• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.381-382
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• 2010

The management system of next digital map will contributes the systematic management for large dataset and huge data. To develop the management system, the requirements are analyzed and applied through the analysis of characteristics of middleware management, editor and component.

• Journal of the Korean Mathematical Society
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• v.58 no.3
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• pp.761-790
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• 2021

For given spaces X and Y, let map(X, Y) and map_*(X, Y) be the unbased and based mapping spaces from X to Y, equipped with compact-open topology respectively. Then let map(X, Y ; f) and map_*(X, Y ; g) be the path component of map(X, Y) containing f and map_*(X, Y) containing g, respectively. In this paper, we compute cohomotopy groups of suspended complex plane π^n+m(ΣⁿℂP²) for m = 6, 7. Using these results, we classify path components of the spaces map(ΣⁿℂP², S^m) up to homotopy equivalence. We also determine the generalized Gottlieb groups G_n(ℂP², S^m). Finally, we compute homotopy groups of mapping spaces map(ΣⁿℂP², S^m; f) for all generators [f] of [ΣⁿℂP², S^m], and Gottlieb groups of mapping components containing constant map map(ΣⁿℂP², S^m; *).

• Journal of Korean Society of Water and Wastewater
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• v.28 no.1
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• pp.135-142
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• 2014

The performance of inorganic sludge separation system is evaluated. Anaerobic digester effluent sludge is used for feed sludge of this system and hydrocyclone is used for inorganic sludge separation. For phosphorus removal and recovery $MgCl_2$ is pumped into MAP growth tank, a component of inorganic sludge separation system. Using this system inorganic sludge which contained less than 40 % of organic matter can be discharged stably and the maximum amount of separated inorganic sludge is 13.4 % of influent sludge based on dry solid. The amount of phosphorus recovered as MAP(as P) is 16.7 % to influent T-P.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.459-470
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• 2012

In this paper, we propose a method to upsample a low-resolution depth map to a high-resolution version. While conventional camera sensors produce high-resolution color images, the sizes of the depth maps of range/depth sensors are usually low. In this paper, we consider the utilization of high-frequency components to the conventional depth map interpolation methods such as bilinear, bicubic, and bilateral. The proposed method is composed of the three steps: high-frequency component extraction, high-frequency component application, and interpolation. Two objective evaluation measures such as sharpness degree and blur metric are used to examine the performance. Experimental results show that the proposed method significantly outperforms other conventional methods by a factor of 2 in terms of sharpness degree. As well, a blur metric is reduced by a factor of 14 %.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.28-36
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• 2013

This study proposed a robust detection algorithm. It detects hands more stably with respect to changes in light and rotation for the identification of a hand shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the hand area through pre-processing using a hand shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a hand area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the hand shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.5.3-5
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• 2003

The boundary of a typical period-2 component in the degree-3 bifurcation set is formulated by a parametrization of its image which is the unit circle under the multiplier map, Some properties on the geometry of the boundary are investigated including the root point, the cusp, the component center and the length as well as the area bounded by the boundary curve. An algorithm drawing the boundary curve with Mathematica codes is proposed and its implementation exhibits a good agreement with the analysis presented here.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.457-460
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• 2006

For avoiding the waste of costs for building each mobile platform according to each mobile communication vender, KWISF proposed WIPI platform standard. Already the venders are providing mobile map services which are adapted on their own platforms. Because the integration of various mobile platform was performed to WIPI standard, the changes of platform and component API may cause the environment changes of mobile nap services. This study shows the design and implementation results of mobile map services adapted to WPI environments.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.545-556
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• 2015

A HEVC-compatible 3D video coding method (3D-HEVC) has been recently developed as an extension of the high efficiency video coding (HEVC) standard. In order to efficiently deal with the multi-view video plus depth (MVD) format, 3D-HEVC exploits an inter-component prediction which allows the prediction between texture and depth map images in addition to a temporal prediction used in the conventional single layer video coding such as H.264/AVC and HEVC. The performance of the inter-component prediction is normally affected by the accuracy of the disparity vector, and thus it is important to have an accurate disparity vector used for the inter-component prediction. This paper, therefore, introduces a disparity derivation method and inter-component algorithms using the disparity vector for the efficient 3D video coding. Simulation results show that the 3D-HEVC provides higher coding performance compared with the simulcast approach using HEVC and the simple multi-view extension (MH-HEVC).

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.