• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.1
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• pp.9-17
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• 1992

Proper resource allocation is also a very important topic in power system problems, especially in operation and planning. One such is optimal maintenance problem in operation and planning. Least cost and highest reliability should be the subjects to be pursued. A probabilistic operation simulation model developed recently by authors is applied to the proboem of optimal maintenance scheduling. Three different methods are compared, marginal maintenance cost, levelized risk and maintenance space. The method by the marginal maintenance costs shows the least cost, the highest reliability and the highest maintenance outage rates. This latter characteristics may considerably influence the results of genetation planning, because the usual maintenance outages obtained from the other methods have shown to be lower.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.9-16
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• 2017

In this paper, we propose to present a model of cloud security that has emerged as the biggest topic of cloud computing, replacing the traditional IT environment. While cloud computing is an extension of existing IT technology, security issues and threats can be applied to traditional security technologies. However, the biggest difference between a typical computing environment and a cloud computing environment is a virtualized environment with a hypervisor. Currently, there are many weaknesses in the virtualized environment, and there are few related security products. In order for a cloud computing environment to function as a reliable IT environment, we expect more research on hypervisor-based security technologies, and we expect to secure safer cloud services through a secure model over the next generation of new-based networks.

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.425-430
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• 2007

Depends on the running dry of the radio resources for the next generation of wireless communication system the estimated possibilities of the visible light which used for the devices such as signal light, the electric display board, guide board and so on applied for the next generation wireless network is the topic to be explored in this paper. Since radiation efficiency utilization for the wireless network has its capacity to become a trend direction we will study also on its application as well as the technique standardization.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.127-130
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• 2022

The number of published journals, conferences, and research papers in computer science is increasing rapidly, which has led to a challenge in coming up with new and unique ideas for research. To alleviate the issue, this paper uses artificial neural networks (ANNs) to generate new computer science research ideas. It does so by using a dataset collected from IEEE published journals and conferences to train an ANN model. The results reveal that the model has a 14% success rate in generating usable ideas. The outcome of this paper has implications for helping both new and experienced researchers come up with novel research topics.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.26-33
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• 2024

With the start of COVID-19 in 2020, the MBTI test became popular among Korean young generation and then developed into a nationwide hot topic. This paper aims to investigate the characteristics of the MBTI popularity in Korea and the public opinions toward this phenomenon. With the analysis of the reports contents, 231 news reports related to MBTI were selected from KINDS (Korea Integrated News Database System) as research samples. The general attitude of the media towards MBTI tests and the reasons for the formation of positive and negative evaluations will be discussed from three perspectives: media attention, media attitudes and cognitive sources. The research finds that the increasing interest in MBTI among the younger generation in Korea is driven by a post-epidemic desire for self-exploration, emotional planning, and online group affiliation. MBTI has gained quasi-scientific status, similar to horoscopes, influenced by celebrities and a substantial fan base in online communication. While widely used for entertainment and social currency, there are concerns that extensive labeling may unconsciously impact individuals' self-perception and hinder the development of a holistic and objective cognitive framework.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.730-733
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• 2004

Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.361-375
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• 2009

The major concern of component users who develop applications using the existing components is to confirm whether a component is collaborating with the different components in accordance with the requirements. Therefore, interoperability testing whose role is to check whether components collaborate with each other within the new operating environment not within the component development content of each component is considered as an importance research topic. In this paper, we propose a test case generation technique for interoperability test of component based software. The proposed technique defines a test model for generating test cases. The proposed technique generates test models from the use case specification and thereafter from these models, test cases for Interoperability testing are derived. In addition, we describe a tool which Implements the procedures for generating test sequences from test models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1284-1297
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• 2019

The network environment is presently becoming very increased. Accordingly, the study of traffic classification for network management is becoming difficult. Automatic signature extraction system is a hot topic in the field of traffic classification research. However, existing automatic payload signature generation systems suffer problems such as semi-automatic system, generating of disposable signatures, generating of false-positive signatures and signatures are not kept up to date. Therefore, we provide a fully automatic signature update system that automatically performs all the processes, such as traffic collection, signature generation, signature management and signature verification. The step of traffic collection automatically collects ground-truth traffic through the traffic measurement agent (TMA) and traffic management server (TMS). The step of signature management removes unnecessary signatures. The step of signature generation generates new signatures. Finally, the step of signature verification removes the false-positive signatures. The proposed system can solve the problems of existing systems. The result of this system to a campus network showed that, in the case of four applications, high recall values and low false-positive rates can be maintained.