• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2067-2077
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• 2011

The recent trend in technology development is characterized as technology convergence, mainly between IT, BT and NT and also more and more industries are starting to use several technologies simultaneously or in a combined way theses days. As a result, the needs on technology interaction analysis is increasing for strategic technology management and policy-making. Responding to the needs, this research deals with technology innovation process in terms of technology competition, particularly focusing on the 17 new growth drivers in 3 areas, which has been announced by the Korean government as a new growth vision for Korean economy, and analyzing their co-evolutionary process. For the analysis, patent data, a representative data on technology innovation, is adopted. Then, Lotka-Volterra Competition model, a model frequently used to describe the dynamism of competitive innovation is applied to the data. The research results are expected to support strategic decision-makings such as effect policy-making or R&D priority-setting, by analyzing the relationship between the 3 areas, the 17 new growth drivers, or the particular technologies in the drivers.

• Electronics and Telecommunications Trends
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• v.23 no.5
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• pp.3-11
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• 2008

본 고에서는 국가 R&D를 통해 개발된 IT 융합기술을 소개하고 국책연구결과물의 시범적용을 통해 새로운 사업화 모델을 발굴하고 더불어 지자체와 함께 서비스 모델의 적용을 통한 상용화 추진내용을 소개하였다. 본 사업이 성공적으로 실시되면 일반 국민들이 새로운 IT 기반의 융합서비스를 이용함으로써 유비쿼터스 환경에서의 융합서비스에 대한 인식확산과 신성장동력으로서 IT 융합 산업 활성화에 기여할 것으로 기대하고 있다. BT는 물론이고 NT, 전통산업 등 다양한 분야와 융합을 확대해 국민의 삶을 더욱 윤택하고 행복하게 할 수 있는 따뜻한 IT, 즐거운 IT를 실현할 수 있을 것이다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.329-337
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• 2012

Capsule Endoscope(CE) is a capsule-shaped electronic device which can examine the lesions in digestive tract of human body. Recently the medical procedure using capsule endoscope is receiving great attention to both doctors and patients, since the conventional push-typed endoscope using cables brings great pain and fear to the patients. The technique was firstly available in 2000 and is based on a convergence techniques among BT(Bio Technology), IT(Information Technology), and NT(Nano Technology). The device consists of an optical parts including LEDs(Light Emitting Diodes), an image sensor, a communication module and a power module. Capsule endoscope is the embodiment of the state-of-the art technology and requires key technologies in the various engineering fields. Therefore, in this paper, we introduce the composition of the capsule endoscope system, and compare the communication method between RF(Radio Frequency) communication and HBC(Human Body Communication), which are typically used for data transmission in the capsule endoscope. Furthermore, we analyze the specification of commercialized capsule endoscopes and present the future developments and technical challenges.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.5
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• pp.368-373
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• 2010

In this study, we have investigated the effects of Cr dopant on the bulk trap levels and grain boundary characteristics of $Bi_2O_3$-based ZnO (ZB) varistor using admittance spectroscopy and dielectric functions (such as $Z^*,\;Y^*,\;M^*,\;{\varepsilon}^*$, and $tan{\delta}$). Admittance spectra show more than two bulk traps of $Zn_i$ and $V_o$ probably in different ionization states in ZnO-$Bi_2O_3-Cr_2O_3$ (ZBCr) system. Three kinds of temperature-dependant activation energies ($E_{bt}'s$) were calculated as 0.11~0.14 eV of attractive coulombic center, 0.16~0.17 eV of $Zn_{\ddot{i}}$, and 0.33 eV of $V_o^{\cdot}$ as dominant bulk defects. The grain boundaries of ZBCr could be electrochemically divided into two types as a sensitive to ambient oxygen i.e. electrically active one and an oxygen-insensitive i.e. electrically inactive one. The grain boundaries were electrically single type under 460 K (equivalent circuit as parallel $R_{gb1}C_{gb1}$) but separated as double one ($R_{gb1}C_{gb1}-R_{gb2}C_{gb2}$) over 480 K. It is revealed that the dielectric functions are very useful tool to separate the overlapped bulk defect levels and to characterize the electrical properties of grain boundaries.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.446-459
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• 2010

The technological convergence of IT, BT and NT is expected to drive technological revolution in the twenty first century, so a large amount of R&D expenditure is being concentrated on the development of fusion technology worldwide. Researches on how to direct and manage fusion technology development, however, are rare up to the present. This study investigates technology development and S&T human resources practices in the fusion technology are a focusing on the career path movement of researchers. On the basis of case study and a field survey of 209 scientists and engineers from academia, research institutes and industry, four strategic directions are recommended for improving human resources development in convergence technologies. The limitations and contributions of the study are also discussed.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.251-259
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• 2017

Recently, the smart healthcare industry that grafted the Internet of Things (IoT) onto the healthcare and medical services is being highlighted. Smart healthcare refers to the healthcare and medical services offered on the basis of information communication technologies including application, wearable devices and platforms, etc. The number of next generation smart healthcare devices are increasing in the smart healthcare industry through the combination of information technology (IT) and Bio Technology (BT), which are the most active areas among the 6T, which are the areas of the next generation industry. With the emergence of a diverse range of smart healthcare systems or devices, whether the smart healthcare system can be linked with other systems organically and the security and quality of the system have become important elements of evaluation. In this Study, the characteristics and service types of smart healthcare systems were examined, and the trends in the technology and industry of the smart healthcare system were analyzed. Moreover, this Study aims to develop the evaluation method for security and standards for quality evaluation by deducing the factors for the evaluation of smart healthcare system on the basis of the results of aforementioned examination. It is anticipated that this can induce improvement of quality and development of highly reliable products of a smart healthcare system, and will become the core technology to substitute the technology protection barrier.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.699-706
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• 2009

The convergence tendency accelerates the realization of the ubiquitous healthcare (u-Healthcare) between the technology including the power generaation and IT-BT-NT of the ubiquitous computing technology. By rapidly analyzing a large amount of collected from the sensor network with processing and delivering to the medical team an u-Healthcare can provide a patient for an inappropriate regardless of the time and place. As to the existing u-Healthcare, since the sensor node all transmitted collected data by using with the Zigbee protocol the processing burden of the base node was big and there was many communication frequency of the sensor node. In this paper, the u-Healthcare system in which it can efficiently apply to mobile apparatuses it provided the transfer rate in which it is superior to the bio-signal delivery where there are the life and direct relation which by using the Bluetooth instead of the Zigbee protocol and in which it is variously used in the ubiquitous environment was designed. Moreover, by applying the EEF(Embedded Event Filtering) technique in which data in which it includes in the event defined in advance selected and it transmits with the base node, the communication frequency and were reduced. We confirmed to be the system in which it is efficient through the simulation result than the existing Electrocardiogram Measurement system.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.171-180
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• 2014

Screen golf may be said as one of the most successful digital contents business along with the game industry. The success of the screen golf is because the high tech virtual reality technology is applied to the business in a way that it can meet the five senses of human and that the user can be absorbed into it. In addition, the interaction and playfulness in the screen golf helps the users to get more involved in the game, thus enhancing its value as one of the entertainments. Especially, this study focuses on its interaction and playfulness, which helped the screen golf succeed as a business because they help people to get more absorbed in the game through the communication and fun. From this point of view, the screen golf can be considered to have the best characteristics by which the users can be motivated to use the screen golf. Now along with the public success of the screen golf, the screen golf is recognized as the core field of digital contents. So, the screen golf needs the approaches and researches from multiple points of views, including culture and arts.