• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3038-3047
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• 1996

In telerobot systems, visual servoing of a task object for a slave arm with an eye-in-hand has drawn an interesting attention. As such a task ingenerally conducted in an unstructured environment, it is very difficult to define the inverse feature Jacobian matrix. To overcome this difficulty, this paper proposes an auto-tuning fuzzy rule-based visual servo algorithm. In this algorithm, a visual servo controller composed of fuzzy rules, receives feature errors as inputs and generates the change of have position as outputs. The fuzzy rules are tuned by using steepest gradient method of the cost function, which is defined as a quadratic function of feature errors. Since the fuzzy rules are tuned automatically, this method can be applied to the visual servoing of a slave arm in real time. The effctiveness of the proposed algorithm is verified through a series of simulations and experiments. The results show that through the learning procedure, the slave arm and track object in real time with reasonable accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.79-84
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• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.391-406
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• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.59-65
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• 2016

With the recent growth in cloud computing, big data processing and collaboration between businesses are emerging as new paradigms in the IT industry. In an environment where a large amount of data is generated in real time, such as SNS, big data processing techniques are useful in extracting the valid data. MapReduce is a good example of such a programming model used in big data extraction. With the growing collaboration between companies, problems of duplication and heterogeneity among data due to the integration of old and new information storage systems have arisen. These problems arise because of the differences in existing databases across the various companies. However, these problems can be negated by implementing the MapReduce technique. This paper proposes a collaboration system based on Database as a Service, or DBaaS, to solve problems in data integration for collaboration between companies. The proposed system can reduce the overhead in data integration, while being applied to structured and unstructured data.

• Human Ecology Research
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• v.52 no.3
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• pp.243-253
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• 2014

This qualitative case study examined the experience of middle-aged homemakers with buying and wearing clothes. Clothing benefits and clothing purchase types were observed in the homemakers' daily clothing-related behavior. This study aims to understand clothing consumption values in light of clothing benefits and to determine purchasing methods, purchasing mental states, and personal characteristics according to the clothing purchase types of middle-aged homemakers. The participants of this study were four full-time homemakers and four homemakers with a job outside the home, all in middle age. This study was conducted through in-depth interviews based on an unstructured questionnaire, and the data were collected from January 2010 to October 2010. The results were as follows: first, the clothing benefits were identified as a social stereotype, aesthetic taste, economy, wearing situation, and age perception. The most important clothing consumption values to the middle-aged homemakers based on the observed clothing benefits were, in order: social value, emotional value, epistemic value, functional value, and conditional value. Second, the type of clothing purchase was observed to be planned buying, followed by impulse buying, and compensatory buying. Even when a homemaker planned to shop regularly, when they were exposed to an attractive retailer promotion, they seized on the opportunity on impulse or made a compensatory purchase to divert oneself. Even though homemakers prefer primarily impulse buying, when they went shopping for clothing with their mother-in-law or husband, they made planned purchase also.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.313-323
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• 2011

We study how the three antecedents of trust such as integrity, ability and benevolence affect trust building, based on the articles extracted from the New York Times during 1981-2010. Major findings are that the ratio of negative impact on trust from integrity is 86%, whereas the ratios of positive impact on trust from ability and benevolence are 70% and 71% respectively. Statistical tests show that the hypothesis that the negative impact of integrity on trust build-up will be higher is supported, but the most unstructured benevolence related hypotheses are not confirmed due to small sample sizes. Based on the study, we suggest that the future direction of IT application should accommodate benevolence factor seriously to fulfill corporate social responsibility.

• Journal of the Ergonomics Society of Korea
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• v.35 no.2
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• pp.75-84
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• 2016

Objective: The aim of this study is to suggest some improvement ideas based on the validity and the reliability analyses of the current safety culture measurement method applied to the Korean nuclear power industry. Background: Wrong safety culture is known as one of the major causes of the disasters such as the space shuttle Columbia disaster or the Fukushima Nuclear Power Plant accident. Assessment of safety culture of an organization is important to build a safer organizational environment as well as to identify the risks hidden in the organization. Method: A face validity of the current safety culture measurement method was analyzed by comparison of the key factors of safety culture in the Korean nuclear power industry with those factors reviewed in the previous studies. The current interview method was analyzed to identify the problems which degrade the consistency of evaluation. Results: Most safety culture factors reviewed in the literatures are covered in the list of the Korean nuclear power industry safety culture factors. However the unstructured questions used in the interview may result in inconsistency of safety culture evaluation among interviewers. Conclusion: This study suggests some examples which might improve the consistency of interviewers' evaluation on safety culture such as a post interview evaluation form. Application: An extended post interview evaluation form might help to increase the accuracy of the interviewing method for Korean nuclear industry safety culture evaluation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.376-382
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• 2005

In this paper, practical biped humanoid robot is presented, designed, and modeled by fuzzy system. The humanoid robot is a popular research area in robotics because of the high adaptability of a walking robot in an unstructured environment. But owing to the lots of circumstances which have to be taken into account it is difficult to generate stable and natural walking motion in various environments. As a significant criterion for the stability of the walk, ZMP (zero moment point) has been used. If the ZMP during walking can be measured, it is possible for a biped humanoid robot to realize stable walking by a control method that makes use of the measured ZMP. In this study, measuring the ZMP trajectories in real time situations throughout the whole walking phase on the flat floor and slope are conducted. And the obtained ZMP data are modeled by fuzzy system to explain empirical laws of the humanoid robot. By the simulation results, the fuzzy system can be effectively used to model practical humanoid robot and the acquired trajectories will be applied to the humanoid robot for the human-like walking motions.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1079-1082
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Excavation experiments are carried out to check the performance of the FLC.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.541-542
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• 2017

In this paper, we intend to develop an integrated management solution that can be easily operated by integrating complex and various cloud environments. This has the advantage that users and administrators can conveniently solve problems by collecting and analyzing fixed log data and unstructured log data based on big data and realizing integrated monitoring in real time. Hypervisor log pattern analysis technology will be able to manage existing complex and various cloud environment more efficiently.