• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.660-667
• /
• 2006

This paper presents a novel region-based snake method for vessel segmentation. According to geometric shape analysis of the vessel structure with different scale, an efficient statistical estimation of vessel branches is introduced into the energy objective function, which applies not only the vessel intensity information, but also geometric information of line-like structure in the image. The defined energy function is minimized using the gradient descent method and a new region-based speed function is obtained, which is more accurate to the vessel structure and not sensitive to the initial condition. The narrow band algorithm in the level set framework implements the proposed method, the solution of which is steady. The segmentation experiments are shown on several images. Compared with other geometric active contour models, the proposed method is more efficient and robust.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.901-905
• /
• 2005

It is very important to arrange landmarks when a mobile robot needs to measure its own location. So, it has been discussed often how to arrange landmarks in the optimal way until now. We, there, chose the RFID (Radio frequency Identification) tags as landmarks which can be observed by a mobile robot, and demonstrated the possibility of the optimal arrangement of them. For this work first, we defined the optimization problem and its parameters for the arrangement of tags. Second, we proposed the algorithm which can be applied to the optimization problem. Finally we could obtain closely optimal and practical arrangement with the minimum number of landmarks which satisfied the necessary condition by experimentation.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.6
• /
• pp.440-447
• /
• 2013

In this paper, a higher harmonic control (HHC) methodology is applied to find the optimum input scenario for the vibratory hub loads reduction. A comprehensive aeroelastic analysis code, CAMRAD II, is used to model the HART (Higher-harmonic-control Aeroacoustic Rotor Test) II rotor, and parametric study is conducted for the best HHC inputs leading to a minimum vibration (MV) condition. The resulting outcomes are compared with the earlier HART II test results. It is indicated that the control input adopted in the MV condition showed less satisfactory results. The new MV condition obtained in the present investigation can achieve 45% lower vibration level than the baseline uncontrolled condition. The optimum HHC input results lead to 3/rev harmonic input having $0.8^{\circ}$ amplitude and $350^{\circ}$ phase angle. About 5% reduction in the required power is possible but accompanies with the increase of vibration level.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.170-178
• /
• 1994

The nearest neighbor classification rule is widely used because it is not only simple but the error rate is asymptotically less than twice Bayes theoretical minimum error. But the method basically use the whole training patterns as the reference vectors. so that both storage and classification time increase as the number of training patterns increases. LVQ(Learning Vector Quantization) resolved this problem by training the reference vectors instead of just storing the whole training patterns. But it is a heuristic algorithm which has no theoretic background there is no terminating condition and it requires a lot of iterations to get to meaningful result. This paper is to propose a new training method of the reference vectors. which minimize the given error function. The nearest neighbor network,the network version of the nearest neighbor classification rule is proposed. The network is funtionally identical to the nearest neighbor classification rule is proposed. The network is funtionally identical to the nearest neighbor classification rule and the reference vectors are represented by the weights between the nodes. The network is trained to minimize the error function with respect to the weights by the steepest descent method. The learning algorithm is derived and it is shown that the proposed method can adjust more reference vectors than LVQ in each iteration. Experiment showed that the proposed method requires less iterations and the error rate is smaller than that of LVQ2.

• Journal of Microbiology and Biotechnology
• /
• v.20 no.4
• /
• pp.835-843
• /
• 2010

The objectives of this study were to investigate the effect of fermentation medium on the hydroxyl radical scavenging activity of exopolysaccharides from Inonotus obliquus by response surface methodology (RSM). A two-level fractional factorial design was used to evaluate the effect of different components of the medium. Corn flour, peptone, and $KH_2PO_4$ were important factors significantly affecting hydroxyl radical scavenging activity. These selected variables were subsequently optimized using path of steepest ascent (descent), a central composite design, and response surface analysis. The optimal medium composition was (% w/v): corn flour 5.30, peptone 0.32, $KH_2PO_4$ 0.26, $MgSO_4$ 0.02, and $CaCl_2$ 0.01. Under the optimal condition, the hydroxyl radical scavenging rate (49.4%) was much higher than that using either basal fermentation medium (10.2%) and single variable optimization of fermentation medium (35.5%). The main monosaccharides components of the RSM optimized polysaccharides are rhamnose, arabinose, xylose, mannose, glucose, and galactose with molar proportion at 1.45%, 3.63%, 2.17%, 15.94%, 50.00%, and 26.81%.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2011.11a
• /
• pp.135-138
• /
• 2011

As a basic research for the development of Korean lunar lander, propulsion system development for ground test is in progress. Thrust for descent is 200 N class. Design target is 220 N in vacuum thrust at 100 g/s flow rate, 200 psi chamber pressure. For ground test, thrust measurement system using LM guide was developed and test was performed. The result shows 160 N thrust in atmosphere condition at 210 psi chamber pressure.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.7
• /
• pp.81-90
• /
• 2018

In this paper, reducing lense Vignetting effect and adaptive learning rate method are proposed to complement Scribner's neural network for nuc algorithm which is the effective algorithm in statistic SBNUC algorithm. Proposed reducing vignetting effect method is updated weight and bias each differently using different cost function. Proposed adaptive learning rate for updating weight and bias is using sobel edge detection method, which has good result for boundary condition of image. The ordinary statistic SBNUC algorithm has problem to compensate lense vignetting effect, because statistic algorithm is updated weight and bias by using gradient descent method, so it should not be effective for global weight problem same like, lense vignetting effect. We employ the proposed methods to Scribner's neural network method(NNM) and Torres's reducing ghosting correction for neural network nuc algorithm(improved NNM), and apply it to real-infrared detector image stream. The result of proposed algorithm shows that it has 10dB higher PSNR and 1.5 times faster convergence speed then the improved NNM Algorithm.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.6
• /
• pp.752-758
• /
• 2004

In this paper, we proposed an adaptivefuzzy sliding control algorithm using gradient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satistfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• Journal of the Korean Wood Science and Technology
• /
• v.38 no.1
• /
• pp.43-48
• /
• 2010

This study was aimed at offering basic data to develop a new use of sawdust and rice husk. The results of this study were as follows: In surface temperature of ceramics by resin impregnation rate, the velocity was great in the early time of heat transfer because the temperature precipitously increased to 10 minutes elapsed. Also, the surface temperature of ceramics manufactured in resin impregnation rate of 60~70% indicated the highest. Heat transfer was fast in terms of the changes in surface temperature of ceramics according to the carbonization temperature, as because the density of ceramics made on condition of the carbonization temperature of $1000^{\circ}C$and $1200^{\circ}C$ was high. Moreover, ceramics maintained heat for a long time because the descent velocity of surface temperature of ceramics was slower than that of heater.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.1 s.106
• /
• pp.27-33
• /
• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.