• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.1708-1710
• /
• 2010

무선 네트워크 기반 실내 측위는 측위를 위한 특수 장비를 필요로 하지 않고, Fingerprinting 방식은 무선네트워크 기반 측위를 위한 기술 중에서 가장 정확도가 높기 때문에 무선 네트워크 Fingerprinting 방식이 가장 적당한 실내 측위 방법이다. Fingerprinting 방식에서 KNN은 WLAN 기반 실내 측위에 가장 많이 적용되고 있지만 KNN의 성능은 k개의 이웃 수와 RP의 수에 따라 민감하다. 논문에서는 KNN 성능을 향상시키기 위해 PFCM 군집화를 적용한 KNN과 PFCM을 혼합한 알고리즘을 제안하였다. 제안한 알고리즘은 신호잡음비 데이터를 KNN 방법에 적용하여 k개의 RP를 선택한 후 선택된 RP의 신호잡음비를 PFCM에 적용하여 k개의 RP를 군집하여 분류한다. 실험 결과에서는 위치 오차가 2m 이내에서 KNN/PFCM 알고리즘이 KNN과 KNN/FCM 알고리즘보다 성능이 우수하다.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.6
• /
• pp.949-957
• /
• 2009

The fashion apparel industries have demanded to be extremely consumer-oriented. Therefore, the need of personalization arises. The purpose of this study is to investigate the relationship between apparel shopping orientation and various personalization strategies provided in the apparel shopping process. A total of 422 questionnaires were used for statistical analysis. Canonical correlation and ANOVA were conducted. Results indicated that higher level of demand for "sale-promotion personalization" and "personalized customer relationship" were significantly related to high level of fashion innovativeness and price consciousness. Consumers who seek for high level of "personalized advice" and "personalized fit" were likely to be price conscious and conforming to clothing but not innovative in terms of fashion and clothing. Shopping orientation group differences were also reported in the study. In personalizing of apparel products, distinctive but relevant strategies should be implemented according to the need of the consumers.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.9
• /
• pp.859-872
• /
• 2004

With the rapid advance of computer and communication techonology, the recent trend of education environment is edveloping in the ubiquitous learning (u-learning) direction that learners select and organize the contents, time and order of learning by themselves. Since the amount of education information through the internet is increasing rapidly and it is managed in document in an effective way is necessary. The document clustering is integrated documents to subject by classifying a set of documents through their similarity among them. Accordingly, the document clustering can be used in exploring and searching a document and it can increased accuracy of search. This paper proposes an efficient incremental clustering method for a set of documents increase gradually. The incremental document clustering algorithm assigns a set of new documents to the legacy clusters which have been identified in advance. In addition, to improve the correctness of the clustering, removing the stop words can be proposed.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.779-786
• /
• 2012

The purpose of this study was to segment latent horse riding market. Demographic characteristic, psychological characteristic, lifestyle, and perception of horse riding factor were included in the segmentation basis but, only lifestyle was useful factor for horse riding industry. The statistical techniques for data analysis were descriptive analysis, explanatory factor analysis, confirmatory factor analysis, reliability analysis, cluster analysis, crosstab analysis, and Chi-square analysis. The result showed that sport activity, activity, and passivity factor were identified by lifestyle. The latent market of horse riding had two segment markets. First segment was known as a sport activity oriented group and the other is nonactivity oriented group. According to three demographic variables and preference of horse riding were statistical significant at the level of .05.

• Korean Journal of Construction Engineering and Management
• /
• v.6 no.2 s.24
• /
• pp.102-110
• /
• 2005

After the IMF bailout, the Environment of Domestic Construction Industry had changed dramatically. Before the IMF, Domestic Construction Firms are secured by the government regulations and some traditional practices. However, due to the following reasons: a decrease in public works, an increase in uncertainty of market prediction, the change of bid system, and increase in construction firms, recently the competition among construction firms has became keen. Under the serious competition, in order that medium-size construction firms survive in the construction market, it is need to establish the strategy that could increase productivity. In order to establish the strategy, firstly, construction firms should set up an appraisal standard of construction firms. Consequently, This study will introduce companies' objective appraisal in domestic construction market as well as basal data for setting-up strategy through adaptation industry structure analysis of business administration for strategic group analysis and a company which has lagged behind competitive power among the competitive companies can choose a target strategic group which should be pursued it in the future through being classified according to a group taken analogical strategy.

• Journal of Korea Society of Industrial Information Systems
• /
• v.11 no.1
• /
• pp.77-85
• /
• 2006

In this paper, we propose a hierarchical classifier of object images using neural networks for content-based image classification. The images for classification are object images that can be divided into foreground and background. In the preprocessing step, we extract the object region and shape-based texture features extracted from wavelet transformed images. We group the image classes into clusters which have similar texture features using Principal Component Analysis(PCA) and K-means. The hierarchical classifier has five layes which combine the clusters. The hierarchical classifier consists of 59 neural network classifiers learned with the back propagation algorithm. Among the various texture features, the diagonal moment was the most effective. A test with 1000 training data and 1000 test data composed of 10 images from each of 100 classes shows classification rates of 81.5% and 75.1% correct, respectively.

• Journal of the Korea Institute of Building Construction
• /
• v.19 no.4
• /
• pp.341-350
• /
• 2019

Construction industry is one of the most dangerous industry. As the construction accidents occur due to the repeated factors found in each accidents, there is a limitation in analyzing all types of occupational accidents by the existing descriptive analysis and statistical test. In this study, we classified safety accidents caused by falling objects among the accident types occurring at construction sites into fatal and nonfatal accidents and deduced the factors. In addition, we deduced the association rules among the safety accidents factors caused by falling objects through the association rule analysis method among the machine learning techniques. Therefore, considering the association rules for fatal and nonfatal accidents proposed in this study, it would be possible to prevent accidents by searching for countermeasures against safety accidents caused by falling objects.

• Korea Science and Art Forum
• /
• v.23
• /
• pp.17-26
• /
• 2016

This study was to segment The 2014 Korean Medicine-Bio Fair visitors based on fair quality factors. From the on-site survey at the destination, a total of 308 useful sample were collected and analyzed in SPSS 21.0. From factor analysis, the result shows 5 quality types of 'fair product', 'convenient facilities', 'accessibility', 'promotional information' and 'contents.' Also Three different segmented groups were derived form clusters analysis, which are 'accessibility preference group', 'promotion preference group', and 'high quality preference group.' The result of this study indicated that there were significant differences in demographic, satisfaction and behavioral variables between these three segments. More theoretical and practical implication were discussed in the conclusion section.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.3
• /
• pp.123-130
• /
• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• Journal of Technology Innovation
• /
• v.23 no.3
• /
• pp.225-253
• /
• 2015

The standard is a nation's one of the most important industrial issues that improve the social and economic efficiency and also the basis of the industrial development and trade liberalization. This research analyzes the enactment and the utilization of Korean industrial standards(KS) of various industries. This paper examines Korean industries' KS utilization status based on the KS possession, enactments and inquiry records. First, we implement multidimensional scaling method to visualize and group the KS possession records and the nation's institutional issues. We develop several hypothesis to find the decision factors of how each group's KS possession status impacts on the standard enactment activities of similar industry sectors, and analyzes the data by implementing regression analysis. The results show that the capital intensity, R&D activities and sales revenues affect standardization activities. It suggests that the government should encourage companies with high capital intensity, sales revenues to lead the industry's standard activities, and link the policies with the industry's standard and patent related activities from R&D. Second, we analyze the impacts of each KS data's inquiry records, the year of enactments, the form and the industrial segment on the utilization status by implementing statistical analysis and decision tree method. The results show that the enactment year has significant impact on the KS utilization status and some KSs of specific form and industrial segment have high utilization records despite of short enactment history. Our study suggests that government should make policies to utilize the low-utilized KSs and also consider the utilization of standards during the enactment processes.