• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.96-111
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• 2002

A lot of accumulated data of many quantity exist within a institution or an organization, but most data is remained in form of standardization as each institution or organization. There are difficulty in exchange and share of information. New concept of knowledge information resource management to overcome this disadvantage was introduced, and the digitization of knowledge information resources to share and manage accumulated data is been doing. Specially, in science technic or education scholarship it, the tendency that importing XML to process necessary data to exchange and share of knowledge information resources structurally, and limitation of back for search and indexing or reusability is happened according as expression of great many mathematics used inside electron document of these sphere is processed to nonstructural data of image or text and so on. There is interest converged in processing of mathematics that use MathML to overcome this, and we require the solution to be able to process MathML easily and efficiently on structural document. In this paper, designed and implemented of XML document editing system which easy structural process of electronic document for knowledge information resources, and create and express MathML easily on structural document without expert knowledge about MathML.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.171-180
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• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.77-87
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• 2021

Smart Factory refers to a factory that can be controlled by itself with an intelligent factory that improves productivity, quality and customer satisfaction by combining the entire process of manufacturing and production with digital automation solutions. The manufacturing industry around the world is rapidly changing, with Germany, Europe, and the United States at the center. In order to cope with such changes, the Korean government is also implementing a policy to spread the supply of smart factories for small and medium-sized companies, and related ministries and agencies such as the Ministry of Commerce, Industry and Energy, the Ministry of SMEs and Venture Business, the Korea Institute of Technology and Information Promotion, and local technoparks, as well as large companies such as Samsung, SK and LG are actively investing in smart manufacturing projects to support smart factories[1]. Factory Automation (FA) construction has many issues regarding the connection of heterogeneous equipment. The most difficult aspect of configuring various communications from various equipment is the reason. Although it may not be known if there are standards or products made up of the same company, it is not easy to build equipment that is old, up-to-date, and different use environments through a series of communications. To solve this problem, we would like to propose a method of communication using Modbus, one of FieldBus, which is one of the many industrial devices of PLC, a representative facility control system, and is used as a communication standard.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.263-285
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• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.50-71
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• 2022

After the declaration of the Covid-19 pandemic impacted most of the industries resulting economic fallout. Firms sought for solutions of governments regulations to prevent spread of infectious diseases. This led to demand rise of digital layer and spectrums of virtual reality. Replacing the reality in to virtual and interactions with the digital contents by augmented reality, the consequences were decrement of human-to-human contact. Concerns of Covid-19 and public interests of digital solutions has led to significant amounts of research and developments of Virtual/Augment Reality resulted to driven up new terms of extended reality. However, the uses in industries and the characteristics of the extended reality are currently not defined. In this paper the goal is to define and classify the uses and characteristics of extended reality based on previous researches suggested by research institute. By developing a new classification models of extended realities core technology, uses of industries and utility to analyze trends of extended reality. Two separate classification models of uses of industries and utility will be used as a tool by creating a linkage matrix. The x-axis is divided by utiliy classification model of extended reality. The y-axis are divided into classification model of uses in industries. This matrix will be used as a tool to present a guideline for industry-utility development where extended reality can be served as a service

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.455-460
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• 2023

Text augmentation is a methodology that creates new augmented texts by transforming or generating original texts for the purpose of improving the performance of NLP models. However existing text augmentation techniques have limitations such as lack of expressive diversity semantic distortion and limited number of augmented texts. Recently text augmentation using large language models and few-shot learning can overcome these limitations but there is also a risk of noise generation due to incorrect generation. In this paper, we propose a text augmentation method called TAGS that generates multiple candidate texts and selects the appropriate text as the augmented text. TAGS generates various expressions using few-shot learning while effectively selecting suitable data even with a small amount of original text by using contrastive learning and similarity comparison. We applied this method to task-oriented chatbot data and achieved more than sixty times quantitative improvement. We also analyzed the generated texts to confirm that they produced semantically and expressively diverse texts compared to the original texts. Moreover, we trained and evaluated a classification model using the augmented texts and showed that it improved the performance by more than 0.1915, confirming that it helps to improve the actual model performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.117-132
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• 2022

Human Human species run into a blind alley due to abnormal weather and climates everywhere in global village. Human beings are helpless against the nature and might begin to learn humbleness just now. However, humans cannot attribute current abnormal weather and climates to only natural phenomenon because we have never been affectionate to global environments sufficiently up to now that results in running into this blind alley. At this point, the only thing that humans can do is to love and care for the earth more. ESG is an emerging topic to cope with this issue and practice of ESG will be the pending mission for the next generation. In this research, 'active participatory learning program for ESG practice' is designed by 'connecting ESG with Entrepreneurship' through over 20 years of experienced current teachers in elementary and junior·senior high school, professors in university and field experts in education. Analysis of learning effectiveness before and after the implementation of education program showed meaningful result in elementary and junior·senior high school. Thus, I would like to suggest a proposal based on concerns about 'What should we do to overcome the global crisis?" by paying attention to ESG from elementary school.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.23-34
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• 2019

The U-Healthcare era has evolved with the development of the Internet of things (IoT) in the early stages of being connected as a society. Already, many changes such as increased well-being and the extension of human life are becoming evident across cultures. Korea entered the growing group of aging societies in 2017, and its silver industry is expected to grow rapidly by adopting the IoT of a super-connected society. In particular, the senior shift phenomenon has resulted in increased interest in the promotion of the health and well-being of the emergent silver generation which, unlike the existing silver generation, is highly active and wields great economic power. This study conducted in-depth interviews to investigate the characteristics of the new silver generation, and to develop the design for a wearable serious game that intends to boost the interest of the elderly in exercise and fitness activities according to their personalized physical training regimes as prescribed by the U-Hospital service. The usage scenario of this wearable serious game for the 'U-silver generation' is derived from social necessity. Medical professionals can utilize this technology to conduct health examinations and to monitor the rehabilitation of senior patients. The elderly can also use this tool to request checkups or to interface with their healthcare providers. The wearable serious game is further aimed at mitigating concerns about the deterioration of the physical functions of the silver generation by applying personalized exercise prescriptions. The present investigation revealed that it is necessary to merge the on / off line community activities to meet the silver generation's daily needs for connection and friendship. Further, the sustainability of the serious game must be enhanced through the inculcation of a sense of accomplishment as a player rises through the levels of the game. The proposed wearable serious game is designed specifically for the silver generation that is inexperienced in using digital devices: simple game rules are applied to a familiar interface grounded on the gourmet travels preferred by the target players to increase usability.