• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.243-251
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• 2000

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause the inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• Communications of the Korean Mathematical Society
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• v.33 no.1
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• pp.127-142
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• 2018

In the present article, authors obtained certain fractional derivative and integral formulas involving incomplete ${\tau}$-hypergeometric function introduced by Parmar and Saxena [14]. Some interesting special cases and consequences of our main results are also considered.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.7
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• pp.639-644
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• 2006

This study was performed to compare the differences in physicochemical characteristics between head and incomplete kernels separated from Ilpumbyeo, Korean rice cultivar. The contents of mineral and protein were higher in incomplete than head kernels. There was significant difference in composition of fatty acid and amino acids, which affect the taste, between two kernels. The gelatinized head kernel had the higher viscosity than incomplete kernel. The content and chain length of amylose were higher in head than incomplete kernels. Differential scanning calorimeter results revealed that head kernel had lower starting temperature, higher maximum temperature, and higher enthalpy for gelatinization than incomplete kernel. Also we could found that the hydrolysis rate by glucoamylase was higher in the head kernel than incomplete kernel.

• Clinical and Experimental Pediatrics
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• v.55 no.3
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• pp.83-87
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• 2012

Several authors suggested that the clinical characteristics of incomplete presentation of Kawasaki disease are similar to those of complete presentation and that the 2 forms of presentation are not separate entities. Based on this suggestion, a diagnosis of incomplete Kawasaki disease in analogy to the findings of complete presentation is reasonable. Currently, the diagnosis of incomplete Kawasaki disease might be made in cases with fewer classical diagnostic criteria and with several compatible clinical, laboratory or echocardiographic findings on the exclusion of other febrile illness. Definition of incomplete presentation in which coronary artery abnormalities are included as a necessary condition, is restrictive and specific. The validity of the diagnostic criteria of incomplete presentation by the American Heart Association should be thoroughly tested in the immediate future.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.383-386
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• 2010

Pattern classification is one of the most important topics for machine learning research fields. However incomplete data appear frequently in real world problems and also show low learning rate in classification models. There have been many researches for handling such incomplete data, but most of the researches are focusing on training stages. In this paper, we proposed two classification methods for incomplete data using triangular shaped fuzzy membership functions. In the proposed methods, missing data in incomplete feature vectors are inferred, learned and applied to the proposed classifier using triangular shaped fuzzy membership functions. In the experiment, we verified that the proposed methods show higher classification rate than a conventional method.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.305-326
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• 2001

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.

• Management Science and Financial Engineering
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• v.21 no.2
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• pp.9-11
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• 2015

This note is concerned with the use of incomplete weights in multiple criteria decision making. In an earlier study, an optimistic use of incomplete weights is developed to prioritize decision alternatives, which applies the most favorable set of weights to the alternative to be evaluated. In this note, we develop a method for a pessimistic use, thereby applying the least favorable weight set to the evaluated alternative. This development makes possible a more detailed prioritization of competing alternatives, and hence enhances decision-making powers.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.677-683
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• 2001

In this paper, optimal block designs for complete diallel crosses are proposed. These optimal block designs for estimating general combining abilities are constructed by using balanced incomplete block designs and nested balanced incomplete block designs. Also, the efficiency of the optimal block design obtained through this method is reported in table.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.65-71
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• 2001

In this paper, optimal block designs for complete diallel crosses are proposed. These optimal block designs are constructed by using triangular partially balanced incomplete designs derived from symmetric balanced incomplete block designs. Also, it is shown that block designs for complete dialle crosses derived from complementary designs of triangular designs are optimal block designs.

• Journal of Animal Science and Technology
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• v.47 no.2
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• pp.147-158
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• 2005

The purpose of this study was to find out the effects that daughters' incomplete lactation records affect sire's breeding values through genetic evaluation using RRTDM(random regression test-day model). First, we estimated genetic parameters and breeding values on sires having complete lactation records of daughter by RRTDM, second, we changed complete lactation records of specific sires into incomplete records by various methods. Third, the breeding values were compared between complete and incomplete records. Finally, this study aimed to find out the methods to minimize the estimation errors of young bulls' breeding values. Data used in this study were collected from the dairy herd improvement program, and a total of 97,562 records were composed of 10,929 first parity with both parents known, since 1999. Breeding values on the daughters from randomly chosen sires were calculated and compared with among 90 day, 150day, and 200 day's incomplete records. For milk yields, sire's ranks of breeding values used by complete lactation records were very different from sire's ranks of breeding values obtained by incomplete lactation records(Rank_90 cut, 150cut, 200 cut).The differences were also obtained between complete lactation records(per305_full) and incomplete lactation record (per_90 cut, 150cut, 200 cut) in breeding values regarding persistency. Especially, the differences between per_90 cut and per305_full were very large(from 1.8 kg to 145kg).