• Journal of KIISE
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• v.42 no.4
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• pp.504-511
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• 2015

Recently, the amount of data is rapidly increasing with the popularity of the SNS and the development of mobile technology. So, it has been actively studied for the effective data analysis schemes of the large amounts of data. One of the typical schemes is a Voronoi diagram based on kNN join algorithm (VkNN-join) using MapReduce. For two datasets R and S, VkNN-join can reduce the time of the join query processing involving big data because it selects the corresponding subset Sj for each Ri and processes the query with them. However, VkNN-join requires a high computational cost for constructing the Voronoi diagram. Moreover, the computational overhead of the VkNN-join is high because the number of the candidate cells increases as the value of the k increases. In order to solve these problems, we propose a MapReduce-based kNN-join query processing algorithm for analyzing the large amounts of data. Using the seed-based dynamic partitioning, our algorithm can reduce the overhead for constructing the index structure. Also, it can reduce the computational overhead to find the candidate partitions by selecting corresponding partitions with the average distance between two seeds. We show that our algorithm has better performance than the existing scheme in terms of the query processing time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1551-1559
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• 2015

Recently, the performance of smart devices is almost similar to that of the existing PCs, thus the users of smart devices can perform similar works such as messengers, SNSs(Social Network Services), smart banking, etc. originally performed in PC environment using smart devices. Although the development of smart devices has led to positive impacts, it has caused negative changes such as an increase in security threat aimed at mobile environment. Specifically, the threats of mobile devices, such as leaking private information, generating unfair billing and performing DDoS(Distributed Denial of Service) attacks has continuously increased. Over 80% of the mobile devices use android platform, thus, the number of damage caused by mobile malware in android platform is also increasing. In this paper, we propose android based malware detection mechanism using time-series analysis, which is one of statistical-based detection methods.We use auto-regressive moving-average model which is extracting accurate predictive values based on existing data among time-series model. We also use fast and exact malware detection method by extracting possible malware data through Z-Score. We validate the proposed methods through the experiment results.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.471-480
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• 2007

Negative emotions play an important function as to human's existence. In this research, we employed the audio-visual film clips to induce negative emotions and examined the classified responses in the autonomic nervous system(ANS) due to each negative emotion.30 adults(22.6 years $old{\pm}1.24$, 15 males and 15 females) took part in this experiment. Through the preliminary experiment, 2 minutes film's stimuli were selected as the emotion-induced stimuli. During the period when participants were viewing and listening to the selected movie, EDA and ECG were examined as soon as one stimulus was displayed, participants were tested by completing the psychological appraisals of their experienced emotion due to each emotional stimulus. With regard to the result of analyzing the psychological responses, each negative emotion appropriately and effectively induced its target emotion. While concerning the result of analyzing ANS responses, each negative emotion induced its respective activation in ANS. What is more, compared with other types of negative emotional stimuli, the scaring stimulus induced higher activation of the sympathetic nervour system(SNS) as to the indexes in EDh and ECG. This research made segmentation of ANS responses to each negative emotion, which has its significance.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.107-113
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• 2016

Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.83-90
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• 2015

This paper examines the rising value of social networked journalism and analyzes the case of a social news site based on the theory of networked journalism. Social networked journalism allows the public to be involved in every aspect of journalism production through crowd-sourcing and interactivity. The networking effect with the public is driving journalism to transform into a more open, more networked and more responsive venue. "wikitree" is a social networking news service on which anybody can write news and disseminate it via Facebook and Twitter. It is operated as an open sourced program which incorporates "Google Translate" to automatically convert all its content, enabling any global citizen with an Internet access to contribute news production and share either their own creative contents or generated contents from other sources. Since its inception, "wikitree global" site has been expanding its coverage rapidly with access points arising from 160 countries. Analyzing its international coverage by country and by news category as well as by the unique visit numbers via SNS, the results of the case study imply that networking with the global public can enhance news traffic to the social news site as well as to specific news items. The results also suggest that the utilization of Twitter and Facebook in social networked journalism can break the boundary between local and global public by extending news-gathering ability while growing audience's interest in the site, and engender a feasible business model for a local online journalism.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.488-498
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• 2015

Form the observation that the successful management and operation of university websites brings about university branding effects, this paper attempts to identify the problems in relation to evaluation elements of university homepages and establish a new evaluation model that allows us to grasp the importance and priority of phased evaluation elements. In particular, we tried to secure the objectivity of the importance of department homepage evaluation elements by using AHP(Analytic Hierarchy Process). Our analysis shows that among 29 evaluation elements of department homepage, mobile service, curriculum, description of department's characteristics, guide to homepage usage/accessibility to site map and differentiated educational method were considered to be relatively important whereas the relative importance of department's slogan, differentiated image and identity, linkage to SNS, Q&A bulletin board, operation of department community, and FAQ was low. Based on the findings from our analysis, we present the basic foundation for successful management and operation of university department homepages along with a few suggestions for vitalizing those hompages.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.35-45
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• 2020

To diversify the agro-food exports of Korea, this study selected Russia, which is located closet to CIS countries, as a sampling area and sought ways to promote the export of Korean hang over drinks to Russia. This study analyzed the contributing factors to the export, such as Russian consumers' purchasing intentions, as well as the willingness to pay of korean hang over drinks in Russia, using the paper review and on-off line survey data correction method. Major results are as follows. First, Russian consumers' intention of purchasing Korean hang over drinks is higher than Europe and the other products. Therefore, it is necessary to understand the demographic characteristics of Russian consumers and then actively use niche marketing strategies. Second, the purchase intention of Russian consumers towards increased when buying behavior occurred in supermarket, hypermarket- and convenience stores. Third, it seems prefer to pricing of Korean hang over drinks in Russian export market similar to the domestic price level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.55-62
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• 2012

In this study, it was observed through the ability of performing secondary tasks and baseline fetal heart rate how the supply of lavender, peppermint and highly concentrated oxygen (40%) affected distraction due to the performance of secondary tasks in the driving environment. Twelve male university students conducted secondary tasks while driving in the environments (6 in total) mixed and designed with oxygen concentration (21%, 40%) and the condition of odors (Normal, Lavender, Peppermint). The test was proceeded in order of stable state (5mins), driving (5mins), and secondary tasks (1min), and by extracting ECG data from every section by 30secs, the mean value of baseline fetal heart rate was calculated. As a result of analysis, in the ability of performing secondary tasks, a percentage of correct answers showed no difference in oxygen concentration and the condition of odors (p > 0.05). In performance completion time, a percentage of correct answers decreased showing a statistically significant difference in the condition of odors compared with the condition where odors were not provided (p < 0.05). As for baseline fetal heart rate, in the comparison between sections, while performing secondary tasks, it increased showing a significant difference compared with stable state and driving state (p < 0.05). The effect of interaction was observed in oxygen concentration and the condition of odors. When odors were not provided, baseline fetal heart rate decreased in 40% oxygen concentration compared with 21% oxygen concentration (p < 0.05), however, when peppermint was provided, it increased in 40% oxygen concentration compared with 21% oxygen concentration (p < 0.05). In conclusion, the fact that the condition of odors increased the ability of calculation, and when only the highly concentrated oxygen was provided, parasympathetic nerve system was activated, however, when highly concentrated oxygen was provided with peppermint at the same time, sympathetic nervous system (sns) was activated, which had a negative effect on the autonomic nervous system was drawn.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.1
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• pp.277-301
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• 2020

The purpose of this study is to analyze art museum websites and derive implications for future operation of art museum websites. To this end, this research collected basic information about art museums according to '2018 National General Report of Cultural Infrastructure' and investigate the websites of 30 art museums through multi-step sampling process. This study analyzed the structure and menu of the art museum websites as well as the current state of various contents provided by the websites and the search service for the collections offered by the websites. Following sentences are the results. First of all, the art museum websites offer 5.6 top menus on average. Secondly, contents related to art museum, exhibitions, news, education, general forum, and SNS are the basic contents that should be provided on the art museum websites. Third, for contents related to news, education, and events have problems with hierarchical structure and need to be adjusted. Fourth, in the content type, specialized information contents are relatively insufficient and thus need to be improved. Fifth, the art museum websites should give sufficient information about the collection and offer directory searching hat includes keyword searching as well as detail searching service. It is also required to reorganize the directory along with the download function for searched results and the sorting service.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.385-393
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• 2013

In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.