• Convergence Security Journal
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• v.17 no.3
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• pp.59-64
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• 2017

Korea is experiencing a rapid increase in the number of elderly living alone accompanying the aging society problem, a nd is making efforts to solve the problem through the policy of 'living alone u-care service'. The purpose of this study is to propose a better u-Care service improvement method by applying new technology to improve the user experience of ucare service for the health and safety of the elderly living alone. First, the improvement of u-Care service for elderly livin g alone by applying IoT technology. It provides remote monitoring service using health information data measured through wearable device, and transmits personal health status to medical institution by using personal device such as smart phone, so that remote medical consultation or telemedicine can be connected in the future. Second, improvement of u-Care service through consideration of emotional stability of elderly living alone as well as simple safety and health care through applica tion of emotional service robot technology.It is expected that it will be able to help independent living of one person's elde rly person in the future by providing caring function service to existing u-care service providing service.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.278-281
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• 2003

본 논문에서는 모듈 기반 퍼스널 로봇 네트워크에서 실시간 서비스를 보장하기 위한 구조에 대하여 기술하였다. 모듈 기반 퍼스널 로봇 네트워크에서는 각기 다른 특징을 가지고 있는 이종의 네트워크 인터페이스를 사용한다. 이런한 환경에서 퍼스널 로봇 제어 메시지의 실시간 전송을 보장하기 위해 각 네트워크 인터페이스의 특징을 고려해 리소스 등을 관리하여 동적으로 할당하는 기능을 효과적으로 수행할 수 있는 구조에 대하여 제안하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1435-1439
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• 2004

Most recently, CP(Cellular Phone) has been one of the most important technologies in the IT(Information Tech-nology) field, and it is situated in a position of great importance industrially and economically. To produce the best CP in the world, a new technological concept and its advanced implementation technique is required, due to the extreme level of competition in the world market. The RT(Robot Technology) has been developed as the next generation of a future technology. Current robots require advanced technology, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition etc. unlike the industrial robots of the past. Therefore, this paper explains conceptual research for development of the RCP(Robotic Cellular Phone), a new technological concept, in which a synergy effect is generated by the merging of IT & RT. RCP infra consists of $RCP^{Mobility}$ $RCP^{Interaction}$, $RCP^{Integration}$ technologies. For $RCP^{Mobility}$, human-friendly motion automation and personal service with walking and arming ability are developed. $RCP^{Interaction}$ ability is achieved by modeling an emotion-generating engine and $RCP^{Integration}$ that recognizes environmental and self conditions is developed. By joining intelligent algorithms and CP communication network with the three base modules, a RCP system is constructed. Especially, the RCP mobility system is focused in this paper. $RCP^{Mobility}$ is to apply a mobility technology, which is popular robot technology, to CP and combine human-friendly motion and navigation function to CP. It develops a new technological application system of auto-charging and real-world entertainment function etc. This technology can make a CP companion pet robot. It is an automation of human-friendly motions such as opening and closing of CPs, rotation of antenna, manipulation and wheel-walking. It's target is the implementation of wheel and manipulator functions that can give service to humans with human-friendly motion. So, this paper presents the definition, the basic theory and experiment results of the RCP mobility system. We confirm a good performance of the RCP mobility system through the experiment results.

• Journal of Korean Gerontological Nursing
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• v.20 no.sup1
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• pp.144-153
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• 2018

Purpose: The purpose of this study was to review the influence of robot systems on nursing and robotics technology. Methods: The research design was a review article. The literature was done to help understand the current status and effects of robotic technology in the healthcare field, both domestic and overseas. The keywords searched were 'Nursing', 'Robot', and 'Patient safety' in Pubmed, CINAHL etc, and 'Nursing Activity', 'Nursing Care Integration Service' in RISS and KISS. Results: In healthcare, robotics is used in five areas; personal care robots, mobility and transfer robots, cognitive and emotional robots, nursing assist robots and care robots in palliative home care settings. Nurses' demands for utilization of robotic systems are high. Especially, if robotics is used for indirect and non-value-added nursing activities, efficiency may increase. Therefore, robotics should be used to help nurses focus on bedside care and perform better nursing care. Conclusion: Future robots and technology can help nurse to provide optimal nursing to patients, and will improve the quality life of patients. It is suggested that nursing research should be actively pursued in the future. Especially, it is an urgent field to improve nursing quality and reduce the burden of nurses.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.7
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• pp.161-166
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• 2001

The prototype of a tactile sensor with $4\times 4$ taxels using PVDF was fabricated. The electrode patterns of the thin Cu tape are attached to the 28${\mu}{\textrm}{m}$ thickness PVDF using conductive adhesive and covering the sensor using polyester film for insulation. The structure of the sensor is flexible and the fabrication procedure is easy relatively. Also the output characteristics of the sensor was nearly linear with 8% deviation. The signals of a contact pressure to the tactile sensor are sensed and processed through A/D converter, DSP system and personal computer. The reasonable performance for the detection of contact shape and force distribution was verified through the experiment.

• Journal of Yeungnam Medical Science
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• v.39 no.2
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• pp.116-123
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• 2022

Background: Recently, there have been various developments in medical service robots (MSRs). However, few studies have examined the perceptions of those who use it. The purpose of this study is to identify user perceptions of MSRs. Methods: We conducted a survey of 320 patients, doctors, and nurses. The contents of the survey were organized as follows: external appearances, perceptions, expected utilization, possible safety accidents, and awareness of their responsibilities. Statistical analyses were performed using t-test, chi-square test, and analysis of variance. Results: The most preferred appearance was the animal type, with a screen. The overall average score of positive questions was 3.64±0.98 of 5 points and that of negative questions was 3.24±0.99. Thus, the results revealed that the participants had positive perceptions of MSR. The overall average of all expected utilization was 4.05±0.84. The most expected utilization was to guide hospital facilities. The most worrisome accident was exposure to personal information. Moreover, participants thought that the overall responsibility of the robot user (hospital) was greater than that of the robot manufacturer in the case of safety accidents. Conclusion: The perceptions of MSRs used in hospital wards were positive, and the overall expected utilization was high. It is necessary to recognize safety accidents for such robots, and sufficient attention is required when developing and manufacturing robots.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.212-218
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• 2002

This research is the development of a distributed tactile sensor using PVDF film far the detection of the contact state. The prototype of the tactile sensor with 8$\times$8 taxels was fabricated using PVDF film and flexible circuitry. In the fabrication procedure, the electrode and the common electrode patterns are attached to the both side of the 28${\mu}m$ thickness PVDF film. The sensor is covered with polyester film for insulation. The signals of a contact pressure to the tactile sensor are sensed and processed in the DSP system in which the signals are digitalized and filtered. And the signals are integrated for taking the force profile. The processed signals of the output of the sensor are visualized to take the shape and force distribution of the contact object in personal computer. The usefulness of the sensor system is verified through the sensing examples.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.211-227
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• 2023

Personal service robots, a type of social robot that has emerged with the aging population and technological advancements, are undergoing a transformation centered around technologies that can extend independent living for older adults in their homes. For older adults to accept and use social robot innovations in their daily lives on a long-term basis, it is crucial to have a deeper understanding of user perspectives, contexts, and emotions. This research aims to comprehensively understand older adults by utilizing a mixed-method approach that integrates quantitative and qualitative data. Specifically, we employ the Van Kaam phenomenological methodology to group conversations into nine categories based on emotional cues and conversation participants as key variables, using voice conversation records between older adults and social robots. We then personalize the conversations based on frequency and weight, allowing for user segmentation. Additionally, we conduct profiling analysis using demographic data and health indicators obtained from pre-survey questionnaires. Furthermore, based on the analysis of conversations, we perform K-means cluster analysis to classify older adults into three groups and examine their respective characteristics. The proposed model in this study is expected to contribute to the growth of businesses related to understanding users and deriving insights by providing a methodology for segmenting older adult s, which is essential for the future provision of social robots with caregiving functions in everyday life.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.357-367
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• 2020

This study is a qualitative study conducted to understand and explain the operating room practice experience of nursing college students. Participants in this study were 67 nursing college students in 3rd and 4th grade at a university in C-gun, Gyeongsangbuk-do who participated in the practice of operating rooms. The data collection period was from January 14, 2019 to January 13, 2020, and the data collection was carried out through an open self-report-style reflection log, and the collected data was analyzed using the traditional content analysis method of Krippendorff [21]. Analysis of the operating room practice experience of nursing college students resulted in 27 sub-themes, 12 themes and 5 categories. The five categories are "Being seized with complicated feelings," "Being faced with dissection body," "Learning the characteristics of the operating room, " "Being confronted with the limits of clinical practice" and "Self-reflection." The results of this study provided an understanding of the operating room practice experience of nursing students and are expected to be used as basic data to improve the quality of practice of nursing students.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.