• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.874-879
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• 2008

In this paper, a new extending method of q-ary low correlation zone(LCZ) sequence sets is proposed, which is a generalization of binary LCZ sequence set by Kim, Jang, No, and Chung. Using this method, q-ary LCZ sequence set with parameters (N,M,L,${\epsilon}$) is extended as a q-ary LCZ sequence set with parameters (pN,pM,p[(L+1)/p]-1,p${\epsilon}$), where p is prime and p|q.

• Journal of the Chungcheong Mathematical Society
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• v.11 no.1
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• pp.45-51
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• 1998

In this paper, we shall define the usual fuzzy distance between two real fuzzy points, using the usual distance between two points in $\mathbb{R}$. We introduce the fuzzy sequence in the fuzzy real line and the notion of limit of fuzzy sequence in $F_p(\mathbb{R})$, and obtain the fuzzy increasing(decreasing) sequence and fuzzy Cauchy sequence of real fuzzy points.

• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.11-19
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• 2012

Generally, a suffix tree is an efficient data structure since it reveals the detailed internal structures of given sequences within linear time. However, it is difficult to implement a suffix tree for a large number of sequences because of memory size constraints. Therefore, in order to compare multi-mega base genomic sequence sets using suffix trees, there is a need to re-construct the suffix tree algorithms. We introduce a new method for constructing a suffix tree on secondary storage of a large number of sequences. Our algorithm divides three files, in a designated sequence, into parts, storing references to the locations of edges in hash tables. To execute experiments, we used 1,300,000 sequences around 300Mbyte in EST to generate a suffix tree on disk.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.175-185
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• 1996

For the Change-point problem in a sequence of binomial variables we consider the maximum likelihood estimator (MLE) of unknown change-point. Its asymptotic distribution is quite limited in the case of binomial variables with different numver of trials at each time point. Hinkley and Hinkley (1970) gives an asymptotic distribution of the MLE for a sequence of Bernoulli random variables. To find the asymptotic distribution a numerical method such as bootstrap can be used. Another concern of our interest in the inference on the change-point and we derive confidence sets based on the liklihood ratio test(LRT). We find approximate confidence sets from the bootstrap distribution and compare the two results through an example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.226-233
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• 2007

In this paper, we construct new LCZ sequence sets with parameters $(2^{n+1}-2,M,L,2)$. In this scheme, we can relatively freely choose the LCZ length L and the resulting LCZ sequence set has the size in which is nearly optimal with respect to Tang, Fan, and Matsufuji bound.

• Journal of the Chungcheong Mathematical Society
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• v.16 no.1
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• pp.15-23
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• 2003

In order to compute the Nielsen number N(f) of a self-map $f:X{\rightarrow}X$, some Reidemeister classes in the fundamental group ${\pi}_1(X)$ need to be distinguished. D. Ferrario has some algebraic results which allow distinguishing Reidemeister classes. In this paper we generalize these results to the Reidemeister sets of iterates.

• Journal of the Korean earth science society
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• v.26 no.8
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• pp.809-820
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• 2005

The fluvial sequence developed along the channel margin of meander bends in the midstream of the Yeongsan River consists of channel deposits at the bottom and overbank deposits at the top, and shows a fining-upward trend. The fluvial deposits consist of 7 sedimentary facies, and facies association forms 7 architectural elements. The channel deposits formed as channel bar or point bar. The channel bar deposits consisted of architectural element of gravel bedform were formed by channel lag deposits within the channel; whereas, the channel bar deposits consisted of architectural elements of downcurrent-dipping inclined strata sets, cross-stratified and horizontally stratified sets, and horizontally stratified sets were formed by downstream migration of sand wave or downstream transport of sand by traction current in the upper flow regime conditions within the channel. The point bar deposits consist of architectural elements of down current-dipping inclined strata sets, horizontally stratified sets, cross-stratified and horizontally stratified sets, and laterally inclined and horizontally stratified sets. These architectural elements are thought to have been formed by the combined effects of the migration of sand dunes and the formation of horizontal lamination in the upper flow regime plane bed conditions. The overbank deposits consist of the architectural elements of overbank fine and sand sheet and lens. The overbank fines were formed by settling of mud from slackwater during flooding over floodplain whereas the sand sheet and lens were formed by traction of sands introduced episodically fiom channel to the overbank during flooding.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.147-153
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• 2009

In this paper, we introduce several concepts of tightness for a sequence of random variables taking values in the space of normal and upper-semicontinuous fuzzy sets with compact support in $R^p$ and give some characterizations of their concepts. Also, counter-examples for the relationships between the concepts of tightness are given.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.655-664
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• 2001

The continuous data such as video streams and voice analog signals can be modeled as multidimensional data sequences(MDS's) in the feature space, In this paper, we investigate the clustering technique for multidimensional data sequence, Each sequence is represented by a small number by hyper rectangular clusters for subsequent storage and similarity search processing. We present a linear clustering algorithm that guarantees a predefined level of clustering quality and show its effectiveness via experiments on various video data sets.

• Genomics & Informatics
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• v.17 no.4
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• pp.39.1-39.20
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• 2019

Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric D_ij(γ₁) in any linear and non-linear feature spaces. We prove that D_ij(γ₁) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of D_ij(γ₁)) in classification of heterogeneous sets of biosequences compared with the decision rules min_𝚵iand median_𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.