• Proceedings of the KSRS Conference
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• v.2
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• pp.884-887
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• 2006

This paper focuses on minimizing flood damage in the Yeongdeok basin of South Korea by establishing a flood prediction model based on a geographic information system (GIS), remote sensing, and geomorphoclimatic instantaneous unit hydrograph (GcIUH) techniques. The GIS database for flash flood prediction was created using data from digital elevation models (DEMs), soil maps, and Landsat satellite imagery. Flood prediction was based on the peak discharge calculated at the sub-basin scale using hydrogeomorphologic techniques and the threshold runoff value. Using the developed flash flood prediction model, rainfall conditions with the potential to cause flooding were determined based on the cumulative rainfall for 20 minutes, considering rainfall duration, peak discharge, and flooding in the Yeongdeok basin.

• Journal of the Korean Burn Society
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• v.24 no.1
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• pp.1-6
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• 2021

Purpose: The purpose of this study was to evaluate the accuracy of four prediction models in adult burn patients. Methods: This retrospective study was conducted on 696 adult burn patients who were treated at burn intensive care unit (BICU) of Hallym University Hangang Sacred Heart Hospital from January 2017 to December 2019. The models are ABSI, APACHE IV, rBaux and Hangang score. Results: The discrimination of each prediction model was analyzed as AUC of ROC curve. AUC value was the highest with Hangang score of 0.931 (0.908~0.954), followed by rBaux 0.896 (0.867~0.924), ABSI 0.883 (0.853~0.913) and APACHE IV 0.851 (0.818~0.884). Conclusion: The results of evaluating the accuracy of the four models, Hangang score showed the highest prediction. But it is necessary to apply the appropriate prediction model according to characteristics of the burn center.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.422-433
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• 2015

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multi-loop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.2 no.1
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• pp.29-36
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• 1998

An instantaneous unit sediment graph (IUSG) model is investigated for prediction of sediment yield from an upland watershed in Northwestern Mississippi. Sediment yields are predicted by convolving source runoff with an IUSG. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. The IUH is derived by the Nash model for each event. The SCD is assumed to be an exponential function for each event and its parameters were correlated with the effective rainfall characteristics. A sediment routing function, based on travel time and sediment particle size, is used to predict the SCD.

• Journal of Environmental Science International
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• v.2 no.1
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• pp.29-36
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• 1993

An instantaneous unit sediment graph (IUSG) model is investigated for prediction of sediment yield from an upland watershed In Northwestern Mississippi. Sediment yields are predicted by convolving source runoff with an IUSG. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. The IUH is derived by the Nash model for each event. The SCD is assumed to be an exponential function for each event and its parameters were correlated with the effective rainfall characteristics. A sediment routing function, based on travel time and sediment particle size, is used to predict the SCD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.875-878
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• 2015

In this paper, we propose an intra prediction hardware architecture with less processing time, computations and reduced hardware area for a high performance HEVC encoder. The proposed intra prediction hardware architecture uses common operation units to reduce computational complexity and uses $4{\times}4$ block unit to reduce hardware area. In order to reduce operation time, common operation unit uses one operation unit to generate predicted pixels and filtered pixels in all prediction modes. Intra prediction hardware architecture introduces the $4{\times}4$ PU design processing to reduce the hardware area and uses intemal registers to support $32{\times}32$ PU processmg. The proposed hardware architecture uses ten common operation units which can reduce execution cycles of intra prediction. The proposed Intra prediction hardware architecture is designed using Verilog HDL(Hardware Description Language), and has a total of 41.5k gates in TSMC $0.13{\mu}m$ CMOS standard cell library. At 150MHz, it can support 4K UHD video encoding at 30fps in real time, and operates at a maximum of 200MHz.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.12
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• pp.79-90
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• 2000

In this paper, a high-performance floating point unit, which is suitable for high-performance superscalar microprocessors and supports IEEE 754 standard, is designed. Floating-point arithmetic unit (AU) supports all denormalized number processing through hardware, while eliminating the additional delay time due to the denormalized number processing by proposing the proposed gradual underflow prediction (GUP) scheme. Contrary to the existing fixed-radix implementations, floating-point divide/square root unit adopts a new architecture which determines variable length quotient bits per cycle. The new architecture is superior to the SRT implementations in terms of performance and design complexity. Moreover, sophisticated exception prediction scheme enables precise exception to be implemented with ease on various superscalar microprocessors, and removes the stall cycles in division. Designed floating-point AU and divide/square root unit are integrated with and instruction decoder, register file, memory model and multiplier to form a floating-point unit, and its function and performance is verified.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.299-309
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• 2022

Recently, The sea water temperature around Korean Peninsula is steadily increasing. Water temperature changes not only affect the fishing ecosystem, but also are closely related to military operations in the sea. The purpose of this study is to suggest which model is more suitable for the field of water temperature prediction by attempting short-term water temperature prediction through various prediction models based on deep learning technology. The data used for prediction are water temperature data from the East Sea (Goseong, Yangyang, Gangneung, and Yeongdeok) from 2016 to 2020, which were observed through marine observation by the National Fisheries Research Institute. In addition, we use Long Short-Term Memory (LSTM), Bidirectional LSTM, and Gated Recurrent Unit (GRU) techniques that show excellent performance in predicting time series data as models for prediction. While the previous study used only LSTM, in this study, the prediction accuracy of each technique and the performance time were compared by applying various techniques in addition to LSTM. As a result of the study, it was confirmed that Bidirectional LSTM and GRU techniques had the least error between actual and predicted values at all observation points based on 1 hour prediction, and GRU was the fastest in learning time. Through this, it was confirmed that a method using Bidirectional LSTM was required for water temperature prediction to improve accuracy while reducing prediction errors. In areas that require real-time prediction in addition to accuracy, such as anti-submarine operations, it is judged that the method of using the GRU technique will be more appropriate.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.5-12
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• 2004

The erosion wear of gun barrel occurs due to heat and chemical reactions. The high pressure and temperature in chamber increase the erosion wear. It is known that the metal phase transfer is the primary wear factor in a gun barrel under high temperature. In this paper, the tool of wear prediction in high pressure gun tube has been developed. The program developed has three modules such as DIRECT(interior ballistics analysis module), INVERSE(gun design module), and WEAR(wear prediction module). The prediction of wear was compared with the experimental data which was collected in the field unit. The prediction results shows good trend with the collected data.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.351-353
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• 2006

Preventive maintenance can avail the generating unit to reduce cost and gain more profit in a competitive supply-side power market. so, it is necessary to perform reliability analysis on the systems in which reliability is essential. In this paper, FMECA assessment adopted using real historical failure data in Korean power plants for apply RCM analytical method. The stochastic FMECA is an engineering analysis and a core activity performed by reliability engineers to review the effects of probable failure modes of generating unit and assemblies of the power system on system performance. Optimal RCM schedule which is considered the severity level of each generating unit and failure probability from failure prediction of generating unit can be planned using proposed FMECA with IOE index.