving is showing limitations, such as accidents in unexpected situations, To compensate for this, HD-map is being used as a core infrastructure for autonomous driving, and interest in the public and private sectors is increasing, and various studies and technology developments are being conducted to secure the latest and accuracy of HD-map. Currently, NGII will be newly built in urban areas and major roads across the country, including the metropolitan area, where self-driving cars are expected to run, and is working to minimize data error rates through quality verification. Therefore, this study analyzes the spatial relationship of reference objects in the attribute structuring process for rapid and accurate renewal and production of HD-map under construction by NGII, By applying the attribute input automation methodology of the reference object in which spatial relations are established using the library of open source-based PyQGIS, target sites were selected for each road type, such as high-speed national highways, general national highways, and C-ITS demonstration sections. Using the attribute automation tool developed in this study, it took about 2 to 5 minutes for each target location to automatically input the attributes of the spatial relationship reference object, As a result of automation of attribute input for reference objects, attribute input accuracy of 86.4% for high-speed national highways, 79.7% for general national highways, 82.4% for C-ITS, and 82.8% on average were secured.
Min Jung Ko;Dong A Park;Sung Hyun Kim;Eun Sook Ko;Kyung Hwan Shin;Woosung Lim;Beom Seok Kwak;Jung Min Chang
Korean Journal of Radiology
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v.22
no.8
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pp.1240-1252
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2021
Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.
Wung Chul Jin;Seung Ik Baek;Yu Feng Sun;Xiang Dan Jin
Journal of Service Research and Studies
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v.14
no.2
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pp.18-36
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2024
As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.
The purpose of the archival appraisal has gradually changed from the selection of records to the documentation of the society. In particular, the qualitative and quantitative developments of the current digital technology and web have become the driving force that enables semantic acquisition, rather than physical one. Under these circumstances, the concept of 'documentary heritage' has been re-established internationally, led by UNESCO. Library and Archives Canada (LAC) reflects this trend. LAC has been trying to develop a new appraisal model and an acquisition model at the same time to revive the spirit of total archives, which is the 'Whole-of-society approach'. Features of this approach can be summarized in three main points. First, it is for documentary heritage and the acquisition refers to semantic acquisition, not the physical one. And because the object of management is documentary heritage, the cooperation between documentary heritage institutions has to be a prerequisite condition. Lastly, it cannot only documenting what already happened, it can documenting what is happening in the current society. 'Whole-of-society approach', as an appraisal method, is a way to identify social components based on social theories. The approach, as an acquisition method, is targeting digital recording, which includes 'digitized' heritage and 'born-digital' heritage. And it makes possible to the semantic acquisition of documentary heritage based on the data linking by mapping identified social components as metadata component and establishing them into linked open data. This study pointed out that it is hard to realize documentation of the society based on domestic appraisal system since the purpose is limited to selection. To overcome this limitation, we suggest a guideline applied with 'Whole-of-society approach'.
News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.
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