• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3832-3840
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• 2014

The rapidly aging population is also increasing the number of dementia patients rapidly. Studies have revealed the early signs of slowing progress. Therefore, dementia patient safety, continuous care, daily living, and health care are becoming more important. In this paper, a smart home care system using smart phones and Bluetooth communication technology was used to monitor the state of dementia patients of based on the results of grading dementia, health care of the dementia patients at home and provide for the safety of the system using motion sensors and gas leak sensors to respond to various emergency situations, such as fire, gas leak protection, and loitering. Using this system, the patient can stay longer in their home due to the nature of Korean culture before admission, while reducing the family's economical, physical and psychological burden and allowing the consultation of specialists through the system by building a database of individuals and providing professional service and specialty care referral agencies through the link.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.727-729
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• 2017

According to the National Statistical Office and the Ministry of Health and Welfare Family Department, Korea has already estimated that the proportion of the elderly population aged 65 or over is estimated to be higher than the global average, and has already entered the "Aging Society". Moreover, it is estimated that the quality of life of the people improved by reaching the information society earlier than expected. However, unlike young people, elderly people show clear differences in access and use of information that is difficult to access new machines easily and cause intergenerational digital divide phenomenon. In order to solve such a phenomenon, we implemented a speech recognition based smart mirror system for elderly people. The installed system can provide lighting control, weather forecast and subway time information search service of the using voice recognition. Through the implemented system, it is expected that the elderly will have accessibility to new machines, information that gives a feeling of participating in the change of the new era will be obtained and the effect of living convenience will be expected.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.37-48
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• 2012

These days many DLNA home media network services start in home network area. DLNA networking softwares included in DLNA media devices contains all of server, renderer and controller functions. But a home media device in home media network environment not uses all of DLNA functions but uses only limited functions. Using all of integrated DLNA functions wastes networking and processing resources especially in home media network, because a home media device uses very limited functions. For example, a smart-TV has a main role of playback and a network attached storage has a main role of media content storage. In this paper, we analyze integrated DLNA networking softwares and design DLNA software models representing each home media device so as to utilize device resources efficiently. And we implement DLNA softwares for smart-TV and smart-phone and test resource efficiency.

• Smart Media Journal
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• v.5 no.1
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• pp.38-43
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• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.16-24
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• 2021

This paper introduces a smart aging service that helps the elderly lead a happy old age by actively utilizing IoT and AI technologies for the elderly who are increasing rapidly as they enter the aging society. In particular, we propose a future-oriented, age-friendly well-being support system that breaks away from the existing welfare concept to solve the aging problem but leads to a paradigm shift toward building a vibrant aging society by protecting from emergency and satisfying emotions. By introducing IoT and AI, it judges the life situation and emotional state from the living information of the elderly can respond to emergencies and suggest meetings as a change of mood and give an emotional comfort. Since the proposed system uses artificial intelligence techniques to determine the degree of depression when inputting information such as pulse-rate, dangerous word usage, and external communication, I think it showed the feasibility of the new concept of wellbeing support system that is totally different from conventional wellbeing concept of health-care.

• Journal of Chest Surgery
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• v.55 no.2
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• pp.108-117
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• 2022

Background: The efficacy of telemedicine among cancer survivors is uncertain. The Smart After-Care Program (SAP), which is an interactive, smartphone-based remote health monitoring system, was developed to help patients manage their health after leaving the hospital. This study was designed to evaluate the efficacy of our remote health care program for lung cancer patients. Methods: We enrolled 50 patients with lung cancer. Self-monitoring devices were supplied to all patients, who were instructed to enter their daily vital signs and subjective symptoms to the Smart After-Care app. The app also provided information about rehabilitation exercises and a healthy diet for lung cancer patients. All patients received health counseling via telephone once a week and visited an outpatient clinic during weeks 6 and 12 to assess satisfaction with the SAP and changes in quality of life and physical performance. Results: Overall satisfaction with the SAP was very high (very good, 61.9%; good, 26.2%). In the multivariate analysis to identify factors affecting satisfaction, the distance between the patient's residence and the hospital was the only significant independent factor (p=0.013). Quality of life improved along all functional scales (p<0.05). Muscle strength significantly improved in the lower limbs (p=0.012). Two-minute walk distance also significantly improved (p=0.028). Conclusion: This study demonstrated that the SAP was acceptable for and supportive of patients with reduced pulmonary function after lung cancer treatment. The SAP was found to be particularly useful for patients living far from the hospital.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.125-130
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• 2021

Implementation of livestock smart-farm can be done more effectively with IoT technology developing. An build of useful stock management system can be possibile if push messages of these judgement are notified on smart-phone after cattle's illness and estrus are judged using IoT technology. These judgement method of cattle's illness and estrus can be done with gathering living stock data using temperature sensor and 3 axis acceleration sensor and sending these data using IoT and internet network into server, and studying AI machine learning using these data. In this paper, to build this cattle management system based on IoT, effective system of the whole architecture is showed. Also an effective analysis and design method to develop this system software will be presented by showing user requirement analysis using object-oriented method, flowchart and screen design.

• The Journal of Korean Physical Therapy
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• v.34 no.1
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• pp.12-17
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• 2022

Purpose: Ankle dorsiflexion is an essential element of normal functions, including walking, activities of daily living and sport activities. The tibialis anterior (TA) muscle functioned as a dorsiflexor and as a dynamic stabilizer of the ankle joint during walking and jumping. This study aimed to compare TA muscle thickness using ultrasonography according to the four different toe and ankle postures for the selective TA strengthening exercise. Methods: This study were recruited 26 (males: 15, females: 11) aged 20-30 years, with no injury ankle and calf in the medical history, had normal dorsiflexion and inversion range of motion (ROM). The thickness of the TA muscle was measured by ultrasonography in the four different toe and ankle postures: 1. Ankle dorsiflexion with all toe extension and ankle inversion (ITEDF); 2. Ankle dorsiflexion with all toe flexion and ankle inversion (ITFDF); 3. Ankle dorsiflexion with all toe extension and neutral position (NTEDF); 4. Ankle dorsiflexion with all toe flexion and neutral position (NTFDF). One-way repeated analysis of variance (ANOVA) and Bonferroni correction were used to confirm the significant difference among conditions. The level of statistical significance was set at α=0.01. Results: TA muscle thickness with ITFDF was significantly greater than in any other ankle positions, including ITEDF, NTFDF, and NTEDF (p<0.01). Conclusion: Among the four toe and ankle postures, isometric contraction in ITFDF postures showed the greatest increase in thickness of TA rather than ITEDF, NTEDF, and NTFDF postures. Based on these results, ITFDF can be recommended in an efficient way to selectively strengthen TA muscle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• Information Systems Review
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• v.25 no.2
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• pp.1-30
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• 2023

This study analyzes and examines the travel behavior of Chinese people in Korea through a questionnaire survey of Chinese people who are long-term residents in Korea using Xiaohongshu App (RED). In this study, we add some variables to the MTEs (Memorable Tourism Experiences) model to analyze the travel behavior of Chinese people who are in Korea for a long period of time. We also chose to survey the users of Xiaohongshu App (RED), a popular software in recent years, and found the following findings in 240 valid questionnaires: (1) Scenery, Entertainment, and Informativeness have positive effects on people sharing travel experiences, while interaction does not. (2) Sharing travel experiences had a positive effect on travel satisfaction and the intention to go to other destinations, and travel satisfaction had a positive effect on the intention to go to other destinations. This paper extends the literature on tourism by combining MTEs and UGC (User-Generated Content) models, and also provides relevant suggestions for further research on the travel behavior of foreigners in Korea.