• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.51-62
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• 2018

High utility sequential pattern (HUSP) mining has been considered as an important research topic in data mining. Although some algorithms have been proposed for this topic, they incur the problem of producing a large search space for HUSPs. The tighter utility upper bound of a sequence can prune more unpromising patterns early in the search space. In this paper, we propose a sequence expected utility (SEU) as a new utility upper bound of each sequence, which is the maximum expected utility of a sequence and all its descendant sequences. A sequence utility list for each pattern is used as a new data structure to maintain essential information for mining HUSPs. We devise an algorithm, high sequence utility list-span (HSUL-Span), to identify HUSPs by employing SEU. Experimental results on both synthetic and real datasets from different domains show that HSUL-Span generates considerably less candidate patterns and outperforms other algorithms in terms of execution time.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.31-38
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• 2007

Code Optimization is converting to a code that is equivalent to given program but more efficient, and this process is processed in Code Optimizer. This paper designed and processed Code Optimizer Generator that automatically generates Code Optimizer. In other words Code Optimizer is automatically generated for DFA Pattern Matching which finds the optimal code for the incoming pattern description. DFA Pattern Matching removes redundancy comparisons that occur when patterns are sought for through normalization process and improves simplification and structure of pattern shapes for low cost. Automatic generation of Code Optimization for DFA Pattern Matching eliminates extra effort to generate Code Optimizer every time the code undergoes various transformations, and enables formalism of Code Optimization. Also, the advantage of making DFA for optimization is that it is faster and saves cost of Code Optimizer Generator.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.478-487
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• 2004

We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.139-147
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• 2009

The memory based reasoning just stores in the memory in the form of the training pattern of the representative pattern. And it classifies through the distance calculation with the test pattern. Because it uses the techniques which stores the training pattern whole in the memory or in which it replaces training patterns with the representative pattern. Due to this, the memory in which it is a lot for the other machine learning techniques is required. And as the moreover stored training pattern increases, the time required for a classification is very much required. In this paper, We propose the EAS(Evaluation And Selection) algorithm in order to minimize memory usage and to improve classification performance. After partitioning the training space, this evaluates each partitioned space as MDL and PM method. The partitioned space in which the evaluation result is most excellent makes into the representative pattern. Remainder partitioned spaces again partitions and repeat the evaluation. We verify the performance of Proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.127-133
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• 2019

Since frequent item extraction so far requires searching for patterns and traversal for the FP-Tree, it is more likely to store the mining data in a tree and thus CPU time is required for its searching. In order to overcome these drawbacks, in this paper, we provide each item with its location identification of transaction data without relying on conditional FP-Tree and convert transaction data into 2-dimensional position information look-up table, resulting in the facilitation of time and spatial accessibility. We propose an algorithm that considers the mapping scheme between the location of items and items that guarantees the linear time complexity. Experimental results show that the proposed method can reduce many execution time and memory usage based on the data set obtained from the FIMI repository website.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.33-33
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• 2019

최근 반복적인 도시침수 피해가 발생하고 있으나 다양한 강우 및 홍수 자료를 이용하여 실시간으로 침수분석을 실시할 수 있는 기술력이 부재한 실정이다. 한정된 시나리오에 따라 다양한 강우패턴에 의한 침수지역 파악에 어려움이 있으며, 불필요한 자료의 사용으로 인해 짧은 시간에 발생하는 도시침수에 대해 실시간으로 대응하는 데에 한계가 있다. 본 연구에서는 다양한 강우패턴과 극치강우 사상을 반영하기 위한 강우시간 분포법을 나타내고자 하였으며, 강우-유출 자료에 대한 최적의 자료조합을 선정하는 정량적 기준을 제시하고자 하였다. 지역 특성에 따른 극치강우사상의 시간분포에 대한 연구가 다양하게 진행되어 왔지만, 기존의 강우시간분포는 다양한 강우의 집중현상을 나타내기에는 한계가 있음을 보였다. 따라서 본 연구에서는 기존 강우시간분포 기법의 단점을 보완하고 극치강우사상의 집중지속시간 특성을 반영한 강우시간분포 방법과 Huff에 의한 강우시간 분포법을 사용하여 다양한 강우시나리오를 생성하였다. 본 연구에서는 부산 및 울산 연구대상지역의 도시유출해석의 입력 자료로서 사용하였다. 강우 및 유출 자료의 상관성 분석과 불확실도 분석을 기반으로 추후 홍수예측을 위한 최적의 입력 자료를 선정하고자 하였다. 위의 과정들을 통해 다양한 강우조건에 따른 연구대상 지역에서의 침수예상도를 분석할 수 있었으며, 선정된 극치강우사상을 통해 다양한 강우의 집중현상을 나타낼 수 있었다. 1차원 도시유출해석을 실시하여 구축한 강우-유출 데이터베이스의 최적화를 위해 불확실도 분석을 실시하였으며, 수리학적 특성이 고려된 입력 및 출력자료에 대한 사용자의 합리적인 판단을 위해 정량적 기준을 제시하고자 하였다. 더욱이 제시된 방법론을 이용함에 따라 지속적으로 나타나는 국지성 호우와 급변하는 수재해 양상에 능동적으로 대처하는데 도움을 줄 수 있는 기초자료를 제공할 것으로 판단된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.349-354
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• 2011

In ROI processing of JPEG2000, a region of large image indicated by the user must be processed preferentially, because it takes a considerable amount of time to display the full image. When the user indicates a region of the outlined image, then the browser masks the region and sends the mask information to the server that transmitted the outlined image. The server that receives the mask information preferentially sends the corresponding code blocks. Here, a quick generation of mask information is important. In this paper, we use 48 predefined mask patterns, which are defined according to the distribution shape of ROI and background to reduce the computing time. As a result, compared to other methods that precisely handles the ROI and background, the processing time of the method is remarkably reduced, but the quality is short of the existing methods just a little bit.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.28-37
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• 1999

In this paper. we developed a delay test architecture and test procedure for clocked 5-bit asynchronous counter circuit based on boundary scan architecture. To develope, we analyze the problems of conventional method on delay test for clocked sequential circuit in boundary scan architecture. This paper discusses several problems of delay test on boundary scan architecture for clocked sequential circuit. Conventional test method has some problems of improper capture timing, of same pattern insertion, of increase of test time. We suggest a delay test architecture and test procedure, is based on a clock count-generation technique to generate continuous clocks for clocked input of CUT. The simulation results or 5-bit counter shows the accurate operation and effectiveness of the proposed delay test architecture and procedure.