• The Journal of Economics, Marketing and Management
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• v.12 no.2
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• pp.73-81
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• 2024

Purpose: South Korea is a close ally of the US and an important partner of China. Caught between the two most powerful countries, South Korea's strategic directions are critical. This article emphasizes that the deeper core of the US-China trade war is to improve the business environment to attract foreign direct investment (FDI) to boost the economy, rather than engaging in the trade war. Research design, data, and methodology: Considering the complexity of this issue, this article applies a systematic analytical tool, the ABCD (Agility, Benchmarking, Convergence, and Dedication) model, to provide strategic guidance for inducing investments into South Korea in the context of the ongoing US-China trade war. Results: Specifically, South Korea needs to provide a more attractive business environment along the four points: expedite commercial activities through deregulation (Agility); adopt global standards of the flexible labor markets and technological developments (Benchmarking); integrate various industries and connect them to global value chains (Convergence); and create more economy-friendly policies rather than politics-oriented ones such as protectionism (Dedication). Conclusion: This study stands out not just by utilizing the ABCD model but, also by providing more systematic analysis and practical implications, particularly within the context of the escalating US-China competition. Unlike many existing studies that analyze the broader impacts of this geopolitical rivalry, this research delves into specific strategic guidelines for South Korea to attract FDI. The findings also provide implications for multinational corporations (MNCs) in choosing the locations for their overseas operations, particularly in South Korea.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.11-20
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• 2024

This study presents TabNet, a novel deep learning method, to enhance corporate credit rating accuracy amidst growing financial market uncertainties due to technological advancements. By analyzing data from major Korean stock markets, the research constructs a credit rating prediction model using TabNet. Comparing it with traditional machine learning, TabNet proves superior, achieving a Precision of 0.884 and an F1 score of 0.895. It notably reduces misclassification of high-risk companies as low-risk, emphasizing its potential as a vital tool for financial institutions in credit risk management and decision-making.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.691-702
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• 2019

Flood inundation map has various important roles in terms of municipal planning, timely dam operation, economic levee design, and building flood forecasting systems. Considering that the riparian areas adjacent to national rivers with high potential flood vulnerability conventionally imposed special cares to justify applications of recently available two- or three-dimensional flood inundation numerical models on top of digital elevation models of dense spatial resolution such as LiDAR irrespective of their high costs. On the contrary, local streams usually could not have benefits from recent technological advances, instead they inevitably have relied upon time-consuming manual drawings or have accepted DEMs with poor resolutions or inaccurate 1D numerical models for producing inundation maps due mainly to limited budgets and suitable techniques. In order to efficiently and cost-effectively provide a series of flood inundation maps dedicatedly for the local streams, this study proposed an OpenGIS-based flood mapping tool named Open Flood Mapper (OFM). The spatial accuracy of flood inundation map derived from the OFM was validated throughout comparison with an inundation trace map acquired after typhoon Nari in Hancheon basin located in Jeju Island. Also, a series of inundation maps from the OFM were comprehensively investigated to track the burst of flood in the extreme flood events.

• Journal of The Korean Association of Information Education
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• v.1 no.1
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• pp.38-48
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• 1997

This study is an attempt to present a usage of the Web as CAI in the classroom and to give a direction to the future education in the face of information age. Characteristcs of information society, current curriculum, educational and teacher education are first analyzed in this article. The features of internet and 'Web are then summarized to present benefits of usage in the classroom as a CAI tool. The literature shows several characteristics of information society as follows : a technological computer, a provision and sharing of information, multi functional society, a participative democracy', an autonomy, a time value..A problem solving and 4 Cs(e.g., cooperation, copying, communication, creativity) are newly needed in this learning environment. The Internet is a large collection of networks that are tied together so that users can share their vast resources, a wealth of information, and give a key to a successful, efficient. individual study over a time and space. The 'Web increases an academic achievement, a creativity, a problem solving, a cognitive thinking, and a learner's motivation through an easy access to : documents available on the Internet, files containing programs, pictures, movies, and sounds from an FTP site, Usenet newsgroups, WAIS seraches, computers accessible through telnet, hypertext document, Java applets and other multimedia browser enhancements, and much more, In the Web browser will be our primary tool in searching for information on the Internet in this information age.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.19-29
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• 2021

Although several industrial revolutions and technological developments have provided time for modern people, more than 75% of modern people are currently suffering from the problem of "lack of time". Therefore, in this paper, it was judged that it was necessary to improve the mobile APP service for efficient time management of modern people, and a study was conducted on the development of usability evaluation tools. First, the current status was analyzed through case studies of six time management apps with different purposes, and then usability studies were conducted to establish a total of five evaluation principles with operability, cognition, user suitability, minimization of work errors, and sharing. Based on this, a draft of the time management mobile app usability evaluation item was prepared, and a total of 44 usability evaluation tool items were derived through three Delphi surveys of design experts over 5 years and less than 10 years. As a result, intuitive screen and menu composition and user's perception of content were evaluated as the most important factors, and conclusions such as the need to improve the structure and function of the main content screen for user error prevention and usability were drawn. This study will not only contribute to improving the usability of existing time management mobile apps, but will also be used as a material for designing an integrated time management platform for efficient time management and purpose promotion in the future, and is expected to be used as an academic reference.

• Archives of design research
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• v.19 no.2 s.64
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• pp.31-42
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• 2006

This study originates from the following critical mind; what will the office of the future be like? and what technology will we rely upon most to communicate with colleagues or to access business information. In the office environment today, new technology has compelled new work paradigm and has greatly affected the capabilities of the individual to work in a more productive and efficient manner. However, even though new computer technology has changed the business world so rapidly, it is very difficult to see the changes that have been taken place. As an aim of the study, creating a mobile tool for office workers that successfully supports their work and communication was explored, and this study explored future work environment with a 5 years technological and social perspective. As a result of this study, the bON brings new visions to the mobile professionals via various interfaces. The bON, a mobile device, is both a system of work and of communication for office workers. The bON, as an integrated tool for working and communicating, forms the basis for a mobile information gateway that is equally capable of functioning as a mobile desk. The basic underlying idea is that all formal meeting places and hallways in the office are equipped with large wall-mounted screens. The bON collaborates with these media in various ways to enhance productivity and efficiency. The main challenge for the bON to enhance both mobility and quality of information is using new technology including bendable and flexible display and soft material display and sensors. To answer for the strong needs for mobility, the whole size of the device is fairly small while the screen is rolled inside the device. For Graphical User Interface, moreover, a new technique called Multi-layering Interface was adopted to stretch user's visual limits and suggests new direction in designing mobile device, equipped with small size display.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.1-20
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• 2008

Today's computing environment which is getting distributed to communicate with various systems needs dynamic inter-connectivity of the systems. MOM(Message Oriented Middleware) is popularly used for transmitting XML messages among the distributed systems for the inter-connectivity. But, they do not support event-based message routing functionalities with XML transformation for processing effective message routing, which is essential to inter-connectivity, and there is no integrated platform to cope with these requirements. Although event-based message routing and XML transformation have been studied in a wide range of computer science areas, development of message routing systems is considered as a tough job due to the technological difficulties. In order to address these requirements, we proposed a novel system, named RMRS(Rule-based Message Routing System), which supports event-based message routing as well as XML message transformation. To make the proposed system easy to use, we also redesigned ECA(Event- Condition-Action) rule to fit in our system and developed a tool to map source XML structure into target XML structure.