• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.33-52
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• 2017

A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.

• Journal of The Korean Astronomical Society
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• v.27 no.2
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• pp.191-201
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• 1994

We propose to use the entropy of power spectra defined in the frequency domain for the deconvolution of extended images. Spatial correlations requisite for extended sources may be insured by increasing the role of power entropy because the power is just a representation of spatial correlations in the frequency domain. We have derived a semi-analytical solution which is found to severely reduce computing time compared with other iteration schemes. Even though the solution is very similar to the well-known Wiener filter, the regularizingng term in the new expression is so insensitive to the noise characteristics as to assure a stable solution. Applications have been made to the IRAS $60{\mu}m\;and\;100{\mu}m$ images of the dark cloud B34 and the optical CCD image of a solar active region containing a circular sunspot and a small pore.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Journal of Environmental Science International
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• v.12 no.4
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• pp.399-417
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• 2003

The seasonal variation and frequency of rainfalls of Korea peninsula in Changma period show strong local weather phenomenon because of it's topographical and geographical factors in Northeast side of Asia. Based on weather entropy(statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical and geographical factors and seasonal variation. The data used for this study are the daily precipitation and cloudiness during the recent ten years(1990-1999) at the 73 stations in Korea. To synthesize weather Entropy, information ratio of decaying tendency and half$.$decay distance, Seoul's weather representativeness has the smallest in Summer Changma period. And Puyo has the largest value in September.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.1-8
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• 2023

It is extremely important to design safety-guaranteed industrial processes because such process determine the ultimate outcomes of industrial activities, including worker safety. Application of artificial intelligence (AI) in industrial safety involves modeling industrial safety systems by using vast amounts of safety-related data, accident prediction, and accident prevention based on predictions. As a preliminary step toward realizing AI-based industrial safety in Korea, this study discusses neural network-based modeling of industrial safety systems. The input variables that are the most discriminatory relative to the output variables of industrial safety processes are selected using two information-theoretic measures, namely entropy and cross entropy. Normalized frequency and severity of industrial accidents are selected as the output variables. Our simulation results confirm the effectiveness of the proposed neural network model and, therefore, the feasibility of extending the model to include more input and output variables.

• Computational Structural Engineering
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• v.10 no.4
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• pp.185-193
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• 1997

A major problem of frequency analysis in the field of low-frequencies such as building or construction vibration is the way of signal processing which is appropriate to obtain included frequency content from the finite process to be measured. Therefore, it is the aim of the investigation reported herein to develop the signal processing algorithm which is analyzed without losing the reliability of the measurements in low-frequency domain. To accomplish the research objective, it was analyzed the problems on the way of signal processing in low-frequency domain, and compared the response characteristics of FFT with those of MEM (Maximum Entropy Method) about the low-frequency of vibration. This evaluation of the response characteristics is used in determining appropriate signal processing algorithm into the low-frequency domain.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.7-14
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• 2012

To analyze any given situation, it is necessary to have information on elements which affect the situation. Particularly, there is greater variability in both frequency and magnitude of agricultural product prices as they are affected by various unpredictable factors such as weather conditions etc. This is the reason why it is difficult for the farmers to maintain their stable income through agricultural production and marketing. In this research, attempts are made to quantify the entropy of various situations inherent in the price changes so that the stability of farmers' income can be increased. Through this research, we developed an entropy model which can quantify the uncertainties of price changes using the probability distribution of price changes. The model was tested for its significance by comparing its simulation outcomes with actual ranges and standard deviations of price variations of the past using monthly agricultural product prices data. We confirmed that the simulation results reflected the features of the ranges and standard deviations of actual price variations. Also, it is possible for us to predict standard deviations for changed prices which will occur after a certain time using the information entropy obtained from relevant agricultural product price data before the time.

• Journal of the Korean Society of Propulsion Engineers
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• v.8 no.4
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• pp.55-66
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• 2004

In this paper a method for finding solutions of acoustic, vortex and entropy wave equations in a cylindrical tube with variable section area was suggested under the consideration of that the high frequency instability in a rocket engine combustion chamber is an acoustic phenomena, which Is coupled with combustion reaction. and that a combustion chamber and exhaust nozzle are usually shaped cylindrically As a consequence of that some method. which enable the mathematical analysis of the influence of entropy and vortex waves to acoustic wave. was suggested. According to the method reflection coefficients of acoustic wave on a supercritical nozzle was numerically calculated, through which it was presented that entropy or vortex waves can strengthen or weaken the reflection rate of acoustic wave.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.47-50
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• 1990

In this study, the degree of spectral transfer to lower frequency caused by accumulation of Latic acid inside the muscle is estimated the convintional dip analysis, zero-crossing method and FFT method have intrinsic errors and estimation problems in case of severe noise. The new spectral analysis method using "$2^{nd}$ order Maximum Entropy Method" was applied to estimate mean frequency and we confirmed that this new method yields fast and reliable estimation over the FFT method.

• Journal of IKEEE
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• v.26 no.2
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• pp.226-231
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• 2022

The concept of information entropy has been widely applied in various fields. Recently, in the field of image processing, many technologies applying the concept of information entropy have been developed. As the importance and demand of computer vision technologies increase in modern industry, real-time processing must be possible in order for image processing technologies to be efficiently applied to modern industries. Extracting the entropy value of an image is difficult to process in real-time due to the complexity of computation in software, and a hardware structure of an image entropy filter capable of real-time processing has never been proposed. In this paper, we propose for the first time a hardware structure of a histogram-based entropy filter that can be processed in real time using a barrel shifter. The proposed hardware was designed using Verilog HDL, and Xilinx's xczu7ev-2ffvc1156 was set as the target device and FPGA was implemented. As a result of logic synthesis using the Xilinx Vivado program, it has a maximum operating frequency of 750.751 MHz in a 4K UHD high-resolution environment, and it processes more than 30 images per second and satisfies the real-time processing standard.