• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.28-28
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• 2003

The International Committee for Taxonomy of Viruses (ICTV), which was formed over 30 years ago, aims to develop a single, universal taxonomic scheme for all viruses or, in other words, "the classification of viruses and the assignment of names to taxa". Plant Virus taxonomy is in charge of Plant Virus Subcommittee, a substructure of the ICTV. The ICTV has been most successfully pursuing that aim and its mammoth 'Seventh Report' records details of the names it has collated and approved, and of the classification, it has devised. The current 7th ICTV report published in 2000 contains plant viruses of 951 species in 79 genera in 17 families, though 24 of the 79 genera are floating genera, that is, they are not included in any established families. Proposed name of new or existing viruses are vote for the accepted taxonomic proposals by ICTV Executive Committee meeting. The approved results have been published as the ICTV reports providing standard names and taxa of viruses all over the world. A number of new plant viruses have been identified or reclassified in the genus or species level, and new genera and families have been proposed.(중략)

• Journal of the Korean Society for Library and Information Science
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• v.47 no.3
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• pp.139-160
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• 2013

Ten Web sites from educational policy authorities, educational research institutions, professional educational, and national libraries that provide educational policy information services are investigated using content analysis method. They are analyzed using various types of information sources, classification schemes, and functions of information retrieval. Standardization of classification scheme of educational policy information, standardization of meta data items, improvement of retrieval systems, provision of personalized information services to educational policy authorities, operation of specialized policy information centers, and cooperation among professional institutions are suggested. A model of a specialized educational policy information center is proposed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.119-127
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• 2004

Butterfly valves are popularly used in service in the industrial and water works pipeline systems with large diameter because of its lightweight, simple structure and the rapidity of its manipulation. Sometimes cavitation can occur. resulting in noise, vibration and rapid deterioration of the valve trim, and do not allow further operation. Thus, the monitoring of cavitation is of economic interest and is very importance in industry. This paper proposes a condition monitoring scheme using statistical feature evaluation and support vector machine (SVM) to detect the cavitation conditions of butterfly valve which used as a flow control valve at the pumping stations. The stationary features of vibration signals are extracted from statistical moments. The SVMs are trained, and then classify normal and cavitation conditions of control valves. The SVMs with the reorganized feature vectors can distinguish the class of the untrained and untested data. The classification validity of this method is examined by various signals that are acquired from butterfly valves in the pumping stations and compared the classification success rate with those of self-organizing feature map neural network.

• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.165-198
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• 2003

This study analyzed authors' use of theory in 654 articles that appeared in two core library and information science journals during last three decades. In order to analyze degree of theory use of LIS, such as, publication productivity, growth and distribution of theory in subfields. name and origin of theory, usability of each theory, subfields and journals, and so on, content analysis of LIS theories was performed through conceptual and empirical study. For the purpose of this study, we suggested a couple of new analytical methods, so called, ‘Subfield Classification Scheme’ within LIS, and ‘5 Degrees of Theory Use’ model for the first time.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.192-202
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• 2017

This study develops a text spam filtering system for Facebook based on two variable categories: keywords learned from Instagram and meta-information of Facebook posts. Since there is no explicit labels for spam/ham posts, we utilize hash tags in Instagram to train classification models. In addition, the filtering accuracy is enhanced by considering meta-information of Facebook posts. To verify the proposed filtering system, we conduct an empirical experiment based on a total of 1,795,067 and 761,861 Facebook and Instagram documents, respectively. Employing random forest as a base classification algorithm, experimental result shows that the proposed filtering system yield 99% and 98% in terms of filtering accuracy and F1-measure, respectively. We expect that the proposed filtering scheme can be applied other web services suffering from massive spam posts but no explicit spam labels are available.

• Journal of the military operations research society of Korea
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• v.35 no.1
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• pp.105-121
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• 2009

Recently, the level of science and technology in our country has reached the level of the advanced countries. However, the level of standards/specifications was insufficient for support. In this study, after a review of the international atmosphere on defense specifications/standards and an investigation of the domestic present situation, three different perspectives of improvement scheme for the defense specifications/standard system are presented. First, in the defense standard classification system perspective, specifications, standards and handbook were defined based on their characteristic and properties. Second, in the perspective concerning the establishment procedure of defense standards/specifications, the bottom-up approach was suggested. Finally, in the perspective of the 'defense standards/specifications instructions', a reinforced drawing number system and other factors to overcome the current limitations are provided.

• Tunnel and Underground Space
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• v.11 no.4
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• pp.311-318
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• 2001

RQD is used to evaluate the degree of fracture in the rock mass and is also used as input into rock mass classification scheme, such as RMR and Q-system. However there are some drawbacks of the RQD caused by anisotropy and calculation length. Thus it is important to understand the variation of RQD in 3-D space in order to evaluate the properties of rock mass. The main purpose of this study is to reveal the distribution of RQD in the equal-angle stereo net, to investigate the effects of scanline length and joint frequency and to inquire the effect on the selection of rock mass strength parameters in the numerical analysis. Analysis has been extended to field joint survey data using same method. The results can be applied to contribute for more accurate interpretation of the results of engineering geological survey for better design and construction work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.6
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• pp.3-13
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• 2006

Internet mail has become a common communication method to send and receive an amount of data due to the tremendous high speed Internet service increment. But in other respect, the risk and damage of Junk mail is growing rapidly and nowadays Junk mail delivery problem is becoming more serious, because this is used for an attack or propagation scheme of malicious code. It's a most dangerous dominant cause for computer system accident. This paper shows the Junk mail characteristic which is based on the analysis of mail log in reality and then shows the implementation of the FQDN (Fully Qualified Domain Name) check and Personalized classification system and evaluates its performance.