• Structural Engineering and Mechanics
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• v.23 no.6
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• pp.675-689
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• 2006

In structural analysis of tall buildings the traditional primary loading analysis approach that assumes all the loads are simultaneously applied to the fully built structure has been shown to be unsuitable by many researches. The construction sequential analysis that reflects the fact of the level-by-level construction of tall buildings can provide more reliable results and has been used more and more. However, too much computational cost has prevented the construction sequential analysis from its application in CAD/CAE software for building structures, since such an approach needs to deal with systematic changing of resultant stiffness matrices following level-by-level construction. This paper firstly analyzes the characteristics of assembling and triangular factorization of the stiffness matrix in the finite element model of the construction sequential analysis, then presents a fast construction sequential analysis strategy and a corresponding step-by-step active column solver by means of improving the existing skyline solver. The new strategy avoids considerably repeated calculation by only working on the latest appended and modified part of resultant stiffness matrices in each construction level. Without any simplification, the strategy guarantees accuracy while efficiency is greatly enhanced. The numerical tests show that the proposed strategy can be implemented with high efficiency in practical engineering design.

• 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.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.05a
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• pp.201-204
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• 2001

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 of length and undesirable strip shapes are corrected to the flat shape. This paper is concerned with a simulation of the tension levelling process based on the analysis of the unit model for the tension leveller. Analysis technique such as the sequential analysis of the nit model is suggested and verified with the assembly analysis of the unit model for the effective and economic analysis of the full set of the tension leveller. Analysis of the full tension levelling process using sequential unit models is carried out and provides the effect of the intermesh and optimum amount of the intermesh in tension levelling process.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Language and Information
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• v.9 no.1
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• pp.35-49
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• 2005

Lakoff(1986) claim that sequential fading alone suffices to sanction ATB violations cannot be supported in Korean verbal coordination of TP, since extraction from the conjunction of TP in Korean is impossible regardless of whether the conjuncts are interpreted sequentially or non-sequentially. However, ATB violations are allowed in the coordination of Non-TP, only when the conjuncts are interpreted sequentially. 1 will argue that Non-TP, in coordination are ambiguous between a conjunct and adjunct analysis. Furthermore, a claim made here is that the distinction between the sequential and non-sequential reading in Non-TP coordination is a distinction made by syntax, while the sequential vs. non-sequential reading in TP coordination is derived from semantics or pragmatics.

• 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.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.7-14
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• 2003

In the back analysis of braced excavation based on displacement measurements, the accumulated errors of abnormal displacement caused by unexpected loads are usually observed. To minimize such errors, in this study, displacement increment was used fur back analysis rather than displacement for the conventional method. That is, the increment of sequential displacement is used as the objective function and the back analysis program is developed by taking advantage of sequential linear programming method by modified method of feasible directions. Based on small scale model test, the analysis of proposed method is verified.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1797-1807
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• 2013

Dams always have the possibility of failure due to unexpected natural phenomena. In particular, dam failure can cause huge damage including damage for humans and properties when dam downstream regions are densely populated or have important national facilities. Although many studies have been conducted on the analysis of flood waves about single dam failure thus far, studies on the analysis of flood waves about the sequential failure of dams are lacking. Therefore, the purpose of this study was to calculate the peak discharge of sequential failure of dams through flood wave analysis of sequential failure of dams and this analysis techniques to predict flood wave propagation situation in downstream regions. To this end, failure flood wave analysis were conducted for Lawn Lake Dam which is a case of sequential failure of dams among actual failure cases using DAMBRK to test the suitability of the dam failure flood wave analysis model. Based on the results, flood wave analysis of sequential failure of dams were conducted for A dam in Korea assuming a virtual extreme flood to predict flood wave propagation situations and 2-dimensional flood wave analysis were conducted for major flooding points. Then, the 1, 2-dimensional flood wave analysis were compared and analyzed. The results showed goodness-of-fit values exceeding 90% and thus the accuracy of the 1-dimensional sequential failure of dams simulation could be identified. The results of this study are considered to be able to contribute to the provision of basic data for the establishment of disaster prevention measures for rivers related to sequential failure of dams.

• 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.