• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.542-551
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• 2009

We proposed the context based user profile which is aware of its user's situation and based on user's situation it recommends personalized services. The user profile which consists of (context, service) pair can be acquired by the context and the service usage of a user; it then can be used to recommend personalized services for the user. In this paper, we show how they can be evolved without previously known user information so that not to violate privacy during the learning phase; in the result our user profile can be applied to any new environment without any modification to model only except context profiles. Using context-awareness based user profile, the service usage pattern of a user can be learned by the union of contexts and the preferred services can be recommended by the current environments. Finally, we evaluate the precision of proposed approach using simulation with data sets of UCI depository and Weka tool-kit.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.744-752
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• 2012

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.85-90
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• 2014

In this paper, we propose a virtual violin implementation using the detection of bowing and finger dropping position from the estimated finger tip and finger board information with the 3D image data from a Kinect. Violin finger board pattern and depth information are extracted from the color image and depth image to detect the touch event on the violin finger board and to identify the touched position. Final decision of activated musical alphabet is carried out with the finger drop position and bowing information. Our virtual violin uses PC MIDI to output synthesized violin sound. The experimental results showed that the proposed method can detect finger drop position and bowing detection with high accuracy. Virtual violin can be utilized for the easy and convenient interface for a beginner to learn playing violin with the PC-based learning software.

• MALSORI
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• no.4
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• pp.20-30
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• 1982

The aim of this paper is to analyse difficulties of the pronunciation in swedish vowels encountered by Koreans learners and to seek solutions in order to correct the possible errors. In the course of the analysis the swedish and Korean vowels in question are compared with the purpose of describing differences aha similarities between these two systems. This contrastive description is largely based on the students' articulatory speech level ana the writer's auditory , judgement . The following points are discussed : 1 ) Vowel length as a distinctive feature in Swedish compared with that of Korean. 2) A special attention is paid on the Swedish vowel [w:] that is characterized by its peculiar type of lip rounding. 3) The six pairs of Swedish vowels that are phonologically contrastive but difficult for Koreans to distinguish one from the other: [y:] ~ [w:], [i:] ~ [y:], [e:] ~ [${\phi}$:], [w;] ~ [u:] [w:] ~ [$\theta$], [$\theta$] ~ [u] 4) The r-colored vowel in the case of the postvocalic /r/ that is very common in American English is not allowed in English sound sequences. The r-colored vowel in the American English pattern has to be broken up and replaced hi-segmental vowel-consonant sequences . Korean accustomed to the American pronunciation are warned in this respect. For a more distinct articulation of the postvocalic /r/ trill [r] is preferred to fricative [z]. 5) The front vowels [e, $\varepsilon, {\;}{\phi}$) become opener variants (${\ae}, {\;}:{\ae}$] before / r / or supradentals. The results of the analysis show that difficulties of the pronunciation of the target language (Swedish) are mostly due to the interference from the Learner's source language (Korean). However, the Learner sometimes tends to get interference also from the other foreign language with which he or she is already familiar when he or she finds in that language more similarity to the target language than in his or her own mother tongue. Hence this foreign language (American English) in this case functions as a second language for Koreans in Learning Swedish.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.81-88
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• 1996

Cluster analysis is based on partitioning a collection of data points into a number of clusters, where the data points in side a cluster have a certain degree of similarity and it is a fundamental process of data analysis. So, it has been playing an important role in solving many problems in pattern recognition and image processing. For these many clustering algorithms depending on distance criteria have been developed and fuzzy set theory has been introduced to reflect the description of real data, where boundaries might be fuzzy. If fuzzy cluster analysis is tomake a significant contribution to engineering applications, much more attention must be paid to fundamental questions of cluster validity problem which is how well it has identified the structure that is present in the data. Several validity functionals such as partition coefficient, claasification entropy and proportion exponent, have been used for measuring validity mathematically. But the issue of cluster validity involves complex aspects, it is difficult to measure it with one measuring function as the conventional study. In this paper, we propose four performance indices and the way to measure the quality of clustering formed by given learning strategy.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.886-895
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• 2018

In this paper, we introduce a technique to detect the video forgery by using the regularity that occurs in the video compression process. The proposed method uses the hierarchical regularity lost by the video double compression and the frame deletion. In order to extract such irregularities, the depth information of CU and TU, which are basic units of HEVC, is used. For improving performance, we make a depth map of CU and TU using local information, and then create input data by grouping them in GoP units. We made a decision whether or not the video is double-compressed and forged by using a general three-dimensional convolutional neural network. Experimental results show that it is more effective to detect whether or not the video is forged compared with the results using the existing machine learning algorithm.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.100-105
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• 2019

As IoT Technology develops and Era of Hyperconnectivity comes, various kinds of customized services became available. As a next-generation display, a smart mirror accesses multimedia devices and provides various services, so it can serve as a social learning tool for the children and the old ones, as well as adults who need information. Smart Mirror must be able to identify users for individualized services. However, since the Smart Mirror is an easily accessible device, there is a possibility that information such as an individual's pattern and habit stored in the smart mirror may be exposed to the outside. Also, the other possibility of leakage of personal location information is through personal schedule or appointment stored in the smart mirror, and another possibility that privacy can be violated is through checking the health state via personal photographs. In this research, we propose a system that identify users by the information the users registered about their physique just like their face, one that provides individually customized service to users after identifying them, and one which provides minimal information and service for unauthenticated users.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.207-223
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• 2019

This study aims to explore the casual relation between construction company employees' Self-Leadership and two variables: Organization Citizenship Behaviour and Organizational Trust through Psychology Empowerment. To explain in details, this study examines how the independent variable, Self Leadership, with its behavior-focused, natural reward and constructive thought pattern strategies, affects the dependent variable, Organization Citizenship Behavior and Organizational Trust through the intervening variable, Psychology Empowerment. A survey was conducted on current employees of construction companies in metropolitan areas to empirically examine the research model. The result of study hypothesis on Self-Leadership is as follows; first, Self-Leadership showed a positive effect on Psychology Empowerment, Organization Citizenship Behaviour and Organizational Trust. Second, Psychology Empowerment showed a positive effect on Organization Citizenship Behaviour. Third, Psychology Empowerment showed a positive effect on Organizational Trust. The capacity of individuals is critical when it comes to competitiveness of construction companies. When employees willingly participate in building trust within the company, the work place will become more and more constructive; based on trust, efficiency will increase because people from different processes can work together and performance will also improve even when project managers are absent because others could help their role instead, thus driving more efficient human resource management to the company. To conclude, a company's vision can be spread wide and far when their employees engage themselves in Learning Organization with Self Leadership. They will also be satisfied with their work through improving interpersonal relationship at work.

• Korean Journal of Childcare and Education
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• v.17 no.3
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• pp.65-87
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• 2021

Objective: This study aimed to examine the effects of maternal monitoring, shared activities with children, maternal education-oriented behavior, and allowing children to own smart-phones on smart media usage patterns based on smart-phone usage time and purposes among elementary school children. Methods: The participants were 1,315 second-grade elementary school children from the 9th wave of PSKC. Latent profile analysis and the three-step estimation approach were used to examine the determinants of the latent profile and the effects of maternal parenting on the profile. Results: Four latent profiles were identified: 'High-level usage & Entertaining oriented,' 'Moderate-level usage & Social/entertaining oriented,' 'Moderate-level usage & Learning oriented,' and 'Low-level usage.' Additionally, results showed that each profile can be predicted by maternal monitoring, education-oriented behavior, and permitting children to own smart-phones. Conclusion/Implications: Our outcomes suggested that it would be necessary to understand the smart media usage patterns of elementary school children, considering both the amount of time spent with smart media and purposes of uses. Further, it is helpful for mothers to monitor children's daily activities, support their educational activities, and take the role of gatekeeper for smart media as a way of appropriate guidance for their children's use of smart media.