• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.101-106
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• 2018

The purpose of this study is to analyze the patterns of unconsciousness smartphone use by using an app and a self-administered survey on smartphone addiction comparatively and examine differences between recognition and behavior about actual smartphone use and examine how smartphone addiction influences learning. With an app installed in smartphones, this author collected and analyzed data about users' unconsciousness using patterns for a month. According to the results, there were significant differences found in users' recognition and actual time for use and also frequency of turning on the display. Also, 22% of the subjects used their smartphone over 8 hours a day, and 76% more than 5 hours. Over 95% turned on the display more than 100 times a day, and in extreme cases, they did more than 300 times. In the meantime, users not only in the smartphone addiction high risk group and the potential risk group but also in the general user group are found to use their smartphone too long and too much and frequently turn on the display. The apps that the general user group is mainly using are entertaining apps, and their school records are rather good, so excessive use does not always lead to addiction or learning disorder. Therefore, if we develop more diverse contents for learning and provide digital literacy education, smartphone use will bring more positive effects instead. In follow-up research, the app should be corrected to collect more accurate information, and as variables in personal areas, this researcher will also measure depression, anxiety, stress, self-esteem, and emotional control, and so on to see how they are associated with smartphone use.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.3
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• pp.51-68
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• 2020

The library provides its services to satisfy the user's approach. Naturally, the development of library services may determine by considering the satisfaction of users. It traces users' perceptions regarding subject access highlighting problems in the retrieval of Bengali documents by subject. This study has designed to assess users' attitudes towards the retrievals of Bengali documents in OPAC through subject headings. For a collection of data, a representative sample has drawn from a large and heterogeneous population consisting of users in university libraries of West Bengal using a stratified sampling technique. Subsequently, under each of the universities, users' community was stratified into students, research scholars, and faculty members. Under each stratum, the sample selected on a random basis. The users met personally to collect relevant data, while they came to the library and went on to search OPAC. A structured schedule, prepared for the purpose, was presented before library users and consequently, interviews and interpretations recorded systematically. In this manner, several factors have identified concerning subject searching and retrieval performance for Bengali documents. This study explores the access using subject headings in multilingual information retrieval systems. Moreover, the suitability of subject headings for retrieval of Bengali resources has ascertained from the users' point of view. The findings demand standard principles and rules for the construction of Bengali subject headings to maintain uniformity and consistency.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.138-145
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• 2010

In this paper, we consider the information processing system, which organizes the collected data to meaningful information when the number of data collected from multiple sources reaches to a predetermined number, and performs any action by processing the collected data, or transmits to other devices or systems. We derive an analytical model to calculate the time until it takes to process information after starting to collect data. Therefore, in order to complete the processing data within certain time constraints, we develop some design criteria to control various parameters of the information processing system. Also, we analyze the discrete time model for packet switching networks considering data with no particular arrival nor drop pattern. We analyze the relationship between the number of required packets and average information processing time through numerical examples. By this, we show that the proposed model is able to design the system to be suitable for user's requirements being complementary the quality of information and the information processing time in the system with time constraints.

• Convergence Security Journal
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• v.11 no.6
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• pp.3-8
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• 2011

Advanced Persistent Threat (APT), aims a specific business or political targets, is rapidly growing due to fast technological advancement in hacking, malicious code, and social engineering techniques. One of the most important characteristics of APT is persistence. Attackers constantly collect information by remaining inside of the targets. Enterprise Security Management (EMS) system can misidentify APT as normal pattern of an access or an entry of a normal user as an attack. In order to analyze this misidentification, a new system development and a research are required. This study suggests the way of forecasting APT and the effective countermeasures against APT attacks by categorizing misidentified data in data-mining through threshold ratings. This proposed technique can improve the detection of future APT attacks by categorizing the data of long-term attack attempts.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.135-150
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• 2016

As the privacy issues are all around the world, the intrusion into personal privacy is concerning. For that reason, government established the article from the personal information protection law that has to notice the privacy policy to users on the online site. and the matter of privacy invasion make concern toward behavior of online user. Although there are rules to carrying legal binding force in accordance with, because it is full of text and uncomfortable to read so that its readability is low. In the same context, each other has different state of understanding with the policy for personal information has been playing an important role. In this approach, companies and government do not think this over deeply and do just for what their practical use is. That is the reason why this research start, and the result expecting for real. As the result in the participant who cognize the privacy policy display pattern, they have certain type to do. In this article, the certain behavior doing is remarkable with the privacy policy. According to privacy concern, privacy fundamentalist reveals such a compromise reaction to protect their information when they know what information which the privacy manager of service provider collect. This study arrives at the result depending on the gap of privacy group that the group of checking the policy contents, especially the group which has high privacy concern, they move forward to protect their emotion and put a constructive plan into protective action. Otherwise, the group of unchecking the policy contents and following their own thinking of privacy policy are not deemed statistically significant. Therefore, this is considered to support more various implications than the previous issues and alternatives about privacy policy pattern and user protection behavior of privacy.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.141-148
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• 2017

The current advancement of mobile devices enables users to collect a sequence of user positions by use of the positioning technology and thus the related research regarding positioning or location information are quite arising. An individual mobility model based on positioning data and time data are already established while group mobility model is not done yet. In this research, group mobility model, an extension of individual mobility model, and the process of establishment of group mobility model will be studied. Based on the previous research of group mobility model from two individual mobility model, a group mobility model with more than two individual model has been established and the transition pattern of the model is represented by Markov chain. In consideration of real application, the computing time to establish group mobility mode from huge positioning data has been drastically improved by use of GPGPU comparing to the use of traditional multicore systems.

• 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 agricultural medicine and community health
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• v.15 no.2
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• pp.118-129
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• 1990

Socioeconomic status in this county progressed rapidly, this has brought about many changes in health care fields, namely, pattern of disease prevalence and morbidity, increase of the aged people, and also availability of health care in rural areas. According to the utilization study of medical care, it showed that the oriental medicine is used for the treatment of lasted chronic disease not the minor and common diseases which is quick in its effect. Particularly, in rural areas. prevalence of chronic disease is higher than that in urban areas. Although the health cafe need of the oriental medicine is high in rural areas, the distribution of manpower and facilities is lower than that in urban areas. Therefore the government has planned to implement the demonstration project for the oriental medicine at the designated 3 health centers in rural areas. The purpose of this study was to collect the utilization level of oriental medical care of the people in rural areas. To meet the purpose of this study, patient interview were applied. 790 patients visited to health center in project areas were selected and analyzed by experienced interviewers from 2 April to 21 April 1990. The major findings of this study were as follows ; 1) Of the 790 patients, 32.6 percent of the respondents had experience of using the oriental medicine. As for the utilization by age and sex. 54.8% of those was female and 70.7% was 40 years of age and more. 2) Reaction to the question of educational achievement showed that on schooling and primary school graduates accounted for 63.1%. 3) The most user of oriental medicine resides in country level, where the health center is located, and 80 percent of those users resides within 10Km. 4) More than 50% of the total was the chronic diseases which lingered for more than 3months. 5) 32.6 percent of the total cases used the oriental medicine. 61.2% among those was treated by oriental medical care hospital and 38.8% by oriental drug dispensaries etc. 6) The contont of oriental medical care varied ; 50.1% for prescription of herb drugs for treatment, 25.1% for health maintenance and 23.9% for acupuncture, moxibustion etc. 7) As for the motivation for using the oriental medicine. 56.6% of the respondents was for treatment of diseases and 27.9% wes for strengthening the physical weakness. 8) As for the effectiveness of the oriental medicine. 70.3% of the total cases satisfied with that treatment and 84.2% of the total cases will use the oriental medicine when is provided by health center.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.1-6
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• 2020

In this study, we propose an association inference model based on data bias optimization for road hazard detection. This is a mining model based on association analysis to collect user's personal characteristics and surrounding environment data and provide traffic accident prevention services. This creates transaction data composed of various context variables. Based on the generated information, a meaningful correlation of variables in each transaction is derived through correlation pattern analysis. Considering the bias of classified categorical data, pruning is performed with optimized support and reliability values. Based on the extracted high-level association rules, a risk detection model for personal characteristics and driving road conditions is provided to users. This enables traffic services that overcome the data bias problem and prevent potential road accidents by considering the association between data. In the performance evaluation, the proposed method is excellently evaluated as 0.778 in accuracy and 0.743 in the Kappa coefficient.