• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.53-58
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• 2024

This study is about the technology convergence analysis of e-commerce related patents containing Artificial Intelligence applied for in Korea. The relationships between core technologies were analyzed and visualized using social network analysis. As a result of social network analysis, the core IPC codes that make up the mutual technology network in e-commerce related patents containing Artificial Intelligence were found to be G06Q, G06F, G06N, G16H, G10L, H04N, G06T, and A61B. In particular, it can be confirmed that there is an important convergence of data processing-related technologies such as [G06Q-G06F], [G06Q-G06N], and voice and image signals such as [G06Q-G10L], [G06Q-H04N], and [G06Q-G06T]. Using this research method, it is possible to identify future technology trends in e-commerce related patents and create new Business Models.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.279-285
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• 2023

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.47-54
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• 2022

We analyze and compare the structure of the networks of Netflix, Disney+, and OCN, which are forerunners in OTT market, on Twitter. This study employs NodeXL pro as a visualization software package for social network analysis. As a result of the comparison with values of Vertices, Connected Components, Average Geodesic Distance, Average Betweenness Centrality, and Average Closeness Centrality. Netflix has comparative advantages at Vertices, Connected Components, and Average Closeness Centrality, OCN at Average Geodesic Distance, and Disney+ at Average Betweenness Centrality. Netflix has a more appropriate social network for influencer marketing than Disney+ and OCN. Based on the analysis results, the purpose of this study is to explain the structural differences in the social networks of Netflix, Disney+, and OCN in terms of influencer marketing.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.69-75
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• 2002

In this paper, we propose the realtime network traffic monitoring system usin SNMP that can supported network and system operation, management, expansion, and design using network analysis and diagnosis to a network administrator. The proposed system consists of two parts: analysis server for collection and analysis of the network information, and supports real-time monitoring of network traffic, and client system shows user a graphical data that analyzed a returned result from the server. This system implements web-based technology using Java and contributes to enhance the effectiveness of network administrator's management.

• Nuclear Engineering and Technology
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• v.32 no.5
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• pp.485-494
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• 2000

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique . Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors.

• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.64-71
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• 2001

In this paper we propose the network traffic monitoring system that can supported network and system operation, management, expansion, and design using network analysis and diagnosis to a network administrator. The proposed system consists of two parts: analysis server for collection and analysis of the network information. and supports real-time monitoring of network traffic, and client system shows user a graphical data that analyzed a returned result from the server This system implements web-based technology using java and contributes to enhance the effectiveness of network administrator's management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.31-50
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• 2023

In the midst of dynamic industrial changes, companies need data analysis considering the effects of integration of various technologies in order to establish innovative R & D strategies. However, the existing technology forecasting model evaluates individual technologies without considering relationship among them. To improve this problem, this study suggests a new methodology reflecting the integration of technologies. In the study, a technology forecasting indicator was developed using the technology integration index based on social network analysis. In order to verify the validity of the proposed methodology, 'drone task performance technology' based on patent data was applied to the research model. This study aimed to establish a theoretical basis to design a research model that reflects the degree of integration of technologies when conducting technology forecasting research. In addition, this study is meaningful in that it quantitatively verified the proposed methodology using actual patent data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1442-1453
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• 2016

Now, there are prodigiously expanding worldwide economic networks in the information society, which require their social structural changes through technology innovations. This paper so tries to formally define a process-centered knowledge model to be used to analyze policy-making procedures on technology innovations. The eventual goal of the proposed knowledge model is to apply itself to analyze a topic network based upon composite keywords from a document written in a natural language format during the technology innovation procedures. Knowledge model is created to topic network that compositing driven keyword through text mining from natural language in document. And we show that the way of analyzing knowledge model and automatically generating feature keyword and relation properties into topic networks.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.849-850
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• 2006

This thesis presents a new analysis method of Vegas network model in single link single source and a new version of Vegas for expanding asymptotically stable region. Actually since original Vegas model is difficult to analysis, we use a modified Vegas network model. Since there is a few tools to analyze nonlinear system with delay, developing other methods is very important and useful. We used state space model in discrete time. Using by Jury's criterion, we could find asymptotically stable region of Vegas network model. And it was a if and only if condition. Moreover, we proposed a new version of Vegas algorithm. To expand asymptotically stable region we modified the original Vegas model. The new analysis method and new Vegas algorithm were justified by ns-2 simulation. And as compare with other result, we could know our method has many advantages.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.3
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• pp.269-278
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• 2022

The buffer is a critical barrier component in an engineered barrier system, and its purpose is to prevent potential radionuclides from leaking out from a damaged canister by filling the void in the repository. No experimental parameters exist that can describe the buffer expansion phenomenon when Kyeongju bentonite, which is a buffer candidate material available in Korea, is exposed to groundwater. As conventional experiments to determine these parameters are time consuming and complicated, simple swelling pressure tests, numerical modeling, and machine learning are used in this study to obtain the parameters required to establish a numerical model that can simulate swelling. Swelling tests conducted using Kyeongju bentonite are emulated using the COMSOL Multiphysics numerical analysis tool. Relationships between the swelling phenomenon and mechanical parameters are determined via an artificial neural network. Subsequently, by inputting the swelling tests results into the network, the values for the mechanical parameters of Kyeongju bentonite are obtained. Sensitivity analysis is performed to identify the influential parameters. Results of the numerical analysis based on the identified mechanical parameters are consistent with the experimental values.