• Culinary science and hospitality research
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• v.23 no.6
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• pp.161-172
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• 2017

The purposes of this study were to examine if a decision making by a tourist sequentially or hierarchically occurs in a tourism destination and to test determinants that have an effect on both a sequential and non-sequential decision making. An instrument for the study was developed with three steps. A total of 420 and 380 questionnaire were collected respectively for the first two round surveys. For the third step, a pilot test was conducted with 30 respondents. And the data analysis utilized SPSS 18.0. A logistic regression analysis with variables of tourism activity and demography was employed to investigate the factors that affect a sequence of decision-making process. As an important result, the higher the age of the tourist in a tourism destination, the more conspicuous the consumption expenditure is made through the sequential decision-making process. Additionally, it is unreasonable to apply the premises and assumptions in extant consumer behavior to tourist behavior. The process of decision making by tourists in tourism areas is driven by either non-sequential or non-hierarchical decision-making process. More discussion and implications were provided.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.161-164
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• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• Research in Plant Disease
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• v.21 no.1
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• pp.20-23
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• 2015

A sequential planting method was developed to screen rice plants with durable resistance against rice blast in a short time, and applied for several years in Korean rice breeding program. In this study, we showed the advantages of a sequential planting method compared to other pathogenicity tests. The correlation analysis among three pathogenicity tests and other factors demonstrated that durable resistance depended on the average of diseased leaf area and the number of compatible pathogens. Significant correlations were found in the nursery test but not in the field test result. In addition, we traced changes in the pathogen population during sequential planting stages through re-isolation of the pathogen. The portion of compatible pathogens was increased during sequential planting. Through this study, we provide an effective sequential planting method and direction of durable resistance in a breeding program.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.257-266
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• 2003

Distribution-free estimation methods are proposed for slope, $\beta$ in the simple linear regression model. In this paper, we suggest the point estimators using the sequential slope based on sign test and Wilcoxon signed rank test. Also confidence intervals are presented for each estimation methods. Monte Carlo simulation study is carried out to compare the efficiency of these methods with least square method and Theil´s method. Some properties for the proposed methods are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4A
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• pp.558-565
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• 2000

While research of ATPG(automatic test pattern generation) for combinational circuits almost reaches a satisfiable level, one for sequential circuits still requires more research. In this paper, we propose new algorithm for sequential ATPG based on state information learning. By efficiently storing the information of the state searched during the process of test pattern generation and using the state information that has been already stored, test pattern generation becomes more efficient in time, fault coverage, and the number of test patterns. Through some experiments with ISCAS '89 benchmark circuits, the efficiency of the proposed method is shown.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1053-1066
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• 2005

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the use of the so-called scale ratio tests for testing the null hypothesis of no outliers. This test is based on the ratio of two residual scale estimates. We show the asymptotic distribution of the test statistics and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed. The new method is compared with classical procedure in the real data example. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.63-77
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• 1991

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the inspection method and technical innovation constraining the motor vehicle emission. In order to establish the more reasonable certified test, the multivariate sequential rectifying inspection plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This inspection method is designed to satisfy the evaluation measure constraining domestic vehicle emission, and it serves the defect rectifying system and performance certification of catalytic converts. As the prior parameter for the domestic vehicles, we used the data for the catalytic converts which passed the certified test excuted by the EPK. For the case of engine test, we used those data which passed the certified test of domestic vehicles. The multivariate sequential rectifying inspection plan of the vector parameter is able to minimize the average sample number and increase the pass probability of operating characteristic curve.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.2
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• pp.10-21
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• 1998

In this paper, we analyze the problems of conventional and previous mehtod on delay test method in IEEE 1149.1. To solve them, we propose two kinds of delay test architectures. One is called ARCH-C, is for combinatonal circuit, and the other is ARCH-S, for clocked sequential circuit. ARCH-C is able to detect delay defect of 0.5 $T_{tck}$ or 1 $T_{tck}$ size. And ARCH-C have a fixed and small amount of hardware overhead, on the contrary preious method has a hardware overhead on the dependent of CUT. This paper discusses weveral problems of Delay test on IEEE 1149.1 for clocked sequential circuit. We suggest the method called ARCH-S, is based on a clock counting technique to generate continuous clocked input of CUT. the simulation results ascertain the accurate operation and effectiveness of the proposed architectures.res.

• Journal of the Ergonomics Society of Korea
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• v.21 no.1
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• pp.1-14
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• 2002

The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1760-1767
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• 2004

Sequential sampling approaches of a metamodel that sampling points are updated sequentially become a significant consideration in metamodeling technique. Sequential sampling design is more effective than classical space filling design of all-at-once sampling because sequential sampling design is to add new sampling points by means of distance between sampling points or precdiction error obtained from metamodel. However, though the extremum points can strongly reflect the behaviors of responses, the existing sequential sampling designs are inefficient to approximate extremum points of original model. In this research, new sequential sampling approach using the sensitivity of Kriging model is proposed, so that new approach reflects the behaviors of response sequentially. Various sequential sampling designs are reviewed and the performances of the proposed approach are compared with those of existing sequential sampling approaches by using mean squared error. The accuracy of the proposed approach is investigated against optimization results of test problems so that superiority of the sensitivity approach is verified.