• Earthquakes and Structures
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• v.3 no.3_4
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• pp.435-455
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• 2012

An impact on the ground surface may represent several phenomena, such as a crash of an airplane or an explosion or the passage of a train. In order to analyze and design structures and equipment to resist such a type of shocks, the response spectra for an impact on the ground must be given. We investigated the half-space motions due to impact using the finite element method. We performed extensive parametric analyses to define a suitable finite element model and arrive at displacement time histories and response spectra at varying distances from the impact point. The principal scope of our study has been to derive response spectra which: (a) provide insight and illustrate in detail the half-space response to an impact load, (b) can be readily used for the analysis of structures resting on a ground subjected to an impact and (c) are a new family of results for the impact problem and can serve as reference for future research.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.17-23
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• 1998

The objective of this study is to investigate the dynamic behaviors of KHSR(Korea High-Speed Railway) bridge supported by elastomeric bearings subjected to high-speed vehicles. The effects of damping on the dynamic behaviors are also studied. The train composed of two power cars, two motor cars and eighteen passenger cars are simulated using constant moving forces for simplicity and effectiveness in the analysis. Direct integration method are used to solve the dynamic equation of motion. The bridge analyzed is real bridge with 2@40m span and concrete continuos box girder. The bridge is model led using frame element in three dimensional space. From the results of this study, the effects of elastomeric bearing on the dynamic responses of bridge(especially vertical accelerations) may cause undesirable behaviors. Damping are very important in the dynamic behaviors of the bridge subjected to high-speed railways. And so, dynamic analysis of steel bridge for high-speed railway supported by elastomeric bearings should be performed carefully.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.398-404
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• 1998

The acoustic power reduction methods of the vibrating structures are valid to design the quite structure. To calculate the acoustic power, the dynamic responses have to be determined. It is not easy to analyse the structure composed of the corrugated panels. Because of the structural complexity and the many analysing times. To make up for these defects, the equivalent orthogonal panel is presented. Also the acoustic power prediction method of the vibrating structures is proposed. As examples, the equivalent material properties of the corrugated plates are obtained and the acoustic powers of the floor structure are calculated at several frequency regions for KHST.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.162-168
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• 2008

To predict efficiency of Interior Permanent Magnet Synchronous Motors(IPMSM) and to cope with the demagnetization risk of permanent magnets used in the IPMSM, accurate iron analysis of the IPMSM is very important at the motor design stage. In the analysis, we developed a new iron loss model of electrical machines for high-speed operation. The calculated iron loss was compared with the experimental data. It was clarified that the proposed method can estimate iron loss effectively at high-speed operation.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1024-1028
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• 2008

The ballast, one of track components, plays an essential role as intermedium in transmitting train load to subgrade safely, and the deterioration of ballast directly effects the growth of track irregularity. In this study, we determined the main factor of ballast deterioration was miniature of ballast gravel caused MTT(Multiple Tie Tamper) works and accumulated traffic loads. To estimate the deterioration characteristics of ballast, we carried out field test through track construction for test and the model test simulating the actual operation environment, have done a comparative analysis with the sample's result(crushing rate) of high-speed railroad running actually.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.590-595
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• 2008

A large-scale fire test was done for interior materials from a vehicle installed within a fire test room. The interior materials are the old style before interior replacement by the Korean guideline for the safety of rail vehicle. Ignition source (gas burner) was increased in several controlled steps. The objectives of this test are to assess the fire performance in terms of ignition and flame spread on interior lining materials and to provide data on an enclosure fires involving train interior materials that grow to flashover. This data will be used to develop and calibrate an Fire Dynamics Simulator (FDS) model for fire growth on the interior vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2180-2197
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• 2019

With the proliferation of the Android malicious applications, malware becomes more capable of hiding or confusing its malicious intent through the use of code obfuscation, which has significantly weaken the effectiveness of the conventional defense mechanisms. Therefore, in order to effectively detect unknown malicious applications on the Android platform, we propose DroidVecDeep, an Android malware detection method using deep learning technique. First, we extract various features and rank them using Mean Decrease Impurity. Second, we transform the features into compact vectors based on word2vec. Finally, we train the classifier based on deep learning model. A comprehensive experimental study on a real sample collection was performed to compare various malware detection approaches. Experimental results demonstrate that the proposed method outperforms other Android malware detection techniques.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.51-58
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• 2021

In this paper, we propose a deep learning classifier for estimating the number of layers in the Earth's structure. When installing a grounding system, knowledge of the subsurface in the area is absolutely necessary. The subsurface structure can be modeled by the earth parameters. Knowing the exact number of layers can significantly reduce the amount of computation to estimate these parameters. The classifier consists of a feedforward neural network. Apparent resistivity curves were used to train the deep learning classifier. The apparent resistivity at 20 equally spaced log points in each curve are used as the features for the input of the deep learning classifier. Apparent resistivity curve data sets are collected either by theoretical calculations or by Wenner's measurement method. Deep learning classifiers are coded by Keras, an open source neural network library written in Python. This model has been shown to converge with close to 100% accuracy.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.593-600
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• 2021

In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.

• Smart Structures and Systems
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• v.29 no.3
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• pp.421-431
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• 2022

Concrete slab cracks monitoring of modern high-speed railway is important for safety and reliability of train operation, to prevent catastrophic failure, and to reduce maintenance costs. This paper proposes a curvature filtering improved crack detection method in concrete slabs of high-speed railway via graph-based anomalies calculation. Firstly, large curvature information contained in the images is extracted for the crack identification based on an improved curvature filtering method. Secondly, a graph-based model is developed for the image sub-blocks anomalies calculation where the baseline of the sub-blocks is acquired by crack-free samples. Once the anomaly is large than the acquired baseline, the sub-block is considered as crack-contained block. The experimental results indicate that the proposed method performs better than convolutional neural network method even under different curvature structures and illumination conditions. This work therefore provides a useful tool for concrete slabs crack detection and is broadly applicable to variety of infrastructure systems.