• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4684-4692
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• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.10-15
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• 2011

Histogram equalization is an effective method to enhance the contrast of the image. However, it can result in unwanted artifacts such as excessive contrast enhancement and noise amplification. These artifacts can be reduced by modifying an intensity mapping function which is generated by histogram equalization. In this paper, we present a variational approach to the modification of the intensity mapping function. We define a functional whose minimization produces a modified intensity mapping function. Experimental results show that the intensity mapping function obtained by the proposed method can enhance the contrast of the image without visual artifacts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3962-3980
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• 2019

To deal with single sample face recognition, this paper presents a patch based semi-supervised linear regression (PSLR) algorithm, which draws facial variation information from unlabeled samples. Each facial image is divided into overlapped patches, and a regression model with mapping matrix will be constructed on each patch. Then, we adjust these matrices by mapping unlabeled patches to $[1,1,{\cdots},1]^T$. The solutions of all the mapping matrices are integrated into an overall objective function, which uses ${\ell}_{2,1}$-norm minimization constraints to improve discrimination ability of mapping matrices and reduce the impact of noise. After mapping matrices are computed, we adopt majority-voting strategy to classify the probe samples. To further learn the discrimination information between probe samples and obtain more robust mapping matrices, we also propose a multistage PSLR (MPSLR) algorithm, which iteratively updates the training dataset by adding those reliably labeled probe samples into it. The effectiveness of our approaches is evaluated using three public facial databases. Experimental results prove that our approaches are robust to illumination, expression and occlusion.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.13-17
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• 2005

This paper presents an information system of noise and vibration caused by people as a major source of the environmental problem in residential areas with which people are dissatisfied. Therefore, it is important to monitor the influence of noise and vibration in residential areas. Generally, Geographical Information Systems (GIS) play an important role in noise and vibration mapping. The purpose of this paper is to investigate noise and vibration effects in an urban area and develop a new information network in GIS. Noise and vibration measurements were carried out at a road randomly chosen near INJE University. The obtained values are graphically represented with GIS. Therefore, it is possible to predict noise and vibration in GIS when establishing effective urban plans.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1054-1059
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• 2007

This paper summarized a solution procedure for a large cylindrical structure mounted underneath a ship as a sonar. Vibration analysis of the water loaded structure is required to enhance the structural reliability as well as acoustic performance of the sonar. It is, however, often very difficult to solve such structures since they have many DOFs, considering the frequency of interest and the waterloading. The cyclic symmetric method is firstly reviewed to show how the eigen properties of the full model can be obtained from the representative segment model. The mode mapping method is then proposed and verified to take into account the waterloading with the minimum DOF for the analysis. The solution procedure is finally proposed and applied for a waterloaded cylindrical array structure.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.10
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• pp.808-815
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• 2002

The nonlinear characteristics for hinge of a deployable missile control fin are investigated experimentally. The nonlinearity is caused by a worn or loose hinge and manufacturing tolerance and cannot be eliminated completely. The structural nonlinearity has an effect on the static and dynamic characteristics of the control fin. Therefore, it is necessary to establish the accurate nonlinear model for the hinge of the control fin. In the present study the existence of nonlinearities in the hinge is confirmed from the frequency response experiments such as tip random excitation and base sine sweep. Using the system identification method. especially, ″Force-state Mapping Technique″, the types of nonlinearities are identified and the nonlinear hinge model of the control fin is established.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.848-854
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• 2002

The nonlinear characteristics for the hinge of a deployable missile control fin are investigated experimentally. The nonlinearity is caused by a worn or loose hinge and manufacturing tolerance and cannot be eliminated completely. The structural nonlinearity has an effect on the static and dynamic characteristics of the control fin. Therefore, it is necessary to establish the accurate nonlinear model for the hinge of the control fin. In the present study the existence of nonlinearities in the hinge is confirmed from the frequency response experiments such as tip random excitation and base sine sweep. Using the system identification method, especially, “Force-State Mapping Technique”, the types of nonlinearities are identified and the nonlinear hinge model of the control fin is established.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.121-128
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• 2005

On the research field for speech signal, neural network mainly uses for the category classification in speech recognition and applies to signal processing. Accordingly, this paper proposes a noise reduction system using a time-delay neural network, which implements the mapping from the space of speech signal degraded by noise to the space of clean speech signal. It is confirmed that this method is effective for speech degraded not only by white noise but also by colored noise using the noise reduction system, which restores the amplitude component of fast Fourier transform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2261-2266
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• 2011

Being the most widely used in ultrasound Doppler color flow mapping, the Kasai algorithm, also known as lag-1 autocorrelation method, is capable of estimating the Doppler mean frequency relatively accurately with a modest amount of computation. Particularly in the case of imaging deep lying areas, however, its performance suffers due to low signal-to-noise ratios. The purpose of this paper is to propose a dealiased lag-2 autocorrelation method which is superior to the Kasai algorithm even at low signal-to-noise ratios and to compare their performances through simulations. The proposed algorithm is found to be better by about 2 to 3 dB than the Kasai algorithm in terms of Doppler mean frequency estimation error in the presence of measurement noise.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.231-243
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• 2021

In this paper, a dynamic response mapping model of the wheel-rail system is established by using the support vector regression (SVR) method, and the hierarchical safety thresholds of the subgrade void are proposed based on the reliability theory. Firstly, the vehicle-track coupling dynamic model considering the subgrade void is constructed. Secondly, the subgrade void area, the subgrade compaction index K30 and the fastener stiffness are selected as random variables, and the mapping model between these three random parameters and the dynamic response of the wheel-rail system is built by using the orthogonal test and the SVR. The sensitivity analysis is carried out by the range analysis method. Finally, the hierarchical safety thresholds for the subgrade void are proposed. The results show that the subgrade void has the most significant influence on the carbody vertical acceleration, the rail vertical displacement, the vertical displacement and the slab tensile stress. From the range analysis, the subgrade void area has the largest effect on the dynamic response of the wheel-rail system, followed by the fastener stiffness and the subgrade compaction index K30. The recommended safety thresholds for the subgrade void of level I, II and III are 4.01㎡, 6.81㎡ and 9.79㎡, respectively.