• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.168-172
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• 2015

In this paper, a balanced bitrate control in transcoding process based on video complexity measure for multi-view system which simultaneously shows multiple channels or video contents in single screen, is proposed. In order to consider the total quality of multiple video streams, the proposed algorithm reduces the complexity of multiple video stream and video quality differences at the same time by controlling bitrates of each stream by weighting when they are stitched for single screen. For the measure of complexity and quality differences between video streams, two different data: histogram of macroblock type and bitrate for each stream are used. The experimental result indicates that proposed algorithm decreases fluctuation of quality difference between videos in the multi-view system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.03a
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• pp.124-130
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• 1995

An upper-bound elemental stream function technique(UBST) is proposed for solivng forging and backward extrusion problems that are geometrically complex or need a forming simulation . And in the forging problems, this study investigates that layer of elements effects dissipation of total energy and load. The element system of UBSTuses the curve fitting property of FEM and the fluid incompressiblity of the stream function . The foumulated optimal design problems with constraints ae solved by the flixible toerance method. In the closed-die forging and backward extrusion, the result of layer of element by this study produces a lower upper-bound solution than that fo UBET and conventional layer of element . And the main advantage of UBST program is that a computer code, once written , can be used for a large variety problems by simply changing the input data.

• Journal of Environmental Science International
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• v.11 no.12
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• pp.1195-1204
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• 2002

We calculated dose rate using radiative transfer equations to consider radiative processes distinctly. The dose rate at Pohang(36°02'N, 129°23'E) was calculated using measured ozone and meteorological data and two-stream approximations(quadrature, Eddington, delta Eddington, PIFM(practical improved flux method), discrete ordinate, delta discrete ordinate) are used in solving equation. The purpose of this study is to determine the most compatible radiative transfer approximation for simulating the radiative and photochemical processes of atmosphere through comparision between calculated and measured values. Dose rate of the biologically effective irradiance in the region 0.28-0.32 U m showed the highest value when quadrature and Eddington was used and lower value on condition that delta scaling was applied. Correlation coefficient between dose rate at surface using radiation transfer equation and measured UV-B at Pohang was 0.78, 0.79 and 0.81 when delta Eddington, PIFM and delta discrete ordinate were used. Also, in case of above approximations were used, MBE(Mean Bias Error) was within -0.3MED/30min and RMBE(Relative Mean Bias Error) was below 10% between 1200 LST and 1400 LST Approximations which are compatible in estimating radiative process are delta Eddington, PIFM and delta discrete ordinate. Especially, in case that radiative process is considered more detail, delta discrete ordinate increased the number of stream is proper.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.253-261
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• 2001

Nowadays, various water quality prediction models have been studied, then these models can support the method which evaluate the effect of various alternative water quality management by simulation without experimentation. But, It is necessary to create complex input data file for applying these water quality model and even though the appropriate result is extracted, it is impossible to use as decision making data effectively because of the limitation of expression of model itself. As this study is about the stream water quality modeling, for overcoming the model's above limitation, by developing an interface which can calculate the pollutant load of watershed, I could create a input data file and visualize the simulation result so that I was going to integrate water quality model and GSIS using Flexible coupling applied to GSIS in the pre-process and post-process on model. The QUAL2E model, used in this study, is verified by stream water quality model in previous various results of study and has many examples through previous study, because that is appropriate to water quality model, especially in Korea, and comparatively accurate and their usage is quite simple.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.2
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• pp.19-32
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• 2015

In Korea, significant riparian areas have been developed due to river maintenance projects. Introduction of new riparian facilities can negatively affect wildlife in the riparian areas. This study focuses on selecting core conservation areas for Eurasian Otter(Lutra lutra) to support decision making process for development of riparian areas. For the study, first of all, field data of study site were collected by field surveys. Secondly, stream naturalness was assessed to understand physical environments of the study sites. Thirdly, habitat suitability was assessed using occurrence data of Eurasian Otter and environmental data. Lastly, core areas for conservation was selected by comparing and synthesizing stream naturalness map and habitat suitability map. The selected core areas showed several characteristics. The number of artificial facilities is low in the core areas. Rocks which are preferred by Eurasian Otter to eat and excrete are plentiful in the core areas. Also, the ratio of adjacent farmland is high. Based on the analyses, it is expected that this study can contribute to decision making process for environmental spatial plans to better conserve habitats of Eurasian Otter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.509-516
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• 2008

Recently, the operator modules to control external devices are concerned about automatic management system to process continuously changed signals. These signals are the stream data of which characteristics are several numbers. a short report interval and asynchronous report time. It is necessary that the system brings about high accuracy and real time process for stream data. The typical queries of these systems consist of the current query to search the latest signal value, the snapshot query at a past time, the sliding window query from a past time to current. In this paper, we propose the efficient method to manage the above signals by using a file structured database in small-size operating systems. We also propose a query model to accommodate various queries including the sliding window query. The file database in the QNX adopts a delta version and a shared memory buffering method for the resource limit of a small storage and a low computing power.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.1-9
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• 2017

Smart Cities intelligently manage numerous infrastructures, including Smart-City IoT devices, and provide a variety of smart-city applications to citizen. In order to provide various information needed for smart-city applications, Smart Cities require a function to intelligently process large-scale streamed big data that are constantly generated from a large number of IoT devices. To provide smart services in Smart-City, the Smart-City Consortium uses stream reasoning. Our stream reasoning requires real-time processing of big data. However, there are limitations associated with real-time processing of large-scale streamed big data in Smart Cities. In this paper, we introduce one of our researches on cloud computing based real-time distributed-parallel-processing to be used in stream-reasoning of IoT big data in Smart Cities. The Smart-City Consortium introduced its previously developed smart-city middleware. In the research for this paper, we made cloud computing based real-time distributed-parallel-processing available in the cloud computing platform of the smart-city middleware developed in the previous research, so that we can perform real-time distributed-parallel-processing with them. This paper introduces a real-time distributed-parallel-processing method and system for stream reasoning with IoT big data transmitted from various sensors of Smart Cities and evaluate the performance of real-time distributed-parallel-processing of the system where the method is implemented.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.483-492
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• 2007

Time series of conventional prediction techniques uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to stream data, the rate of prediction accuracy will be decreased. This paper proposes an stream data prediction technique using sliding window and regression. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of stream data prediction experiment are performed by the proposed technique IMQR(Incremental Multiple Quadratic Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).

• Journal of Wetlands Research
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• v.25 no.1
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• pp.64-73
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• 2023

Before 2022, there was a lot of confusion in the process of planning and implementing the projects for ecological restoration of the stream due to dualization the principal agent of stream management. Because the Ministry of Environment took charge of the project in 2022, securing the health of aquatic ecosystem of stream became an essential factor in the project. Therefore, in this study, the streams that require the project for ecological restoration was selected in Han River estuary, where it is essential to secure the health of the stream aquatic ecosystem as blackish water zone and Ramsar wetland are located. Physical, chemical, spatial/humanistic, health of aquatic ecosystems evaluation indexes were calculated based on the detailed facts and figures of the project for ecological restoration of the stream in the beginning. Ranking, re-scaling, z-score, and t-score normalization methods were applied to the calculated evaluation index, and the values were compared and analyzed. After that, the entropy weight method was applied to each evaluation index. Through this process, the streams(Mokgamcheon, Anyangcheon etc.) that require the project for ecological restoration were selected for the purpose of securing the health of the aquatic ecosystem in Han River estuary. The result of this study can be used as basic research data in the process of selecting the priority determination of the projects for ecological restoration of the stream.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.417-422
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• 2015

A service size of the IoT environment is determined by the number of sensors. The number of sensors increase means increases the amount of data generated by the IoT environment. There are studies to reliably operate a network for research and operational dynamic buffer for data when network congestion control congestion in the network environment. There are also studies of the stream data that has been processed in the connectionless network environment. In this study, we propose a sensor gateway for processing big data of the IoT environment. For this, review the RESTful for designing a sensor middleware, and apply the double-buffer algorithm to process the stream data efficiently. Finally, it generates a big data traffic using the MJpeg stream that is based on the HTTP protocol over TCP to evaluate the proposed system, with open source media player VLC using the image received and compare the throughput performance.