• East Asian mathematical journal
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• v.38 no.1
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• pp.95-105
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• 2022

In this paper, we consider a quadratic matrix equation Q(X) = AX² + BX + C = 0 where A, B, C ∈ ℝ^n×n. A new approach is proposed to find solutions of Q(X), using the novel structure of the information processing system. We also present some numerical experimetns with Artificial Neural Network.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.165-172
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• 2020

Industrial Revolution means the improvement of productivity through technological innovation and has been a driving force of the whole change of economic system and social structure as the characteristic of technology as the tool of this productivity has changed. Since the first industrial revolution of the 18th century, productivity efficiency has been advanced through three industrial revolutions so far, and this fourth industrial revolution is expected to bring about another revolution of production. In this study, the demand for the introduction of artificial intelligence(AI) technology has been increasing in various business fields due to the rapid development of ICT technology, and the classification of HS(harmonized commodity description and coding system) items has been decided using artificial intelligence technology, which is the core of the fourth industrial revolution. And it is enough to construct HS classification system based on AI technology using inference and deep learning. Performing the HS item classification is not an easy task. Implementation of item classification system using artificial intelligence technology to analyze information of HS item classification which is performed manually by the current person more accurately and without any mistake, And the customs administrations, customs offices, and customs agencies, it is expected to be highly utilized in the innovation of trade practice and the customs administration innovation FTA origin agent.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.519-526
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• 2001

At present. about 0.3 million and more THRs (Total Hip Replacement) in a rear are being done worldwide. The increase in mechanical failure with the increase in THR, required more revisions. Revisions compensate mainly the wear of the artificial joint frictional surface and the loosening of the cup and stem. According to recent researches, loosening is mainly due to wear debris UHMWPE (Ultra High Molecular Weight Polyethylene) from frictional surfaces . To overcome the wear problems associated with artificial joint materials , new surface structures with regular Patterns were designed and fabricated The lubrication Properties were examined to evaluate the wear of the frictional surfaces. The surface structure manifested a Pattern of "dents" with a 0.2-1.0 mm of diameter and 0.6-2.0 mm of Pitch. From the friction test of the SUS316L vs UHMWPE using the frictional tester, we found that the lubrication Performance was improved due to of drastically reduced amount of abrasion. There were optimum sizes for the diameter and the pitch of the Pattern. The results demonstrated that the lubrication properties could be improved by Patterning of the frictional surfaces. The surface Patterning was effective in preventing wear of the frictional surfaces, and the life of an artificial joint could be extended with such Patterning.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.439-446
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• 1998

One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.969-976
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• 2017

This paper proposes the learning method of an artificial neural network and a convolutional neural network using the WFSO algorithm developed as an optimization algorithm. Since the optimization algorithm searches based on a number of candidate solutions, it has a drawback in that it is generally slow, but it rarely falls into the local optimal solution and it is easy to parallelize. In addition, the artificial neural networks with non-differentiable activation functions can be trained and the structure and weights can be optimized at the same time. In this paper, we describe how to apply WFSO algorithm to artificial neural network learning and compare its performances with error back-propagation algorithm in multilayer artificial neural networks and convolutional neural networks.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.188-192
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• 2012

In this study, a carbon nanotube (CNT) flexible strain sensor was fabricated with CNT based epoxy and rubber composites for tactile sensing. The flexible strain sensor can be fabricated as a long fibrous sensor and it also may be able to measure large deformation and contact information on a structure. The long and flexible sensor can be considered to be a continuous sensor like a dendrite of a neuron in the human body and we named the sensor as a biomimetic artificial neuron. For the application of the neuron in biomimetic engineering, an ANMS (Artificial Neuron Matrix System) was developed by means of the array of the neurons with a signal processing system. Moreover, a strain positioning algorithm was also developed to find localized tactile information of the ANMS with Labview for the application of an artificial e-skin.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.1
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• pp.59-65
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• 2003

The changes of beach profile with a natural longshore bar and beach profile with a fixed artificial bar are studied, respectively, using a numerical model. The quasi three dimensional wave-current-sediment transport model is applied with an addition of boundary condition for sediment transport on the artificial structure under water. The study shows that the natural bar adapts itself to the change of coastal physical environment by adjusting its location but the fixed artificial bar causes the formation of a second natural bar seaward of the fixed bar and scouring at the rear of the fixed bar. This study can be applied to work on the change of beach profile with submerged breakwaters.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.280-288
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• 2019

A submerged breakwater is one of the coastal structures used to reduce wave energy and coastal erosion. However, a submerged breakwater has a negative aspect in that a strong rip current occurring around an open inlet due to a difference in mean water levels at the front and rear sides of the structure leads to scouring. Such scouring has a bad effect on its stability. In order to eliminate this kind of demerit, this study investigated an artificial reef of the overflow type with openings. We also developed a program where the flows around the artificial reef of the overflow type could be analyzed numerically. An unstructured grid system was used to cover the various geometries, and the level set method was applied to treat the movement of the free surface. To verify these numerical schemes, hydraulic physical tests were performed on the submerged breakwater and double breaking type artificial reef. Then, the wave height and velocity distribution around the reef were examined using the experimental results. Comparisons between the results of hydraulic and numerical tests showed reasonable agreement.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.2
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• pp.344-354
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• 2009

Side scan sonar using acoustic wave plays a very important role in the underwater, sea floor, and shallow marine geologic survey. In this study, we have acquired side scan sonar data for the underwater man-made structures, artificial reefs and fishing grounds, installed and distributed in the survey area. We applied digital image processing techniques to side scan sonar data in order to improve and enhance an image quality. We carried out digital image processing with various kinds of filtering in spatial domain and frequency domain. We tested filtering parameters such as kernel size, differential operator, and statistical value. We could easily estimate the conditions, distribution and environment of artificial structures through the interpretation of side scan sonar.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.