• Tribology and Lubricants
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• v.15 no.1
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• pp.8-16
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• 1999

The electrorheological (ER) behavior of suspensions in silicone oil of phosphoric ester cellulose powder (average particle size : 18$\pm$1 ${\mu}{\textrm}{m}$) was investigated on the elevated temperature up to 10$0^{\circ}C$. For development of anhydrous ER fluids using at wide temperature range, it should be researched to how the effect of temperature on the ER activities. As a first step, the anhydrous ER suspensions mixing with the phosphoric ester cellulose particles which were made from the phosphoric ester reaction of cellulose were measured. As increasing the temperature, not only the analysis of electrical properties such as dielectric constant current density and electrical conductivity but also the rheological properties of ER fluids were studied. From the experimental results, the temperature had a large influence to the ER properties of anhydrous ER fluids. The current density, conductivity and elecoorheological effect ($\tau$$_{A}$$\tau$$_{0}$) of phosphoric ester cellulose ER fluids were proportional to the temperature with power law. And the shear stress of them was closely related with the square of dielectric constant mismatch parameter ($\beta$$^2$) under constant shear rate and electric field.d.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.433-439
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• 2000

Lots of semi-active control devices have been developed in recent years because they have the best features of passive and active system. Especially, controllable magneto-rheological(MR) fluid devices have received significant attention in these area of research. The MR fluid is the material that reversibly changes from a free-flowing, linear viscous fluid to a semisolid with a controllable yield strength in milliseconds when exposed to a magnetic field. If the magnetic field is induced by moving a permanent magnet instead of applying current to a solenoid, it is possible to design a MR damper consuming low power because the power consumption is reduced at steady state. This paper proposes valve mode MR damper using permanent magnetic circuit that has wide range of operation with low power consumption and small size. To design a MR damper that has a large maximum dissipating torque and a low damping coefficient, a design parameter is adopted. The magnetic circuit, material of choke and choke type are selected experimentally with the design parameter. The behaviors of the damper are examined and torque tracking control using PID feedback controller is performed for step, ramp and sinusoidal trajectories.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.41-48
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• 2005

In this paper, we present a low complexity modified Gaussian model based pre-processing filter to improve the performance of H.264 compressed video. Video sequence captured by general imaging system represents the degraded version due to the additive noise which decreases coding efficiency and results in unpleasant coding artifacts due to higher frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In addition, in order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• Interaction and multiscale mechanics
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• v.2 no.4
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• pp.353-374
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• 2009

A new seamless multiscale simulation was developed for coupling the continuum model with its molecular dynamics. Kriging-based Finite Element Method (K-FEM) is employed to model the continuum base of the entire domain, while the molecular dynamics (MD) is confined in a localized domain of interest. In the coupling zone, where the MD domain overlaps the continuum model, the overall Hamiltonian is postulated by contributions from the continuum and the molecular overlays, based on a quartic spline scaling parameter. The displacement compatibility in this coupling zone is then enforced by the Lagrange multiplier technique. A multiple-time-step velocity Verlet algorithm is adopted for its time integration. The validation of the present method is reported through numerical tests of one dimensional atomic lattice. The results reveal that at the continuum/MD interface, the commonly reported spurious waves in the literature are effectively eliminated in this study. In addition, the smoothness of the transition from MD to the continuum can be significantly improved by either increasing the size of the coupling zone or expanding the nodal domain of influence associated with K-FEM.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.123-130
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• 2004

The automobile suspension system is composed of parts that affect performances of a vehicle such as ride quality, handling characteristics, straight performance and steering effort, etc. Moreover, by using the finite element analysis the cost for the initial design step can be decreased. In the design of a suspension system, usually system vibration and structural rigidity must be considered simultaneously to satisfy dynamic and static requirements simultaneously. In this paper, we consider the weight reduction and the increase of the first eigen-frequency of a suspension part, the upper control arm, especially using topology optimization and size optimization. Firstly, we obtain the initial design to maximize the first eigen-frequency using topology optimization. Then, we apply the multi-objective parameter optimization method to satisfy both the weight reduction and the increase of the first eigen-frequency. The design variables are varying during the optimization process for the multi-objective. Therefore, we can obtain the deterministic values of the design variables not only to satisfy the terms of variation limits but also to optimize the two design objectives at the same time. Finally, we have executed reliability based optimal design on the upper control arm using the Monte-Carlo method with importance sampling method for the optimal design result with 98％ reliability.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.22-28
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• 2017

The Convolutional Neural Network(CNN) can be divided into two stages: feature extraction and classification. The hyperparameters such as kernel size, number of channels, and stride in the feature extraction step affect the overall performance of CNN as well as determining the structure of CNN. In this paper, we propose a method to optimize the hyperparameter in CNN feature extraction stage using Parameter-Setting-Free Harmony Search (PSF-HS) algorithm. After setting the overall structure of CNN, hyperparameter was set as a variable and the hyperparameter was optimized by applying PSF-HS algorithm. The simulation was conducted using MATLAB, and CNN learned and tested using mnist data. We update the parameters for a total of 500 times, and it is confirmed that the structure with the highest accuracy among the CNN structures obtained by the proposed method classifies the mnist data with an accuracy of 99.28%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.726-747
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• 2013

In order to support a large number of mobile stations (MSs) with statistical multiplexing in cellular networks, a random access scheme is widely used for uplink (UL) bandwidth request (BR). In the design of a random access based BR scheme, there are two important requirements: short connection delay and diverse Quality of Services (QoSs) support. Such requirements are crucial for IMT-Advanced systems like IEEE 802.16m to provide various types of fourth generation (4G) data services. IEEE 802.16m provides advanced UL BR schemes for non-real time polling service (nrtPS) and best-effort (BE) service to meet the requirements of short connection time and multiple QoS level support. In order to provide short connection time and multiple QoS support, three-step and differentiated BR procedures are adopted. In this paper, a novel modelling of IEEE 802.16m contention based BR scheme is proposed that uses a 2-dimensional discrete time Markov chain. Both the short access delay three-step BR procedures and normal five-step BR procedure are considered in the model. Our proposed model also incorporates the IEEE 802.16m differentiated BR procedure. With the proposed model, we extensively evaluate the performance of IEEE 802.16m BR for two different service classes by changing QoS parameters, such as backoff window size and BR timer. Computer simulations are performed to corroborate the accuracy of the proposed model for various operation scenarios. With the proposed model, accurate QoS parameter values can be derived for the IEEE 802.16m contention-based BR scheme.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.513-518
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• 1996

This report presents a demonstration of application of realistic evaluation methodology to a posturated cold leg large break LOCA in a Westinghouse three-loop pressurized water reactor with 17$\times$17 fuel. The new method of this analysis can be divided into three distinct step: 1) Best Estimate Code Validation and Uncertainty Quantification 2) Realistic LOCA Calculation 3) Limiting Value LOCA Calculation and Uncertainty Combination RELAP5/MOD3/K ［1］, which was improved from RELAP5/MOD3.1, and CONTEMPT4/MOD5 code were used as a best estimate thermal-hydraulic model for realistic LOCA calculation. The code uncertainties which will be determined in step 1) were quantified already in previous study ［2］, and thus the step 2) and 3) for plant application were presented in this paper. The application uncertainty parameters are divided into two categories, i.e. plant system parameters and fuel statistical parameters. Single parameter sensitivity calculations were performed to select system parameters which would be set at their limiting value in Limiting Value Approach (LVA) calculation. Single run of LVA calculation generated 27 PCT data according to the various combinations of fuel parameters and these data provided input to response surface generation. The probability distribution function was generated from Monte Carlo sampling of a response surface and the upper 95$^{th}$ percentile PCT was determined. Break spectrum analysis was also made to determine the critical break size. The results show that sufficient LOCA margin can be obtained for the demonstration NPP.