• Proceedings of the Technology Innovation Conference
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• 2005.06a
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• pp.116-139
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• 2005

ICT(information and communication technology) has played a pivotal role in the world economy, and the out look for ICT has improved markedly. One of the noticeable characteristics in the ICT sector Is the global rationalization of its technology and service. Specialization on the specific ICT capability is a pressing problem for many countries. Along the line of classical innovation cluster and network studies, this paper suggests a way to find and analyze the role of core technologies on the ICT network First, technology network is constructed by using patent citation data from USPTO. Then, a couple of cluster is generated by K-means clustering technique. Finally, brokerage analysis is applied to manifest the role of principal technologies. The network visualization and some stylized facts on dynamics are briefly given altogether Based on the role and relationship of technologies across clusters, it is expected that this research could contribute to the ICT cluster formation and the vision-making for ICT specialization at the viewpoint of technology Policy.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.85-92
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• 2021

The research topics of the appropriate technology include environment, medical, education, and energy etc. Therefore, having a review on appropriate technology requires huge efforts of specialists from many difference research areas. Social network analysis has been applied to understand the relationships among the components in the network and to provide insights by visualizing the huge network having many components. In this study, the co-authors and their research topics at the international conference on appropriate technology (ICAT) held by Academic Society for Appropriate Technology (ASAT) from 2017 to 2019 were analyzed using the statistical and visualization tools. The networks between co-authors were analyzed using the pretreated data which were collected from ASAT. The annual trend or characteristics of the general information on ICAT were also analyzed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.550-555
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• 2018

This study aims to identify and compare contents and keywords used in articles related to blockchain applications to various industries. The text mining and Semantic Network Analysis, as methods of keyword network analysis, were used to analyze articles including terms of 'finance' 'energy' and 'logistics', which media and government frequently mentioned as areas that can apply blockchain technologies. For this study, data were collected from 43,093 articles from January, 2017 through July, 2018. Data crawling was carried out by using Python BeautifulSoup and data cleaning was performed in order to eliminate mutual redundancies of the three terms. After that, text mining and semantic network analysis were performed using Textom and UCInet for network analysis between keywords. The results showed that all the three terms were similar in terms of 'technology', but there were differences in the contents of 'government policy' or 'industry' issues. In addition, there were differences in frequencies and centralities of these terms.

• Proceedings of the Technology Innovation Conference
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• 1999.12a
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• pp.197-215
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• 1999

With the advent of knowledge-based economy and information society, information and telecommunications(IT) industry is reckoned as the crucial sector for the creation and diffusion of technological knowledge. In this study, we analyze the process of 'industrialization of IT'and 'informatization of industries' based on the technology linkage structure, or technological knowledge network. The former is defined as the process whereby IT industry absorbs technological knowledge from other industries to grow as an independent industrial sector. The latter is defined as the process whereby other industries adopt IT technology to enhance productivity and upgrade industrial structure, We employ the R&D stock as a proxy for technological knowledge of respective industries and measure the flow of technological knowledge between industries in terms of I/O relationship. By applying the network analysis, we examine the changing pattern of technology linkage structure of the Korean industry throughout the years from 1983 to 1997. Some policy implications are presented based on the findings from the analysis.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.605-628
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• 2007

We analyze the embedded structure of the cooperative research network of innovation studies in Korea by employing the social network methodology. The network covers all the contributing authors of two journals such as JTI and KTIS, which are the representative journals in the area. Across the networks, the following is noted: networks are highly segmented and the link density is low. However, the KTIS network contains a huge component with 131 authors which implies the existence of a strong cooperative research infrastructure. We derived three sub-networks such as technology economics, technology management, and technology policy. The technology policy network has the lowest link density, while the technology management network of KTIS shows relatively high cohesion among the researchers. Simulation analysis for the mean links of networks by author affiliation divided into university and others show no significant difference between the two networks. We also found a higher ratio of linkage within affiliated network than between networks, rejecting our hypothesis that researchers will not discriminate their research partners due to strong governmental inducement of academia-res each-industry cooperation. The explainability of indices from network structure such as structural holes and clustering coefficients on the performance of researchers measured by the number of citations confirms the results reported in Oh, Choi & Kim (2006) which dealt with the research network of information systems.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.614-627
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• 2022

Aspect-based sentiment analysis is to discover the sentiment polarity towards an aspect from user-generated natural language. So far, most of the methods only use the implicit position information of the aspect in the context, instead of directly utilizing the position relationship between the aspect and the sentiment terms. In fact, neighboring words of the aspect terms should be given more attention than other words in the context. This paper studies the influence of different position embedding methods on the sentimental polarities of given aspects, and proposes a position embedding interactive attention network based on a long short-term memory network. Firstly, it uses the position information of the context simultaneously in the input layer and the attention layer. Secondly, it mines the importance of different context words for the aspect with the interactive attention mechanism. Finally, it generates a valid representation of the aspect and the context for sentiment classification. The model which has been posed was evaluated on the datasets of the Semantic Evaluation 2014. Compared with other baseline models, the accuracy of our model increases by about 2% on the restaurant dataset and 1% on the laptop dataset.

• Current Optics and Photonics
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• v.4 no.4
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• pp.310-316
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• 2020

We propose and experimentally demonstrate an all-optical radio frequency (RF) spectrum broadening system based on time compression. By utilizing the procedure of dispersion compensation values, the frequency domain is broadened by compressing the linear chirp optical pulse which has been multiplexed by the radio frequency. A detailed mathematical description elucidates that the time compression is a very preferred scheme for spectrum broadening. We also report experimental results to prove this method, magnification factor at 2.7, 8 and 11 have been tested with different dispersion values of fiber, the experimental results agree well with the theoretical results. The proposed system is flexible and the magnification factor is determined by the dispersion values, the proposed scheme is a linear system. In addition, the influence of key parameters, for instance optical bandwidth and the sideband suppression ratio (SSR), are discussed. Magnification factor 11 of the proposed system is demonstrated.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.94-99
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• 2010

This paper is to present how a network between words is formed. Not only have we looked at the distributivity, frequency and strength in connections between related words, but we have also presented some way to shed lights on what this network means to linguistic and social studies. The target source is morpho-analysis components of Trends 21 corpus which cover all newspaper articles from lour major newspapers, including Chosun, Joongang, Donga, and Hankyoreh, issued between 2000 and 2008. Based on nodes, links, and their connectivity indexes - density, degree, and centralizations, we have been able to retrieve and cluster related words forming the network with 20 event nouns. To reduce noise, we have considered the words whose t-score is above 1.64. By conducting both network and statistical analyses, we have presented the network of each event noun.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.413-422
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• 2022

Smart farms are receiving a lot of attention as a way to solve the chronic labor shortage and aging problems in agriculture. The smart farm industry, called the 6th industrial revolution, needs to strengthen its competitiveness. In order to apply innovative IT technology to agriculture, it is important to collect and analyze information about prior research or patents. This paper examines smart farm patent trends through 5,789 patent data related to smart farm using the domestic patent information search service(KIPRIS). This paper examines the domestic patent trends of smart farm information through keyword network, ego network, simultaneous appearance network, and bigram network analysis. As a result of network analysis related to smart farm patents, patents related to smart farm systems and control technologies were the most common. This paper can provide help in setting the direction of future smart farm-related patent research.