• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.1-8
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• 2003

We introduce a efficient vertical mining algorithm that reduces searching complexity for frequent k-itemsets significantly. This method includes sorting items by their LSI(Least Support Itemsets) similarity and then searching frequent itemsets in tree-based manner. The search tree structure provides several useful heuristics and therefore, reduces search space significantly at early stages. Experimental results on various data sets shows that the proposed algorithm improves searching performance compared to other algorithms, especially for a database having long pattern.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.249-258
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• 2002

One of the jai or purposes of multiprocessor system is to get a high efficiency in performance improvement. But in most cases, it is unavoidable to use some special programming languages or tools for full use of multiprocessor system. In general, loop and recursive call statements of algorithms are considered as typical parts for parallelization. Especially, recursive call statements are easy to parallelize conceptually without support of any special languages or tools. But it is difficult to control the degree of parallelism caused by high depth of recursive call leading to execution crash. This paper proposes a device to control Parallelism in the process of POSIX thread bated parallelization of recursive algorithms. For this, we define the concept of thread and process in UNIX system, and analyze the results of experimental application of the device to quick sorting algorithm.

• The KIPS Transactions:PartA
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• v.15A no.6
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• pp.325-334
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• 2008

Flash memory is widely used as a storage medium for mobile devices such as cell phones, MP3 players, PDA's due to its tiny size, low power consumption and shock resistant characteristics. Additionally, some computer manufacturers try to replace hard-disk drives used in Laptops or personal computers with flash memory. More recently, there are some literatures on developing a flash memory-aware $B^+$-tree index for an efficient key-based search in the flash memory storage system. They focus on minimizing the number of "overwrites" resulting from inserting or deleting a sequence of key values to/from the $B^+$-tree. However, in addition to this factor, the size of a physical page allocated to a node can affect the maintenance cost of the $B^+$-tree. In this paper, with diverse experiments, we compare and analyze the costs of construction and search of the $B^+$-tree and the space requirement on flash memory as the node size increases. We also provide sorting-based or non-sorting-based algorithms to be used when inserting a key value into the node and suggest an header structure of the index node for searching a given key inside it efficiently.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.108-115
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• 2007

This paper proposes a new optimization algorithm prescribed by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) whose result satisfies the user's needs and goals to enhance the performance of optimization. Typically, lots of real-world engineering problems encounter simultaneous optimization subject to satisfying prescribed multiple objectives. Unfortunately, since these objectives might be mutually competitive, it is hardly to find a unique solution satisfying every objectives. Instead, many researches have been investigated in order to obtain an optimal solution with sacrificing more than one objectives. This paper introduces a novel optimization scheme named by GBNSGA obeying both goals as well as objectives as possible as it can via allocating candidated solutions on Pareto front, which enhances the performance of Pareto based optimization. The performance of the proposed GBNSGA will be compared with that of the conventional NSGA and weighted-sum approach.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1217-1228
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• 2005

Recently, since DNA computing has been widely studied for various applications, DNA sequence design which is the most basic and important step for DNA computing has been highlighted. In previous works, DNA sequence design has been formulated as a multi-objective optimization task, and solved by elitist non-dominated sorting genetic algorithm (NSGA-II). However, NSGA-II needed lots of computational time. Therefore, we use an $\varepsilon$- multiobjective evolutionarv algorithm ($\varepsilon$-MOEA) to overcome the drawbacks of NSGA-II in this paper. To compare the performance of two algorithms in detail, we apply both algorithms to the DTLZ2 benchmark function. $\varepsilon$-MOEA outperformed NSGA-II in both convergence and diversity, $70\%$ and $73\%$ respectively. Especially, $\varepsilon$-MOEA finds optimal solutions using small computational time. Based on these results, we redesign the DNA sequences generated by the previous DNA sequence design tools and the DNA sequences for the 7-travelling salesman problem (TSP). The experimental results show that $\varepsilon$-MOEA outperforms the most cases. Especially, for 7-TSP, $\varepsilon$-MOEA achieves the comparative results two tines faster while finding $22\%$ improved diversity and $92\%$ improved convergence in final solutions using the same time.

• Resources Recycling
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• v.26 no.2
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• pp.46-55
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• 2017

In this study, the design methodology of Radial Basis Function Neural Networks is developed with the aid of Laser Induced Breakdown Spectroscopy and also applied to the practical plastics sorting system. To identify black plastics such as ABS, PP, and PS, RBFNNs classifier as a kind of intelligent algorithms is designed. The dimensionality of the obtained input variables are reduced by using PCA and divided into several groups by using K-means clustering which is a kind of clustering techniques. The entire data is split into training data and test data according to the ratio of 4:1. The 5-fold cross validation method is used to evaluate the performance as well as reliability of the proposed classifier. In case of input variables and clusters equal to 5 respectively, the classification performance of the proposed classifier is obtained as 96.78%. Also, the proposed classifier showed superiority in the viewpoint of classification performance where compared to other classifiers.

• Radiation Oncology Journal
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• v.33 no.2
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• pp.149-154
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• 2015

Purpose: We performed exome sequencing in a breast cancer family without BRCA mutations. Materials and Methods: A family that three sisters have a history of breast cancer was selected for analysis. There were no family members with breast cancer in the previous generation. Genetic testing for BRCA mutation was negative, even by the multiplex ligation-dependent probe amplification method. Two sisters with breast cancer were selected as affected members, while the mother of the sisters was a non-affected member. Whole exome sequencing was performed on the HiSeq 2000 platform with paired-end reads of 101 bp in the three members. Results: We identified 19,436, 19,468, and 19,345 single-nucleotide polymorphisms (SNPs) in the coding regions. Among them, 8,759, 8,789, and 8,772 were non-synonymous SNPs, respectively. After filtering out 12,843 synonymous variations and 12,105 known variations with indels found in the dbSNP135 or 1000 Genomes Project database, we selected 73 variations in the samples from the affected sisters that did not occur in the sample from the unaffected mother. Using the Sorting Intolerant From Tolerant (SIFT), PolyPhen-2, and MutationTaster algorithms to predict amino acid substitutions, the XCR1, DLL1, TH, ACCS, SPPL3, CCNF, and SRL genes were risky among all three algorithms, while definite candidate genes could not be conclusively determined. Conclusion: Using exome sequencing, we found 7 variants for a breast cancer family without BRCA mutations. Genetic evidence of disease association should be confirmed by future studies.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.29-38
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• 2007

Computer programming in computer education draws much attention recently. Encouraged by the increased tendency of acquiring logical ability and creativity through learning, various attempts have been made to develop them through learning computer programming in the area of computer education as well. The fact that a computer program is the representation of a computer algorithm expressed in a computer language makes us realize that the devise of a logical method for a solution - i.e., the design of an algorithm - is the key to the solution of a problem. Recognizing the importance of computer algorithm would lead us to such a point that systematic investigations for directional establishment for algorithm education are necessary. We observe that researches on teaching computer algorithm have concentrated mostly on specific problems such as sorting and searching, which can be characterized as problem-dependent and individual. In this paper, the idea of conceptual algorithm is stated from the standpoint of conceptual types of problem-solving methods which are considered as problem-independent and collective. A novice approach to algorithm education based on the characteristics of types of conceptual algorithms is proposed for the purpose of developing systematic, problem-independent, algorithmic problem-solving capabilities of learners, which is widely different from the current methods of individual and problem-dependent algorithm education.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.395-402
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• 2002

In the conventional public switched telephone network(PSTN), there are various types of modulation that can be used in ADSL to offer fast data communication, two of which are CAP(Carrierless Amplitude Phase) and DMT(Discrete MultiTone). As we consider the current situation, DMT is getting more predominant in the market than CAP. One of the reasons is that it gives high performance in spite of its high complexity Since DMT divides the full range of bandwidth into 256 sub-channels, it can be highly adaptive in the circumstances, where the problems of attenuation and noise caused by the propagation distance are very crucial. In this paper, a new bit loading algorithm for DMT modulation is proposed. The proposed algorithm can be efficiently implemented in a way that it requires less computation than the conventional modulation techniques. In contrast to the conventional algorithms which perform sorting processing, the proposed algorithm uses look-up tables to reduce the repetition of calculation. Consequently, it is shown that less processing time and lower complexity can be achieved.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.674-684
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• 2000

One key obstacle which has been identified in achieving parallel processing is to communicate effectively between processors during execution. One approach to achieving an optimal delay time is to use expander graph. The networks and algorithms which are based on expander graphs are successfully exploited to yield fast parallel algorithms and efficient design. The AKS sorting algorithm in time O(logN) which is an important result is based on the use of expanders. The expander graph also can be applied to construct a concentrator and a superconcentrator. Since Margulis found a way to construct an explicit linear expander graph, several expander graphs have been developed. But the proof of existence of such graphs is in fact provided by a nonconstructive argument. We investigate the expander network on the hypercube network. We prove the expansion of a sin81e stage hypercube network and extend this from a single stage to multistage networks. The results in this paper provide a theoretical analysis of expansion in the hypercube network.