• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.117-127
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• 2005

Numerous internet pop advertisement are being provided according to the rapid development of e-commercial and a rise in users. However, it has not been based on analysis of users' inclination but just one-sided providing. With that reason, many web-site provider want to advertis e more efficient and distinguished Internet-advertisement as analyzing Server's Log accessed. In this thesis, we have studied and tested relatively simply adoption system to provide personalized advertisement service. In order to influence personal disposition to system as the most effective way, it first of all uses History files as source data and after refining it, it can search not only visitors' inclination but also the others' visit-list on the other server. As a result of it, it can make advertisement more reality and activity.

• CRM연구
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• v.4 no.1
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• pp.55-68
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• 2011

Recently with the development of Web services by utilizing a variety of web content, the studies on user experience and personalization based on web usage has attracted much attention. Majority of personalized analysis are have been carried out based on existing data, primarily using the database and statistical models. These approaches are difficult to reflect in a timely mannerm, and are limited to reflect the true behavioral characteristics because the data itself was just a result of customers' behaviors. However, recent studies and commercial products on web analytics try to track and analyze all of the actions from landing to exit to provide personalized service. In this study, by analyzing the customer's click-stream behaviors, we define U-Score(Usage Score), P-Score (Preference Score), M-Score(Mania Score) to indicate variety of customer preferences. With the devised three indicators, we can identify the customer's preferences more precisely, provide in-depth customer reports and customer relationship management, and utilize personalized recommender services.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.6
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• pp.949-957
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• 2009

The fashion apparel industries have demanded to be extremely consumer-oriented. Therefore, the need of personalization arises. The purpose of this study is to investigate the relationship between apparel shopping orientation and various personalization strategies provided in the apparel shopping process. A total of 422 questionnaires were used for statistical analysis. Canonical correlation and ANOVA were conducted. Results indicated that higher level of demand for "sale-promotion personalization" and "personalized customer relationship" were significantly related to high level of fashion innovativeness and price consciousness. Consumers who seek for high level of "personalized advice" and "personalized fit" were likely to be price conscious and conforming to clothing but not innovative in terms of fashion and clothing. Shopping orientation group differences were also reported in the study. In personalizing of apparel products, distinctive but relevant strategies should be implemented according to the need of the consumers.

• The Mathematical Education
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• v.59 no.4
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• pp.373-387
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• 2020

The purpose of this study is to verify the effects of personalized learning platforms applied with machine learning recommendation modules that upgrade recommended algorithms by themselves through learning big data analysis on students' learning time, self-directed learning ability, mathematics achievement, and attitudes toward mathematics, and the correlation between them. According to the study, customized learning affected learning time, self-directed learning ability and mathematics attitude, while learning time affected self-directed learning ability. Self-directed learning ability has had a significant impact on the attitude of mathematics and mathematical achievements. As a result of the mediated effectiveness test, the indirect impact of customized learning on mathematics attitude and mathematics performance was significant through the medium of learning time and self-directed learning ability.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.73-79
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• 2013

Recently, smart TVs have widely spread in our daily lives. However, it is difficult for users to find proper TV contents among a lot of TV and application contents because of inconvenience of input devices compared with those of smart phones or smart pads, so there are some problems with very low utilization of the smart functionalities of smart TVs. We suggest a personalized contents recommender system on smart TVs to resolve these problems and help for users to search appropriate contents easily and quickly in this research. We design and implement an intelligent system for personalized contents recommendation on the smart TVs based on multi-dimensional analysis considering user profiles and preferences, watching patterns of TV programs, and TV contents use statistics of TV users.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.2
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• pp.179-186
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• 2014

Metabolomics is the study of changes in the metabolic status of an organism as a consequence of drug treatment, environmental influences, nutrition, lifestyle, genetic variations, toxic exposure, disease, stress, etc, through global or comprehensive identification and quantification of every single metabolite in a biological system. Since most chronic diseases have been demonstrated to be linked to nutrition, nutritional metabolomics has great potential for improving our understanding of the relationship between disease and nutritional status, nutrient, or diet intake by exploring the metabolic effects of a specific food challenge in a more global manner, and improving individual health. In particular, metabolite profiling of biofluids, such as blood, urine, or feces, together with multivariate statistical analysis provides an effective strategy for monitoring human metabolic responses to dietary interventions and lifestyle habits. Therefore, studies of nutritional metabolomics have recently been performed to investigate nutrition-related metabolic pathways and biomarkers, along with their interactions with several diseases, based on animal-, individual-, and population-based criteria with the goal of achieving personalized health care in the future. This article introduces analytical technologies and their application to determination of nutritional phenotypes and nutrition-related diseases in nutritional metabolomics.

• Journal of Physiology & Pathology in Korean Medicine
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• v.29 no.1
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• pp.90-100
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• 2015

There are a lot of effort to improve medical service quality and medical trust in Korean Medicine. However, in spite of importance of personalized medicine, there are still few research about it. Thus, the purpose of this study is to grope ways to improve medical service quality and medical trust by sympathy module group and personalized trust. People over 19 were participated in investigation. We divided respondents into 4 groups depending on sympathy module group and 2 groups depending on speed of trust. Questionnaire was consisted of questions about sympathy module group, speed of trust, medical service quality, medical trust, satisfaction and happiness. This questionnaires were conducted through personal interviews. Total 220 members responded to the survey and the results of the analysis were as follows. Rational type had the highest proportion. At Medical service quality scale, Prevention focus group had most highest figure on Confidence. Promotion focus group and Rational Group had most highest figure on Sympathy. At Medical trust scale, Medical team had the highest proportion at all group. Prevention focus group put more emphasis on sense of sanitation, At Satisfaction and Happiness scale, Satisfaction and Happiness was most affected by Trust in Sincerity and Ability. This study can be very useful for composing kit of treatment of personalized medicine. But this study has also some limits such as respondent selection, disease selection etc. So, more detailed and comprehensive survey is needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.873-878
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• 2020

Due to the recent development of 3D printers, interest in 3D printing is growing. 3D printing should reflect individual needs and various requirements by designing products to suit the user's requirements. Research on how to use 3D printed products for the purpose of purchasing products according to user's demand characteristics is insufficient. Therefore, this study conducted a survey and statistical analysis to find out the factors influencing the intention of purchasing custom controller products in 3D printing environments. Research has confirmed that user innovation and convenience safety are important factors for the satisfaction and purchase intent of personal-tailored controller products. Considering user innovation, convenience, and safety when producing controller products using 3D printing, it is expected that value of custom controller manufacturing can be increased. Research is needed on the personalized product development framework that successfully introduces and systematically supports the production methods of personalized products in the early stages.

• Journal of Korean Academy of Nursing
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• v.52 no.5
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• pp.535-549
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• 2022

Purpose: The study aimed to design and develop an automated personalized self-care (APSC) program for patients with type 2 diabetes mellitus. The secondary aim was to present a clinical protocol as a mixed-method research to test the program effects. Methods: The APSC program was developed in the order of analysis, design, implementation, and evaluation according to the software development life cycle, and was guided by the self-regulatory theory. The content validity, heuristics, and usability of the program were verified by experts and patients with type 2 diabetes mellitus. Results: The APSC program was developed based on goal setting, education, monitoring, and feedback components corresponding to the phases of forethought, performance/volitional control, and self-reflection of self-regulatory theory. Using the mobile application, the participants are able to learn from educational materials, monitor their health behaviors, receive weekly-automated personalized goals and feedback messages, and use an automated conversation system to solve the problems related to self-care. The ongoing two-year study utilizes a mixed method design, with 180 patients having type 2 diabetes mellitus randomized to receive either the intervention or usual care. The participants will be reviewed for self-care self-efficacy, health behaviors, and health outcomes at 6, 12, 18, and 24 months. Participants in the intervention group will be interviewed about their experiences. Conclusion: The APSC program can serve as an effective tool for facilitating diabetes health behaviors by improving patients' self-care self-efficacy and self-regulation for self-care. However, the clinical effectiveness of this program requires further investigation.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.13-18
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• 2008

In these days, wearable and mobile physiological sensing devices have been studied according to the increasing interest on the healthy and wellbeing life. However, these sensing devices display just the sensing results, such as heart rate, skin temperature, and its daily records. In this work, we propose the novel type of mobile physiological sensing device which deliver the user comfortable grabbing feeling. In addition, we indicate the personalized physiological signal analysis result which be concluded by the different analysis results according to the person to person. In order to verify this sensing device, we collect the data set from 4 different users during a week and measure the physiological signal such as heart rate, hand temperature, and skin conductance. And we observe the result how the analysis results shows the difference between the users. We expect that this work can be applied in the various health care applications in the near future.