• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.217-224
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• 2017

In this paper, we propose a fusion classification method combining HRRP and JEM classifier with complementary properties for the classification of aircraft. The fusion method is based on the confidence of a classifier for a classification result to improve performance compared with single classifier in various situations. The confidence is defined as the posterior probability estimated from the classification performance of a classifier and it depends on the aspect angle and the certainty for a classification result. Through the classification test using simulation data, we can verify that the proposed fusion method shows good performance by fusing the classifiers effectively.

• The Journal of Society for e-Business Studies
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• v.8 no.3
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• pp.69-86
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• 2003

A Protection Profile(PP) is a common security and assurance requirements for a specific class of Information Technology security products such as firewall and smart card. A PP should be included "TOE(Target of Evaluation) Security Environment", which is consisted of subsections: assumptions, treat, organizational security policies. This paper presents a new threats statement generation method for developing TOE security environment section of PP. Our survey guides the statement of threats in CC(Common Criteria) scheme through collected and analysed hundred of threat statements from certified and published real PPs and CC Tool Box/PKB that is included a class of pre-defined threat and attack statements. From the result of the survey, we present a new asset classification method and propose a threats statement generation model. The former is a new asset classification method, and the later is a production rule for a well formed statement of threats.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.21-27
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• 1999

In this paper. we propose a new method for automatic classification of documents using the degree of similarity between words. First, we seek relevance terms using automatic indexing. Second, we found frequency in use words in documents and the degree of relevance between the words using probability model. Continuously, we extracted the set of words which is connected the relevance closely and created the profiles characterizing each classification And, with the profile we finally classified them. We experimented on classifying two groups of documents. Some documents were about Genetic Algorithm. The others were about Neural Network. The results of the experiments indicated that automatic classification with word accordance of degree enable us to manage the retrieved documents structurally.

• Journal of fish pathology
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• v.16 no.1
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• pp.51-59
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• 2003

Streptococcal infection is one of the most serious disease of cultured olive flounder, Paralychthys olivaceus in Korea and caused by more than one species. However, there has been considerable confusions about the taxonomic position of the fish pathogenic streptococci. In this study, We performed the randomly amplified polymorphic DNA(RAPD) pattern analysis to evaluate the possible classification in 8 streptococci isolated from diseased olive flounder and reference strains based on their DNA structure. RAPD PCR with DNA solution prepared by simple boiling and 10-mer random primer was appeared to be a good tool for discrimination of different streptococcal strains. Phenotypical characters by simple biological test and API 20 Strep corresponded well to the specific profiles of RAPD in streptococcal isolates of this study. Therefore, the RAPD profile was considered as one of differential characters to discriminate the streptococcal isolates from diseased olive flounder.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.142-147
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• 2009

The recent H.264/AVC video coding standard provides a higher coding efficiency than previous standards. H.264/AVC achieves a bit rate saving of more than 50 % with many new technologies, but it is computationally complex. Most of fast mode decision algorithms have focused on Baseline profile of H.264/AVC. In this paper, a fast block mode decision scheme for P- slices in High profile is proposed to reduce the computational complexity for H.264/AVC because the High profile is useful for broadcasting and storage applications. To reduce the block mode decision complexity in P- pictures of High profile, we use the SAD value after $16{\times}16$ block motion estimation. This SAD value is used for the classification feature to divide all block modes into some proper candidate block modes. The proposed algorithm shows average speed-up factors of 47.42 ${\sim}$ 67.04% for IPPP sequences.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.99-106
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• 2006

Type classification is a very needed step in recognizing huge character set language such as korean characters. Since most previous researches are based on the composition rule of Korean characters, it has been difficult to correctly classify composite vowel characters and problem space was not divided equally for the lack of classification of last consonant which is relatively bigger than other graphemes. In this paper, I Propose a new type classification method in which horizontal vowel is extracted before vortical vowel and last consonants are further classified into one of five small groups based on horizontal projection profile. The new method uses 19 character types which is more stable than previous 6 types or 15 types. Through experiments on 1.000 frequently used character sets and 30.614 characters scanned from several magazines, I showed that the proposed method is more useful classifying Korean characters of huge set.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1466-1483
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• 2008

This paper discusses the development of an up-to-date computerized CPT (Cone Penetration Test) based soil engineering classification system to provide geotechnical engineers with a handy tool for their daily design activities. Five CPT soil engineering classification systems are incorporated in this effort. They include the probabilistic region estimation and fuzzy classification methods, both developed by Zhang and Tumay, the Schmertmann, the Douglas and Olsen, and the Robertson et al. methods. In the probabilistic region estimation method, a conformal transformation is used to determine the soil classification index, U, from CPT cone tip resistance and friction ratio. A statistical correlation is established between U and the compositional soil type given by the Unified Soil Classification System (USCS). The soil classification index, U, provides a soil profile over depth with the probability of belonging to different soil types, which more realistically and continuously reflects the in-situ soil characterization, which includes the spatial variation of soil types. The CPT fuzzy classification on the other hand emphasizes the certainty of soil behavior. The advantage of combining these two classification methods is realized through implementing them into visual basic software with three other CPT soil classification methods for friendly use by geotechnical engineers. Three sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the probabilistic region estimation and fuzzy classification methods are cross-correlated with conventional soil classification from borings logs and three other established CPT soil classification methods.

• Toxicological Research
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• v.22 no.4
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• pp.323-328
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• 2006

Global gene expression profile was analyzed by microarray analysis of rat liver RNA after acute acetaminophen (APAP) administration. A single dose of 1g/kg body weight of APAP was given orally, and the liver samples were obtained after 24, 48 h, and 2 weeks. Histopathologic and biochemical studies enabled the classification of the APAP effect into injury (24 and 48 h) and regeneration (2 weeks) stages. The expression levels of 4900 clones on a custom rat gene microarray were analyzed and 484 clones were differentially expressed with more than a 1.625-fold difference(which equals 0.7 in log2 scale) at one or more time points. Two hundred ninety seven clones were classified as injury-specific clones, while 149 clones as regeneration-specific ones. Characteristic gene expression profiles could be associated with APAP-induced gene expression changes in lipid metabolism, stress response, and protein metabolism. We established a global gene expression profile utilizing microarray analysis in rat liver upon acute APAP administration with a full chronological profile that not only covers injury stage but also later point of regeneration stage.

• Molecules and Cells
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• v.28 no.3
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• pp.195-200
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• 2009

Protein tyrosine kinases (PTKs) play a central role in the modulation of a wide variety of cellular events such as differentiation, proliferation and metabolism, and their unregulated activation can lead to various diseases including cancer and diabetes. PTKs represent a diverse family of proteins including both receptor tyrosine kinases (RTKs) and non-receptor tyrosine kinases (NRTKs). Due to the diversity and important cellular roles of PTKs, accurate classification methods are required to better understand and differentiate different PTKs. In addition, PTKs have become important targets for drugs, providing a further need to develop novel methods to accurately classify this set of important biological molecules. Here, we introduce a novel statistical model for the classification of PTKs that is based on their structural features. The approach allows for both the recognition of PTKs and the classification of RTKs into their subfamilies. This novel approach had an overall accuracy of 98.5% for the identification of PTKs, and 99.3% for the classification of RTKs.