• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.213-220
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• 2006

Plant construction industry is a high value-adding industry because it is complex industry comprising engineering, procurements of equipments and construction. So, Revenue increase in overseas plant projects would boost up not only domestic construction industry but also growth of national economy. Recently, overseas plant-construction market is expanding dramatically. For instant, Middle-east countries are constantly increasing their orders for the construction of petro-chemical plants stimulated by sky-rocketing oil prices. The purpose of this research is to develop management techniques for plant projects such as work break-down structure, knowledge management system, logistics & procurement system, and risk assessment tools. We believe our research would contribute to the competion of Korean engineeing companies and contractors in overseas plant-construction market.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.555-564
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• 2022

Recently, cyberattacks are using hacking techniques utilizing intelligent and advanced malicious codes for non-face-to-face environments such as telecommuting, telemedicine, and automatic industrial facilities, and the damage is increasing. Traditional information protection systems, such as anti-virus, are a method of detecting known malicious URLs based on signature patterns, so unknown malicious URLs cannot be detected. In addition, the conventional static analysis-based malicious URL detection method is vulnerable to dynamic loading and cryptographic attacks. This study proposes a technique for efficiently detecting malicious URLs by dynamically learning malicious URL data. In the proposed detection technique, malicious codes are classified using machine learning-based feature selection algorithms, and the accuracy is improved by removing obfuscation elements after preprocessing using Weighted Euclidean Distance(WED). According to the experimental results, the proposed machine learning-based malicious URL detection technique shows an accuracy of 89.17%, which is improved by 2.82% compared to the conventional method.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.283-295
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• 2022

The number of citations in a patent is one of the indicators of the qualitative value of a patent. In this study, negative binomial regression model analysis was performed focusing on 47,354 US patents of 14 global top automotive makers in order to examine the major factors affecting the number of patent citations. As a result of the review, it was found that, elapsed years since filing, the number of patent claims, the number of claim letters, the number of inventors, the number of patent family countries, and the number of patent families, as well as IPC diversity, had a positive and significant effect on the number of citations. The results of this study are expected to provide a basic basis for considering the IPC diversity index together in analyzing and evaluating future patents and establishing strategies for creating excellent patents.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.86-98
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• 2020

The artificial intelligence (AI) is a technology that will lead the future connective and intelligent era by combining with almost all industries in manufacturing and service industry. Although Korea is one of the world's leading artificial intelligence group with the United States, Japan, and Germany, but its competitiveness in terms of artificial intelligence patent is relatively low compared to others. Therefore, it is necessary to carry out quantitative analysis of artificial intelligence patents in various aspects in order to examine national competitiveness, major industries and future development directions in artificial intelligence technology. In this study, we use the IPC technology classification code to estimate the overall life cycle and the speed of development of the artificial intelligence technology. We collected patents related to artificial intelligence from 2008 to 2018, and analyze patent trends through one-dimensional statistical analysis, two-dimensional statistical analysis and network analysis. We expect that the technological trends of the artificial intelligence industry discovered from this study will be exploited to the strategies of the artificial intelligence technology and the policy making of the government.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1760-1767
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• 2008

In this study, we analyzed the physical and chemical properties such as proximate analysis, ultimate analysis, heating values, and thermogravimetric analysis for the organic sludges discharged from an industrial complex in Ulsan. The average water, combustible, and ash content of organic sludges were 72.9, 18.5, and 8.6%, respectively. And according to the ultimate analysis of organic sludges, the C, O, H, N, and S compositions were 33.9, 26.4, 4.4, 4.4, and 0.6%, respectively. According to the results of investigating the lower heating values, 6 sludges were on the range of $1,500{\sim}2,000\;kcal/kg$ and 4 sludges were on the range of over 2,000 kcal/kg. Therefore, these 10 sludges could be directly applied to industries which try to use the energy by direct incineration.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.536-543
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• 2005

3D online game, with its striking realistic value, is leading the entire Korean game market which has various game genres. Technology sharing is very hard within the Korean game industry. That is because 1)there are few professionals, 2)most of the companies are small-scaled, and 3)there are security reasons. Therefore, it should be significant if we have software design techniques which make it possible to reuse the existing code when developing a network game so that we could save a lot of efforts. In this paper, the author analyzes the demand through the case in the client's design of the network game based on DirectX and proposes the effective software design methods for reusable code based on the creative patterns application in the GoF in the class design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.101-107
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• 2018

Recently, Korea's defense industry has advanced highly, and defense R&D budget is gradually increasing in defense budget. However, without objective analysis of defense industry technology, effective defense R&D activities are limited and defense budgets can be used inefficiently. Therefore, in addition to analyzing the defense industry technology quantitatively reflecting the opinions of the experts, this paper aims to analyze the defense industry technology objectively by quantitative methods, and to make efficient use of the defense budget. In addition, we propose a patent analysis method to grasp the characteristics of the defense industry technology and the vacant technology objectively and systematically by applying the big data analysis method, which is one of the keywords of the 4th industrial revolution, to the defense industry technology. The proposed method is applied to the technology of the firepower industry among several defense industrial technologies and the case analysis is conducted. In the process, the patents of 10 domestic companies related to firepower were collected through the Kipris in the defense industry companies' classification of the Korea Defense Industry Association(KDIA), and the data matrix was preprocessed to utilize IPC codes among them. And then, we Implemented association rule mining which can grasp the relation between each item in data mining technique using R program. The results of this study are suggested through interpretation of support, confidence lift index which were resulted from suggested approach. Therefore, this paper suggests that it can help the efficient use of massive national defense budget and enhance the competitiveness of defense industry technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.785-794
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• 2019

Recently Deep Learning technology, one of the fourth industrial revolution technologies, is used to identify the hidden meaning of network data that is difficult to detect in the security arena and to predict attacks. Property and quality analysis of data sources are required before selecting the deep learning algorithm to be used for intrusion detection. This is because it affects the detection method depending on the contamination of the data used for learning. Therefore, the characteristics of the data should be identified and the characteristics selected. In this paper, the characteristics of malware were analyzed using network data set and the effect of each feature on performance was analyzed when the deep learning model was applied. The traffic classification experiment was conducted on the comparison of characteristics according to network characteristics and 96.52% accuracy was classified based on the selected characteristics.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.247-249
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• 2020

In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.107-114
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• 2020

Technologies related scan-to-BIM for BIM-based reverse engineering techniques are beginning to be actively introduced in the A.E.C. industry, and the scalability of the technology is growing considerably. This study uses patent analysis based on objective data to find the right direction for Korean Scan-to-BIM technology by identifying the trends in Korea, the United States, Europe, and Japan. This was done using the WIPSON patent search system to find previous research on patent analysis related to building technology, theoretical consideration of scan-to-BIM technology, and published patents. We collected information, verified the process, and extracted valid patents. We used the effective patent data to analyze the annual trend of patent applications, national trends, and technological trends through the International Patent Classification (IPC) code, the types of the top 20 major applicants, and family patent trends.