• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.419-425
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• 2020

DC distribution system has been evaluated as an excellent one in comparison with existing AC distribution network because it needs fewer power conversion stages and the full capacity of the equipment can be used without consideration for power factor. Recently, research and development on the implementation of DC distribution networks have been progressed globally based on the rapid advancement in power-electronics technology, and the technological developments from the viewpoint of infrastructure are also in progress. However, to configure a distribution network which is a distribution line for DC, more accurate and rapid introduction of analysis technology is needed for the monitoring, control and operation of the system, which ensure the system run flexible and efficiently. However, in case of a bipolar DC distribution network, there are two buses acting as slack buses, so the Jacobian matrix cannot be configured. Without solving this problem, DC distribution network cannot be operated when the network is unbalanced. Therefore, this paper presented a comprehensive method of analysis with consideration of operating elements which are directly connected between neutral electric potential caused by the unbalanced of load in DC distribution network with bipolar structure.

• Computers and Concrete
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• v.15 no.2
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• pp.167-181
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• 2015

"Mortar or concrete pneumatically projected at high velocity onto a surface" is called Shotcrete. Models that predict shotcrete design parameters (e.g. compressive strength, slump etc) from any mixing proportions of admixtures could save considerable experimentation time consumed during trial and error based procedures. Artificial Neural Network (ANN) has been widely used for similar purposes; however, such models have been rarely applied on shotcrete design. In this study 19 samples of shotcrete test panels with varying quantities of water, steel fibers and silica fume were used to determine their slump, cost and compressive strength at different ages. A number of 3-layer Back propagation Neural Network (BPNN) models of different network architectures were used to train the network using 15 samples, while 4 samples were randomly chosen to validate the model. The predicted compressive strength from linear regression lacked accuracy with $R^2$ value of 0.36. Whereas, outputs from 3-5-3 ANN architecture gave higher correlations of $R^2$ = 0.99, 0.95 and 0.98 for compressive strength, cost and slump parameters of the training data and corresponding $R^2$ values of 0.99, 0.99 and 0.90 for the validation dataset. Sensitivity analysis of output variables using ANN can unfold the nonlinear cause and effect relationship for otherwise obscure ANN model.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.83-95
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• 2019

It is becoming more and more difficult to cope with new knowledge and technology required by society by the efforts of one person or organization according to the development of science and technology. As a method to overcome this, collaborative research is becoming important. This tendency is increasing in the government R&D projects as well, and the 'A' test research institute, which is the subject of this paper, is also increasing a collaborative research. The purpose of this study is to analyze the network characteristics among the participating researchers in the government R&D project conducted by the institution A, and to ascertain how the network characters of the researchers actually affect the financial performance of the team. The results of the analysis show that 'closeness centrality' and 'degree of centrality' contribute positively to the financial performance of the team. On the other hand, 'betweenness centrality' and 'eigenvector centrality' have a negative effect on the financial performance of the team because they are not directly related to financial performance.

• Management & Information Systems Review
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• v.35 no.2
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• pp.221-254
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• 2016

With increasing interest of health due to population aging, medical device industry is highlighted as a promising industry. However, Korea medical device industry is not enough market competitiveness compared to global company due to a narrow domestic market and a small company structure. In order to retain the national competitiveness, it is necessary that we have to derive a central technology and its trend. This study has predicted a central technology for medical device industrial using patent network analysis. The central technology is defined as a key technology that is connected to most other technologies and that significantly affects them. For the empirical study, we conducted social network analysis using covariance and correlation coefficient between IPC codes extracted from medical device patents, introduced by Jun(2012). A social network is a social structure of diverse items as well as of human beings. In this study, we set each medical device as a node in an SNA and analyze the Degree values between them. Also, Korea health industrial statistics system are utilized for verification of selected central technology. As a result, we found that the central technology is located on the medical device items, which are listed higher the amount of production. The central technology selected through the proposed methodology will provide a inspiration for establishment of R&D policy.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.462-475
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• 2022

Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.

• Journal of Hydrogen and New Energy
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• v.33 no.2
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• pp.130-141
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• 2022

Due to continuous climate change, greenhouse gases in the atmosphere are gradually accumulating, and various extreme weather events occurring all over the world are a serious threat to human sustainability. Countries around the world are making efforts to convert energy sources from traditional fossil fuels to renewable energy. Hydrogen energy is a clean energy source that exists infinitely on Earth, and can be used in most areas that require energy, such as power generation, transportation, commerce, and household sectors. A fuel cell, a device that produces electric and thermal energy by using hydrogen energy, is a key field to respond to climate change, and major countries around the world are spurring the development of core fuel cell technology. In this paper, research trends in China, the United States, Germany, Japan, and Korea, which have the highest number of papers related to fuel cells, are analyzed through keyword network analysis.

• Journal of Information Technology Services
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• v.13 no.4
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• pp.93-107
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• 2014

Interests on collaborative research and academic relationship among researchers have been increased. Collaborative researchers can maximize productivity, time and cost savings, and reduce the risk of research. An empirical study on the research productivity of co-authors' network and review efficiency of the reviewer network was conducted based on co-author networks and reviewer networks in Korea Society of IT Service. This study aims to find the characteristics of the co-author and reviewer networks, and to analyze research productivity and review efficiency in order to draw some implications. The meaning of interactions among professional groups was analyzed. Research productivity index was calculated using 728 authors' papers submitted to the society. In order to verify the effects of indicators of social network analysis on research productivity and review efficiency, correlation and regression analyses were used. As a result, the indicators of network centrality did not affect the review efficiency, but affect the research productivity.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.637-648
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• 2013

Purpose: The objective of this study is to provide a methodology that can facilitate efficient development of a product portfolio by utilizing Korean Standards(KS) networks. Methods: A case study on a steel manufacturing company is provided. Social network analysis h as been conducted on KS network and KS certification information of the company. Core test standards of a company have been identified. The core standards, then, used to construct a product-standard network of a corresponding industry. Results: As a result of analyzing product-standard networks, a product portfolio of a company has been developed. It has been shown that the candidate product portfolio is a cost-effective alternative in terms of standard maintenance cost. Conclusion: By using social network analysis, standards information can be used to support new product development process.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.165-172
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• 2017

In this paper, we analyze the research / technology trends of electric vehicles from 2001 to 2014, through keyword analysis using paper data published in SCIE or SSCI Journal on electric vehicles, time series analysis using patent data by IPC, and network analysis using nodeXL. also we predicted promising technologies of electric vehicles using one of the prediction methods, weighted moving average method. As a result of this study, battery technology among the electric vehicle component technologies appeared as a promising technology.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.