• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.271-279
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• 2001

Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1069-1072
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• 2009

Field sequential display has some advantages but color breakup (CBU) is the significant problem. Many researches had introduced several methods to reduce CBU phenomenon, however there are no reliable methods to measure the degree of CBU. In this report, a novel CBU measurement technique which was based on the image processing method and subjective analysis results had proposed to evaluate the degree of CBU. Color Breakup Index (CBI) was presented to be a useful index to recognize the CBU phenomenon in the different field sequential technique displays.

• Transactions of Materials Processing
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• v.11 no.2
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• pp.147-154
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• 2002

The tension levelling Process is Performed to elongate the strip plastically In combination of tensile and bending strain so that all longitudinal fibers In the strip have an approximately equal amount ofn length and undesirable strip shapes are corrected to the flat shape. Thus paper is concerned with a simulation of the tension levelling process based on the analysis of tile unit model for the tension leveller. Analysis technique such as the sequential analysis of the unit model is suggested and verified with the assembly analysis of the unit model for the effective arts economic analysis of the full set of the tension leveller. Analysis of the full tension levelling Process using sequential unit models Is carried out for steel strips with the shape defect and provides the effect of the intermesh and optimum amount of the intermesh in tension levelling process.

• Smart Structures and Systems
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• v.17 no.4
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• pp.611-629
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• 2016

This study presents a new approach of surrogate modeling for time-consuming finite element analysis. A surrogate model is widely used to reduce the computational cost under an iterative computational analysis. Although a variety of the methods have been widely investigated, there are still difficulties in surrogate modeling from a practical point of view: (1) How to derive optimal design of experiments (i.e., the number of training samples and their locations); and (2) diagnostics of the surrogate model. To overcome these difficulties, we propose a sequential surrogate modeling based on Gaussian process model (GPM) with self-adaptive sampling. The proposed approach not only enables further sampling to make GPM more accurate, but also evaluates the model adequacy within a sequential framework. The applicability of the proposed approach is first demonstrated by using mathematical test functions. Then, it is applied as a substitute of the iterative finite element analysis to Monte Carlo simulation for a response uncertainty analysis under correlated input uncertainties. In all numerical studies, it is successful to build GPM automatically with the minimal user intervention. The proposed approach can be customized for the various response surfaces and help a less experienced user save his/her efforts.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.563-582
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• 2021

This paper deals with developing a general class of accelerated sequential procedures and obtaining the associated second-order approximations for the expected sample size and 'regret' (difference between the risks of the proposed accelerated sequential procedure and the optimum fixed sample size procedure) function. We establish that the estimation problems based on various lifetime distributions can be tackled with the help of the proposed class of accelerated sequential procedures. Extensive simulation analysis is presented in support of the accuracy of our proposed methodology using the Pareto distribution and a real data set on carbon fibers is also analyzed to demonstrate the practical utility. We also provide the brief details of some other inferential problems which can be seen as the applications of the proposed class of accelerated sequential procedures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.111-117
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• 1992

In order to design and construct a safe and economic underground structure, it is essential to understand the structural behavior of underground openings considering the effect of the sequential excavation. Therefore, this paper includes the study of initial stress distribution before excavation and stress redistribution due to the sequential excavation. And discussion on numerical simulation techniques for the sequential excavation is also included. Then, the underground structure is analyzed using the finite element and distinct element methods of analysis considering the effect of the sequential excavation. Based on the results of the analysis, the followings are discussed: shape of the openings, effect and timing of structural reinforcements. methods and sequence of excavation.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.231-238
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• 2020

Generally, sequential data refers to data having continuity. Text data, which is a representative type of unstructured data, is also sequential data in that it is necessary to know the meaning of the preceding word in order to know the meaning of the following word or context. So far, many techniques for analyzing sequential data such as text data have been proposed. In this paper, four methods of 1d-CNN, LSTM, BiLSTM, and C-LSTM are introduced, focusing on neural network techniques. In addition, by using this, IMDb movie review data was classified into two classes to compare the performance of the techniques in terms of accuracy and analysis time.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.1
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• pp.13-17
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• 2018

According to the recent blackouts, large blackouts can be described by cascading outages. Cascading outage is defined by sequential outages from an initial disturbance. Sequential and probabilistic approach are necessary to minimize the blackout damage caused by cascading outages. In addition, conventional cascading outage analysis models are computationally complex and have time constraints, it is necessary to develop the new analytical techniques. In this paper, we propose the advance visualization model for probabilistic analysis of cascading failure risks. We introduce the visualization model for identifying size of cascading and potential outages and estimate the propagation rate of sequential outage simulation. The proposed model is applied to Korean power systems.

• 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.