• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.71-75
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• 2013

Recently proliferating heterogeneous multimedia service environments should be able to deal with many different transmission speeds, image sizes, or qualities of video. However, not many existing video compression standards satisfy those necessities. To satisfy the functional requirements, the standardization of the H.264/AVC Scalable Extension (SE) technique has been recently completed. It is an extension of the H.264/AVC which can encode several image sizes and qualities at the same time as a single bitstream. To perform optimum mode decision, motion estimation is performed for all MB modes, and the RD costs are compared to identify an MB mode with the smallest RD cost. This increases computational complexity of H.264/AVC SE encoding. In this paper, we propose an early skip mode detection scheme to reduce candidate modes and suggest an algorithm of fast mode decision utilizing reference modes according to the mode history.

• Progress in Medical Physics
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• v.28 no.4
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• pp.164-170
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• 2017

One of the methods to consider the effect of respiratory motion of a tumor target in radiotherapy is to establish a treatment plan with the internal target volume (ITV) created based on an accurate analysis of the target motion displacement. When this method is applied to intensity modulated radiotherapy (IMRT), it is expected to yield a different treatment dose distribution under the motion condition according to the IMRT method. In this study, we prepared ITV-based IMRT plans with conventional IMRT using fixed gantry angle beams, RapidArc using volumetric modulated arc therapy, and tomotherapy using helical therapy. Then, the variation in dose distribution caused by the target motion was analyzed by the dose measurement in the actual motion condition. A delivery quality assurance plan was prepared for the established IMRT plan and the dose distribution in the actual motion condition was measured and analyzed using a two-dimensional diode detector placed on a moving phantom capable of simulating breathing movements. The dose measurement was performed considering only a uniform target shape and motion in the superior-inferior (SI) direction. In this condition, it was confirmed that the error of the dose distribution due to the target motion is minimum in tomotherapy. This is thought to be due to the characteristic of tomotherapy that treats the target sequentially by dividing it into several slices. When the target shape is uniform and the main target motion direction is SI, it is considered that tomotherapy for the ITV-based IMRT method has a characteristic which can reduce the dose difference compared with the plan dose under the target motion condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2827-2848
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• 2012

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.41-53
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• 2002

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. According to the regions and consecutive durations, optimal design rainfalls were derived by the regional frequency analysis for L-moment in the second report of this project. Using the LH-moment ratios and Kolmogorov-Smirnov test, the optimal regional probability distribution was identified to be the Generalized extreme value (GEV) distribution among applied distributions. regional and at-site parameters of the GEV distribution were estimated by the linear combination of the higher probability weighted moments, LH-moment. Design rainfall using LH-moments following the consecutive duration were derived by the regional and at-site analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design rainfall were computed and compared in the regional and at-site frequency analysis. Consequently, it was shown that the regional analysis can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than at-site analysis in the prediction of design rainfall. Relative efficiency (RE) for an optimal order of L-moments was also computed by the methods of L, L1, L2, L3 and L4-moments for GEV distribution. It was found that the method of L-moments is more effective than the others for getting optimal design rainfall according to the regions and consecutive durations in the regional frequency analysis. Diagrams for the design rainfall derived by the regional frequency analysis using L-moments were drawn according to the regions and consecutive durations by GIS techniques.

• Journal of KIISE
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• v.44 no.8
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• pp.832-841
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• 2017

Bug reports are essential documents for developers to localize and fix bugs. These reports contain information regarding software bugs or failures that occur during software operation and maintenance phase. Information Retrieval-based Bug Localization (IR-BL) techniques have been proposed to reduce the time and cost it takes for developers to resolve bug reports. However, if a low-quality bug report is submitted, the performance of such techniques can be significantly degraded. To address this problem, we propose a quality prediction method that selects low-quality bug reports. This process; defines a Quality property of a Bug report as a Query (Q4BaQ) and predicts the quality of the bug reports using machine learning. We evaluated the proposed method with 3 open source projects. The results of the experiment show that the proposed method achieved an average F-measure of 87.31% and outperformed previous prediction techniques by up to 6.62% in the F-measure. Finally, a combination of the proposed method and traditional automatic query reformulation method improved the MRR and MAP by 0.9% and 1.3%, respectively.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.458-465
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• 2013

The purpose of this research is possible to reduce cost of management and maintenance to realization of smartphone and using data server network technology instead of GPS. Former wireless bus information system was focused on supply side management structure and national spread thus it needs to establish GPS terminal, Windows CE, Window XP embedded and LCD panels which provide only one way communication of information of public traffic information. Therefore, former system management and maintenance cost are very expansive. This research is not use GPS terminal and other hardware equipment but design and realization using smartphone and data network server. This system also provides low cost of management and maintenance. It is not only service downtown area but also out of town and small and medium-sized cities. This system functionally gets a satisfying result user convenience and satisfaction using function of set-up route map, real-time display, and running statically analysis.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

• Journal of the Korean Institute of Landscape Architecture
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• v.18 no.4
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• pp.17-28
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• 1991

The purpose of this study is to investigate and present a method for measuring public accessibility to urban open spaces. A basic assumption is that, for urban open space policies, accessibility is more important than per capita area. In this study, for the purpose of simplicity, a residential area is assumed to have access to open space if it is within a certain distance from an urban open space. Official city planning map is overlayed with a 200m grid and each cell of dwelling area is checked whether it is within a certain distance from a cell categorized as urban open space. A computer program for widely commercialized personal computer is developed for data processing so that local governments without access to more sophisticated systems can carry out similar studies for their own jurisdictions. Five cities, big, small, old and new, are selected to test the proposed method. Dwelling areas of Ansan new Town have highest accessibility to open spaces(93.4% of dwelling cells have open space cell within 500m). Seoul (91.2%), Suwon(78.2%), Pusan(73.8%), and Inchon(61.4%) have less accessibility. If we assume the Ansan City residents are evenly distributed over the dwelling area, 93.4% of the population has open spaces within walking distance of 500m. However, if we consider physical barriers such as arterial roads, railroads, and streams that reduce the accessibility, less than 93.4% of Ansan city residents enjoy good access to open spaces. Though a further detailed analysis is needed to picture the microscopic accessibility, this method can serve as a useful tool for urban open space policy and open space alternatives evaluations.

• KIEAE Journal
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• v.13 no.6
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• pp.55-65
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• 2013

Korean Government has developed Sejong City as a new administration city. This city of future was planned and designed toward one of the most eco-friendly city on the basis of ICTs. To attain this object, a carbon emission monitoring system (CEMS) was designed and installed as a part of u-city service which provides various information anytime and anywhere to enrich the people's quality of life. In this paper, at first, the structure and functions of CEMS are introduced. This system is consist of 5 parts - data collection from user and linked public DBs, transforming data into meaningful information for the policy makers, system-user interfacing via statistical tables and graphs, and system maintenance. This system can be operated by the citizen participation through whole the process. With the help of GIS map and graphic interface, statistics of monitored data for both citizen and decision maker provided and after feed-back, they have affected on the behaviour of citizen's energy consumption and related policy as well. By the CEMS, energy consumption data of 124 agreed households were collected during 9 months in 2012. Electricity, gas and water consumption were remote-metered automatically by the system and analysed. This showed that more than 85% of CO2 emission is rely on electricity usage. Furthermore, number of family members and size of house influences on the emission of CO2 by each household together with the life-style of the occupants. Electricity and water consumption showed the seasonal factor while gas consumption represents the number of family members. Even this paper has limitations caused by 9 months of data collection, it shows the policy directions to reduce the emission of CO2 focusing on the house size and number of family members of each households. With the result of this research, life-style of the generation of dwellers should be investigated and the CO2 emission characteristics of other housing type as well for the data building for future policy making.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.9-18
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• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.