• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.379-382
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• 2015

무선 센서 네트워크는 제한된 에너지 자원으로 동작하므로 에너지 소비를 최소화하여 통신하는 기법이 무선 센서 네트워크 설계에 있어 매우 중요한 요소이다. 센서 노드들의 에너지 효율을 개선하기 위한 다양한 방법 중 클러스터링 알고리즘에 기반 한 계층적 라우팅 방법이 무선 센서 네트워크의 성능과 수명을 증가시키기 위해 효과적인 기술임이 알려지면서 다양한 접근법이 제시되고 있다. 클러스터 기반 아키텍처에서 클러스터의 부하 균형을 위한 효율적인 군집 모델은 게이트웨이와 센서 노드의 수명을 증가시켜 전체 네트워크의 성능을 향상 시킨다. 본 논문에서는 네트워크의 수명과 에너지 효율성을 높이기 위해 새로운 부하 균형 군집 모델을 제시한다. 또한 최적해를 보장하는 분기 한정 알고리즘을 설계하고 이를 이용해 다양한 조건에서 기존에 제시된 부하 균형 군집 모델과 실험하고 성능을 비교한다.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.39-51
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• 2012

Cluster analysis has proven to be a useful tool for investigating the association structure among genes and samples in a microarray data set. We applied several cluster validation measures to evaluate the performance of clustering algorithms for analyzing microarray gene expression data, including hierarchical clustering, K-means, PAM, SOM and model-based clustering. The available validation measures fall into the three general categories of internal, stability and biological. The performance of clustering algorithms is evaluated using simulated and SRBCT microarray data. Our results from simulated data show that nearly every methods have good results with same result as the number of classes in the original data. For the SRBCT data the best choice for the number of clusters is less clear than the simulated data. It appeared that PAM, SOM, model-based method showed similar results to simulated data under Silhouette with of internal measure as well as PAM and model-based method under biological measure, while model-based clustering has the best value of stability measure.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.355-369
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• 2005

Genome sequencing and microarray technology produce ever-increasing amounts of complex data that needs statistical analysis. Visualization is an effective analytic technique that exploits the ability of the human brain to process large amounts of data. In this study, biplot approach applied to microarray data to see the relationship between genes and samples. The supplementary data method to classify new sample to known category is suggested. The methods are validated by applying it to well known microarray data such as Golub et al.(1999), Alizadeh et al.(2000), Ross et al.(2000). The results are compared to the results of several clustering methods. Modified graph which combine partitioning method and biplot is also suggested.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.17-52
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• 2018

The purpose of this paper is to measure the clustering change and analyze empirical results. Additionally, by using k-means, hierarchical, and mixed models on Asian container ports over the period 2006-2015, the study aims to form a cluster comprising Busan, Incheon, and Gwangyang ports. The models consider the number of cranes, depth, birth length, and total area as inputs and container twenty-foot equivalent units(TEU) as output. Following are the main empirical results. First, ranking order according to the increasing ratio during the 10 years analysis shows that the value for average linkage(AL), mixed ward, rule of thumb(RT)& elbow, ward, and mixed AL are 42.04% up, 35.01% up, 30.47%up, and 23.65% up, respectively. Second, according to the RT and elbow models, the three Korean ports can be clustered with Asian ports in the following manner: Busan Port(Hong Kong, Guangzhou, Qingdao, and Singapore), Incheon Port(Tokyo, Nagoya, Osaka, Manila, and Bangkok), and Gwangyang Port(Gungzhou, Ningbo, Qingdao, and Kasiung). Third, optimal clustering numbers are as follows: AL(6), Mixed Ward(5), RT&elbow(4), Ward(5), and Mixed AL(6). Fourth, empirical clustering results match with those of questionnaire-Busan Port(80%), Incheon Port(17%), and Gwangyang Port(50%). The policy implication is that related parties of Korean seaports should introduce port improvement plans like the benchmarking of clustered seaports.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.1-9
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• 2019

The purpose of this study is to examine the system of the Jeokbyeok-ga's version using the Computer analysis technique of bibliographies and to examine the achievements of the Jeokbyeok-ga's version studies. First, in order to provide basic data for analysis, a raw corpus was constructed for 46 species of Jeokbyeok-ga. Through this, the common narrative units of the Jeokbyeok-ga were identified as 5 layers, and thus 146 individual paragraphs could be extracted. Based on the encoded corpus, we tried to measure the similarity and the distance between the two. Next, we applied the Multidimensional scaling method, Hierarchical cluster analysis and Cladistic analysis method of the system to confirm the distribution of versions group and it was possible to visually grasp the distance between versions and the system of the work. As a result of analyzing Computer analysis technique of bibliographies, it was found that version's group of the Jeokbyeok-ga was divided into a Wanpan(完板) series and Changbon(唱本) series. Also, it was possible to examine the influence relationship between the Pansori's traditions and transmission.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.177-187
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• 2013

Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering, table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.504-504
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• 2015

수공구조물을 설계하기 위해서는 설계수문량을 빈도해석을 통해 산정할 수 있다. 빈도해석 중 지점빈도해석을 보완한 지역빈도해석을 적용하기 위해서는 군집분석을 통한 지역구분이 무엇보다 중요하다. 또한 스케일 성질(scaling property)은 강우의 시 공간적 특성을 지속기간별 관측된 강우자료를 이용하여 재현기간에 대한 지속기간의 함수로 강우의 IDF곡선을 제시할 수 있는 방법이다. 따라서 스케일 성질을 통해 군집된 지역에서의 강우자료에 적용하여 스케일 인자(scaling exponent)를 추정한 후 수문학적 동질성을 통계적 특성으로 설명하고자 한다. 본 연구를 수행하기에 앞서 군집 분석은 4개의 군집방법(평균연결법, Ward방법, Two-Step방법, K-means방법)을 적용하였고, 한강유역에 위치한 104개의 강우지점은 4개의 지역으로 구분하는 것이 적절하다고 판단되어 비계층적 방법인 k-means방법을 이용하여 지역을 구분하였다. 본 연구에서는 군집된 결과를 바탕으로 4개의 지역으로 구분된 지역에 포함된 강우지점을 대상으로 스케일 인자를 추정하고 수문학적 동질성을 통계적 방법으로 제시하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.6
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• pp.385-391
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• 2022

This paper presents to develop a path planning algorithm combining gradient descent-based path planning (GBPP) and particle swarm optimization (PSO) for considering prohibited flight areas, terrain information, and characteristics of fixed-wing unmmaned aerial vehicle (UAV) in 3D space. Path can be generated fast using GBPP, but it is often happened that an unsafe path can be generated by converging to a local minimum depending on the initial path. Bio-inspired swarm intelligence algorithms, such as Genetic algorithm (GA) and PSO, can avoid the local minima problem by sampling several paths. However, if the number of optimal variable increases due to an increase in the number of UAVs and waypoints, it requires heavy computation time and efforts due to increasing the number of particles accordingly. To solve the disadvantages of the two algorithms, hierarchical path planning algorithm associated with hierarchical particle swarm optimization (HPSO) is developed by defining the initial path, which is the input of GBPP, as two variables including particles variables. Feasibility of the proposed algorithm is verified by software-in-the-loop simulation (SILS) of flight control computer (FCC) for UAVs.

• Journal of Platform Technology
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• v.11 no.5
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• pp.23-36
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• 2023

This study aims to analyze the similarities and dissimilarities of various versions of <Heungbu-jeon> at both micro- and macro-levels using contents analysis techniques and the Hamming distance metrics. The 28 versions of <Heungbu-jeon> were segmented into 341 content units, and for each unit, the value of the content type was encoded. The dissimilarities between content types were compared among all versions by the content unit, respectively. The (dis-)similarities based on the content types of the 28 versions were aggregated and transformed into a distance matrix. The matrix was interpreted by multi-dimensional scaling, resulting into the two-dimensional coordinates. By visualizing the results by multi-dimensional scaling analysis, it was confirmed that the versions of <Heungbu-jeon> can be broadly divided into two groups. Hierarchical clustering and phylogenetic analysis were applied to analyze the clusters of the 28 versions, using the same distance matrix. The results showed that there are five clusters based on the micro-level analysis of (dis-)similarities within two major clusters. This study demonstrated the usefulness of applying digital humanities methods to encode the content of classical literary versions and analyze the data using clustering analysis techniques based on the (dis-)similarity of literary content.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.15-25
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• 2022

This study aims to identify the family and lineage of a part of a "Fish Tribe Conference" in the section Tokkijeon by utilizing computer literature analysis techniques. First of all, we encode the classification for a pairwise comparison's type of each paragraph to build a corpus, and based on this, we use the Hamming distance to calculate the distance matrix between each classification for a pairwise comparison's. We visualized classification for a pairwise comparison's clustering pattern by applying multidimensional scale method, and hierarchical clustering to explore the characteristics of the 'fish family' line and lineage compared to the existing cluster analysis study on entire paragraphs of "Tokkijeon". As a result, unlike the cluster analysis of the entire paragraph of "Tokkijeon", which consists of six categories, the "Fish Tribe Conference" section has five categories and some classification for a pairwise comparison's accesses. The results of this study are that the relative distance between Yibon was measured and systematic classification was performed in an objective and empirical way by calculation, and the characteristics of the line of the fish family were revealed compared to the analysis of the entire rabbit exhibition.