• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.241-246
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• 2000

Blasting vibrations velocity had been used to design blasting pattern and predict damage-possibility of structures. As vibration levels are currently required to estimate the damage concerning human-body and livestock, so measured vibration velocities must be transformed into vibration levels. In this study, the digital filter program was developed to transform measured data into vibration levels. Simple harmonic vibrations and measured data obtained by Blastmate series (Instantel Inc.) were applied to the digital filter program. As a result, simple harmonic vibrations and measured data were successfully transformed into vibration levels using the developed program. Measured data from any instrument with ASCII output-function will similarly be transformed into level units.

• Journal of the Korean Ceramic Society
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• v.49 no.1
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• pp.111-117
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• 2012

Dependencies of thermal properties on the crystallization behavior of $0.9CaMgSi_2O_6-0.1MgSiO_3$ glass-ceramics were investigated as a function of heat-treatment temperature from $750^{\circ}C$ to $950^{\circ}C$. The crystallization behavior of the specimens depended on the heat-treatment temperature, which could be evaluated by differential thermal analysis (DTA), Fourier transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD) analysis by the Rietveld-reference intensity ratio (RIR) combined procedure. With an increase of the heat-treatment temperature, the thermal conductivity and thermal diffusivity of the heat-treated specimens increased. These results could be attributed to the increase of crystallization with heat-treatment temperature. However, the specific heat capacity of the heat-treated specimens was not affected by the heat-treatment temperature. The thermal conductivities measured from $25^{\circ}C$ to $100^{\circ}C$ were also discussed for application to lighting-emitting diode (LED) packages and substrate materials.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1060-1069
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• 2016

In this paper, we introduce the fingerprint recognition system based on Radial Basis Function Neural Network(RBFNN). Fingerprints are classified as four types(Whole, Arch, Right roof, Left roof). The preprocessing methods such as fast fourier transform, normalization, calculation of ridge's direction, filtering with gabor filter, binarization and rotation algorithm, are used in order to extract the features on fingerprint images and then those features are considered as the inputs of the network. RBFNN uses Fuzzy C-Means(FCM) clustering in the hidden layer and polynomial functions such as linear, quadratic, and modified quadratic are defined as connection weights of the network. Particle Swarm Optimization (PSO) algorithm optimizes a number of essential parameters needed to improve the accuracy of RBFNN. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. The performance evaluation of the proposed fingerprint recognition system is illustrated with the use of fingerprint data sets that are collected through Anguli program.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.118-125
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• 2003

This paper presents a scheme for the placement of dispersed generator systems(DGs) based on load model in unbalanced systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm The method proposed is applied to IEEE 13 bus unbalanced distribution systems to demonstrate its effectiveness.

• Biomedical Science Letters
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• v.11 no.2
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• pp.129-134
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• 2005

Three different deconvolution techniques for quantifying cerebral blood flow (CBF) from whole brain $T2^{\ast}-weighted$ bolus tracking images were implemented (parametric Fourier transform P-FT, parametric single value decomposition P-SVD and nonparametric single value decomposition NP-SVD). The techniques were tested on 206 regions from 38 hyperacute stroke patients. In the P-FT and P-SVD techniques, the tissue and arterial concentration time curves were fit to a gamma variate function and the resulting CBF values correlated very well $(CBF_{P-FT}\;=\;1.02{\cdot}CBF_{p-SVD},\;r^2\;=\;0.96)$. The NP-SVD CBF values correlated well with the P-FT CBF values only when a sufficient number of time series volumes were acquired to minimize tracer time curve truncation $(CBF_{P-FT}\;=\;0.92{\cdot}CBF_{NP-SVD},\;r^2\;=\;0.88)$. The correlation between the fitted CBV and the unfitted CBV values was also maximized in regions with minimal tracer time curve truncation $(CBV_{fit}\;=\;1.00{\cdot}CBV_{ Unfit},\;^r^2\;=\;0.89)$. When a sufficient number of time series volumes could not be acquired (due to scanner limitations) to avoid tracer time curve truncation, the P-FT and P-SVD techniques gave more reliable estimates of CBF than the NP-SVD technique.

• Journal of Power Electronics
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• v.18 no.3
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• pp.766-777
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• 2018

In this paper, a sliding mode and proportional plus integral (SM-PI) control combined with self-sustained phase shift modulation (SSPSM) for LLC resonant converters is presented. The proposed control scheme improves the transient response while preserving good steady-state performance. An averaged large signal model of an LLC converter with the ZVS modulation technique is developed for the SM control design. The sliding surface is obtained based on the input-output linearization concept. A system identification method is adopted to obtain the transform function of the LLC resonant converter, which is used to design the PI control. In order to reduce the inherent chattering problem in the steady state, the combined SM-PI control strategy is derived with fuzzy control, where the SM control is responsive during the transient state while the PI control prevails in the steady state. The combination of SSPSM and the SM-PI control provides ZVS operation, robustness and a fast transient response against step load variations. Simulation and experimental results validate the theoretical analysis and the attractive features of the proposed scheme.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.141-146
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• 2013

This research investigates the stability analysis for the rotating and the stationary grooved journal bearing. The dynamic coefficients of the journal bearing are calculated by using FEM and the perturbation method. When journal bearing is in whirling motion, the dynamic coefficients have time-varying components as a sine wave due to the reaction force of oil film toward the center of journal even in the steady state. The solutions for the equations of motion can be assumed as the Fourier series expansion. The equations of motion can be rewritten as the linear algebraic equations with respect to the Fourier coefficients. Then, stability of the grooved journal bearing can be calculated by Hill's infinite determinant. The periodic function of dynamic coefficients is derived using Fourier Fast Transform(FFT).The stability of journal bearing is determined as rotating speed increases and the stability of rotating grooved journal bearing is compared and discussed with the stability of stationary grooved journal bearing.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.184-193
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• 2001

In vector control technique, stator currents of an induction motor are transformed to equivalent d-q currents in a reference frame consist of d and q axis, each of which is coincide with flux and torque direction respectively. Since the current in q-axis is related to the torque in a synchronously rotating frame, torque is estimated as a function of q-axis current and flux. In this paper, a method to estimate torque of an induction motor based on the measurement of 3-phase currents and rotating velocity of a rotor is presented. Graphic-programming is used to measure signals, to estimate the torque and to show the result in the form of user friendly graph in window environment. To stabilize the fluctuation of estimated torque caused from the small measurement error of the rotor velocity, the stator current is reconstructed in a program based on measured signals. The experimental results executed under the velocity of 500 rpm, 1500 rpm without load and 1500 rpm with load show that the proposed method estimates the torque very well.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.125-132
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• 2007

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM), NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The eight most important coefficients of d3 and d4 are selected by the non-overlap area distribution measurement method. The selected 8 coefficients are used for 3 data sets showing reliable accuracy rates 99,80%, 99,21%, and 98.78%, respectively, which means the selected input features are less dependent to the data sets. The ECG signal segments and fuzzy membership functions of the 8 coefficients enable input features to interpret explicitly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.