• Korean Journal of Community Nutrition
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• v.17 no.1
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• pp.26-37
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• 2012

This study was done to analyze the consumption patterns of health functional food (HFF) as well as to perform needs assessment for the development of web-contents on HFF according to age of adults. The subjects were 238 male and female adults, divided into 4 groups by their age. This study collected all information by self-administrated questionnaires. The awareness on HFF was high in the older adults. The younger adults showed more negative responses to reliability and safety on HFF. The main reason for the consumption of HFF was to supplement nutrients and to prevent diseases. The main types of HFF consumed by adults were nutritional supplementary food, red ginseng products, and glucosamine products. There was higher consumption of nutritional supplementary food in the younger adults and glucosamine products in the older adults. Internet users had low level of satisfaction, with tendency to complain poor contents, reliability, difficulties in searching as problems of the pre-existing HFF websites. As useful methods for provision of information on HFF, most adults wanted general information, articles written by experts and videos. They also wanted to know the safety and side effects of HFF. Requirement of contents composition were various in-depth information, clear indication of citation, fresh updated data while that of display composition was easily-findable, uncomplicated, allowing mutual exchange of communication through bulletin board. These results can be used as basic data that reflect the consumer's needs for developing HFF web-contents according to age of adults.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.3020-3028
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• 2014

In the present study, A protocol gateway between agent is designed by using an optimized protocol for the exchange of ISO / IEEE 11073-20601 in order to compensate the disadvantage of the existing gateway and a international standard healthcare set-top. The gate way was designed to smooth data transmission to overcoming the geographical limits of the service and to enable data transfer on emergency vehicle and the mountain area.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.222-245
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• 2020

In the pandemic crisis, many governments implemented harsh interventions that might contradict democratic values and civil liberties. In Taiwan, the debate over whether or not to reveal personal information of infected persons to limit the coronavirus's spread poses the democratic dilemma between public health and civil liberties. This study examines whether and explains how Taiwan's people respond to the choice between individual privacy and collective security. We used survey data gathered in May 2020 to show that, first, the democratic values did not deter the pursuit of collective safety at the cost of civil liberty; rather, people with higher social trust were more likely to give up their civil liberties in exchange for public safety. Second, people who support democratic values and pursue collective security tend to avoid violating privacy by opposing the release of personal information. This study proves that democratic values do not necessarily threaten collective safety and that the pursuit of common good can co-exist with personal privacy.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.111-116
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• 2017

This paper proposes a data mining approach to predicting stock price direction. Stock market fluctuates due to many factors. Therefore, predicting stock price direction has become an important issue in the field of stock market analysis. However, in literature, there are few studies applying data mining approaches to predicting the stock price direction. To contribute to literature, this paper proposes comparing single classifiers and ensemble classifiers. Single classifiers include logistic regression, decision tree, neural network, and support vector machine. Ensemble classifiers we consider are adaboost, random forest, bagging, stacking, and vote. For the sake of experiments, we garnered dataset from Korea Stock Exchange (KRX) ranging from 2008 to 2015. Data mining experiments using WEKA revealed that random forest, one of ensemble classifiers, shows best results in terms of metrics such as AUC (area under the ROC curve) and accuracy.

• ETRI Journal
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• v.45 no.4
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• pp.594-602
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• 2023

Internet of things (IoT) is commonly employed to detect different kinds of diseases in the health sector. Systemic lupus erythematosus (SLE) is an autoimmune illness that occurs when the body's immune system attacks its own connective tissues and organs. Because of the complicated interconnections between illness trigger exposure levels across time, humans have trouble predicting SLE symptom severity levels. An effective automated machine learning model that intakes IoT data was created to forecast SLE symptoms to solve this issue. IoT has several advantages in the healthcare industry, including interoperability, information exchange, machine-to-machine networking, and data transmission. An SLE symptom-predicting machine learning model was designed by integrating the hybrid marine predator algorithm and atom search optimization with an artificial neural network. The network is trained by the Gene Expression Omnibus dataset as input, and the patients' data are used as input to predict symptoms. The experimental results demonstrate that the proposed model's accuracy is higher than state-of-the-art prediction models at approximately 99.70%.

• Korean Journal of Health Education and Promotion
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• v.27 no.5
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• pp.73-78
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• 2010

Background: Although collaboration for community health is emphasized, the concept and process of collaboration are rather unclear. International research has classified the types of collaboration and focused on the factors influencing successful collaboration. Greater attention is needed for collaboration practice and research domestically. Findings: By the level of intensity, the types of collaboration range from simpler networking to more formal and sophisticated collaboration. A 4-stage collaboration development consists of formation, implementation, maintenance, and institutionalization stages. Influential factors for collaboration development include: shared goals; operational structure and process; sufficient resources; member and leadership characteristics; environment and climate for collaboration; and information exchange and communication. Discussion: Most of collaboration research so far has dealt with partnerships and coalition building with community-based organizations, and much attention is given to private-public partnership for health. Contextual understanding and collaborative environment are the foremost tasks for us to enhance collaboration for community health in our centralized public health system.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.332-338
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• 2010

In this paper, Zigbee/PLC gateway system is designed for Ubiquitous health care. A protocol conversion algorithm for smooth information exchange between Zigbee and PLC communication has been implemented on the gatway. If a moving object is detected by wireless sensor, the data is transmitted to gateway. Zigbee/PLC gateway analyzes received data and transmits to Power Line Communication for real-time monitoring. Implemented system is can support elder who lives alone activity analysis, crime prevention system, Home network service.

• Journal of Korean Academy of Nursing
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• v.38 no.1
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• pp.152-160
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• 2008

Purpose: It has been attempted to support mother of premature infants by providing information of premature infant care using e-Learning because premature infants need continuous care from birth to after discharge. Method: The e-Learning Program for mother of premature was developed with Xpert, Namo web editor, Adobe Photoshop, and PowerPoint and applied for 4 weeks from 4 to 30 September 2006. Result: 1) We found that the contents of information which premature infants' need when being in the hospital and after discharge were the definition of a premature infant, orientation of NICU, care of premature infants, care of premature infants' common diseases, the connection of healthcare resources, exchange of information, and the management of rearing stress. 2) The program content consisted of cause of premature birth, comparison to full-term baby, physiology character, orientation of NICU, common health problems, follow up care, infection control, feeding, normal development physically and mentally, weaning method, and vaccination. Conclusion: Considering the results, this program for mother of premature is a useful means to provide premature-care information to mothers. This information can be readily accessible and can be varied and complex enough to be able to help mothers to the information and assistance they require.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.514-523
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• 2024

In the Internet of Medical Things, due to the sensitivity of medical information, data typically need to be retained locally. The training model of heart disease data can predict patients' physical health status effectively, thereby providing reliable disease information. It is crucial to make full use of multiple data sources in the Internet of Medical Things applications to improve model accuracy. As network communication speeds and computational capabilities continue to evolve, parties are storing data locally, and using privacy protection technology to exchange data in the communication process to construct models is receiving increasing attention. This shift toward secure and efficient data collaboration is expected to revolutionize computer modeling in the healthcare field by ensuring accuracy and privacy in the analysis of critical medical information. In this paper, we train and test a multiparty decision tree model for the Internet of Medical Things on a heart disease dataset to address the challenges associated with developing a practical and usable model while ensuring the protection of heart disease data. Experimental results demonstrate that the accuracy of our privacy protection method is as high as 93.24%, representing a difference of only 0.3% compared with a conventional plaintext algorithm.

• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.41-48
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• 2010

It is essential to guarantee a smooth communication and data exchange in a PHD(Personal Healthcare Device) network for applications providing U-health services. In spite of that, most of PHDs are heterogeneous, so the heterogeneity of their protocols makes it difficult to develop an integrated gateway sending sensed healthcare data to U-health service providers. To solve this problem, we suggest the design and implementation of a device adapter model based on dynamic managed module in this paper. Our model were implemented to work on the OSGi-based gateway middleware and to have interoperability in connection with the HL7 system that is the standard of the Healthcare Information systems. In addition, our model has an architecture supporting a communication based on the object serialization in order to provide extensibility in the functional aspect of applications. Through the experiment on a test-bed which is an implementation of the device adapter module for electrocardiogram and blood-pressure/blood-sugar device having one channel, we have confirmed the accuracy of sensing and sending data.