• Journal of Life Science
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• v.11 no.3
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• pp.266-272
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• 2001

A total of 79 Salmonella spp. were isolated from Pusan area in 2000. The serotypes of 79 Salmonella isolates were classified as 42 strains of S. typhi(53.1%), 24 strains of S. enteritidis(30.4%), 9 strains of S. montevideo(11.4%), 2 strains of S. typhimurium(2.5%), 1 strain of S. infantis(1.3%) and 1 strain of S. indiana(1.3%) strains(16.5%) of Salmonella sp. were isolated at May July, respectively. The isolates of S. typhi were sensitive to most sntibiotics except streptomycin. All isolates of S. typhi were especially sensitive to tobramycin, gentamicin, colistin, kanamycin, samikacin, sulfamethozazole/ trimethoprim, cefriaxone, ceftazdime, cifrofloxacin, cefoxitin and cefotaxime. Isolates of S. enteritidis wer presented higher resistance than isolates of S. typhi. Twenty-four strains of S. enteritidis were sensitive to kanamycin, amikacin cifrofloxacin, cefoxitin and cefotaxime, however 13 strains(54.2%) of S. enteritidis were resistant to carbenicillin, ampicillin and ticarcillin. Nine strains of S. montevideo were sensitive to most antibiotics except carbenicillin and streptomycin. Each 1 stain of S. indiana and S. infantis was sensitive to most antibiotics used in this study except streptomycin. Three kinds of resistant pattern (CB, SM, TE, AM, TC). In the case of S. enteritidis isolates, 9 kinds resistant pattern were detected. Most frequent resistant pattern of S. enteritidis isolates was CB, AM, TC type(16.7%)

• Journal of the East Asian Society of Dietary Life
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• v.18 no.1
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• pp.14-21
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• 2008

Flavor is one of the most important factors for determining wine characteristics and quality. Flavor pattern of wines(brewed from America, France, Italy, Chile, and Australia) was analyzed by the electronic nose that is equipped with 12 metal oxide sensors. In the results, the flavor pattern of wines was discriminated according to their origins by the principal component analysis(PCA). Each proportion of the first principal component score in the PCA plot was 94.79%(America), 73.62%(France), 99.06%(Italy), 96.74%(Chile), and 96.53%(Australia), respectively. Consequently, the imported wines could be practically differentiated into one from the other origins by volatile properties, suggesting that electronic nose could be successfully used for easy screening and quality evaluation of wines.

• Animal cells and systems
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• v.9 no.3
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• pp.107-111
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• 2005

C. elegans DLK-1 has been reported to play an important role in synaptogenesis by shaping the structure of presynaptic terminal. In this study, we investigated the expression pattern and regulation of the dlk-1 gene in C. elegans. To determine the expression pattern, we made a dlk-1::gfp fusion construct, named pPDdg1, which consisted of -2.2 kb 5' upstream region, the first exon, the first intron, and a part of the second exon of the dlk-1 gene. By microinjecting this construct into the worm, we observed that the DLK-1::GFP was expressed mainly in neurons. We next examined the regulatory elements of gene expression by deletion analysis of pPDdg1. Removal of a large portion of the 5' upstream region (${\Delta}-361$ to -2246) of the gene had little effect on the expression pattern, whereas deletion of the first intron led to elimination of the DLK-1::GFP expression in most of the neurons. Our results suggest that the first intron of the C. elegans dlk-1 gene contains the regulatory element critical for gene expression.

• ETRI Journal
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• v.32 no.5
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• pp.676-686
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• 2010

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real-world scenarios. In this paper, we propose a novel framework for mining high-utility sequential patterns for more real-life applicable information extraction from sequence databases with non-binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high-utility sequential patterns, we propose two new algorithms: UtilityLevel is a high-utility sequential pattern mining with a level-wise candidate generation approach, and UtilitySpan is a high-utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high-utility sequential patterns.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.274-282
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• 2005

Customer retention is one of the major issued in life insurance industry, in which competition is increasingly fierce. There are many things to do to retain customers. One of those things is to be continuously in touch with all customers. The objective of this study is to design the contact scheduling system(CSS) to support the planers who must touch the customers without having subjective information. Support-planers suffer from lack of information which can be used to intimately touch. CSS that is developed in this study generates contact schedule to touch customers by taking into account existing contact history. CSS has a two stage process. In the first stage, it segments customers according to his or her demographics and contract status data. Then it finds typical pattern and pattern is combined to business rules for each segment. We expert that CSS would support support-planers to make uncontacted customers' experience positive.

• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.491-496
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• 2003

This paper proposes modeling of human behavior and a method of finding irregular human behavior. At first, human behavior model is proposed by paying attention to habitual human behavior at home. Generally, it is difficult to obtain the information of individual life pattern because of high cost for setting sensors such as cameras to observe human action. Therefore we capture turning on/off consumer electronic equipments as actual human behavior action, where some or many consumer electric equipments were used such as television, room light, video and so on in our daily life. Noting that are some relations between turning on/off those consumer electric equipments and our action, we proposes how to construct a human behavior knowledge by analyzing human behavior based on observation of human habitual life. Also an algorithm to identify on find irregular behavior different from habitual life behavior are described. Finally, the significance of the proposed method is shown by some experimental results.

• Journal of Family Resource Management and Policy Review
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• v.2 no.1
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• pp.79-90
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• 1998

The main purpose of this study was to investigate the level of the soundness of home life. This study was focused to analyze the soundness of home life according to the objective variables and the psychological variables. It was not also to provide some fundamental information that helped to elevate the home life soundness, but also to prevent family problems. The subjects of this study was married female teachers living in Seoul area. The sample size was 237. The significant results were as follows: 1) The soundness of home life differed significantly according to age, income, the number of children, and family pattern among the objective variables. 2) The soundness of home life differed significantly according to self-actualization and internal-external of control. 3) The variables such as income, self-actualization and internal-external of control affected the soundness of home life.

• Journal of the Korea Fashion and Costume Design Association
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• v.12 no.2
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• pp.107-118
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• 2010

The purpose of this study is to be data and to help understanding of pattern of Korean, Chinese and Japanese traditional dress. The methods of this study are the study of academic literatures as well as practical study through the analysis of case studies about actual works. The summary of this study's results is like followings. First, standard of Pattern are nature, mam-made in motif object, Naturalistic, Geometric, Stylized, Abstract in motif express, Order, Disorder in pattern express. Second, a point of sameness of motif object in traditional dress of three nations were that nature and letter abstractive of mam-made is a lot. but motif of Japan was used in daily life motif of mam-made which was not in Korea and China Third, commonly, motif expression of three nations were developed Naturalistic, Stylized. but in Naturalistic, Korea was simple, plane, China was three-dimensional, Japan was expressed super realism. Fourth, as formative aesthetic of Pattern, Korea is natural, plane, simple and symbolic, China is gorgeous, three-dimensional, immaculacy, filling and symbolic, Japan is delicate, complicated, decoration and symbolic.

• Proceedings of the KSRS Conference
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• v.2
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.