• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.658-672
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• 2021

Since the signal with strong power need be demodulated first for successive interference cancellation (SIC) receiver in non-orthogonal multiple access (NOMA) systems, the base station (BS) need inform the near user terminal (UT), which has allocated higher power, of the far UT's modulation mode. To avoid unnecessary signaling overhead of control channel, a blind detection algorithm of NOMA signal modulation mode is designed in this paper. Taking the joint constellation density diagrams of NOMA signal as the detection features, the deep residual network is built for classification, so as to detect the modulation mode of NOMA signal. In view of the fact that the joint constellation diagrams are easily polluted by high intensity noise and lose their real distribution pattern, the wavelet denoising method is adopted to improve the quality of constellations. The simulation results represent that the proposed algorithm can achieve satisfactory detection accuracy in NOMA systems. In addition, the factors affecting the recognition performance are also verified and analyzed.

• Composites Research
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• v.31 no.4
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• pp.151-155
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• 2018

Mechanical joint and adhesive joint are two typical joining methods for structures. The adhesive joints distribute the load over a larger area than mechanical joints and have excellent fatigue properties. However, the strength of adhesive joint greatly depends on the environmental conditions and the skill of the operator. Therefore, there is a need for techniques to evaluate the quality of the adhesive joints. The electric resistance method is a very promising technique for detecting defects by measuring the electrical resistance of an adhesive joint in which CNTs are dispersed in an adhesive. In this study, Aluminium-Aluminium adhesive single lap joint specimens were fabricated by using the adhesive dispersing CNTs using a sonicator and a 3-roll mill, and the static strengths and defect detection capabilities of the joints using the electrical resistance method were evaluated according to the CNTs content.

• 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 Ocean Engineering and Technology
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• v.23 no.6
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• pp.124-130
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• 2009

This study presents a finite element simulation of elastic waves for detecting anti-symmetric damages in an adhesively-bonded single lap joint. Plane strain elements were used for modeling adherents (aluminum) and adhesives (epoxy). Three types of damage were introduced: thickness reduction, elasticity deterioration, and voids in the adhesive layers, and two excitation and reception arrangements (ER1 and ER2) were used to investigate the detectability of the damage. The simulation showed that symmetrically located damage, such as a thickness reduction, can be detected by one excitation and one reception arrangement (ER1) and anti-symmetric damages, such as elasticity deterioration and voids, can be detected by modified two-point elastic wave excitation (ER2). Compared with the ER1 arrangement, the ER2 arrangement does not require a baseline signal for damage detection; hence, an efficient method of anti-symmetric damage detection in an adhesively-bonded single lap joint is proposed.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.554-556
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• 2002

It has little possibility that cable and cable joint causes any problem in transmission system. But when cable fault occurs, the damage is very severe. There are weak points to have potential problem due to many cable joint especially in high voltage transmission line. In this study, we propose nobel method to detect PD in cable joints and show the effectiveness of the proposed method through experiment results.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.922-927
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• 2007

The present urban maglev which has been developed in Korea is controlled by 4-edge control method over each bogie. The control output which is derived from two gap sensors and one vertical acceleration sensor controls magnet to maintain a nominal gap. But, the gap signal acts as a big disturbance in rail joint though two gap sensors are used and finally result in unstable response and poor ride comfort. This paper treats of a method to compensate the gap signal in rail joint for the levitation control of urban maglev. The physically abnormal change of gap is detected when one gap sensor passes a rail joint, the disturbance of gap in rail joint is estimated. Finally the disturbance in gap signal is eliminated by processing the information of vehicle speed and estimated disturbance in when the other gap sensor passes a rail joint.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.613-614
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• 2009

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.