• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.757-772
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• 2019

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Artificial Neural Network, Social Network, and Tabu Search models on 38 Asian container ports over the period 2007-2016. The models consider number of cranes, depth, birth length, and total area as inputs and container throughput as output. Followings are the main empirical results. First, the variables ranking order which affects the clustering according to artificial neural network are TEU, birth length, depth, total area, and number of cranes. Second, social network analysis shows the same clustering in the benevolent and aggressive models. Third, the efficiency of domestic ports are worsened after clustering using social network analysis and tabu search models. Forth, social network and tabu search models can increase the efficiency by 37% compared to that of the general CCR model. Fifth, according to the social network analysis and tabu search models, 3 Korean ports could be clustered with Asian ports like Busan Port(Kobe, Osaka, Port Klang, Tanjung Pelepas, and Manila), Incheon Port(Shahid Rajaee, and Gwangyang), and Gwangyang Port(Aqaba, Port Sulatan Qaboos, Dammam, Khor Fakkan, and Incheon). Korean seaport authority should introduce port improvement plans by using the methods used in this paper.

• Journal of Information Technology and Architecture
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• v.9 no.2
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• pp.199-207
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• 2012

This study analyzed how the subcontracting business relations and structures of cooperation affect the relationship skills (Outcome) that is divided into three steps. We analyzed integrated data every other year from 2005 to 2009. As a results, in the execution of technical cooperation trade relations have influenced the positive attributes, but recently their influence has been weakened. As for technical cooperation, the structure should alleviate the problem of the uneven performance of technical cooperation. We suggested that technical expertise and infrastructure make possible the culmination of the long-term technological competitiveness level.

• Journal of Information Management
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• v.40 no.2
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• pp.95-115
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• 2009

Author resolution is to disambiguate same-name author occurrences into real individuals. For this, pair-wise author similarities are computed for author name entities, and then clustering is performed. So far, many studies have employed hierarchical clustering techniques for author disambiguation. However, various hierarchical clustering methods have not been sufficiently investigated. This study covers an empirical evaluation and analysis of hierarchical clustering applied to Korean author resolution, using multiple distance functions such as Dice coefficient, Cosine similarity, Euclidean distance, Jaccard coefficient, Pearson correlation coefficient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.418-421
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• 2007

In this paper, we proposed a hierarchical nearest-neighbor searching method for deciding fitness of a clustered segment. It is difficult to distinguish the difference between correct spots and atypical noisy spots in footprint patterns. Therefore we could not completely remove unsuitable noisy spots from binarized image in image preprocessing stage or clustering stage. As a preprocessing stage for recognition of insect footprints, this method decides whether a segment is suitable or not, using degree of clustered segment fitness, and then unsuitable segments are eliminated from patterns. Removing unsuitable segments can improve performance of feature extraction for recognition of inset footprints.

• The KIPS Transactions:PartD
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• v.17D no.3
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• pp.175-184
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• 2010

Experiments and research on genes have become very convenient by using DNA chips, which provide large amounts of data from various experiments. The data provided by the DNA chips could be represented as a two dimensional matrix, in which one axis represents genes and the other represents samples. By performing an efficient and good quality clustering on such data, the classification work which follows could be more efficient and accurate. In this paper, we use a bio-inspired algorithm called the Particle Swarm Optimization algorithm to propose an efficient clustering mechanism for large amounts of DNA chip data, and show through experimental results that the clustering technique using the PSO algorithm provides a faster yet good quality result compared with other existing clustering solutions.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.15-26
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• 2002

The purpose of this study was to classier the somatotype of late middle-aged women and to analyze the characteristics of each somatotype. The subjects were 337 late middle-aged women and their age range os from 45 to 59 fears old. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis and discriminant analysis. The results were as follows; 1. The result of factor analysis indicated that 9 factors were extracted through factor analysis and those factors comprised 83.56 percent of total valiance. 2. Using factor scores, cluster analysis was carried out and the subject were classified into 4 cluster. Each cluster was classified as their body front and side view contour. Type 1 is tall, slim, and lower balk is flat on the side. Type 2 is standard and lean-back type on the side. Type 3 is standard height and weight, H type in front, and belly-protruded on the side. Type 4 is short, fat, and the side is hip-protruded. 3. According to the stepwise discriminant analysis, the 9 important items in classifying the somatotype of the late middle-aged women are as follows ; lower back tilt angle, hip depth(back) -back waist depth(back), bust depth(fore) - anterior waist depth(fore), jugular fossa point(fore), upper back tilt angle, burst breadth -waist breadth, right shoulder tilt, height of shoulder - height of anterior waist, abdomen breath. The correct classification rate for these items is as exact as 84.62%.

• Korean Journal of Environment and Ecology
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• v.11 no.2
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• pp.149-159
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• 1997

Eleven plots(10m*10m) were established in Pinus densiflora forests and analized in with TWINSPAN and DCA techniques, to study the comparison of the structure of plant community by soil depth in Ulsan Grand Park. As a result of this analyusis, the communities were divided into two groups : Community B which have shallow one. Community A showed climatic climax which have proceeded from Pinus densiflora to Quercus variabilis, Castanea crenata, Platycarya strobilacea, and at last to Carpinus laxiflora. Community A showed climatic climax which have proceeded fro, Pimus densiflora to Quercus variabilis, Castanea crenata, Platycarya strobilacea, and at last to carpenus laxiflora. Community B showed edaphic climax in sere of Pinus desiflora. The diffrernce of the growth of tree height was showed significantly between two communities. The sample tree aged 30 in Community A was 8.50m high and the sample tree aged 35 in Community B was 3.80m high. Community A was better than Community B in soil characteristics and species diversity indicies.

• Korean Journal of Environment and Ecology
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• v.5 no.1
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• pp.32-41
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• 1991

A survey of subalpine zone (altitude is 1,360-1,410m) in Mt. Chiri, was conducted using 25 sample plots of 500$m^2$ size. The classification by TWINSPAN and DCA ordination were applied to the study area in order to classify them into several groups based on woody plants and environmental variables. By TWINSPAN techniques, the plant community were divided into five groups by importance value of Abies nephrolepis. The dividing groups are Fraxinus rhynchophylla - Magnolia sieboldii community, Quercus mongolica - Rhododendron schlippenbachii community, Q. mongolica - F. rhynchophylla - Acer pseudo-sieboldianum community, Q. mongolica- A. nephrolepis- Rh. schlippenbachii community, and A. nephrolepis- Pinus densiflora - Rh. schlippenbachii community. The successional trends of tree species by both techniques seem to be from Q. mongolica to A. nephrolepis in the canopy layer. It was no difference between the stand scores of DCA and environmental variables.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.211-223
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• 2022

This study aims to verify the possibility of using the blog mining to collect public opinion in the field of housing policy, thus, it collected blog posts with the keyword 'Happy Housing', extracted the main keywords from them, and analyzed the public's perception through keyword and word cluster analysis. 137,002 blog posts were used as analysis data from May 2013, when social discussion about happy housing spread, to August 2021, and the words derived by dividing the period into three stages in consideration of major housing policies and data collection were analyzed. The results are as follows. In the keyword analysis, overall, the importance of words related to the location, the number, the size, and the conditions for occupancy of Happy Housing is high. In the first stage, government policy implementation, in the second stage, the application process for Happy Housing, and in the third stage, recruitment notices, occupancy qualifications, and rental conditions are found to be highly important. In cluster analysis, project progress, application process, and project area were drawn as main themes at all stages. In particular, policy implementation and implementation plan in the first stage, occupancy qualification and financial support in the second stage, and policy implementation and occupancy qualification in the third stage were drawn as main themes. These results present the possibility of the blog mining as a method of collecting public opinion by sharing policy-related information, reflecting social issues, evaluating whether policies are delivered, and inferring the public's participation in policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.34-42
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• 2014

This study is a fundamental research to determine the emergency evacuation roads considering road network function and connectivity. First of all, the functional aspects of the road networks are analyzed in the target area, Sejong city, by using degree centrality(DC) and closeness centrality(CC) from GIS based database. Secondly, how network connectivity makes a change in user's travel pattern and travel time and how it affects the whole network are analyzed using TransCAD simulation program. Finally, after performing cluster analysis of index, first and second emergency evacuation roads are determined by judging the characteristics of clusters. The results of this research will be helpful for making a decision to diminish secondary damages when confronting unexpected disasters.