• Journal of Digital Convergence
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• v.14 no.6
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• pp.253-261
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• 2016

As many people use internet through the various programs of PC and mobile devices, the possibility of private data leak is increasing. A program should be used after checking security of information flow. Security analysis of information flow is a method that analyzes security of information flow in program. If the information flow is secure, there is no leakage of personal information. If the information flow not secure, there may be a leakage of personal information. This paper proposes a method of analyzing information flow that facilitates SAT solver. The method translates a program that includes variables where security level is set into propositional formula representing control and information flow. The satisfiability of the formula translated is determined by using SAT solver. The security of program is represented through the result. Counter-example is generated if the program is not secure.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.349-357
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• 2016

The purpose of this study is to analyze demands of education training about copyright for Infant and early childhood education institutions. This study investigated demands of education training about copyright for infant and early childhood education institutions targeting 248 directors and teachers. Using a questionnaire, research data was analyzed using the program spss. Demands of education training about copyright for infant and early childhood education institutions appeared differently depending on education institution type, position, education career, etc. copyright training topics include the highest demands for understanding of the copyright associated with the work of the early childhood education. Training contents had higher demands for using typeface(font) and video material. So these results reported that directors and teachers require copyright education relating to the work of Early childhood education. The results of this study suggest the implications for developing and implementing copyright training programs for Infant and Early childhood education institutions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.1
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• pp.26-45
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• 2001

The Flash memory market: is an exciting market that has quickly over the last 10 years. Recently Flash memory provides a high-density. truly non-volatile, high performance read write memory solutions, also is characterized by low power consumption, extreme ruggedness and high reliability. Flash memory is an optimum solution for large nonvolitilc storage operations such as solid file storage, digital video recorder, digital still camera, The MP3 player and other portable multimedia communication applications requiring non-volatility. Regardless of the type of Flash memory, Flash media management software is always required to manage the larger Flash memory block partitions. This is true, since Flash memory cannot be erased on the byte level common to memory, but must be erased on a block granularity. The management of a Flash memory manager requires a keen understanding of a Flash technology and data management methods. Though Flash memory's write performance is relatively slow, the suggested algorithm offers a higher maximum write performance. Algorithms so far developed is not suitable for applications which is requiring more fast and frequent accesses. But, the proposed algorithm is focused on the justifiable operation even in the circumstance of fast and frequent accesses.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.651-661
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• 2014

The complexity to search a specific content over TV platform is drastically increasing. Based on previous studies from computer data management system, we propose a new method that helps users to search and select content effectively. In general, contents over computers are represented by spatial metaphor, which replicates our physical environment and value systems about space. We suggest 3D lattice structure to construct information space for TV platform. Users can infer relevance between contents via special clue in information space, so as to select content more easily. Also, they can search contents through its temporal property that also represented in space. We make full use of our natural capability that can reduce additional overload to learning new interface. The results of this study can be significant and heuristic contributions, as they can be applied to diverse service areas utilizing video contents.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.599-606
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• 2017

'Video Commerce' has grown significantly, and is in the era of so-called V-commerce 2.0. Based on this background, this study focused on the link and the possibility of creating synergy between V-commerce 2.0 content and MCN, and examined the linkage strategy considering its characteristics. In conclusion, first, V-Commerce has evolved into the age of 2.0, centered on the characteristics of content that are oriented towards fun and sympathy, beyond the 1.0 era. Second, V-commerce 2.0 content has the characteristic of replacing the sharing and recommendation based on the nature of SNS networks as promotion and purchase enhancement. Therefore, competitiveness as 'content' is relatively important before 'commerce'. Third, V-commerce 2.0 and MCN industry have a strong connection with each other in terms of securing core competitiveness and creating a new profit model. In order to create the synergy between V-Commerce 2.0 and MCN, we proposed the use of big data to reinforce V-Commerce 2.0 customized content competitiveness, building of storytelling marketing and branding, and enhancement of live performance and interactive communication.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.269-275
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• 2014

The DAB system was designed to provide CD quality audio and data services for fixed, portable and mobile applications with the required BER below $10^{-4}$. However for the T-DMB system with the video service of MPEG-4 stream, BER should go down $10^{-8}$ by adding FEC blocks which consist of the Reed-Solomon (RS) encoder/decoder and convolutional interleaver/deinterleaver. In this paper we propose two types of turbo coded T-DMB system without altering the puncturing procedure and puncturing vectors defined in the standard T-DMB system for compatibility. One(Type 1) can replace the existing RS code, convolutional interleaver and RCPC code by a turbo code and the other one (Type 2) can substitute the existing RCPC code by a turbo code. Simulation results show that two new turbo coded systems are able to yield considerable performance gain after just 2 iterations. Type 2 system is better than type 1 but the amount of performance improvement is small.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.123-128
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• 2012

In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.383-391
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• 2017

The purpose of this study was to examine users' attitude toward likability, understanding level, reliability, satisfaction, and continuous usage intention depending on a difference in a type between card news and straight news. A questionnaire survey was conducted targeting 232 people. As a result of the research, compared to the straight news, the card news was easy for a user to understand, was strong even in a desire to use continuously. Second, a factor of users' attitude toward news was having influence upon the mutually positive(+) direction. Likability, understanding level and reliability had an effect on satisfaction. The satisfaction had an impact again on continuous usage intention. The intensity of this impact was varied, respectively, in card news and straight news. The influential level upon satisfaction in card news was strong in order of likability, understanding level and reliability. The influence in the straight news was strong in order of reliability, likability and understanding level. The outcome of this study will become empirical data in proceeding with seeking a method available for strengthening the function of offering information in news through increasing delivery and impact in information with producing news chosen by consumers.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1142-1149
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• 2004

Motion Estimation(ME) has been developed to reduce temporal redundancy in digital video signals and increase data compression ratio. ME is an Important part of video encoding systems, since it can significantly affect the output quality of encoded sequences. However, ME requires high computational complexity, it is difficult to apply to real time video transmission. for this reason, motion estimation algorithms with low computational complexity are viable solutions. In this paper, we present an efficient method with low computational complexity based on spatial and temporal correlations of motion vectors. The proposed method uses temporally and spatially correlated motion information, the motion vector of the block with the same coordinate in the reference frame and the motion vectors of neighboring blocks around the current block in the current frame, to decide the search pattern and the location of search starting point adaptively. Experiments show that the image quality improvement of the proposed method over MVFAST (Motion Vector Field Adaptive Search Technique) and PMVFAST (Predictive Motion Vector Field Adaptive Search Technique) is 0.01～0.3(dB) better and the speedup improvement is about 1.12～l.33 times faster which resulted from lower computational complexity.