• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1192-1192
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• 2001

Usually there are many furnaces in a ethylene plant and the performance of total furnaces can be improved if that of each furnace is monitored and controlled. For this purpose real-time data for the effluent of each furnace is necessary. However, it is very difficult to analyze the total effluent stream of a ethylene furnace by real-time because it is composed of so many components including heavy hydrocarbons. Fortunately, component data for lighter hydrocarbons is much more important than that of heavier ones for ethylene furnace. In ordinary case, the on-line measurement of light hydrocarbons is performed by on-stream gas chromatography, after separating gas-phase part from effluent. The main and important components of gas-phase are Methane, Ethane, Ethylene, and Propylene. If we can use Near-infrared spectroscopy for measuring those components within good reproducibility, shorter analysis time, better repeatability, easier maintenance and lower cost will make Near-infrared (NIR) analyzer replace on-stream gas chromatography in this process. Although it is known to be very difficult to measure gas components because of very weak absorption in Near-infrared region, we have studied the feasibility of the application of NIR for the measurement of gas-phase hydrocarbon in the effluent of ethylene furnace. The samples were obtained from actual process and NIR spectra were collected over 1100 to 2500nm range. NIR spectra and calibrations showed and demonstrated the possibility of extending NIR spectroscopy to the measurement of gas-phase hydrocarbon in the effluent of ethylene furnace.

• Journal of Korea Water Resources Association
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• v.39 no.7 s.168
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• pp.553-562
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• 2006

The relative contributions of overland-flow and stream-flow to the response process at the basin scale are evaluated in the present study. The moments of GIUH models were applied to the data of the Bocheong watershed in the Geum river basin in Korea in order to discuss the feasibility. The GIUH model derived in this study consists of the stream path and overland region. The characteristic velocities for the flows between two cases mentioned above make a clear distinction as expected and would have more physical meaning than the ones of the model by Rodriguez-Iturbe and Valdes(1979). The path lengths of overland for each stream order are nearly constant, whereas the case of stream is shown to grow larger according to the basin sizes. As a result, the overall basin response process was founded out to be greatly under the influence of the hydrodynamic behavior of overland, and its behavior is suggested to be further researched for catching the broader meanings.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1150-1156
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• 2008

This paper introduces the PC clustering of the SIMD structure for a distributed processing of on-line contingency to assess a static security of a power system. To execute on-line contingency analysis of a large-scale power system, we need to use high-speed execution device. Therefore, we constructed PC-cluster system using PC clustering method of the SIMD structure and applied to a power system, which relatively shows high quality on the high-speed execution and has a low price. SIMD(single instruction stream, multiple data stream) is a structure that processes are controlled by one signal. The PC cluster system is consisting of 8 PCs. Each PC employs the 2 GHz Pentium 4 CPU and is connected with the others through ethernet switch based fast ethernet. Also, we consider N-1 line contingency that have high potentiality of occurrence realistically. We propose the distributed process algorithm of the SIMD structure for reducing too much execution time on the on-line N-1 line contingency analysis in the large-scale power system. And we have verified a usefulness of the proposed algorithm and the constructed PC cluster system through IEEE 39 and 118 bus system.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.831-840
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• 2001

In this study, We introduce the process of web usage mining, which has lately attracted considerable attention with the fast diffusion of world wide web, and explain the web log data, which Is the main subject of web usage mining. Also, we illustrate some real examples of analysis for web log data and look into practical application of web usage mining for eCRM.

• Korean Management Science Review
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• v.22 no.1
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• pp.15-26
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• 2005

The bootstrap is a method of computational inference that simulates the creation of new data by resampling from a single data set. We propose a new job for the bootstrap: generating inputs from one historical trace using Threshold Bootstrap. In this regard, the most important quality of bootstrap samples is that they be functionally indistinguishable from independent samples of the same stochastic process. We describe a quantitative measure of difference between two time series, and demonstrate the sensitivity of this measure for discriminating between two data generating processes. Utilizing this distance measure for the task of generating inputs, we show a way of tuning the bootstrap using a single observed trace. This application of the threshold bootstrap will be a powerful tool for Monte Carlo simulation. Monte Carlo simulation analysis relies on built-in input generators. These generators make unrealistic assumptions about independence and marginal distributions. The alternative source of inputs, historical trace data, though realistic by definition, provides only a single input stream for simulation. One benefit of our method would be expanding the number of inputs achieving reality by driving system models with actual historical input series. Another benefit might be the automatic generation of lifelike scenarios for the field of finance.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.67-73
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• 2018

From a software engineering point of view, tracing is a special form of logging that records program execution information. Tracers using dedicated hardware are often used because of the characteristics of tracers that need to generate and decode huge amounts of data in real time. Intel(R) PT uses proprietary hardware to record all information about software execution on each hardware thread. When the software execution is completed, the PT can process the trace data of the software and reconstruct the correct program flow. The hardware trace program can be integrated into the operating system, but in the case of the window system, the integration is not tight due to problems such as the kernel opening. Also, it is possible to trace only a single process and not provide a way to trace multiple process streams. In this paper, we propose a method to extend existing PT trace program to support multi - process stream traceability in Windows environment in order to overcome these disadvantages.

• Hwankyungkyoyuk
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• v.20 no.4
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• pp.12-26
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• 2007

The purpose of this research is to develop a water environmental education (EE) program using streams, based on the core ideas of ENVISION and materializing elements that were extracted in this research. This research realized the elements and presented a model of the water EE program using a local stream. First, this research developed a basic model of a water EE program using streams by extracting 10 materializing elements and realizing the elements in 4 stage-procedural model. The 10 materializing elements were 1. experiencing the process of inquiry, 2. inquiring local environments, 3. self-directing learning and mutual interaction with colleagues, 4. collecting real data and interpreting, 5. utilizing the ICT(information and communication technology), 6. inquiring with the view point of the 'Environmental Studies for EE', 7. inquiring with the watershed concept, 8. inquiring with the integrating and the holistic view point, 9. pursuing the macroscopic understanding about environment, and 10. connecting the real world phenomena with the environmental concepts and theories. This research materialized these 10 elements in 4 stage model, following the previous ENVISION research, which are 1. preparing stage and visual assessment, 2. writing the report of the inquiry plan, 3. collecting the real data in the environment and performing the investigation, and 4. presenting the inquiry results. Second, with using this basic model, this research developed and presented a model of the specific water EE program using a case stream called 'Baig Cheon' stream, which is a local stream. This research is considered to have a considerable meaning in developing a EE program with ENVISION ideas for the watershed concept and inquiry with environmental science using local streams. The developed model can help the professional development of teachers and teacher education of water EE.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.62-69
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• 2013

This paper proposes real-time video transmission system by the car-mounted cameras based on MOST Network. Existing vehicles transmit videos by connecting the car-mounted cameras in the form of analog. However, the increase in the number of car-mounted cameras leads to development of the network to connect the cameras. In this paper, DSP is applied to process MPEG 2 encoding/decoding for real-time video transmission in a short period of time. MediaLB is employed to transfer data stream between DSP and MOST network controller. During this procedure, DSP cannot transport data stream directly from MediaLB. Therefore, FPGA is used to deliver data stream transmitting MediaLB to DSP. MediaLB is designed to streamline hardware/software application development for MOST Network and to support all MOST Network data transportation methods. As seen in this paper, the test results verify that real-time video transmission using proposed system operates in a normal matter.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.245-256
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• 1999

Watershed delineation is the process of tracing surface water flow across a landscape to identify hydrologic basins. Manual and automated techniques have been developed to trace surface waters and locate watersheds on a variety of landscape. Low topographic relief landscapes, however, are particulary problematic for automated watershed delineation techniques. Therefore, this study aims at focusing the watershed delineation algorithm of low topographic relief landscape. By using topogrid, which manages enforcement drainage algorithms and incorporates topographic data into stream data, this study delineates watershed boundary in low relief landscape. Based on this research, in a low topographic relief landscape, enforcement drainage algorithms using topogrid generate better source grid to delineate watershed boundary than using only TIN. Also, comparing automated watershed delineation which incorporates contours and elevations into stream data with manual watershed delineation, we can know that the incorporation of both elevation and stream data generate more effective results.