• 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.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.253-267
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• 2016

The world's major cities operate public rental bicycle systems to complement the existing problems of public transport in the city. Disclosing the rental history data in Daejeon has opened new analytical possibilities. In this paper, we proposed a method to analyze the data using the visualization. We found a positional feature of the station according to the bicycle usage. In addition, we examined the bicycle usage patterns according to the time/day/month. On the other hand, the usage patterns between each of the bicycle stations were identified through a path analysis. The specific objectives were identified through each stop destination ratio analysis. Based on these data, we suggest a direction of Daejeon public bicycle rental system development.

• Journal of Environmental Impact Assessment
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• v.29 no.2
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• pp.122-131
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• 2020

Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.875-883
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• 2015

The purpose of this study was to examine the differences by gender in influence recognition, usage, convenience and preference on purchase intention for traditional Korean rice cake. For this study, the effect of the gender-based consumption patterns-degree of recognition, usage, convenience, and preference towards the traditional Korean rice cake-on purchasing intention was investigated among the university students in Busan area. Of the entire students, 47.5% were male and 52.5% female; 51.0% had less than \5,000,000 and 49.0% had \5,000,000 or more in household income level per month; and 46.0% live with parent(s) whereas 54.0% by themselves. The findings showed that consumption patterns lie between 4.0 and 6.0 in Likert-type 7-point scale. It showed differences by gender in all of the degree of recognition, usage, convenience, and preference.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.97-110
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• 2004

As modem web services become enormously complex, web attacks has become frequent and serious. Existing security solutions such as firewalls or signature-based intrusion detection systems are generally inadequate in securing web services, and analysis of raw web log data is simply impractical for most organizations. Visual display of "interpreted" web logs, with emphasis on anomalous web requests, is essential for an organization to efficiently track web usage patterns and detect possible web attacks. In this paper, we discuss various issues related to effective real-time visualization of web usage patterns and anomalies. We implemented a software tool named SAD (session anomaly detection) Viewer to satisfy such need and conducted an empirical study in which anomalous web traffics such as Misuse attacks, DoS attacks, Code-Red worms and Whisker scans were injected. Our study confirms that SAD Viewer is useful in assisting web security engineers to monitor web usage patterns in general and anomalous web sessions in particular.articular.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.295-313
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• 2019

The purpose of this study is to analyze library space use patterns through users' smartphone WiFi. This study is applied a method to detect WiFi signal of users' smartphone to analyze the in-library wayfinding of users. The library usage data were collected for four months in a library in Seoul, Korea. The results show that the average 37.9% of library users revisits the library the next month. Half of users stay under 7 minutes in the library. Users mainly visit the library between 2 and 3 o'clock, and few users visit the library after 5 pm on weekends. The floor moving pattern result shows that the co-visit rate between the third and fourth floor is higher than others, in that these two floors are mainly composed of book shelves. These results indicate that the method to detect the WiFi signal for spatial pattern analysis could be more effective than observation which was used in previous research. It, therefore, is expected that this method would be applied in other libraries to analyze and enhance the library space usage.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.6
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• pp.283-292
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• 2015

A model of apartment heating load in a district heating system could be useful in the management and utilization of energy resources, since it could predict energy usage and so could assist in the efficient use of energy resources. The heating load in a district heating system varies in a highly nonlinear manner and is subject to many different factors, such as heating area, number of people living in that complex, and ambient temperature. Thus there are few published papers with accurate models of heating load, especially in domestic literature. This work is concerned with the modeling of apartment heating load in a district heating system in winter, using the reduced least square support vector machine (LS-SVM), and with the purpose of using the model to predict heating energy usage in domestic city area. We collected 23,856 pieces of data on heating energy usage over a 12-week period in winter, from 12 heat exchangers in five apartments. Half of the collected data were used to construct the heating load model, and the other half were used to test the model's accuracy. The model was able to predict the heating energy usage pattern rather accurately. It could also estimate the usage of heating energy within of mean absolute percentage error. This implies that the model prediction accuracy needs to be improved further, but it still could be considered as an acceptable model if we consider the nonlinearity and uncertainty of apartment heating energy usage in a district heating system.

• Journal of the Korean Dietetic Association
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• v.11 no.4
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• pp.440-448
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• 2005

This study explores some basic issues behind adults' seeking and using patterns of alternative medicine as well as health food (health food/medicine). In order to do this, 791 adult participants in Seoul and Busan were interviewed face-to-face. The results of the survey showed that 1) interpersonal influence was the most influential factor in relation to the adoption of health food/medicine(46.9% of the participants reported on the influences), 2) keeping healthy was the main motivation for the usage of health food/medicine(34.5% of the participants), 3) mass media was the important information source for health food/medicine, 4) with regard to trustworthiness of information sources, experts were believed to be the most trustworthy while information from acquaintances were thought less, and finally, 5) pharmacies and health food stores were main suppliers of health food/medicine. This study suggests some marketing strategies for health food/medicine. For example, it can be suggested that interpersonal communication among other information channels should be focused and might be increased trust by using professionals.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.300-306
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• 2011

In this paper, we suggest a usage profiles for electric home appliances. In Korea, it is published the records for total consumption of electricity in a house but the electric home appliance consumption records in a households are not. To build the data, we must collect the usage of every appliances in a house and the information of the household which live in the house. Unfortunately, it is hard to get the data because of the worry about the breach of privacy. In this paper, we make a scenarios on the electricity consumption pattern of a few households type. Based on the conjecture, we make the power consumption profiles for some home appliances. Comparison to the total electric consumption records for a house, we found our scenarios are quite reasonable.

• Journal of Global Scholars of Marketing Science
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• v.15 no.2
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• pp.203-225
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• 2005

The purpose of this study is to supply basic marketing information and establish marketing strategy on local market by analyzing related using behavior of lifestyle type and buying behaviour of local residents. On this viewpoint, we focused on identifying the lifestyle, shopping behaviour, and media usage pattern. For this research, we surveyed consumers living in Jecheon city and analyzed questionnaires by multivariate statistical analysis. Through empirical analysis, we derived overall lifestyle profiles including demographic traits, media usage, leisure pattern in each lifestyle types and marketing implications.