• Journal of Information Processing Systems
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• v.13 no.1
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• pp.104-113
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• 2017

In this paper, we present an approach to transmit data from the source to the destination through a minimal path (least-cost path) in a computer network of n nodes. The motivation behind our approach is to address the problem of finding a minimal path between the source and destination. From the work we have studied, we found that a Steiner tree with bounded Steiner vertices offers a good solution. A novel algorithm to construct a Steiner tree with vertices and bounded Steiner vertices is proposed in this paper. The algorithm finds a path from each source to each destination at a minimum cost and minimum number of Steiner vertices. We propose both the sequential and parallel versions. We also conducted a comparative study of sequential and parallel versions based on time complexity, which proved that parallel implementation is more efficient than sequential.

• 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.

• 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.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.53-60
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• 2002

Typical Apriori-like methods for mining sequential patterns have some problems such as generating of many candidate patterns and repetitive searching of a large database. And PrefixSpan constructs the prefix projected databases which are stepwise partitioned in the mining process. It can reduce the searching space to estimate the support of candidate patterns, but the construction cost of projected databases is still high. For efficient sequential pattern mining, we need to reduce the cost to generate candidate patterns and searching space for the generated ones. To solve these problems, we proposed SuffixSpan(Suffix checked Sequential Pattern mining), a new method for sequential pattern mining, and show a formal approach to our method.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.848-855
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• 1989

By structural comparison of process optimization strategies based on Simultaneous Modular Approach, they can be classified into two groups : the Sequential Module Based Approach and the Two-Tier Approach. The Sequential Module Based Approach needs rigorous models and a set of accurate solutions are guranteed. However, it requires large amount of computation time. In the Two-Tier Approach composed of rigorous and simplified models, optimization calculation uses simplified models, therefore comparatively smaller amount of computation time is required but the obtained solutions may not be accurate. These optimization problems were somewhat improved by the alternate application of the two strategies. In this study, improved optimization strategy is suggested, in which Jacobian Matrix is modified to accomodate the strong points of above mentioned strategies. The results of case study show that this approach is superior to the other strategies.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.3
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• pp.397-410
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• 2023

This study examined the efficacy of various chlorinating agents in partitioning light water reactor spent fuel, with the aim of optimizing the chlorination process. Through thermodynamic equilibrium calculations, we assessed the outcomes of employing MgCl₂, NH₄Cl, and Cl₂ as chlorinating agents. A comparison was drawn between using a single agent and a sequential approach involving all three agents (MgCl₂, NH₄Cl, and Cl₂). Following heat treatment, the utilization of MgCl₂ as the sole chlorinating agent resulted in a moderate separation. Specifically, this method yielded a solid separation with 96.9% mass retention, 31.7% radioactivity, and 44.2% decay heat, relative to the initial spent fuel. In contrast, the sequential application of the chlorinating agents following heat treatment led to a final solid separation characterized by 93.1% mass retention, 5.1% radioactivity, and 15.4% decay heat, relative to the original spent fuel. The findings underscore the potential effectiveness of a sequential chlorination strategy for partitioning spent fuel. This approach holds promise as a standalone technique or as a complementary process alongside other partitioning processes such as pyroprocessing. Overall, our findings contribute to the advancement of spent fuel management strategies.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.129-132
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• 2021

Two feature selection approaches are analyzed in this study. First Approach used in this paper is Filter Approach which comprises of correlation technique. It provides two reduced feature sets using positive and negative correlation. Secondly Approach used in this paper is the wrapper approach which comprises of Sequential Forward Selection technique. The reduced feature set obtained by positive correlation results comprises of Rate of Acceleration, Intensity and Formant. The reduced feature set obtained by positive correlation results comprises of Rasta PLP, Log energy, Log power and Zero Crossing Rate. Pitch, Rate of Acceleration, Log Power, MFCC, LPCC is the reduced feature set yield as a result of Sequential Forwarding Selection.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.4 no.2
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• pp.369-378
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• 2014

The Reed-Muller code is one of the efficient algorithms for multiple bit error correction, however, its high-computation requirement inherent in the decoding process prohibits its use in practical applications. To solve this problem, this paper proposes a graphics processing unit (GPU)-based parallel error control approach using Reed-Muller R(r, m) coding for real-time wireless communication systems. GPU offers a high-throughput parallel computing platform that can achieve the desired high-performance decoding by exploiting massive parallelism inherent in the algorithm. In addition, we compare the performance of the GPU-based approach with the equivalent sequential approach that runs on the traditional CPU. The experimental results indicate that the proposed GPU-based approach exceedingly outperforms the sequential approach in terms of execution time, yielding over 70× speedup.

• Journal of the Korean Institute of Telematics and Electronics
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• v.13 no.3
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• pp.1-6
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• 1976

In this paper, a method of test pattern generation for the functional failure in both combinational and sequentlal logic networks by using exterded Boole an difference is proposed. The proposed technique provides a systematic approach for the test pattern generation procedure by computing Boolean difference of the Boolean function that represents the Logic network for which the test patterns are to be generated. The computer experimental results show that the proposed method is suitable for both combinational and asynchronous sequential logic networks. Suitable models of clocked flip flops may make it possible for one to extend this method to synchronous sequential logic networks.