• The Journal of Bigdata
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• v.7 no.2
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• pp.103-111
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• 2022

There are many institutions, organizations, and sites related to responding to infectious diseases, but as the pandemic situation such as COVID-19 continues for years, there are many changes in the initial and current aspects, and accordingly, policies and response systems are evolving. As a result, regional gaps arise, and various problems are scattered due to trust, distrust, and implementation of policies. Therefore, in the process of analyzing social data including information transmission, Twitter data, one of the major social media platforms containing inaccurate information from unknown sources, was developed to prevent facts in advance. Based on social data, which is unstructured data, an algorithm that can automatically detect infectious disease threats is developed to create an objective basis for responding to the infectious disease crisis to solidify international competitiveness in related fields.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.113-118
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• 2024

In this study, we designed and analyzed two main structures for effectively implementing the behavior of intelligent NPCs the Hierarchical Finite State Machine (HFSM) and the Behavior Tree, by creating experimental games. The HFSM was found to be efficient for complex interaction-centered actions where state changes and transitions are crucial, while the Behavior Tree was effective in dynamic environments where ease of modification and expansion are required for dynamic responses under various conditions. These structures were experimentally applied using the Unity engine to verify their efficiency. This study focused on the basic structure design and plans to apply these structures to an upcoming action-adventure escape game. The results of this research are expected to assist game developers in efficiently implementing intelligent NPCs, thereby contributing to the improvement of game quality and player satisfaction.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.271-291
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• 2014

The purpose of this study is to analyze undergraduate nursing students' electronic document use and reading behavior. To do this, a survey questionnaire was collected from 509 respondents who experienced reading behavior for the last semester. The results of this study show that nursing students' preference of electronic documents is higher than that of printed documents in general. They also prefer electronic documents to printed documents when they want to keep documents. Of respondents, about 94% or higher spent 30mins or more to find information and the main source to find information is 'Naver' search engine as the highest information source, and the place to access information is 'Home' as their highest information access location. In particular, the preference of the document 'on the move' is electronic documents and the main reason includes convenience and easiness to access and move the documents. The findings of this study expect to facilitate the understanding of undergraduate nursing students electronic document use and reading behavior so that it can be used to design and develop medical digital library services and tools more effectively and efficiently in medical area in the future. Furthermore, it expects to provide useful data in promoting user services in digital library in a whole.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.58-64
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• 2010

As a modem urban train is getting complex in terms of high-technology in its systems and components, the failure management should be performed with scientific and systematic technique. FMEA is a technique to analyze the failure trends of component parts and influences to the higher level system in order to discover the design incompleteness and potential defects, which is for improving reliability. Especially, FMECA (Failure Mode Effects, and Criticality Analysis) is used in case that the criticality that has an immense influence to the system is important. In case of urban train, in its design and manufacturing steps, FMEA is frequently used as an analysis technique to meet the safety objectives and eliminate potential hazards/failures since the concepts of reliability of train is introduced these days. Though, FMEA technique in the maintenances steps lacks in its investigation and applications yet. FMEA is also not applied to the trains operated by Seoul metro in the design and manufacture steps excepts the newest trains. In this paper, through analyzing the failures/maintenance data of the belt-type door systems used in trains operated in Seoul metro Line 1, which is accumulated in RIMS (Rolling-stock Information Maintenance System), FMEA procedures to the belt-type door engines are proposed. Especially, an effort is made, to approach the detailed FMECA procedures to the door magnet valve and switch and door engine devices which vastly influences the customer safety and satisfaction.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.107-115
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• 2014

Recently, increased use of the internet resulted in generation of large and diverse types of data due to increased use of social media, expansion of a convergence of among industries, use of the various smart device. We are facing difficulties to manage and analyze the data using previous data processing techniques since the volume of the data is huge, form of the data varies and evolves rapidly. In other words, we need to study a new approach to solve such problems. Many approaches are being studied on this issue, and we are describing an effective design and development to build indexing engine of big data platform. Our goal is to build a system that could effectively manage for huge data set which exceeds previous data processing range, and that could reduce data analysis time. We used large SNMP log data for an experiment, and tried to reduce data analysis time through the fast indexing and searching approach. Also, we expect our approach could help analyzing the user data through visualization of the analyzed data expression.

• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.9-20
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• 2013

Defense M&S for weapons effectiveness is a realistic way to support virtual warfare similar to real warfare. As the war paradigm becomes platform-centric to network-centric, people try to utilize smartphones as the source of sensor, and command/control data in the simulation-based weapons effectiveness analysis. However, there have been limited researches on integrating smartphones into the weapon simulators, partly due to high modeling cost - modeling cost to accomodate client-server architecture, and re-engineering cost to adapt the simulator on various devices and platforms -, lack of efficient mechanisms to exchange large amount of simulation data, and low-level of security. In this paper, we design and implement Smartphone Adaptor to utilize smartphones for the simulationbased weapons effectiveness analysis. Smartphone Adaptor automatically sends sensor information, GPS and motion data of a client's smartphone to a simulator and receives simulation results from the simulator on the server. Also, we make it possible for data to be transferred safely and quickly through JSON and SEED. Smartphone Adaptor is applied to OpenSIM (Open simulation engine for Interoperable Models) which is an integrated simulation environment for weapons effectiveness analysis, under development of our research team. In this paper, we will show Smartphone Adaptor can be used effectively in constructing a Live simulation, with an example of a chemical simulator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.311-316
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• 2017

The network analysis method has emerged as a new methodology for various disciplines, due to its ability to provide a representative knowledge network of references, co-authors and keywords. Bulletproof technology is an interdisciplinary field involving various disciplines, such as material mechanics, structural mechanics, and ballistics, so it is essential to keep up with the recent trends in technological research. In this research, the recent R&D trends in the field of bulletproof materials were analyzed using keyword based network analysis. From the results, the core keywords were identified as 'Composite', 'Model' and 'Head' using the scholar search engine, google scholar. The centrality analysis for the core keywords showed that bulletproof technology has developed in 3 different areas, viz. material, structure and effects. To the best of our knowledge, this is the first application of (network analysis?) to bulletproof technology. Moreover, we are also convinced that the results of this study will be useful for defense technology planning and determining the direction of R&D in the field of bulletproof technology.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.93-106
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• 2021

Blenderbot 2.0 is a dialogue model representing open domain chatbots by reflecting real-time information and remembering user information for a long time through an internet search module and multi-session. Nevertheless, the model still has many improvements. Therefore, this paper analyzes the limitations and errors of BlenderBot 2.0 from three perspectives: model, data, and dialogue. From the data point of view, we point out errors that the guidelines provided to workers during the crowdsourcing process were not clear, and the process of refining hate speech in the collected data and verifying the accuracy of internet-based information was lacking. Finally, from the viewpoint of dialogue, nine types of problems found during conversation and their causes are thoroughly analyzed. Furthermore, practical improvement methods are proposed for each point of view, and we discuss several potential future research directions.

• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.67-74
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• 2018

Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.539-549
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• 2024

This study employed text mining techniques like frequency analysis, word clouds, and LDA topic modeling to assess consumer satisfaction and dissatisfaction with Hyundai Motor Company in the Chinese market, compared to brands such as Toyota, Volkswagen, Buick, and Geely. Focusing on compact vehicles from these brands between 2021 and 2023, this study analyzed customer reviews. The results indicated Hyundai Avante's positive factors, including a long wheelbase. However, it also highlighted dissatisfaction aspects like Manipulate, engine performance, trunk space, chassis and suspension, safety features, quantity and brand of audio speakers, music membership service, separation band, screen reflection, CarLife, and map services. Addressing these issues could significantly enhance Hyundai's competitiveness in the Chinese market. Previous studies mainly focused on literature research and surveys, which only revealed consumer perceptions limited to the variables set by the researchers. This study, through text mining and comparing various car brands, aims to gain a deeper understanding of market trends and consumer preferences, providing useful information for marketing strategies of Hyundai and other brands in the Chinese market.