• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.69-76
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• 2014

This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.107-115
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• 2009

Traditionally, simulation method is used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this paper, wireless network simulator is implemented using the C++ object-oriented programming language. This simulator can simulate wireless data services, like as ad-hoc networks, by considering the user's mobility. In this paper, the simulator includes network traffic model to reflect wireless data service and traffic source model to represent a user's mobility similar to real service environment and traffic characteristics can be reflected on the simulation, and also more accurate simulation results can be got through that. In addition, by using object-oriented techniques, new service feature or environment can be easily added or changed so that the developed mobile communication simulator can reflect the real service environment all the time. This simulator can be used in adjusting the characteristics of wireless data hosts following the mobility of the user, and also can be used in building new wireless ad-hoc network routing protocols.

• Journal of Korea Multimedia Society
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• v.7 no.6
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• pp.814-823
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• 2004

Current video games and game room games are played as a single player mode on the basis of various emulators. With the evolution of data communications and game technology, a new trend in the game industry has made the primary interests of game developers and companies in the game industry be moved toward a multiplayer mode from the traditional single player mode. In this paper, we represent how to implement a network game platform by allowing network modules to be run in conjunction with the current video emulator games. It also suggests a synchronization scheme for real-time game playout and practical mechanism that can support network games to be played with the Peer-to-Peer process using a lobby system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.127-136
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• 2023

Many research results on the traffic enforcement of illegal driving of twowheeled motor vehicles using license plate recognition are introduced. Deep learning convolutional neural networks can be used for character and word recognition of license plates because of better generalization capability compared to traditional Backpropagation neural networks. In the plates of twowheeled motor vehicles, the interdependent government and city words are included. If we implement the mutually independent word recognizers using error correction rules for two word recognition results, efficient license plate recognition results can be derived. The CPU based convolutional neural network without library under real time processing has an advantage of low cost real application compared to GPU based convolutional neural network with library. In this paper twowheeled motor vehicle license plate recognition algorithm is introduced using CPU based deep-learning convolutional neural network. The experimental results show that the proposed plate recognizer has 96.2% success rate for outdoor twowheeled motor vehicle images in real time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.47-58
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• 2011

Snoop was suitably designed for wired and wireless network as having snoop agent module in BS(Base Station) which is connecting to both wired and wireless network in order to supplement the problems of TCP. This study examined performance difference by using the web traffic taken wide possession in current internet traffic. The web traffic has greater amount of traffic, shorter life time, and smaller size than other traffics. This study found that snoop producing performance improvement of wireless network in the network mixed with the wired and wireless lead performance loss when transmitting web traffic. This study found that in case of web traffic is transmitted it bring a performance improvement of web traffic as computing BWE((Bandwidth Expansion), and also found that this study prove of performance improvement by decreasing local retranmission.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.133-141
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• 2018

The purpose of this study was to propose a model of knowledge transfer in IT outsourcing. In this study, structural holes were chosen as antecedent factors, and job performance as a consequence factor. We conducted a survey in which we collected data from 42 respondents working in one of the leading IT companies in Seoul, South Korea. The data were analyzed using UCINET 6 and SmartPLS 2.0. The antecedent factors (structural holes in closeness network and in professional network) turned out to be statistically significant. Knowledge transfer considerably influenced job performance. Lastly, implications and limitations of these findings were discussed, and directions for future research were suggested.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.87-97
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• 2019

Reaction of people is importantly considered about specific case as a social network service grows. In the previous research on analysis of social network service, they predicted tendency of interesting topic by giving scores to sentences written by user. Based on previous study we proceeded research of sentiment analysis for social network service's sentences, which predict the result as positive or negative for movie reviews. In this study, we used movie review to get high accuracy. We classify the movie review into positive or negative based on the score for learning. Also, we performed embedding and morpheme analysis on movie review. We could predict learning result as positive or negative with a number 0 and 1 by applying the model based on learning result to social network service. Experimental result show accuracy of about 80% in predicting sentence as positive or negative.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.4
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• pp.677-693
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• 2016

Using Social Network Analysis and Trade in Value Added Database(TiVA), this paper examines the world trade network. Main findings are as follows. Firstly, there are three types of industries, which have dominant status in the world value added trade network. Those are the manufacturing industries in the developing countries such as China's electronics industry, the service industries in the developed countries such as U.S. R&D, and the manufacturing industries in the developed countries such as German motor vehicle industry. Secondly, the major hub industries in the world trade network have their own specific types in the brokerage roles. Most interestingly, U.S. service industries such as the R&D, the logistics industry, and the whole sale and retail industry reveal itinerant and liaison brokerage roles. Thirdly, Korean industries have been dominated by Chinese industries. However, the financial industry and the R&D industry could have revealed superior status as the brokerage role of itinerant. This implies Korean industries could sustain their competitiveness of the hubness status only by openness policy in the service industry.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.1
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• pp.16-33
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• 2017

This study analyzed the actual condition of the purchasing and selling network structures of manufacturing firms related the shipbuilding and offshore plant industry in Jeollanam-do using the social network analysis. The analysis results are as follows. The networks are often traded by subcontracting relationship with large firms because the industry is configured in most small and medium-sized firms. In particular, it was found to actual situation that selling transactions are being concentrated in the manufacturing firms of Yeongnam where large firms have located. Structural adjustment of the large firms located in the Yeongnam is expected to strike a blow to the manufacturing firms related the shipbuilding and offshore plant industry in Jeollanam-do due to the recently crisis in the shipbuilding industry. Therefore, it is necessary to secure a diversity of networks for selling transactions, and to discover and promote that selling firms related the shipbuilding and offshore plant industry in Jeollanam-do, in order to cope with such a crisis.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.