• Proceedings of the KSRS Conference
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• v.1
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• pp.200-203
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• 2006

Cloud detection algorithm is being developed as major one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-1R and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithm and preliminary test result of both algorithms.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.65-72
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• 2001

With the recent rising project complexities and competitive environments in the construction projects, a risk management is recognized as more important management tool than the others. However, as most risk management techniques applied to the construction projects are centered around their initial phases and risk analyses, they are not developed into general project management technique such as time management, cost management and quality management, etc., that are usually applied in the process of construction. Thus, this paper proposes a response process to construction project risks based on the risk threshold and its calculation methodology applying a concept of VaR to establish risk management as general management technique in the construction projects.

• Nuclear Engineering and Technology
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• v.49 no.4
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• pp.663-667
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• 2017

Delayed hydride cracking (DHC) was first observed in pressure tubes in Canadian CANDU reactors. In light water reactors, DHC was not observed until the late 1990s in high-burnup boiling water reactor (BWR) fuel cladding. In recent years, the focus on DHC has resurfaced in light of the increased interest in the cladding integrity during interim conditions. In principle, all spent fuel in the wet pools has sufficient hydrogen content for DHC to operate below $300^{\circ}C$. It is therefore of importance to establish the critical parameters for DHC to operate. This work studies the threshold stress intensity factor ($K_{IH}$) to initiate DHC as a function of temperature in Zry-4 for temperatures between $227^{\circ}C$ and $315^{\circ}C$. The experimental technique used in this study was the pin-loading testing technique. To determine the $K_{IH}$, an unloading method was used where the load was successively reduced in a stepwise manner until no cracking was observed during 24 hours. The results showed that there was moderate temperature behavior at lower temperatures. Around $300^{\circ}C$, there was a sharp increase in $K_{IH}$ indicating the upper temperature limit for DHC. The value for $K_{IH}$ at $227^{\circ}C$ was determined to be $2.6{\pm}0.3MPa$ ${\surd}$m.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.111-118
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• 2004

Techniques based on thresholding of wavelet coefficients are gaining popularity for denoising data because of the reasonable performance at the low complexity. The VisuShrink which removes the noise with the universal threshold is one of the techniques. The universal threshold is proportional to the noise deviation and the number of data samples. In general, because the noise deviation is not known, one needs to estimate the deviation for determining the value of the universal threshold. But, only for the finest scale wavelet coefficients, it has been known the way of estimating the noise deviation, so the noise in coarse scales cannot be removed with the VisuShrink. We propose here a new denoising method which removes the noise in each scale except the coarsest scale by Visushrink method. The noise deviation at each band is estimated by the monotonic transform and weighted deviation, the product of estimated noise deviation by the weight, is applied to the universal threshold. By making use of the universal threshold and the Soft-Threshold technique, the noise in each band is removed. The denoising characteristics of the proposed method is compared with that of the traditional VisuShrink and SureShrink method. The result showed that the proposed method is effective in denoising on Gaussian noise and quantization noise.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.331-336
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• 1986

Because the threshold technique using the histogram of intensity is the most attractive for segmentation in the sense of fast image processing, this paper defined the new function of inverse histogram of intensity and found out a threshold by means of it. The segmented errors are removed by regulating a scan size of blob coloring. Blob-coloring algorithm presented by [6] was reproved for good performance i.e., no change of feature in bolobs after blob coloring. The ratio of successful recognition was about 85 percents.

• Bulletin of the Korean Mathematical Society
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• v.43 no.4
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• pp.813-820
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• 2006

We consider a MAR model with ARCH type conditional heteroscedasticity. MAR-ARCH model can be derived as a smoothed version of the double threshold AR-ARCH model by adding a random error to the threshold parameters. Easy to check sufficient conditions for strict stationarity, ${\beta}-mixing$ property and existence of moments of the model are given via Markovian representation technique.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.62-62
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• 1999

In this paper, we propose a new technique of estimating tail of steady-state queue length distribution; Pr(Q>q), fo ATM multiplexer. Pr(Q>q) is a fundamental measure of network congestion. Assessing Pr(Q>q) properly is crucial for design and control of ATM networks. Data traffic pattern of high-speed networks is highly correlated and bursty. Estimating Pr(Q>q) is very difficult because of correlation and burstiness. We estimate entropy(rate-function) using large deviation principles and threshold bootstrap. Simulation studies are conducted to compare the performance of an existing method and our new method.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.18-25
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• 2016

As more people have cars, the threat of traffic accidents is posed on men and women of all ages. The main culprit of traffic accidents is driving while intoxicated or drowsy. The method to recognize and prevent the cause of traffic accidents is to use lane detection. In this study, a total of 4,000 frames (day image: 2,900 frames, night image: 1,100 frames) were used to test lane detection. According to the test, in the case of day image, when the threshold of Sobel edge detection technique was detected with second-order differential equation, there was the highest candidate lane detection rate which was 86.1%. In the threshold of Canny edge detection technique, the highest detection rate of 88.0% was found at Low=50, and High=300. In the case of night image, the threshold of Sobel edge detection technique, when horizontal calculation and vertical calculation had second-order differential equation, and when horizontal-vertical calculation had 1.5th-order differential equation, there was the highest detection rate which was 83.1%. In the threshold of Canny edge detection technique, the highest detection rate of 89.9% was found at Low=50, and High=300.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.678-684
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• 2015

Near-threshold computing (NTC) is now regarded as a promising candidate for innovative power reduction, which cannot be achieved with conventional super-threshold computing (STC). However, performance degradation and vulnerability to process variation in the NTC regime are the primary concerns. In this paper, we propose a voltage- and frequency-tuning methodology for mitigating the process-variation-induced problems in NTC-based manycore architectures. To implement the proposed methodology, we build up multiple-voltage multiple-frequency (MVMF) islands and apply a voltage-frequency tuning algorithm based on the critical-path monitoring technique to reduce the effects of process variation and maximize energy efficiency in the post-silicon stage. Experimental results show that the proposed methodology reduces overall power consumption by 8.2-20.0%, compared to existing methods in variation-sensitive NTC environments.