• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.549-558
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• 2001

It is important to reuse existing motion capture data for reduction of the animation producing cost as well as efficiency of producing process. Because its motion curve has no control point, however, it is difficult to modify the captured data interactively. The motion transition is a useful method to reuse the existing motion data. It generates a seamless intermediate motion with two short motion sequences. In this paper, Uniform Posture Map (UPM) algorithm is proposed to perform the motion transition. Since the UPM is organized through quantization of various postures with an unsupervised learning algorithm, it places the output neurons with similar posture in adjacent position. Using this property, an intermediate posture of two active postures is generated; the generating posture is used as a key-frame to make an interpolating motion. The UPM algorithm needs much less computational cost, in comparison with other motion transition algorithms. It provides a control parameter; an animator could control the motion simply by adjusting the parameter. These merits of the UPM make an animator to produce the animation interactively. The UPM algorithm prevents from generating an unreal posture in learning phase. It not only makes more realistic motion curves, but also contributes to making more natural motions. The motion transition algorithm proposed in this paper could be applied to the various fields such as real time 3D games, virtual reality applications, web 3D applications, and etc.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4435-4439
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• 2012

Purpose: This study aimed to explore the role of the Twist gene in the epithelial-mesenchymal transition of ovarian cancer. Methods: An RNA interference plasmid expressing a small interfering RNA (siRNA)-targeting Twist (Twist siRNA vector) was designed, constructed, and transfected into the human ovarian cancer cell line A2780. Transfection efficiency was assessed under a fluorescence microscope. Changes in the expression of Twist mRNA in A2780 after transfection with the pGenesil Twist shRNA plasmid were analyzed through RT-PCR. MTT assays and adhesion experiments were applied to determine changes in proliferation and adhesion ability of A2870 after transfection with the Twist shRNA plasmid. Changes in the expression of the E-cadherin and N-cadherin proteins in A2780 after transfection with the Twist shRNA plasmid were analyzed using Western blotting. Result: The restructuring plasmid pGenesil-Twist shRNA was constructed successfully. After 48 h of culture, 80% of the cells expressed high-intensity GFP fluorescence and stability. The expression of Twist decreased significantly after the transfection of the Twist shRNA plasmid (P<0.05). Proliferation of the transfected Twist shRNA cells showed no difference with that of the A2780-nontransfection or A2780-si-control groups (P>0.05) but the adhesion ability of A2780 decreased dramatically (P<0.05). Expression of the E-cadherin protein increased, whereas that of the N-cadherin protein decreased compared with that in the A2780-nontransfection or A2780-si-control groups (P<0.05). Conclusion: Twist is essential for epithelial-mesenchymal transition, invasion, and metastasis of ovarian cancer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1652-1656
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• 2014

In this work, we demonstrated a 77 GHz waveguide VCO with transition from WR-12 to WR-10 for anti-collision radar applications. The fabricated waveguide VCO consists of a GaAs-based Gunn diode, a varactor diode, a waveguide transition, and two bias posts for operating as a LPF and a resonator. The cavity is designed for fundamental mode at 38.5 GHz and operated at second hormonic of 77 GHz. The waveguide transition has a 1.86 dB of insertion loss and -30.22 dB of S11 at the center frequency of 77 GHz. The fabricated VCO achieves an oscillation bandwidth of 870 MHz. Output power is from 12.0 to 13.75 dBm and phase noise is -100.78 dBc/Hz at 1 MHz offset frequency from the carrier.

• Journal of Hydrogen and New Energy
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• v.29 no.6
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• pp.635-641
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• 2018

To select the operating condition of 0.5 MWth chemical looping combustion system, minimum fluidization velocity, transition velocity to fast fluidization and solid circulation rate were measured using mass produced new oxygen carrier (N016-R4) which produced by spray drying method for 0.5 MWth chemical looping combustion system. A minimum fluidization velocity decreased as the pressure increased. The measured transition velocity to fast fluidization was 2.0 m/s at ambient temperature and pressure. The measured solid circulation rate increased as the solid control valve opening increased. We could control the solid circulation rate from 26 to $93kg/m^2s$. Based on the measured minimum fluidization velocity and transition velocity to fast fluidization, we choose appropriate operating conditions and demonstrated continuous solid circulation at high pressure condition (5 bar-abs) up to 24 hours.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.10
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• pp.470-476
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• 2005

In this paper PU control scheme is presented. The proposed scheme has following features. The one is oft-starting method which is used for preventing to flow large current in motor phase winding when motor starts. The ther is the selection of the level of the over current. The first feature is implemented by increasing the PWM duty lowly, the second feature is implemented by limiting the magnitude of the phase current level by which the over heat f motor by copper losses and magnetic saturation decreases. By the analysis using FEM considering load condition, the peed of mode transition from PW to single pulse control is selected and confirmed by simulation that there is no ver current occurs during the mode transition. For the verification of proposed scheme, the simulation using MATLAB Simulink with considering non-linearity of inductance profile from FEM analysis is performed and the experiment with SRM drive system which has the DSP controller and single Phase SRM are peformed.

• Vacuum Magazine
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• v.5 no.1
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• pp.13-17
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• 2018

Phase transition is not unique to solid state systems or homogeneous molecular systems but it is also observed in highly heterogeneous biological systems. Phase transition and phase separation in cells are recently being found to be central to many biological functions by temporarily and locally controlling the storage and exchange of certain proteins and RNAs. There are also clues suggesting them to be playing pivotal roles in the spatial organization of chromosomes into topological domains and its time-dependent control. Here we introduce early efforts to explain at the molecular level how the spatiotemporal organization of chromosomes are programmed and modulated by the sequence and chemical modifications of the DNA. Continuing works may provide a physical framework to understand the molecular level control of chromosome structure and dynamics that determine the epigenetic state and the fate of the cells.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.763-770
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• 2004

The important issue of emotion recognition from speech is a feature extracting and pattern classification. Features should involve essential information for classifying the emotions. Feature selection is needed to decompose the components of speech and analyze the relation between features and emotions. Specially, a pitch of speech components includes much information for emotion. Accordingly, this paper searches the relation of emotion to features such as the sound loudness, pitch, etc. and classifies the emotions by using the statistic of the collecting data. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.694-700
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• 1998

A novel zero-voltage-transition (ZVT) isolated PWM boost converter for single stage power factor correction (PFC) is presented to improve the performance of the previously presented ZVT converter[8]. A simple auxiliary circuit which includes only one active switch provides zero-voltage-switching (ZVS) condition to all semiconductor devices. (Two active switches are required for the previous ZVT converter) This leads to reduced cost and simplified control circuit comparing to the previous ZVT converter. The ZVS is achieved for wide line and load ranges with minimum device voltage and current stresses. Operation principle, control strategy and features of the proposed converter are presented and verified by the experimental results from a 1.5 kW, 100 KHz laboratory prototype.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.354-361
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• 2004

To improve fault isolation performance of the Bayes isolator, this paper proposes the Fuzzy-Bayes isolator, which uses the Fuzzy-Bayes classifier as a fault isolator. The Fuzzy-Bayes classifier is composed of the Bayes classifier and weighting factor, which is determined by fuzzy inference logic. The Mahalanobis distance derivative is mapped to the weighting factor by fuzzy inference logic. The Fuzzy-Bayes fault isolator is designed for the BLDC motor fault diagnosis system. Fault isolation performance is evaluated by the experiments. The research results indicate that the Fuzzy-Bayes fault isolator improves fault isolation performance and that it can reduce the transition region chattering that is occurred when the fault is injected. In the experiment, chattering is reduced by about half that of the Bayes classifier's.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.