• Journal of Information Technology Services
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• v.11 no.sup
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• pp.139-152
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• 2012

In the medical web forum, people share medical experience and information as patients and patents' families. Some people search medical information written in non-expert language and some people offer words of comport to who are suffering from diseases. Medical web forums play a role of the informative support and the emotional support. We propose the automatic classification model of articles in the medical web forum into the information support and emotional support. We extract text features of articles in web forum using text mining techniques from the perspective of linguistics and then perform supervised learning to classify texts into the information support and the emotional support types. We adopt the Support Vector Machine (SVM), Naive-Bayesian, decision tree for automatic classification. We apply the proposed model to the HealthBoards forum, which is also one of the largest and most dynamic medical web forum.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.9-13
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• 2007

국내 금형 및 사출 제조업체들을 대상으로 경쟁력을 강화하기 위한 e-매뉴팩처링 인력양성이 필요한 실정이다. 본 연구에서는 금형 e-매뉴팩처링에 대한 교육을 위하여 e-러닝 사리트를 개발하고 이에 대한 교육 콘텐츠를 개발하였다. 금형 e-매뉴팩처링을 위한 e-러닝 싸이트는 교육 콘텐츠를 체계적으로 관리하고 수강할 수 있도록 LMS(Learning Management System)으로 개발하였다. 교육 콘텐츠로는 금형 e-매뉴팩처링 기본과점, UG-Mold Wirard 과정, UG-MX 중급과정, 금형 기술과정, 금형 협업허브시스템 사용자 교육과점 등을 개발하였다.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.351-356
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• 2007

현재의 사실상 국제 이러닝 표준으로 자리 잡은 SCORM 2004 기술규격은 '단일 사용자 콘텐츠 학습' 환경의 '웹 기반 자기 주도적 학습'에 근거하고 있다. 즉, 학습자 그룹을 포함한 협력적인 학습과정 설계가 가능하도록 하는 규격 부분이 부재한 상태이다. 이에 SCORM 규격을 기반으로 하여 협력학습 콘텐츠를 개발하는 연구가 활발히 진행되어 왔으나, 협력학습 콘텐츠를 탑재하는 플랫폼 즉, 협력학습을 지원하기 위한 학습관리 시스템의 표준화에 대한 연구는 거의 이루어지지 않은 실정이다. 따라서, 본 논문에서는 이러닝 협력학습의 표준화를 주도하고 있는 국제 이러닝 표준기구인 ISO/IEC JTC1 SC36의 연구 자료를 토대로 협력학습을 지원 가능한 방안을 제안하여 SCORM 2004 규격의 실행환경에 협력학습과 관련된 데이터모델을 추가하여 협력학습지원 시스템을 설계하고 구현하고자 한다.

• Proceedings of KOSOMES biannual meeting
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• 2000.05a
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• pp.27-36
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• 2000

Managing quality is nothing new, but it increasingly become more challenging. Demands form customers, flatter organizations, measuring and assessing outcomes, stiffer competition for resources, technology, environmental concerns and others, all have created changes in the workplace for which enhanced leadership is needed. TQM, CQI, TQL, (managing quality), other acronyms can be summarized as a means of moving an organization into the new millennium with a keen focus on people, service, efficiencies, effectiveness and excellence. It is not an accident. It is the result of a clear, well-directed strategically focused thinking. Attention to quality encourages individuals and teams throughout organizations to continually learn, think and contribute ideas on how to explore processes that affect them. The organization must change into a learning organization that seeks to continually improve its processes and services. This learning attitude requires a cultural shift from autocratic to more participatory leadership. This presentation will examine the principles and lessons learned form implementation of quality initiatives from different organizations. Many of the themes shared are independent of the source and, as such, may be helpful in validating what you are doing or give you ideas on leading and implementing change within your organizations.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.301-307
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• 2021

After the spread of the data collection devices such as smart meters, energy data is increasingly collected in a variety of ways, and its importance continues to grow. However, due to technical or practical limitations, errors such as missing or outliers in the data occur during data collection process. Especially in the case of customer-related data, billing problems may occur, so energy companies are conducting various research to process such data. In addition, efforts are being made to create added value from data, which makes it difficult to provide such services unless reliability of data is guaranteed. In order to solve these challenges, this research analyzes prior research related to bad data processing specifically in the energy field, and propose new missing value processing methods to improve the reliability and field utilization of energy data.

• Journal of Digital Convergence
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• v.13 no.3
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• pp.31-36
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• 2015

The Many universities and educational institutions have focused on shifting education paradigm into smart learning using high-tech devices and internet as the level of technology has growing rapidly in every society. Especially, cyber universities and open universities in Korea are trying to develop educational network system and infrastructure corresponding to new convergence technology environment. Therefore, the purpose of this study is to introduce clouded based education system in order to suggest an effective way of using new educational learning system. This study shows the case of Hangout learning system used in K University in Korea to suggest a new educational learning model for real-time lecture and cloud based service platform for improving educational learning environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.766-773
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• 2021

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.1-18
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• 2021

An academic library is one of the largest information sources for international students to obtain learning resources, which have a great impact on their studies. However, most academic libraries currently have not provided adequate multilingual services except English, which makes it difficult for international students whose mother language is not English to perform academic work. Accordingly, the present study defines the customized services for international students as the ones that have been supported in ltiple languages among academic library services and aims to examine their effect on user satisfaction in academic libraries. Furthermore, the study has compared international students' satisfaction with academic libraries - one that provides appropriate customized services with the other that does not. The surveys have been conducted with Chinese international students in two different universities and a total of 138 responses were analyzed. The study found that the customized services for the international students influenced their satisfaction with library use. In particular, multilingual services had positive effects on satisfaction with services such as brochures/signs, access to and use of resources through the homepage, and user instruction. The findings of the study suggest practical insights on how academic libraries provide effective services for supporting international students' academic tasks.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.73-79
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• 2019

Selecting a proper journal to submit a research paper is a difficult task for researchers since there are many journals and various decision factors to consider during the decision process. For this reason, journal recommendation services are exist as a kind of intelligent research assistant which recommend potential journals. The existing services are executing a recommendation based on topic similarity and numerical filtering. However, it is impossible to calculate topic similarity when a researcher does not input paper data, and difficult to input clear numerical values for researchers. Therefore, the journal recommendation method which consider the importance of decision factors is proposed by constructing the preference matrix based on the paper publication history of a researcher. The proposed method was evaluated by using the actual publication history of researchers. The experiment results showed that the proposed method outperformed the compared methods.