• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1969-1980
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• 2013

The Traffic congestion is caused by the increasing traffic demand. Thus, economic losses have been increasing every year. To solve these problems, car sharing and rental car systems that are equipped with IT technologies emerge. Car sharing has many advantages-the alleviation of the traffic congestion, the saving of maintenance cost for cars, the reduction of car possessiveness, the solution for the hassle of car ownership, for business and personal duty, and the improvement of connectivity between public transportations-. The goal of the car sharing is to achieve low-carbon and eco-friendly transportation. In this study, we review papers related to the car sharing system and the cost system of traffic systems. We estimate the optimal cost of the cloud traffic system that is one of the car sharing services. We suggest a methodology to estimate operational cost and use cost through the analysis of cost system between similar traffic means. The range of the maximum and minimum cost was determined through the comparison and analysis of similar traffic means. Expected demand and the cost that people are willing to pay were estimated through optimized value pricing. The minimum cost per hour that was compared to the cost of rental car was estimated at 5,333 won and the maximum cost per hour that was compared to taxi cost was estimated at 17,700 won. The cost for users was estimated at 6,930 won. The cost of 50% demands was estimated at 6,550won. Future studies should analyze service hours of users, weather, demand pattern and trend and consider them into the cost estimation.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.243-250
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• 2021

Recently, with the development of cloud computing, interest in database outsourcing is increasing. However, when the database is outsourced, there is a problem in that the information of the data owner is exposed to internal and external attackers. Therefore, in this paper, we propose a parallel range query processing algorithm that supports privacy protection. The proposed algorithm uses the Paillier encryption system to support data protection, query protection, and access pattern protection. To reduce the operation cost of a checking protocol (SRO) for overlapping regions in the existing algorithm, the efficiency of the SRO protocol is improved through a garbled circuit. The proposed parallel range query processing algorithm is largely composed of two steps. It consists of a parallel kd-tree search step that searches the kd-tree in parallel and safely extracts the data of the leaf node including the query, and a parallel data search step through multiple threads for retrieving the data included in the query area. On the other hand, the proposed algorithm provides high query processing performance through parallelization of secure protocols and index search. We show that the performance of the proposed parallel range query processing algorithm increases in proportion to the number of threads and the proposed algorithm shows performance improvement by about 5 times compared with the existing algorithm.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.36-42
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• 2016

Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.

• Conservation Science in Museum
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• v.15
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• pp.38-55
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• 2014

Three costumes excavated from the tomb of Yu Gyeongjong ^1565-1623, which are now own at Buyeo National Museum, underwent conservation treatment. As a result of this treatment, the costume types were correctly identified and their original forms were restored. Through the restoration process, various key features were discovered, enabling the costume types to be correctly identified as a dallyeong ^{Official's Uniform with Round Collar}, jingnyeong ^{Coat with Straight Collar}, and changui ^{Coat with Slits in the Rear and Sides}. One of the newly discovered key features was a new variety of pattern that differed from the prevalent cloud pattern of the time. Also, on the dallyeong, it was found that the ground of the hyungbae ^{Rank Badge}, was made from yeongeumsa ^{Wrapped Gold Thread}. These costumes are significant artifacts showing trends, patterns, forms, and other key characteristics of clothing from the late sixteenth to the early seventeenth century.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.373-386
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• 2014

A word cloud is a visualization of word frequency in a given text. The importance of each word is shown in font size or color. This plot is useful for quickly perceiving the most prominent words and for locating a word alphabetically to determine its relative prominence. With dynamic graphics, we can find the changing pattern of prominent words and their frequencies according to the changing selection of chapters in a given text. We can define the word frequency matrix. In this matrix, rows are chapters in text and columns are ranks corresponding to word frequency about the words in the text. We can draw the word frequency matrix plot with this matrix. Dynamic graphic can indicate the changing pattern of the word frequency matrix according to the changing selection of the range of ranks of words. We execute an English Bible text visualization using word clouds and dynamic graphics technology.

• Journal of the Korean Society of Costume
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• v.60 no.6
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• pp.48-61
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• 2010

Pearl gowns(Jeanju-eui)' of Princess Jekukdaejang which were imported from Yuan to Goryeo in 13'th century, but correct shape and detail were unkown. Princess Jekukdaejang was a queen of Goryeo and a daughter of Kublai Khan of early Yuan period, and pearls were the most precious jewel in Mongolia of medieval time. It is possible that the shapes of Jeanju-eui were nomadic mogolian women's costume or very new style yet in early Yuan just like sleeveless long vest. In the period of Yuan, pearls were beaded on the stiff thin fabric for summer or ornaments of ladies. Big pearls were made use of point spot of pattern or line of pattern, and small pearls were usually used to fill up devided parts or to bind outline. The shapes of deducted pearl gown are five kinds of women's deel and four kinds of long vest, and deducted parts for pearl decoration are golden band from shoulder to wrist and on the knees of gown, cloud shape collar, patches on the breast and on the back, slant collar, and patterns of fabric. Red color(the favorite color of Yuan ladies), artifical pearls, ramie, and golden brocade with the gloss of satin are selected as stuffs for sample of pearl gown, but 'reproducting old fabrics' was the most important problem in making correct pearl gowns. Suggested is a cooperation with fabric makers to develop alternate fabircs with patterns just like Yuan's.

• The International Journal of Costume Culture
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• v.2 no.2
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• pp.60-70
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• 1999

The purposes of this study were to investigate preference and images of Korean traditional motifs, and to identify the relationship between them. The subjects consisted of 369 male and 356 female undergraduate students. The experimental materials used in this study were 48 stimuli and a questionnaire composed of 7-point semantic differential scales of 26 adjectives. Twelve motifs selected from 3 groups of Korean motifs were used as pattern design stimuli. Twelve repeated patterns were constructed from them to be applied on a CAD-simulated dress. The data were analyzed by ANOVA, Duncan's multiple range test, and regression. The major findings were as follows : 1. Category, composition type, and application object had a significant effect on the preference. Interpretation type has no significant effects on the preference independently, but it had interaction effects when combined with composition type, and category. Especially the composition type had a greater effect than the other variables on the preference. Cloud motif and its abstract and decorative type were found to be more related to the preference than the other category and interpretation type. On the basis of the analysis results, image charts and preference charts were developed. By combining information from the image chart and preference chart, motifs and images preferred by consumers may be selected and developed into new valuable designs. 2. The preference was affected mainly by 'quality'image followed by 'simplicity', 'interest', and 'modernity'image. The preference on pattern design was affected by 'quality', 'simplicity', 'interest', and 'interest', 'simplicity', and 'modernity'image in the order. The relationship between the preference and sensibility images has been represented by equations.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.86-96
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• 2016

Recently, virtualization is becoming the critical issue in the cloud computing due to its advantages of resource utilization and consolidation. In order to efficiently use virtualization services, several issues should be taken into account, including data reliability, security, and performance. In particular, a high write bandwidth on the virtual machine must be guaranteed to provide fast responsiveness to users. In this study, we implemented a way of visualizing comparison results between the block write pattern of KVM-based virtual machine and that of the real machine. Our final objective is to propose an optimized virtualization environment that enables to accelerate the disk write bandwidth.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• ETRI Journal
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• v.36 no.5
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).