• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.11
• /
• pp.7754-7760
• /
• 2015

The outer tie rod is one of the part of steering system, the optimization process was executed to find the lightweight design. The inner tie rod was considered in the optimum design of an outer tie rod. it could be closer to the test condition than in the case of considering outer tie rod only. The aluminum forging material was considered as a weight reduction proposal. The target of optimization was the shape of the minimum weight to resist at the load of buckling. RSM and Kriging interpolation method were applied as a optimization method to consider the nonlinear shape optimization problem. Then, 16.3%, 16.6% of weight reduction was obtained from the result comparing with that of the initial model. The results of meta model optimization was compared with that of finite element method. The error values of buckling load estimation were 2.6%, 2.04%. and those of weight estimation were 0.17%, 0.13%. Therefore, it seemed that the result of Kriging model could be obtained closer to optimum value than that of RSM model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.7
• /
• pp.3508-3517
• /
• 2013

District is not only a place that every urban activities are executing but also basic unit that are forming urban structure. Therefore this study tried to make land use-transportation model through analyzing $CO_2$ exhausting volumes by assuming 270 scenarios those are postulated various land use patterns and transport policies in District. As results, this study shows best District Unit Design technique is the policy that develop equally all blocks or only outer blocks and introduction of car free zone to inner 2 way streets. Most important policy in order to reduce $CO_2$ gas is to introduce Transportation Demand Management especially in case of hyper high density development. In case of low density development, policy of car free streets in 2 ways roads is efficiency for reducing $CO_2$ gas. And suggested land use-transportation model will be good for choosing alternatives those are able to reduce $CO_2$ in District Unit.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.2
• /
• pp.817-821
• /
• 2012

In this paper we applied the optimal mixture number estimation technique in GMM(Gaussian mixture model) using BIC(Bayesian information criterion) and MDL(minimum description length) as a model selection criterion for environmental sounds recognition. In the experiment, we extracted 12 MFCC(mel-frequency cepstral coefficients) features from 9 kinds of environmental sounds which amounts to 27747 data and classified them with GMM. As mentioned above, BIC and MDL is applied to estimate the optimal number of mixtures in each environmental sounds class. According to the experimental results, while the recognition performances are maintained, the computational complexity decreases by 17.8% with BIC and 31.7% with MDL. It shows that the computational complexity reduction by BIC and MDL is effective for environmental sounds recognition using GMM.

• Journal of Soil and Groundwater Environment
• /
• v.21 no.4
• /
• pp.30-41
• /
• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.13 no.1
• /
• pp.75-85
• /
• 2000

When applying a system identification technique, which incorporates an experimental model to a corresponding finite element model of a structure, one of the major problems is the large difference in the numbers of degrees of freedom (dof) between the two models. While there are large number of dofs in a finite element model, the number of measurement points is practically limited. So it is very difficult to incorporate them. Especially rotational dofs are hard to measure. In this study a method is presented for estimating structural dynamic responses at unmeasurable locations in frequency domain. The proposed method is tested numerically and the feasibility for practical application has been demonstrated through an example structure under moving loads, where translational and rotational dofs of beam at a center point are estimated from the partial measurements of responses at accessible points.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.11 no.1
• /
• pp.106-113
• /
• 1997

In this paper, we introduce the design method using CAE(Computer Aided Engineering) which is profitable in the compatibility and standardization of the developed product and in the reduction of construction time and price to develop and design a machine equipment. Particularly, we select the standard model to design ot develop from the large machinery to the super precision one, extract the peculiar characters of the model by the close analysis of the physical and technical part, can predict the previous result of experimental characteristics on objective dimensions through the analogical mathematical analysis, and can induce the design model demanded by user investigating optimal data in advance. We present the analogical algorithms and process method of design factors and restriction factors in the systematization design with computer. Then we analyze step functions for each systematization equipment and induce the process of technical data with actuator model.

• Structural Engineering and Mechanics
• /
• v.52 no.5
• /
• pp.1019-1032
• /
• 2014

Rails are key elements in railway superstructure since these elements receive directly the train load transmitted by the wheels. Simultaneously, rails must provide effective stress transference to the rest of the track elements. This track element often deteriorates as a consequence of the vehicle passing or manufacturing imperfections that cause in rail several defects. Among these rail defects, transverse cracks highlights and are considered a severe pathology because they can suddenly trigger the rail failure. This study is focused on UIC-60 rails with transverse cracks. A 3-D FEM model is developed in ANSYS for the flawless rail in which conditions simulating the crack presence are implemented. To account for the inertia loss of the rail as a consequence of the cracking, a reduction of the bending stiffness of the rail is considered. The numerical models have been calibrated using the first four bending vibration modes in terms of frequencies. These vibration frequencies have been obtained using the Experimental Modal Analysis technique, studying the changes in the modal parameters of the rails induced by the crack and comparing the results obtained by the model with experimental results. Finally, the calibrated and validated models for the single rail have been implemented in a complete railway ballasted track FEM model in order to study the static influence of the cracks on the rail deflection caused by a load passing.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.5
• /
• pp.533-539
• /
• 2019

This study proposes a malware classification model that can handle arbitrary length input data using the Microsoft Malware Classification Challenge dataset. We are based on imaging existing data from malware. The proposed model generates a lot of images when malware data is large, and generates a small image of small data. The generated image is learned as time series data by Dynamic RNN. The output value of the RNN is classified into malware by using only the highest weighted output by applying the Attention technique, and learning the RNN output value by Residual CNN again. Experiments on the proposed model showed a Micro-average F1 score of 92% in the validation data set. Experimental results show that the performance of a model capable of learning and classifying arbitrary length data can be verified without special feature extraction and dimension reduction.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.101-112
• /
• 2024

Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.9 no.5 s.45
• /
• pp.41-52
• /
• 2005

Using the variable control gain scheme on the basis of fuzzy-based decision-making process, Fuzzy supervisory control (FSC) technique exhibits better control performance than linear control technique with one static control gain. This paper demonstrates the effectiveness of the FSC technique by evaluating the robust performance of the FSC technique under the presence of uncertainties in the models and the excitations. Robust performance of the FSC system is compared with that of optimally designed LQG control system for the benchmark cable-stayed bridge presented by Dyke et al. Parameter studies on the robust performance evaluation are carried out by varying the stiffness of the bridge model as well as the magnitudes of several earthquakes with different frequency contents. From the comparative study of two control systems, FSC system shows the enhanced control performance against various magnitudes of several earthquakes while maintaining lower level of power required for controlling the bridge response. Especially, FSC system clearly guarantees the improved robust performance of the control system with stable reduction effects on the seismic responses and slight increases in total power and stroke for the control system, while LQG control system exhibits poor robust performance.