• Journal of Korea Technology Innovation Society
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• v.7 no.1
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• pp.64-88
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• 2004

This paper aims at investigating which factors play important roles in selecting government's new core IT industries and how competitive they are. We surveyed 6 competitiveness factors and 17 IT industries for the expert group. The logit and probit models were estimated and SWOT analysis was performed. The empirical results show that government put emphasis on marketability, externality and technology, not publicity, when selecting IT new core industry. The skilled human resources turn out to be a threat factor in the government selected IT new core industries such as home-network, third generation semi-conductor. Therefore, training or education system for skilled labors is required to develop and nurture such industries. The contribution to small medium venture industry and publicity are lower in the several industries such as intelligent service robots, post PC, embodied S/W, next generation battery, which are selected by government, not by standardized data based criterion. in such industries, marketabilities, technology, skilled human resources are threats factors to such industries. Therefore every effort for enhancing the marketability and R&D investment and education system for skilled labor are necessary to develop the industries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.742-743
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• 2017

The smart factory market is expected to show high growth rate in the future, supported by demand for manufacturing innovation in order to overcome structural low growth. Especially in the future manufacturing industry, robots are combined with IT, becoming the most important core technology. In this paper, we proposed and implemented state information classification method for IoT-based robot control in smart manufacturing environment.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.329-331
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• 2020

Edutech is a compound word of education and technology, and is an educational paradigm in the era of the 4th industrial revolution. This refers to next-generation education using information and communication technology (ICT) such as big data, artificial intelligence (AI), robots, and virtual reality (VR) of the 4th industrial revolution. e-Learning is being used as an online lecture for education in ICT, but edutech is attracting attention along with e-learning as the feeding of non-face-to-face education has rapidly increased due to COVID-19. Therefore, this paper summarizes the reviewed papers on the blockchain-based badge service platform, simulation-based collaborative e-Learning system, video English dictionary, and blockchain-based access control audit system.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.676-686
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• 2010

An URC (Ubiquitous Robot Companion) is aimed for providing the best service according to situational information that it recognizes. In order to offer human-friendly and intelligent services, a robot middleware requires the technique to automate and control URC service processes, which are based on context-awareness. In this paper, we propose a context-aware workflow system to provide web services based URC services according to situational information. The proposed system offers a platform-independent command object model to control heterogeneous URCs, and supports web services based context-aware URC services. Therefore, the proposed system can increase the reliability of URC services in ubiquitous network environment, on which the diverse URC robots and platforms exist. And it can enhance the flexibility and adaptability of the functional and structural changes of URC systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.80-85
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• 2007

As home network system begins serving in earnest, the recent fruits of research in home service robot show that the new epoch that human and intelligent robots are living, communicating and interacting together at home, may come true in the near future. In the other hand, it is generally known that the multiagent system, performing distributed process together with other different devices in a home network system, is better than single robot or single home server for adapting themselves to home environment and completing their mission because the characteristic of home environment is 'open'. Therefore, in this paper we suggest the framework model to define agents, which is needed lot the home with a home network system, and the communication protocol architecture between agents. For this, we focus our attention on an agent comprising the set of many agent instances rather than the single intelligent or ability of a robot or home server, and also suggest the way of adaptation for agent systems to their environments and interaction with human in the manner of cooperation and negotiation among agents or agent instances in each agent.

• Journal of Digital Contents Society
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• v.14 no.3
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• pp.333-341
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• 2013

Robot education has the favorable influence on creativity and problem-solving ability of students. Therefore, it is commonly known to elementary school students, their parents and teacher through robot education for after school and contests. However, it has not been actively taught at university of education students because of the lack of systematic education program. In this paper, we have developed robot education program using problem-based learning and educational robot for pre-service elementary teachers. We have examined their recognition on robot education and education program after applying the developed program. Interviews for improving robot education program were also conducted. We find out robot education program has the favorable influence on the recognition, satisfaction and effectiveness for robot education. In particular, we know that education will related to robot was augmented by this education program.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.463-466
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• 2017

The purpose of this paper is to develop a module capable of all-directional driving different from conventional wheeled robots, and to solve the problems of the conventional mobile robot with side driving performance degradation, It is possible to overcome the disadvantages such as an increase in the time required for the unnecessary driving. The all - direction spherical wheel drive module for driving a ball - balancing robot is required to develop a power transfer mechanism and a driving algorithm for driving the robot in all directions using three rotor casters. 3DoF (Axis) A driver with built-in forward motion algorithm is embedded in the module and a driving motor module with 3DoF (axis) for driving direction and speed is installed. The movement mechanism depends on the sum of the rotation vectors of the respective driving wheels. It is possible to create various movement directions depending on the rotation and the vector sum of two or three drive wheels. It is possible to move in different directions according to the rotation vector field of each driving wheel. When a more innovative all-round spherical wheel drive module for forward movement is developed, it can be used in the driving part of the mobile robot to improve the performance of the robot more technically, and through the forward-direction robot platform with the drive module Conventional wheeled robots can overcome the disadvantage that the continuous straightening performance is lowered due to resistance to various environments. Therefore, it is necessary to use a full-direction driving function as well as a cleaning robot and a mobile robot applicable in the Americas and Europe It will be an essential technology for guide robots, boarding robots, mobile means, etc., and will contribute to the expansion of the intelligent service robot market and future automobile market.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.41-61
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• 2023

The universal form of life in the era of the 4th industrial revolution can probably be summarized as the keyword "non-face-to-face". In particular, in terms of consumption activities, face-to-face contact is gradually changing to a system that minimizes, and offline stores are rapidly changing to non-contact services through kiosks and robots. The social structure is also changing with the passage of time, and most fundamentally, our dietary consumption patterns are changing. In particular, the increase in single-person households and the aging population are having a great impact on changes in the food service industry, which is closely related to dietary life. The HMR (Home Meal Replacement) market has grown significantly as the labor of cooking at home has decreased and the use of substitute foods has increased. As the size of the market has grown, the types of businesses that provide products have also diversified. The development of technology, non-face-to-face culture, and corporate management efficiency are intertwined, and unmanned stores are spreading recently. In this study, service quality attributes of HMR unmanned stores, where competition is gradually intensifying, are classified, and service quality classification using the Kano model and Timko's customer satisfaction coefficient are calculated to provide implications for service management based on customer satisfaction. As a result of the analysis, 'products with short cooking time' and 'variety of products (menu)' were classified as attractive qualities, and 'cleanliness inside/outside of the store' and 'products at reasonable prices' were classified as unified quality. In addition, 'convenience of self-checkout process' was classified as a natural quality, and 'convenience of in-store passage' was classified as an indifferent quality. Furthermore, when the service factor was satisfied within the HMR unmanned store, the factor with the highest satisfaction coefficient was 'product (menu) variety', and the factor with the highest dissatisfaction factor was 'convenience of self-checkout process'. Through the results of this study, it is intended to derive priorities in service quality management of HMR unmanned stores and provide strategic implications for related businesses.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.