• 한국가시화정보학회지
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• 제21권1호
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.21-43
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• 2008

The task network which is formed of different individuals can be recognized as a social network. Therefore, the way to communicate with people inside or outside the network has considerable influence on their outcome. Moreover, the position on which a member stands in a network shows the different effects of the information systems supporting communication with others. In this paper, it is to be studied how personal CMC (computer-mediated communication) tools affect the mission that those who work for a network perform through diverse task networks. Especially, we focused on synchronicity of CMC. On this score, the perspective of Media Synchronicity Theory was taken that had been suggested by criticizing Media Richness Theory. It is the objective, from this perspective, to find which characteristics of networks make the value of IT supporting synchronicity high. In the research trends of social networks, there have been two traditional perspectives to explain the effect of network: embeddedness and diversity ones. These differ from the aspect which type of social network can provide much more economic benefits. As similar studies have been reported by various researchers, these are also divided into the bonding and bridging views which are based on internal and external tie, respectively, Size, density, and centrality were measured as the characteristics of personal task networks. Size means the level of relationship between members. It is the total number of other colleagues who work with a specific member for a certain project. It means, the larger the size of task network, the more the number of coworkers who interact each other through the job. Density is the ratio of the number of relationships arranged actually to the total number of available ones. In an ego-centered network, it is defined as the ratio of the number of relationship made really to the total number of possible ones between members who are actually involved each other. The higher the level of density, the larger the number of projects on which the members collaborate. Centrality means that his/her position is on the exact center of whole network. There are several methods to measure it. In this research, betweenness centrality was adopted among them. It is measured by the position on which one member stands between others in a network. The determinant to raise its level is the shortest geodesic that represents the shortest distance between members. Centrality also indicates the level of role as a broker among others. To verify the hypotheses, we interviewed and surveyed a group of employees of a nationwide financial organization in which a groupware system is used. They were questioned about two CMC applications: MSN with a higher level of synchronicity and email with a lower one. As a result, the larger the size of his/her own task network, the smaller its density and the higher the level of his/her centrality, the higher the level of the effect using the task network with CMC tools. Above all, this positive effect is verified to be much more produced while using CMC applications with higher-level synchronicity. Among the a variety of situations under which the use of CMC gives more benefits, this research is considered as one of rare cases regarding the characteristics of task network as moderators by focusing ITs for the operation of his/her own task network. It is another contribution of this research to prove empirically that the values of information system depend on the social, or comparative, characteristic of time. Though the same amount of time is shared, the social characteristics of users change its value. In addition, it is significant to examine empirically that the ITs with higher-level synchronicity have the positive effect on productivity. Many businesses are worried about the negative effect of synchronous ITs, for their employees are likely to use them for personal social activities. However. this research can help to dismiss the concern against CMC tools.

• Journal of Power Electronics
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• 제8권1호
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• pp.23-34
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• 2008

This paper deals with a Direct Torque Control (DTC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) for the Electric Vehicle (EV) propulsion system using a Neural Network (NN). The Conventional DTC with optimized switching lookup table and three level torque controller generates relatively large torque ripples in an electric vehicle motor drive. For reducing the torque ripples, a three level torque controller is hereby replaced by the five level torque controller. Furthermore, the switching lookup table of the five level torque controller based DTC is replaced with a Neural Network. These DTC schemes of an IPMSM drive are simulated using MATLAB/SIMULINK. The simulated results are compared with the conventional DTC and it is found that the ripples in the torque, as well as in the stator current, are reduced drastically.

• KIEAE Journal
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• 제3권2호
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• pp.59-66
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• 2003

To be the design method supporting aesthetic ability of human, CAAD system should essentially recognize architectural form in the same way of human. In this study, visual perception process of human was analyzed to search proper computational method performing similar step of perception of it. Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate. This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.89-92
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• 1996

It is generally recognized that Video On Demand (VOD) service will become a promising interactive service in B-ISDN. We consider a hierarchical two level network architecture for VOD service. The first level consists of connected Local Video Servers(LVSs) in which a limited number of high vision programs are stored. The second level has one Central Video Server(CVS) containing all the programs served in the network. The purpose of this paper is to analyze the network traffic and to propose the storage policy for LVSs. For this purpose, we present an analysis of program storage amount in each LVS, transmission traffic volume between LVSs, and link traffic volume between CVS and LVSs, according to changing the related factors such as demand, the number of LVSs is also presented on the basis of the tradeoffs among program storage cost, link traffic cost, and transmission cost.

• The Korean Journal of Ecology
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• 제21권5_3호
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• pp.723-733
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• 1998

Restoration to improve the ecological quality of Mt. Nam was explored in a viewpoint of restoration in both landscape and ecosystem levels. A restoration plan in landscape level was based on the result on the land-use pattern in Mt. Nam including its surrounding area and that in ecosystem level on the ecological quality of each landscape element. A plant to construct the green network, which extending from Mt. Nam to the Han river through the Yongsan family park and through the Eungbong urban park was prepared as a restoration project in landscape level to improve the ecological quality of Mt. Nam as an ecological park. On the other hand, a plan for restoration and creation of biotop as a restoration project in ecosystem level was also prepared to improve the ecological quality of each green area consisting green network. Green areas composing green network include keystone green area (Mt. Nam), green stations (Yongsan family park, Eungbong urban park, and the han river citizen's park), and green pathway (or ecological corridor) connecting those green areas.

• ETRI Journal
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• 제34권4호
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• pp.625-628
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• 2012

In this letter, a novel method for localizing a user in a smart home environment is presented. We propose a two-level structure, in which the first level determines an occupant's location in the block level using RSSI in a ZigBee network, while the second level accurately estimates the occupant's location using a particle filter to handle the variations in the signal strength measurement. We devise an experimental setup with people performing significant tasks in the smart home. The results obtained from the testbed indicate that the proposed model leads to an improvement in the mean distance error.

• Ocean Systems Engineering
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• 제7권4호
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.

• Asia pacific journal of information systems
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• 제22권3호
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• pp.75-97
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• 2012

Knowledge residing in the heads of employees has always been regarded as one of the most critical resources within a firm. However, many tries to facilitate knowledge transfer among employees has been unsuccessful because of the motivational and cognitive problems between the knowledge source and the recipient. Social capital, which is defined as "the sum of the actual and potential resources embedded within, available through, derived from the network of relationships possessed by an individual or social unit [Nahapiet and Ghoshal, 1998]," is suggested to resolve these motivational and cognitive problems of knowledge transfer. In Social capital theory, there are two research streams. One insists that social capital strengthens group solidarity and brings up cooperative behaviors among group members, such as voluntary help to colleagues. Therefore, social capital can motivate an expert to transfer his/her knowledge to a colleague in need without any direct reward. The other stream insists that social capital provides an access to various resources that the owner of social capital doesn't possess directly. In knowledge transfer context, an employee with social capital can access and learn much knowledge from his/her colleagues. Therefore, social capital provides benefits to both the knowledge source and the recipient in different ways. However, prior research on knowledge transfer and social capital is mostly limited to either of the research stream of social capital and covered only the knowledge source's or the knowledge recipient's perspective. Social network theory which focuses on the structural dimension of social capital provides clear explanation about the in-depth mechanisms of social capital's two different benefits. 'Strong tie' builds up identification, trust, and emotional attachment between the knowledge source and the recipient; therefore, it motivates the knowledge source to transfer his/her knowledge to the recipient. On the other hand, 'weak tie' easily expands to 'diverse' knowledge sources because it does not take much effort to manage. Therefore, the real value of 'weak tie' comes from the 'diverse network structure,' not the 'weak tie' itself. It implies that the two different perspectives on strength of ties can co-exist. For example, an extroverted employee can manage many 'strong' ties with 'various' colleagues. In this regards, the individual-level structure of one's relationships as well as the dyadic-level relationship should be considered together to provide a holistic view of social capital. In addition, interaction effect between individual-level characteristics and dyadic-level characteristics can be examined, too. Based on these arguments, this study has following research questions. (1) How does the social capital of the knowledge source and the recipient influence knowledge transfer respectively? (2) How does the strength of ties between the knowledge source and the recipient influence knowledge transfer? (3) How does the social capital of the knowledge source and the recipient influence the effect of the strength of ties between the knowledge source and the recipient on knowledge transfer? Based on Social capital theory and Social network theory, a multi-level research model is developed to consider both the individual-level social capital of the knowledge source and the recipient and the dyadic-level strength of relationship between the knowledge source and the recipient. 'Cross-classified random effect model,' one of the multi-level analysis methods, is adopted to analyze the survey responses from 337 R&D employees. The results of analysis provide several findings. First, among three dimensions of the knowledge source's social capital, network centrality (i.e., structural dimension) shows the significant direct effect on knowledge transfer. On the other hand, the knowledge recipient's network centrality is not influential. Instead, it strengthens the influence of the strength of ties between the knowledge source and the recipient on knowledge transfer. It means that the knowledge source's network centrality does not directly increase knowledge transfer. Instead, by providing access to various knowledge sources, the network centrality provides only the context where the strong tie between the knowledge source and the recipient leads to effective knowledge transfer. In short, network centrality has indirect effect on knowledge transfer from the knowledge recipient's perspective, while it has direct effect from the knowledge source's perspective. This is the most important contribution of this research. In addition, contrary to the research hypothesis, company tenure of the knowledge recipient negatively influences knowledge transfer. It means that experienced employees do not look for new knowledge and stick to their own knowledge. This is also an interesting result. One of the possible reasons is the hierarchical culture of Korea, such as a fear of losing face in front of subordinates. In a research methodology perspective, multi-level analysis adopted in this study seems to be very promising in management research area which has a multi-level data structure, such as employee-team-department-company. In addition, social network analysis is also a promising research approach with an exploding availability of online social network data.

• 한국통신학회논문지
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• 제40권4호
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• pp.659-665
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• 2015

최근 네트워크의 전송 효율 증가를 위한 네트워크 코딩 기법에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 네트워크 코딩 기법 중 하나인 Random Linear Network Coding(RLNC)를 서브패킷 단위로 적용하고 이를 오류 정정 코드중 하나인 Low-Density Parity-Check(LDPC)와 결합한 결합 코드인 A Joint Sub-Packet Level Network Coding and LDPC 기법을 제안하고, 네트워크 코딩 기법의 특성을 동일하게 가지며 제안방법을 사용함으로써 발생하는 추가적인 오류정정 성능을 보이고자 한다. 시뮬레이션 결과, 여분의 패킷을 획득하였을 때, LDPC만을 사용하는 것과 비교하여 오류 정정 능력이 향상되는 것을 확인하였다.