• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• Journal of The Korean Astronomical Society
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• v.38 no.3
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• pp.357-363
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• 2005

A deep stellar analysis is introduced for the poorly studied open cluster NGC 2509. The Near-IR database of the digital Two Micron All Sky Survey (2MASS) has been used to re-estimate and refine the fundamental parameters of the cluster, i.e. age, reddening, distance, and diameter. As well as, luminosity function, mass function, total mass, relaxation time, and mass segregation of NGC 2509 have been estimated here for the first time..

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.234-237
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• 2007

Road networks are important geospatial databases for various GIS (Geographic Information System) applications. Road digital maps may contain geometric spatial errors due to human and scanning errors, but manually updating roads information is time consuming. In this paper, we developed a new road features updating methodology using from multispectral high-resolution satellite image and pre-existing vector map. The approach is based on initial seed point generation using line segment matching and a modified double snake algorithm. Firstly, we conducted line segment matching between the road vector data and the edges of image obtained by Canny operator. Then, the translated road data was used to initialize the seed points of the double snake model in order to refine the updating of road features. The double snake algorithm is composed of two open snake models which are evolving jointly to keep a parallel between them. In the proposed algorithm, a new energy term was added which behaved as a constraint. It forced the snake nodes not to be out of potential road pixels in multispectral image. The experiment was accomplished using a QuickBird pan-sharpened multispectral image and 1:5,000 digital road maps of Daejeon. We showed the feasibility of the approach by presenting results in this urban area.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.1-10
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• 2019

Research classification of software modules was done to validate the approaches proposed for addressing limitations in existing classification approaches. The objective of this study was to replicate the experiments of a recently published research study and re-evaluate its results. The reason to repeat the experiment(s) and re-evaluate the results was to verify the approach to identify the faulty and non-faulty modules applied in the original study for the prioritization of test cases. As a methodology, we conducted this study to re-evaluate the results of the study. The results showed that binary logistic regression analysis remains helpful for researchers for predictions, as it provides an overall prediction of accuracy in percentage. Our study shows a prediction accuracy of 92.9% for the PureMVC Java open source program, while the original study showed an 82% prediction accuracy for the same Java program classes. It is believed by the authors that future research can refine the criteria used to classify classes of web systems written in various programming languages based on the results of this study.

• Journal of Distribution Science
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• v.22 no.5
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• pp.11-26
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• 2024

Purpose: The concept of News-finds-me Perception (NFMP) is gaining increasing scholarly interest due to its wide-ranging findings and implications in digital communications and marketing. From the retail marketing and communication approaches, social media is an effective tool to effectively communicate and persuade customers and stakeholders. Nevertheless, a scarcity of systematic review studies that systematically assemble prior research in the field is recognized. Consequently, this research investigated the Scopus database for articles pertaining to NFMP. Research design, data and methodology: The search was conducted on August 24, 2023, retrieving 46 documents. Following a data-cleaning process, 31 documents remained, providing evidence of the subject area's five-year development. The data was refined with OpenRefine and analyzed with VosViewer. Results: An overview of the subject's expansion is presented, which comprises the most cited documents, authors, organizations, journals, and countries. Furthermore, the investigation examines the influential studies that furnished scientists with essential knowledge and identify the current research trend of the research subject. Conclusions: Based on the results, the study proposes theoretical and practical implications, encouraging academics to further integrate the concept with various communication and marketing theories, as well as the retail marketing context, to gain a better understanding of its complex impacts.

• Wind and Structures
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• v.15 no.1
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• pp.27-41
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• 2012

Wind loads on low-rise buildings in general and residential homes in particular can differ significantly depending upon the laboratory in which they were measured. The differences are due in large part to inadequate simulations of the low-frequency content of atmospheric velocity fluctuations in the laboratory and to the small scale of the models used for the measurements. The imperfect spatial coherence of the low frequency velocity fluctuations results in reductions of the overall wind effects with respect to the case of perfectly coherent flows. For large buildings those reductions are significant. However, for buildings with sufficiently small dimensions (e.g., residential homes) the reductions are relatively small. A technique is proposed for simulating the effect of low-frequency flow fluctuations on such buildings more effectively from the point of view of testing accuracy and repeatability than is currently the case. Experimental results are presented that validate the proposed technique. The technique eliminates a major cause of discrepancies among measurements conducted in different laboratories. In addition, the technique allows the use of considerably larger model scales than are possible in conventional testing. This makes it possible to model architectural details, and improves Reynolds number similarity. The technique is applicable to wind tunnels and large scale open jet facilities, and can help to standardize flow simulations for testing residential homes as well as significantly improving testing accuracy and repeatability. The work reported in this paper is a first step in developing the proposed technique. Additional tests are planned to further refine the technique and test the range of its applicability.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.419-426
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• 2023

Objectives: This study aims to develop an Occupational Safety and Health (OSH) guide for the safe cleaning of contaminated machinery, equipment, and parts used in the electronics manufacturing process. Methods: A literature review, field investigations, and discussions were conducted. An initial draft of an OSH guide was developed and reviewed by experts with significant experience in maintenance work in the electronics manufacturing process in order to refine the guide. Results: Workers involved in cleaning processes with chemicals, solvents, and abrasive blasting can face exposure to a wide range of chemicals, abrasives, and noise. Identifying potential risks associated with each cleaning technique was an essential first step toward enhancing safety measures. The OSH guide comprises approximately eleven to twelve sections spanning 20-25 pages. It includes engineering and administrative protocols systematically organized to address the necessary actions before, during, and after cleaning tasks, depending on the technique. It is recommended that airline respirator masks be used in conjunction with an air purification system to ensure adherence to air quality standard "D" for atmosphere level. The use of an oil-free air compressor is advised, preferably a stationary model that does not rely on fuel sources like diesel. Conclusions: This OSH guide is designed to protect workers involved in maintenance activity in the electronics industry and aligns with global standards, such as those from the International Organization for Standardization (ISO) and Semiconductor Equipment and Material International, ensuring a higher level of safety and compliance.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.135-149
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• 2014

This study proposed the ubiquitous learning system by finding the difficulties which students have in learning the course of science and analyzing the current learning applications that are used commercially. Through case studies, we found 4 problems. First, the request of long learning time by most of the existing video-based learning applications. Second, it is impossible to know their level of learning due to the lack of open learning contents. Third, it is difficult for learners to participate in interactive learning. Fourth, there are educational contents without considerations on the level of learners. To refine the difficulties due to these problems, we designed and implemented a new ubiquitous learning system which applies the small learning contents for short-term learning, open learning system and enhanced hierarchical learning contents. The system was implemented based on Android. It provides learners with useful science education. We conducted a questionnaire for third grade middle school students in order to show that the proposed system has a good educational effects. The questionnaire asks for the differences between the proposed ubiquitous learning system and the existing learning application. We concluded that the proposed system is better than the existing application by using t-test for improvement of learning effects using feedback with which students participate in interactive learning but not in unidirectional learning, and share the learning result.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.53-77
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• 2015

Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

• The Research Journal of the Costume Culture
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• v.24 no.6
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• pp.709-724
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• 2016

The purpose of this study is to develop a multi-dimensional scale measuring consumers' perceived challenge in shopping fashion products online, and to verify its validity and reliability. Relevant literature is first reviewed to identify possible dimensions of perceived challenge. Next, Study 1 is conducted in order to explore the dimensions empirically and to see whether the dimensions that emerged were consistent with prior findings. A total of 190 responses to an open-ended question was qualitatively analyzed by using content analysis. The findings of Study 1 generate 26 items reflecting four dimensions (i.e., product knowledge, previous experience, website functionality, and product availability), which correspond to the dimensions suggested in literature review. Study 2 is subsequently conducted to refine the items so that the perceived challenge scale establishes cross-validation, convergent validity, discriminant validity, reliability, and predictive validity. A total of 238 responses is quantitatively analyzed by using exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. In the results of Study 2, the perceived challenge scale is found to consist of a total of 16 items reflecting three dimensions: E-commerce Challenge (corresponding to Previous Experience reported in Study 1), Retailer Challenge (corresponding to Website Functionality), and Product Challenge (corresponding to Product Knowledge); all Product Availability items have been eliminated through the item refinement process. Specifically, E-commerce Challenge and Retailer Challenge are found to predict flow, supporting flow theory, while Product Challenge fails to lead to flow significantly. Implications, limitations, and suggestions for future studies are also discussed.