• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.846-851
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• 2010

In this paper, we newly propose a novel control strategy of a three joints-robot finger for the purpose of artificial hands. The robot finger is specifically modeled by using a 3D CAD program (CATIA), considering human fingers, and then the proposed control method is verified through the dynamic simulation tool (Simulink and Recurdyn R2). Each slider is individually controlled to be located at the optimal positions where the maximal joint torque can be generated. To prove the effectiveness of the proposed control method, we devise two cases for the reference position of sliders. By comparing the control performance of two cases, the validity of the proposed control method will be verified.

• Journal of Korean Neurosurgical Society
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• v.38 no.2
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• pp.151-154
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• 2005

A 43-year-old woman was admitted with the chief complaint of progressive visual disturbance and her brain radiological studies disclosed well demarcated tumor at tuberculum sellae area and bilateral mirror image paraclinoid internal carotid artery saccular aneurysms. A larger left side aneurysm was pointing medialy and almost encased by the tumor. Although a brain tumor and intracranial aneurysm can be simultaneously treated by surgery, the high risk of intra-operative aneurysm rupture should be considered. Therefore, the author secondly performed tumor resection after the endovascular embolization of the aneurysm which was embedding the tumor using a Guglielmi detachable coil. After successful treatment of the patient with tuberculum sellae meningioma associated with bilateral mirror image paraclinoid aneurysms using endovascular and surgical techniques, the authors present the case with a review of the related literatures.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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• pp.89-104
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• 1997

Performance bottleneck of parallel computer systems has mostly been I/O devices because of disparity between processor speed and I/O speed. Therefore I/O node placement strategy is required such that it can minimize the number of I/O nodes, I/O access time and I/O traffic in an interconnection network. In this paper, we propose an optimal distance-k embedding algorithm, and analyze its effect on system performance when this algorithm is applied to n x n torus architecture. We prove this algorithm is an efficient I/O node placement using software simulation. I/O node placement using the proposed algorithm shows the highest performance among other I/O node placements in all cases. It is because locations of I/O nodes are uniformly distributed in the whole network, resulting in reduced traffic in the intE'rconnection network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4143-4159
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• 2015

We-the-media (aka wedia) is a concept where the users of social networking sites, such as Facebook, turn into the broadcasters. This study used the popular application Bitstrips as the experiment tool. Facebook was used as the Wedia platform for publishing designed comics, then used the three elements of Goffman's dramaturgy model-role, scene and dialog-to analyze 265 comics created by 3 researchers and observe the audience's responses within 9 months. The results showed that people want to see a good story with positive dialogue, and prefer scene is school more than work. As all these elements are controllable, Wedia communication has the potential for more applications. We also found that including the elements of news, gambling and gift-giving tended to trigger greater response. Furthermore, We suggesting that such embedding of product information in web episodes (webisodes) with caricature could be a successful marketing strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4557-4572
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• 2020

The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis. Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines. In this paper, we propose a method to ensemble multiple deep learning steganalyzers. We select SRNet and RESDET as our base models. Then we design a three-layers model ensemble network to fuse these base models and output the final prediction. By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved. The proposed method won second place in the Alaska 1 competition in the end.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.80-88
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• 2023

RGB-thermal (RGB-T) tracking using unmanned aerial vehicles (UAVs) involves challenges with regards to the similarity of objects, occlusion, fast motion, and motion blur, among other issues. In this study, we propose dynamic tracking aggregation (DTA) as a unified framework to perform object detection and data association. The proposed approach obtains fused features based a transformer model and an L1-norm strategy. To link the current frame with recent information, a dynamically updated embedding called dynamic tracking identification (DTID) is used to model the iterative tracking process. For object association, we designed a long short-term tracking aggregation module for dynamic feature propagation to match spatial and temporal embeddings. DTA achieved a highly competitive performance in an experimental evaluation on public benchmark datasets.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.360-374
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• 2024

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.7-14
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• 2022

Sensor Registry System (SRS) has been devised for maintaining semantic interoperability of data on heterogeneous sensor networks. SRS measures the connectability of the mobile device to ambient sensors based on positions and only provides metadata of sensors that may be successfully connected. The step of identifying the ambient sensors which can be successfully connected is called sensor filtering. Improving the performance of sensor filtering is one of the core issues of SRS research. In reality, GPS sometimes shows the wrong position and thus leads to failed sensor filtering. Therefore, this paper proposes a new sensor filtering strategy using geographical embedding and neural network-based path prediction. This paper also evaluates the service provision rate with the Monte Carlo approach. The empirical study shows that the proposed method can compensate for position abnormalities and is an effective model for sensor filtering in SRS.

• The Korean Journal of Franchise Management
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• v.8 no.1
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• pp.19-30
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• 2017

Purpose - As environmental issues, along with the growth of companies, are accelerating, social interests in eco-friendly management that requires corporate social role and responsibility are increasing. The eco-friendly management activity reflects the changes in environmental awareness of consumers. Therefore, the eco-friendly images of companies influence consumers, and the establishing of eco-friendly management strategy has become a very important factor in the greenmarket. In this regard, this study examined the impacts of green leadership and environmental attractiveness on strategic environmental marketing, tactical environmental marketing, and environmental performance towards the employees of franchisee headquarters. Research design, data, and methodology - The survey was conducted towards the 800 headquarters among 2,600 brands that are registered with the Fair Trade Commission of Korea by mail. Among the total of 162 questionnaires collected, 7 respondents were excluded for their incompletion, and thus 155 responses were used in this study. The data were analyzed with SPSS 21.0 and SmartPLS 3.0. Frequency analysis was carried out to understand the general characteristics of the subjects, and confirmatory factor analysis to measure the reliability and validity of the measurement. Correlation analysis was conducted to identify the correlation between constructs, and structural equation modeling to examine the structural relationships among the constructs. Result and Conclusions - First, green leadership had a positive impact on strategic environmental marketing, tactical environmental marketing, and environmental performance. Second, environmental attractiveness had a positive effect on strategic environmental marketing, tactical environmental marketing, and environmental performance. Finally, strategic environmental marketing and tactical environmental marketing had positive impacts on environmental performance. This study can be recognized for proposing new perspectives on eco-friendly management strategy for firms to be able to win competitive superiority and performance by embedding awareness of the importance of environmental market and suggesting practical implications on understanding of environmental attractiveness, strategies and tactics of environmental management, and environmental performance in the franchise industry.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.4
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• pp.782-798
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• 2016

This paper discusses the European Union's smart specialization strategy and US manufacturing renaissance policy and then proposes new directions for regional industrial policy in Korea. The smart specialization strategy is summarized as the entrepreneurial self-discovery and strategic coordination; the manufacturing renaissance policy as the construction of industrial commons based on ecosystem; and Korea's regional industrial policy as the build-up of regional innovation system based upon industrial clusters. The policy cases of the EU and the United States demonstrate the fact that regional industrial policy should be geographically embedded. Also, they show the relevance of policy mix by linking industrial policy with innovation policy for cross-fertilization between different industry and technology. In addition, the state plays a role as a coordinator and mediator by embedding the democratic discipline into industrial ecosystems. Considering these points, regional industrial policy should be transformed into a platform system that can facilitate linkage between industry and technology.