• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.523-532
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• 2013

Since conventional methods for the reconstruction of 3D objects used a number of cameras or pictures, they required specific hardwares or they were sensitive to the photography environment with a lot of processing time. In this paper, we propose a 3D object reconstruction method using one photograph based on structured light in ubiquitous environments. We use color pattern of the conventional method for structured light. In this paper, we propose a novel pipeline consisting of various image processing techniques for line pattern extraction and matching, which are very important for the performance of the object reconstruction. And we propose the optimal cost function for the pattern matching. Using our method, it is possible to reconstruct a 3D object with efficient computation and easy setting in ubiquitous or mobile environments, for example, a smartphone with a subminiature projector like Galaxy Beam.

• The Journal of Information Systems
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• v.27 no.2
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• pp.1-28
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• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1675-1686
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• 2011

We propose a spectrally efficient relaying scheme with multiple antennas for cellular networks which consist of base station (BS), relay station (RSs), and mobile stations (MSs). In general, a BS has more antennas than an RS or an MS. By using multiple antennas, a BS can support another MS with the same frequency resource, where an RS transmits data to a specific MS. In this case, the MS receiving data form an RS also receives the interference form the BS because the BS also uses the same frequency resource at the same time. In this paper, we propose ing and pre-whitening techniques as a pre-coding scheme at the BS for reducing the interference at the MS receiving data from the RS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.693-696
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• 2008

The systems for mobile communication services of fourth generation use OFDM (Orthogonal Frequency Division Multiplexing) scheme that ran transmit large amounts of data to support the multimedia services, and consist of several types of cell, such as Macro Cell, Pico Cell, Femto Cell to improve the qualify of service. According to subdivision of communication region, superposition of cells in co-channel different from conventional single cell is used, but it cause inter band interference between systems. In particular, an OFDM signal consists of a number of independently modulated subcarriers, and superposition of these subcarriers causes a problem that ran give a large PAPR. Increased PAPR induces signal distortion passing through components such as power amplifier so that inter band interference is caused by out-of-band spectrum radiation. In order to minimize the inter band interference, this paper applies PAPR reduction scheme and analyzes the out-of-band spectrum radiation when the signal passes through nonlinear components such an power amplifier.

• The Journal of the Convergence on Culture Technology
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• v.2 no.1
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• pp.93-98
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• 2016

As information technologies are rapidly developed recently, social networking services through a variety of mobile devices and smart screen is becoming popular. SNS is a social networking based services which is online forms from existed offline. SNS can also be used differently which is confused with the online community. A modelling algorithm is a variety of techniques, which are assocoation, clustering, neural networks, and decision trees, etc. By utilizing this technique, it is necessary to study to effectively using the large number of materials. In this paper, we evaluate in particular the performance of the algorithm based on the results of the clustering using Facebook Insights data for the EM algorithm to be evaluated as a good performance in clustering. Through this analysis it was based on the results of the application of the experimental data of the change and the South Australian state library according to the performance of the EM algorithm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2179-2187
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• 1999

To privide multimedia mobile communication services for the users in scattered locations, the application ATM cells efficiently in wireless communications, it is effective to the use TDMA method. However, it is necessary to have methods to compensate the CDV(cell delay variation) caused by the difference between TDMA-ATM and cell stream multiplexing of the users. This paper optimizes the cell control time(Tc) when VBR traffic inputs have MMPP by applying CDV characteristics of time stamp method, which has the most advantages among compensation methods of CDV. This paper suggests a cell stream multiplex method employing time stamp techniques to reduce CDV for wireless suggest method shows that CDV distribution and cell stream multiples rangd can be controlled to 1.2${\times}$Tc which reduced over the VBR service in the TDMA-WATM transmission. This paper also presents evaluation of the suggested architecture obtained simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1838-1847
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• 1994

Until recently, they decided the standard of the digital mobile communication speech coding method and competively developed the more detailed techniques in North America, Europe, Japan, etc. But, we have not yet determined. In this paper, we compared the RPE-LTP speech coding algorithm, standard in Europe, with the VSELP speech coding algorith, standard in North America, with respect to the soruce coding. We described the comprehensive verification and comparison with each speech coder, and discussed the improvement plan. Next, we also compared the number of computations which affects the real time processing seriously. Moreover, we performed the simulation with the Korean speech data, concreting the algorithm of each speech coder. Finally, we compared the performance of each speech coder with segmental SNR and 5-point MOS. The number of computations was calculated, and the result was that the number of multiplication computing times of VSELP speech encoder was the largest. With 26 speech data, the segmental SNR of VSELP was calculated larger than that of RPE-LTP. The 5-point MOS test was performed, and the result was that the basic speech quality of VSELP was equivalent or better than that of RPE-LTP.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.95-99
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• 2010

Spatial information systems have developed in order to provide users with customized land information in u-City environments. The spatial information systems can detect spatial information for users anytime anywhere. Information which is analyzed by data mining techniques can be offered for other users. Therefore, we propose open map API-based prototype which utilizes frequent pattern mining technique. Proposed prototype can mine interesting trip routes and unknown attractions in location data of geophoto. Also, proposed prototype is the first attempt which analyzes spatial patterns can be represented on a map which is selected by users. Our prototype can be applied to the smart phone like mobile devices.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3176-3182
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• 2009

The PBNM on MANET is being researched to ensure the reliability and efficiency between mobile nodes. Therefore, it is essential to determine the cluster effectively which will perceive the movements of nodes and distribute the policies. In PBNM mechanism, to determine the node cluster for PDP and manage PEP nodes, Active PDP Discovery Protocol is proposed as a mechanism which is more efficient than preexistent techniques. While k-hop cluster selects the PEP nodes which PDP node manages, Active PDP Discovery actively selects the PDP node among the moving PEP node. This method prevents orphan nodes that are not connected to PDP and reduces continual broadcasting messages. This paper implements Active PDP Discovery which determines cluster in the real networks and analyzes its capability, expanding COPS-PR to detect the movement of nodes and adding MNL to PDP node.