• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2004.06a
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• pp.258-265
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• 2004

Numerous genes of Escherichia coli have been shown to growth phase-dependent expression throughout growth. The global patterns of growth phase-dependent gene expression of E. coli throughout growth using oligonucleotide microarrays containing a nearly complete set of 4,289 annotated open reading frames. To determine the change of gene expression throughout growth, we compared RNAs taken from timecourses with common reference RNA, which is combined with equal amount of RNA pooled from each time point. The hierarchical clustering of the conditions in accordance with timecourse expression revealed that growth phases were clustered into four classes, consistent with known physiological growth status. We analyzed the differences of expression levels at genome level in both exponential and stationary growth phase cultures. Statistical analysis showed that 213 genes are shown to, growth phase-dependent expression. We also analyzed the expression of 256 known operons and 208 regulatory genes. To assess the global impact of RpoS, we identified 193 genes coregulated with rpoS and their expression levels were examined in the isogenic rpoS mutant. The results revealed that 99 of 193 were novel RpoS-dependent stationary phase-induced genes and the majority of those are functionally unknown. Our data provide that global changes and adjustments of gene expression are coordinately regulated by growth transition in E. coli.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.875-884
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• 2001

Although the self organizing map (SOM) is widely utilized in such fields of data visualization and topology preserving mapping, since it should have the topology fixed before trained, it has some shortcomings that it is difficult to apply it to practical problems, and classification capability is quite low despite better clustering performance. To overcome these points this paper proposes the dynamic topology preserving self-organizing map(DTSOM) that dynamically splits the output nodes on the map and trains them, and attempts to improve the classification capability by combining multiple DTSOMs K-Winner method has been applied to combine DTSOMs which produces K outputs with winner node selection method. This produces even better performance than the conventional combining methods such as majority voting weighting, BKS Bayesian, Borda, Condorect and reliability sum. DTSOM remedies the shortcoming of determining the topology in advance, and the classification rate increases significantly by combing multiple maps trained with different features. Experimental results with handwritten digit recognition indicate that the proposed method works out to problems of conventional SOM effectively so to improve the classification rate to 98.1%.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.509-514
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• 2015

In this paper, we introduce a new pattern classifier which is based on the learning algorithm of Extreme Learning Machine the sort of artificial neural networks and fuzzy set theory which is well known as being robust to noise. The learning algorithm used in Extreme Learning Machine is faster than the conventional artificial neural networks. The key advantage of Extreme Learning Machine is the generalization ability for regression problem and classification problem. In order to evaluate the classification ability of the proposed pattern classifier, we make experiments with several machine learning data sets.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.97-106
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• 2015

In recent, hybrid market segmentation techniques have been widely adopted, which conduct segmentation using both general variables and transaction based variables. However, the limitation of the techniques is to generate incorrect results for market segmentation even though its methodology and concept are easy to apply. In this paper, we propose a novel scheme to overcome this limitation of the hybrid techniques and to take an advantage of product information obtained by customer's transaction data. In this scheme, we first divide a whole market into several unit segments based on the general variables and then agglomerate the unit segments with higher QAP correlations. Each product network represents for purchasing patterns of its corresponding segment, thus, comparisons of QAP correlation between product networks of each segment can be a good measure to compare similarities between each segment. A case study has been conducted to validate the proposed scheme. The results show that our scheme effectively works for Internet shopping malls.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.57-68
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• 2014

This article analyses frame transition of personal information leakage in Korea from 1984 to 2014. In order to investigate the transition, we have collected newspaper article's titles. This study adopts classification, text network analysis(by co-occurrence symmetric matrix), and clustering techniques as part of social network analysis. Moreover, we apply definition of centrality in network in order to reveal the main frame formed in each of four periods. As a result, accessibility of personal information is extended from public sector to private sector. The boundary of personal information leakage is expanded to overseas. Therefore it is urgent to institutionalize the protection of personal information from a global perspective.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.103-112
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• 2006

Since sensor node has a limited energy supply in a wireless sensor network, it is very important to maximize the network lifetime through energy-efficient routing. Thus, many routing protocols have been developed for wireless sensor networks and can be classified into flat and hierarchical routing protocols. Recent researches focus on hierarchical routing scheme and LEACH is a representative hierarchical routing protocol. In this paper, we investigated the problems of the LEACH and proposed a novel energy efficient routing scheme, called ENTER(ENergy efficient Two-tiEr Routing protocol), to resolve the problem. ENTER reduces an energy consumption and increases a network lifetime by organizing clusters by the same distributed algerian as in the LEACH and establishing paths among cluster-heads to transmit the aggregated data to the sink node. We compared the performance of the ENTER with the LEACH through simulation and showed that the ENTER could enhance the network lifetime by utilizing the resources more efficiently.

• The Journal of Korean Association of Computer Education
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• v.12 no.6
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• pp.21-32
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• 2009

This paper proposes a method to extract a user's intention automatically and implementation of intention map that support a user can appropriate search results using a user' information need accurately. It selects user intention based on searching history obtained from previous users' same queries and extracts user intentions by using clustering algorithm and user intention extraction algorithm, extracted user intentions are represented in an intention map base on a theory of knowledge representation. For the efficiency analysis of intention map, we extracted user intentions using 2,600 search history data which provided by a current domestic commercial search engine. The experimental results using the information intention map search when using general search engines represent more than satisfaction was statistically significant.

• Korean Journal of Child Studies
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• v.34 no.6
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• pp.57-75
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• 2013

The purpose of this study was to examine changes in the rate of occurrence of challenging behaviors in young children according to their increase in age. The study is based on the responses of teachers in child care centers(N=246). They were asked which 38 types of challenging behavior occur most among ages 2, 3, 4, or 5 in young children's classrooms. The major results of this study were as follows. First, the occurrence rates of young children's challenging behaviors were classified into 5 clusters; decreased(Cluster 1, Cluster 2, Cluster 3), maintained(Cluster 4), or increased(Cluster 5) according to increases in their respective ages. Second, the behaviors such as throwing tantrums and biting, evident in Cluster 1, decreased very rapidly from a very high occurrence rate by age 3. The classroom culture maladjustment behaviors such as running aimlessly around the classroom and shouting, apparent in Cluster 2, had decreased rapidly from a high occurrence rate by age 4. The intentional classroom disruptive behaviors such as dropping objects to create noise and the peer culture maladjustment behaviors studied in Cluster 3 decreased gradually from a rate of medium occurrence by age 5. These results revealed the discontinuity which a few young children exhibit. Third, hurting others, observed in Cluster 4 maintained a low occurrence rate from age 2 until age 5. Using inappropriate language and threatening others in Cluster 5 increased gradually from a low occurrence at 2 to a high rate of occurrence at age 5. By carefully examining the change of young children's challenging behaviors on the basis of objective data in terms of the continuity/discontinuity and increased/decreased rate of diverse challenging behaviors, we will be better able help teachers and parents to plan the instruction, prevention and intervention of young children's challenging behaviors.

• Journal of the Korean Society of Food Culture
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• v.28 no.4
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• pp.371-385
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• 2013

This study aimed to classify attendants of a wine training institute according to loyalty for wine training service program and to deduce the core managing points in a wine training program by IPA (Importance-Performance Analysis). Self-administered questionnaires were collected from 192 trainees and statistical data analysis completed using SPSS ver. 18.0. As a result of clustering analysis based on trainee loyalty from both attitude and behavioral perspectives, four classification groups were identified: a "genuine" loyalty group, a "latent" loyalty group, a "mendacious" loyalty group, and a "low" loyalty group. For the genuine loyalty group, the importance of total service quality was 4.32 on average whereas the performance was measured as 4.22; thus there was little difference between importance to quality and performance. However, for the other three groups, especially the low loyalty group, there were significant wide gaps between importance to quality and performance. According to IPA, different service quality items were posted on the 'Focus here' quadrant (a domain with high service quality importance but low performance) by group, while the other three quadrants had several common items regardless of the group. Finally, the core quality managing points were different depending on the level of trainee loyalty. Therefore, it is necessary to plan and conduct a wine training program that reflects the characteristics and needs of its students, which will lead to a differentiated management strategy according to the level of loyalty.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.387-396
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• 2016

Multiuser communication has been an important research area of underwater acoustic communications and networking. This paper studies the use of adaptive orthogonal frequency-division multiple access (OFDMA) in a downlink scenario, where a central node sends data to multiple distributed nodes simultaneously. In practical implementations, the instantaneous channel state information (CSI) cannot be perfectly known by the central node in time-varying underwater acoustic (UWA) channels, due to the long propagation delays resulting from the low sound speed. In this paper, we explore the CSI feedback for resource allocation. An adaptive power-bit loading algorithm is presented, which assigns subcarriers to different users and allocates power and bits to each subcarrier, aiming to minimize the bit error rate (BER) under power and throughput constraints. Simulation results show considerable performance gains due to adaptive subcarrier allocation and further improvement through power and bit loading, as compared to the non-adaptive interleave subcarrier allocation scheme. In a lake experiment, channel feedback reduction is implemented through subcarrier clustering and uniform quantization. Although the performance gains are not as large as expected, experiment results confirm that adaptive subcarrier allocation schemes based on delayed channel feedback or long term statistics outperform the interleave subcarrier allocation scheme.