• Steel and Composite Structures
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• v.45 no.4
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• pp.501-511
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• 2022

In this study, a two-dimensional model of the contact problem has been examined using the finite element method (FEM) based software ANSYS and based on the multilayer perceptron (MLP), an artificial neural network (ANN). For this purpose, a functionally graded (FG) half-infinite layer (HIL) with a crack pressed by means of two rigid blocks has been solved using FEM. Mass forces and friction are neglected in the solution. Since the problem is analyzed for the plane state, the thickness along the z-axis direction is taken as a unit. To check the accuracy of the contact problem model the results are compared with a study in the literature. In addition, ANSYS and MLP results are compared using Root Mean Square Error (RMSE) and coefficient of determination (R2), and good agreement is found. Numerical solutions are made by considering different values of external load, the width of blocks, crack depth, and material properties. The stresses on the contact surfaces between the blocks and the FG HIL are examined for these values, and the results are presented. Consequently, it is concluded that the considered non-dimensional quantities have a noteworthy influence on the contact stress distributions, and also, FEM and ANN can be efficient alternative methods to time-consuming analytical solutions if used correctly.

• Steel and Composite Structures
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• v.50 no.1
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• pp.77-87
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• 2024

In this study, the two-dimensional crack problem was investigated by using the finite element method (FEM)-based ANSYS package program and the artificial neural network (ANN)-based multilayer perceptron (MLP) method. For this purpose, a half-infinite functionally graded (FG) layer with a crack pressed through two rigid blocks was analyzed using FEM and ANN. Mass forces and friction were neglected in the solution. To control the validity of the crack problem model exercised, the acquired results were compared with a study in the literature. In addition, FEM and ANN results were checked using Root Mean Square Error (RMSE) and coefficient of determination (R²), and a well agreement was found. Numerical solutions were made considering different geometric parameters and material properties. The stress intensity factor (SIF) was examined for these values, and the results were presented. Consequently, it is concluded that the considered non-dimensional quantities have a noteworthy influence on the SIF. Also FEM and ANN can be logical alternative methods to time-consuming analytical solutions if used correctly.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.92-99
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• 2013

High oil price and global warming problem are being continued all over the world. For this reason, fuel economy and emission of greenhouse gas are regulated by law in many countries. Therefore many companies are researching and producing hybrid electric vehicles (HEVs) which substitute conventional internal combustion engine vehicle. However, these researches and productions are restricted to mainly passenger cars. Because of cost and physical problems, commercial vehicles are difficult to evaluate fuel economy. So simulations are important and it is necessary to know how sensitive parameters that enter into simulation affect. In this paper, forward simulations using AVL Cruise were conducted for analysis of fuel economy for parallel hybrid bus and were repeated by changing each parameter. Based on these results, root mean square errors (RMSE) are calculated for analysis of fuel economy sensitivity. The number of target parameters are 15. These parameters were classified with high and low sensitivity parameter relatively.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.433-439
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• 2016

Several low-cost global navigation satellite system (GNSS) receivers do not support general range-domain correction, and DGNSS-CP (differential GNSS) method had been suggested to solve this problem. It improves its position accuracy by projecting range-domain corrections to the position-domain and then differentiating the stand-alone position by the projected correction. To project the range-domain correction, line-of-sight vectors from the receiver to each satellite should be calculated. The line-of-sight vectors can be obtained from GNSS broadcast ephemeris data or satellite direction information, and this paper shows positioning performance for the two methods. Stand-alone positioning result provided from Septentrio PolaRx4 Pro receiver was used to show the difference. The satellite direction information can reduce the computing load for the DGNSS-CP by 1/15, even though its root mean square(RMS) of position error is bigger than that of ephemeris data by 0.1m.

• Smart Structures and Systems
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• v.15 no.4
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.393-400
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• 2016

Recently, there have been various researches on efficient and automatic analysis on urban environment methods that utilize the computer vision and machine learning technology. Among many new analyses, urban safety analysis has received a major attention. In order to predict more accurately on safety score and reflect the human visual perception, it is necessary to consider the generic and local information that are most important to human perception. In this paper, we use Double-column Convolutional Neural network consisting of generic and local columns for the prediction of urban safety. The input of generic and local column used re-sized and random cropped images from original images, respectively. In addition, a new learning method is proposed to solve the problem of over-fitting in a particular column in the learning process. For the performance comparison of our Double-column Convolutional Neural Network, we compare two Support Vector Regression and three Convolutional Neural Network models using Root Mean Square Error and correlation analysis. Our experimental results demonstrate that our Double-column Convolutional Neural Network model show the best performance with Root Mean Square Error of 0.7432 and Pearson/Spearman correlation coefficient of 0.853/0.840.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.955-966
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• 2010

Canonical correlation biplot is a useful biplot for giving a graphical description of the data matrix which consists of the association between two sets of variables, for detecting patterns and displaying results found by more formal methods of analysis. Nevertheless, when some values are missing in data, most biplots are not directly applicable. To solve this problem, we estimate the missing data using the median, mean, EM algorithm and MCMC imputation methods according to missing rates. Even though we estimate the missing values of biplot of incomplete data, we have different shapes of biplots according to the imputation methods and missing rates. Therefore we use a RMS(root mean square) which was proposed by Shin et al. (2007) and PS(procrustes statistic) for measuring and comparing the shape variability between the original biplots and the estimated biplots.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.146-151
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• 2014

This paper analyzes the previous Anjok model of the Gayageum and describes a method to improve the frequency modeling based on previous model. In the previous work, relation between the fundamental frequency and Anjok's location on the body is assumed as an exponential function and these frequencies are integrated by a first-order leaky integrator. Finally, a parameter of the formula to calculate the fundamental frequency is obtained by applying integrated frequencies to the linear regression. This model shows 2.5 Hz absolute deviation on average and has maximum error 7.75 Hz for the low fundamental frequencies. In order to overcome this problem, this paper proposes that the Anjok's locations are grouped according to the rate of error increase and linear regression is applied to each group. To find the optimal parameter, the RMSE(Root Mean Square Error) between measured and calculated fundamental frequencies is used. The proposed model shows substantial reduction in errors, especially maximum three times.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.3
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• pp.221-228
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• 2016

In this paper, we introduce our simulation software for EEG signal accuracy improvement. Users can check and train own EEG signal accuracy using our simulation software. Subjects were shown emotional imagination condition with landscape photography and logical imagination condition with a mathematical problem to subject. We use that EEG signal data, and apply Independent Component Analysis algorithm for noise removal. So we can have beta waves(${\beta}$, 14-30Hz) data through Band Pass Filter. We extract feature using Root Mean Square algorithm and That features are classified through Support Vector Machine. The classification result is 78.21% before EEG signal accuracy improvement training. but after successive training, the result is 91.67%. So user can improve own EEG signal accuracy using our simulation software. And we are expecting efficient use of BCI system based EEG signal.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.285-289
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• 2004

Recently, due to the high development of the internet, needs for multimedia streams such as digital audio and video is increasing much more. In case of transmitting multimedia streams using the User Datagram Protocol (UDP), it may cause starvation of TCP traffic on the same transmission path, thus resulting in congestion collapse and enormous delay because UDP does not perform TCP-like congestion control. Because of this problem, diverse researches are being conducted on new transmission schemes and protocols intended to efficiently reduce the transmission delay of real-time multimedia streams and perform congestion control. The TCP-friendly congestion control schemes can be classified into the window-based congestion control, which uses the general congestion window management function, and the rate-based congestion control, which dynamically adjusts transmission rate by using TCP modeling equations and the like. In this paper, we suggest the square-root congestion avoidance algorithm with the hybrid TCP-friendly congestion control scheme which the window-based and rate-based congestion controls are dealt with in a combined way. We apply the proposed algorithm to the existing TEAR. We simulate the performance of the proposed TEAR by using NS, and the result shows that it gives better improvement in the stability needed for providing congestion control than the existing TEAR.