• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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• pp.75-84
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• 1995

Fault simulators are used for accurate evaluation of fault coverages of digital circuits. But fault simulation becomes time and memory consuming job because computation time is proportional to wquare of size of circuits. Recently, several approximate algorithms for testability analysis have been published to cope with the problems. COP is very fast but cannot be used for sequential circuits, while STAFAN can ve used for sequential circuits but requires large amount of computation because it utilizes logic simulation results. In this paper EXTASEC(An Extension of Testability Analysis for Sequential Circuits) is proposed. It is an extension of COP in the sense that it is the same as COP for combinational circuits, but it can handle sequential circuits, Xicontrollability and backward line analysis are key concept for EXTASEC. Performance of EXTASEC is proven by comparing EXTASEC with a falut simulator, STAFAN, and COP for ISCAS circuits, and the result is demonstated.

• 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.

• Structural Engineering and Mechanics
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• v.51 no.6
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• pp.989-1003
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• 2014

In the preliminary design stage of an RC 3D-frame, repeated sequential analyses to determine optimal members' sizes and the investigation of the parameters required to minimize the differential column shortening are computational effort consuming, especially when considering various types of loads such as dead load, temperature action, time dependent effects, construction and live loads. Because the desired accuracy at this stage does not justify such luxury, two backpropagation feedforward artificial neural networks have been proposed in order to approximate this information. Instead of using a commercial software package, many references providing advanced principles have been considered to code a program and generate these neural networks. The first one predicts the typical amount of time between two phases, needed to achieve the minimum maximorum differential column shortening. The other network aims to prognosticate sequential analysis results from those of the simultaneous analysis. After the training stages, testing procedures have been carried out in order to ensure the generalization ability of these respective systems. Numerical cases are studied in order to find out how good these ANN match with the sequential finite element analysis. Comparison reveals an acceptable fit, enabling these systems to be safely used in the preliminary design stage.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• 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.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.4
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• pp.11-20
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• 1998

Fault simulatior has been used to compute exact fault coverages of test vectors for digial circuits. But it is time consuming because execution time is proportional to square of circuit size. Recently, several algorithms for testability analysis have been published to cope with these problems. COP is very fast and accurate but cannot be used for sequential circuits, while STAFAN can be used for sequential circuits but needs vast amount of execution time due to good circuit simulation. We proposed EXTASEC which gave fast and accurate fault coverage. But it shows noticeable errors for a few sequential circuits. In this paper, it is shown that the inaccuracy is due to uninitializble flipflops, and we propose ITEM to improve the EXTASEC algorithm. ITEM is an improved evaluation method of fault coverage by analysis of backward lines and uninitializable flipflops. It is expected to perform efficiently for very large circuits where execution time is critical.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.20-22
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• 2015

Recently, the study of smart phone user habits has become a highly focused topic due to the rapid growth of the smart phone market. Indeed, sequential pattern analysis methods were efficiently used for web-based user habit mining long time ago. However, by means of simulations, it has been observed that these methods might fail for smart phone-based user habit mining. In this paper, we propose a novel approach that leads to a considerably increased performance of the traditional sequential pattern analysis methods by reasonably cutting off each chronological sequence of user logs on a device into shorter ones, which represent the sequential user activities in various periods of a day.

• 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.

• International Journal of Contents
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• v.16 no.1
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• pp.44-56
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• 2020

The purpose of this study was to examine how the presentation mode (sequential- vs. simultaneous-mode) of information influences its evaluation. Three experiments revealed the interaction effect between the presentation mode and the valence of the product information. When respondents read about the positive aspects of the product, the evaluation was higher in the simultaneous presentation mode than in the sequential presentation mode. For negative product information, respondents' evaluation was higher in the sequential presentation mode than in the simultaneous presentation mode. The simultaneous presentation mode intensified the impact of the information valence on evaluation. This study proposed that the sequential and the simultaneous presentation modes prime high and low construal levels, respectively. The mediation analysis provides support for such a prediction. Finally, the mediating effect of construal levels in evaluation was shown to disappear when respondents focused on the product information for a longer duration, while the mediation effect remained when the response time was short.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.3
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• pp.213-223
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• 2001

This paper presents an analytical procedure for the time-dependent analysis of the multi-story prestressed concrete structure under the construction stage. To account for the actual structural behavior, the procedure considers the effects due to the construction interval and the time-dependent losses of prestress at every construction step on the entire structural response. A numerical study is performed to demonstrate the general validity of the approach and to quantitatively evaluate the effects resulted from the time-dependent behaviors during construction. Recommendations and conclusions are developed by comparisons with structural responses using the present and conventional methods of analysis. The comparative results show that both effects of sequential construction and time-dependent prestress losses should be considered for the construction stage analysis.