• Journal of Families and Better Life
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• v.20 no.5
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• pp.149-166
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• 2002

In this study, 1 have analyzed the state of the use of information technology by the at-risk children who are residing in Husan metropolitan area. The ultimate goal of this study is to help ensure the healthy development of the children and improve the quality of their lives in this information-oriented society. For this research, 1 surveyed 183 children living in an institution or a low-income family in Busan metropolitan area. The survey questionnaire was designed to obtain information on the respondents, socio-demographic characteristics, computer-related conditions of the immediate and social environments, patterns of computer and Internet use, their experience and degree of so called, Net-generation syndrome, Internet addiction disorder, changes in social and familial life caused by Internet use, and exposure to pornographic materials. The results show that 95.9 % of at-risk children in Husan own a computer, 60.9 % of those computers being Pentium Ⅲ. A majority of the children (74.9 %) are connected to Internet at a high-speed, using such devices as LAN, ADSL or cables. About seventy-six percent of the children have used a PC and Internet less than two years. In other words, a majority of them have not used those for a long period of time. The main results of the research are summarized in the following: There is a significant difference among at-risk children in terms of experiences in computer and Internet use according to their grade levels. There is a gender difference in the amount of time spent on computer and Internet. Boys spend more time every week on computer and Internet than girls do. There is a significant difference in the pattern of computer and Internet use, according to the type of their risk, and grade level. The so-called 'Net Generation Syndrome' is not serious in this group. A majority of the at-risk children think that Internet is more interesting than TV. They hardly shop on Internet, and they don think the advertisements on Internet are a serious problem. Also, unlike many people assumptions, their desire to communicate through on-line chatting was very low. They do not tend to buy computer game programs, and Internet Addiction Disorder was not pronounced among them. The at-risk children rarely had an exposure to pornographic materials in the cyber space. However, the exposure was more frequent for institutionalized children than children in low-income families. These results point to a need for a policy to improve the welfare of at-risk children and guarantee their right to information.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.598-602
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• 2001

Recently, due to the widely use of personal computers and internet, many computer users requested intelligent system that can cope with various types of requirements and user-friendly interfaces. Based on this background, researches on the intelligent agent are now activating in various fields. In this paper, we modeled, designed and implemented an intelligent agent system for pattern classification by adopting intelligent agent concepts. We also investigated the pattern classification method by utilizing some pattern classification algorithms for the common data. As a result, we identified that 300 3-dimensional data are applied to three pattern classification algorithms and returned correct results. Our system showed a distinguished user-friendly interface feature by adopting various agents including graphic agent.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.11-19
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• 2017

The growing use of XML markup language has made amount of heterogeneous. XML documents are widely available in the Web. As the number of applications that utilize heterogeneous XML documents grow, the importance of XML document extraction increases greatly. In this paper, we propose a XML schema conversion technique that converts reusable XML schema from XML documents. We convert the schema graph and we use the reusability pattern list. The converted XML schema is evaluated in terms of cohesion, coupling, and reusability. The converted XML schema could be used to construct databases for various fields where XML is used as an intermediation of data exchange.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.707-713
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• 2003

Convenience and promptness of the internet have been not only making the electronic commerce grow rapidly in case of website, analyzing a navigation pattern of the users has been also making personalization and customization techniques develop rapidly for providing service accordant to individual interestingness. Web personalization and customization skill has been utilizing various methods, such as web log mining to use web log data and web mining to use the transaction of users etc, especially e-CRM analyzing a navigation pattern of the users. In this paper, We measure exact duration time of the users in web page and web site, compute weight about duration time each page, and propose a way to comprehend e-loyalty through the computed weight.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.74-83
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• 2023

In this paper, we propose an image compression scheme which uses a demosaicking network and a channel-wise decoder in the decoding network. For the demosaicing network, we use as the input a colored mosaiced pattern rather than the well-known Bayer pattern. The use of a colored mosaiced pattern results in the mosaiced image containing a greater amount of information pertaining to the original image. Therefore, it contributes to result in a better color reconstruction. The channel-wise decoder is composed of multiple decoders where each decoder is responsible for each channel in the color image, i.e., the R, G, and B channels. The encoder and decoder are both implemented by wavelet based auto-encoders for better performance. Experimental results verify that the separated channel-wise decoders and the colored mosaic pattern produce a better reconstructed color image than a single decoder. When combining the colored CFA with the multi-decoder, the PSNR metric exhibits an increase of over 2dB for three-times compression and approximately 0.6dB for twelve-times compression compared to the Bayer CFA with a single decoder. Therefore, the compression rate is also increased with the proposed method than with the method using a single decoder on the Bayer patterned mosaic image.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.149-161
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• 2023

Internet of Things (IoT) is a relatively new concept that has gained immense popularity in a short period of time due to its wide applicability in making human life more convenient and automated. As an illustration: the development of smart homes, smart cities, etc. However, it is also accompanied by a substantial number of risks and flaws. IoT makes use of low-powered devices, so secure, less time-consuming and energy-intensive transmission (routing) of messages due to the limited availability of energy is one of the many and most significant concerns for IoT developers. The following paper presents a trust-based routing scenario for the Internet of Things (IoT) that exploits the past transmission record from the cupcarbon simulator's log files. Artificial Neural Network is used to quantify knowledge of trust, calculate the value of trust, and share this information with other network devices. As a human behavioural pattern, trust provides a superior method for making routing decisions. If there is a tie in the trust values and no other path is available, the remaining battery power is used to break the tie and make a forwarding decision; this is also seen as a more efficient use of the available resources. The proposed algorithm is observed to have superior energy consumption and routing decisions compared to conventional routing algorithms, and it improves the communication pattern.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.389-400
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• 2001

The Internet Game is widespreaded quickly on web, and there are many kinds of funny games for users to use easily, so that can be applied to ICT(Information Communication Technology)education. In this paper, we provide the analysis on the usage of Internet games for children and teachers that is conducted by the decision tree algorithm, which is one of the popular data mining techniques. The results show the pattern of children's and teachers' usages of Internet games.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.219-234
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• 2009

This paper presents a novel approach for extracting simultaneously human daily activity patterns and discovering the temporal relations of these activity patterns. It is necessary to resolve the services conflict and to satisfy a user who wants to use multiple services. To extract the simultaneous activity patterns, context has been collected from physical sensors and electronic devices. In addition, a context model is organized by the proposed incremental statistical method to determine conflicts and to infer user intentions through analyzing the daily human activity patterns. The context model is represented by the sets of the simultaneous activity patterns and the temporal relations between the sets. To evaluate the method, experiments are carried out on a test-bed called the Ubiquitous Smart Space. Furthermore, the user-intention simulator based on the simultaneous activity patterns and the temporal relations from the results of the inferred intention is demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).