• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1501-1512
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• 2024

Plasma disruption in tokamak experiments is a challenging issue that causes damage to the device. Reliable prediction methods are needed, but the lack of full understanding of plasma disruption limits the effectiveness of physics-driven methods. Data-driven methods based on supervised learning are commonly used, and they rely on labelled training data. However, manual labelling of disruption precursors is a time-consuming and challenging task, as some precursors are difficult to accurately identify. The mainstream labelling methods assume that the precursor onset occurs at a fixed time before disruption, which leads to mislabeled samples and suboptimal prediction performance. In this paper, we present disruption prediction methods based on anomaly detection to address these issues, demonstrating good prediction performance on J-TEXT and EAST. By evaluating precursor onset times using different anomaly detection algorithms, it is found that labelling methods can be improved since the onset times of different shots are not necessarily the same. The study optimizes precursor labelling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.277-283
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• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.284-285
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• 2004

• Journal of The Korean Astronomical Society
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• v.42 no.6
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• pp.155-159
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• 2009

In order to determine color excess in the $uvby\beta$ color system for high amplitude $\delta$ Scuti stars, reddening free $[m_1]$, $[c_1]$, and $\beta$ indices data were obtained from the existing literature for 21 stars. Then, the three intrinsic relations of $(b-y)_0$ - $[m_1]$, $(b-y)_0$ - $[c_1]$, and $(b-y)_0$ - $\beta$ were investigated. Among these, it was shown that the $(b-y)_0$-$[c_1]$ relation is the most useful. By establishing intrinsic $(b-y)_0$-$[c_1]$ relations for six reddening calibration stars, color excesses of other stars were determined.

• Molecular & Cellular Toxicology
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• v.3 no.2
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• pp.145-149
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• 2007

Studies of relationship between structure and toxicity of azo dyes have been performed with comparative molecular field analysis (CoMFA) techniques. 3D QSTR analyses indicate that the steric and electrostatic interactions are important. The steric field based model gives strong correlation ($q^2$=0.57, $r^2$= 0.92). The steric field in conjunction with electrostatic field give more strong correlation ($q^2$=0.57, $r^2$=0.95). All study indicates that a bulky and electronegative group at benzene ring and a small group at position 3 of aniline ring might be significant to reduce the mutagenicity.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.58-58
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• 2003

The envelope glycoprotein of HIV, gp41, mediates the membrane fusion with human cells. The extracellular domain of gp41 has two helical regions. The N-terminus helical region (N-helix) forms trimeric coiled coil, interacts with the C-terminus helical region (C-helix) of gp41 to form a stable helical bundle structure. In this study, we have shown that the N-helix of gp41 has membrane interacting and disrupting abilities. It was localized into the interface of the lipidic phase and head group of the membrane. In contrast, the N-helix region with membrane fusion defective mutations could not bind to membrane. In addition, the N-helix bound on the membrane was released from the membrane by the C-helix, and the complex of the N- and C-helix did not interact with membrane. These results suggested that the membrane binding ability of the N-helix is necessary for the fusion activity of gp41, and such property is possibly controlled by the C-helm.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1042-1044
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• 2003

A methodology of the integrating the similar color circle search of the spectral data and segmentation of the height data is developed. The method is then applied to study areas, and the results by IKONOS, LIDAR and data fusion are verified with the ground truth, and examined in terms of the accuracy. Results show that with the data fusion the accuracy are improved by about 15% in most of the study areas. The methodology for the detection of individual tree stands by data fusion is explored, and the utility of combinatorial use of the spectral and the height information is demonstrated.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.461-469
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• 2010

In this paper, we have proposed an improved fusion method of detection features which can enhance the detection probability under the given false alarm rate in the prescreening stage of SAR ATR(Synthetic Aperture Radar Automatic Target Recognition) system. Since the detection features have the positive correlation, the detection performance can be improved if the joint probability distribution of detection features is considered in the fusion process. The detection region is designed as a simple piecewise linear function which can be represented by few parameters. The parameters for the detection region can be derived by training the sample SAR images to maximize the detection probability with the given false alarm rate. Simulation result shows that the detection performance of the proposed method is improved for all combinations of detection features.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1181-1196
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• 2011

Image fusion is the process of combining information from two or more source images of a scene into a single composite image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and defense. The most common wavelet-based fusion is discrete wavelet transform fusion in which the high frequency sub-bands and low frequency sub-bands are combined on activity measures of local windows such standard deviation and mean, respectively. However, discrete wavelet transform is not translation-invariant and it often yields block artifacts in a fused image. In this paper, we propose a robust image fusion based on the stationary wavelet transform to overcome the drawback of discrete wavelet transform. We use the activity measure of interquartile range as the robust estimator of variance in high frequency sub-bands and combine the low frequency sub-band based on the interquartile range information present in the high frequency sub-bands. We evaluate our proposed method quantitatively and qualitatively for image fusion, and compare it to some existing fusion methods. Experimental results indicate that the proposed method is more effective and can provide satisfactory fusion results.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2728-2739
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• 1999

This paper proposes an effective fusion algorithm for retrieval results from heterogeneous information sources in federated digital libraries. The algorithm determines the population of documents retrieved from involved information sources for a given query and evaluates the degree of relevance between the query and the population. The evaluated results are used as relevance distribution information for collection fusion. The main informations used for the fusion are relevance distribution among collections, the population size N, and ranking information of relevant documents in their origin. We also present th performance evaluation of the algorithm by developing the prototype of a meta-searcher.