• Journal of Aquaculture
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• v.16 no.3
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• pp.142-150
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• 2003

Performance of a biological filter, the rotating biological contactor (RBC), is affected by rotational speed and hydraulic residence time (HRT). A RBC with a disc diameter of 62 cm, total surface area of 48.28 $m^2$, volume of 0.34 ㎥, and submergence ratio of 35.4% was tested for the combinations of five rotational speeds (1, 2, 3, 4 & 5 rpm) and three HRT (0.5, 1.0 & 2.0 hr) to find out the maximum removal efficiencies of total ammonia nitrogen (TAN) and nitrite nitrogen of a simulated recirculating aquaculture system. Ammonia loading rate in the system was 25 g of TAN/ ㎥. day. Removal efficiencies were checked when TAN concentrations in the system stabilized for 3 days in each treatment. The concentration of TAN in the system decreased with increasing rotational speed of the RBC up to 4 rpm in all HRT (P<0.05). At the rotational speed of 5 rpm, the efficiencies decreased in all HRT (P<0.05). When the rotational speeds were 1, 2, 3, 4, and 5 rpm, TAN concentrations in the system were 1.35, 0.94, 0.69, 0.66, and 0.76 mg/L at the 0.5 hr HRT, 2.86, 1.18, 0.96, 0.87, and 1.11 mg/L at the 1.0 hr HRT, and 5.30, 2.44, 1.99, 1.77, and 2.01 mg/L at the 2.0 hr HRT, respectively. The TAN removal efficiencies of the RBC at the rotational speeds of 1, 2, 3, 4, and 5 rpm were 32.9, 49.5, 65.1, 72.9, and 62.9% in 0.5 hr HRT,33.1, 74.1, 87.1, 95.8, and 78.5% in 1.0 hr HRT, and 35.5, 76.7, 89.6, 97.0, and 85.5% in 2.0 hr HRT, respectively. TAN removal efficiency of RBC per pass increased with increasing HRT. However, TAN concentration in the system also increased. The best operating condition among the treatments was obtained at the treatment of 0.5 hr HRT and 4 rpm (P<0.05). The TAN concentration was 0.66 mg/L. Concentrations of nitrite nitrogen (NO$_2$$^{[-10]}$ -N) in the system decreased with increasing rotational speed in all HRT while that in the system increased with increasing HRT in all rotational speeds. The ranges of NO$_2$$^{[-10]}$ -N concentrations at HRT of 0.5, 1.0, and 2.0 hr in the system were 0.26~0.32, 0.31~0.56, and 0.43~l.45 mg/L, respectively. The ranges of daily removal rates of TAN in this system were 20.03~23.0 g TAN/㎥ㆍday and those of nitrite nitrogen were 19.65~30.25 g NO$_2$$^{[-10]}$ -N/㎥ㆍday.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.65-72
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• 2010

We propose the asymmetric 2.5Gbps/622Mbps PON(Passive Optical Network) in order to reduce the bandwith of filter at receiver with inverse RZ(Return to Zero) code coded downstream and NRZ(Non Return to Zero) upstream re-modulation. I theoretically analyze BER(Bit Error Rate) performance and the power sensitivity with the optimal threshold level by performing simulation with MATLAB according to the types of downstream data. The results have shown that the optimal threshold level at the optical receiver could be saturated at 0.33 as the optical received power increase more than -26dBm to keep $10^{-12}$ of BER to a minimum. Also the power sensitivity is more improved by about 3dB by fixing the threshold level at 0.33 than the conventional receiver. The proposed system can be a useful technology for optical access networks with asymmetric upstream and downstream data rates because the optical receiver can be used without controlling threshold levels and that does not require a light source in optical network unit (ONU) and its control circuits in the optical line termination (OLT).

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.1-6
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• 2014

In this study, we propose optimized RBFNNs based on night vision face recognition simulator with the aid of $(2D)^2$ PCA algorithm. It is difficult to obtain the night image for performing face recognition due to low brightness in case of image acquired through CCD camera at night. For this reason, a night vision camera is used to get images at night. Ada-Boost algorithm is also used for the detection of face images on both face and non-face image area. And the minimization of distortion phenomenon of the images is carried out by using the histogram equalization. These high-dimensional images are reduced to low-dimensional images by using $(2D)^2$ PCA algorithm. Face recognition is performed through polynomial-based RBFNNs classifier, and the essential design parameters of the classifiers are optimized by means of Differential Evolution(DE). The performance evaluation of the optimized RBFNNs based on $(2D)^2$ PCA is carried out with the aid of night vision face recognition system and IC&CI Lab data.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.347-354
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• 2009

Physical properties of rocks are strongly dependant on details of pore micro-structures, which can be used for quantifying relations between physical properties of rocks through pore-scale simulation techniques. Recently, high-resolution scan techniques, such as X-ray microtomography and high performance computers make it possible to calculate permeability from pore micro-structures of rocks. We try to extend this simulation methodology to velocity and electrical conductivity. However, the smoothing effect during tomographic inversion creates artifacts in pore micro-structures and causes inaccurate property estimation. To mitigate this artifact, we tried to use sharpening filter and neural network classification techniques. Both methods gave noticeable improvement in pore structure imaging and accurate estimation of permeability and electrical conductivity, which implies that our method effectively removes the smoothing effect in pore structures. However, the calculated velocities showed only incremental improvement. By comparison between thin section images and tomogram, we found that our resolution is not high enough, and it is mainly responsible for the inaccuracy in velocity despite the successful removal of the smoothing effect. In conclusion, our methods can be very useful for pore-scale modeling, since it can create accurate pore structure without the smoothing effect. For accurate velocity estimation, the resolution of pore structure should be at least three times higher than that for permeability simulation.

• Korean Chemical Engineering Research
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• v.50 no.2
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• pp.310-316
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• 2012

The chromaticity of polyethylene glycol (PEG) generated from the recyling of a silicone slurry waste was improved by using activated carbon powder and a carbon filter. The color change of the PEG waste was investigated by changing the amount of adsorbent, adsorption time and temperature. The surface area of activated carbon did not have a significant impact on improving the color of the PEG waste. According to the results for the APHA color variation of the PEG waste changing the amount of the carbon adsorbent, the optimal usage to achieve the low APHA value was 100~150 mg-C/g-PEG. From the investigatnion on the effect of the adsorption temperature range from $25^{\circ}C$ to $100^{\circ}C$, it was found that the optimal temperatures were $40{\sim}50^{\circ}C$ in terms of achieving the lowest APHA value. The variation of the APHA color was investigated by changing the operation condition of the activated carbon filters. The use of ACF was a good way to enhance the chromaticity of the PEG waste. As a result, the APHA value of the PEG waste (APHA=53 at the initial waste) was reduced to be 10 through the ACF purification. It was also confirmed that the performance of the used carbon adsorbent can be recovered by the washing with purified water.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.802-810
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• 2006

For a thorough train control, the precise train position detection is necessarily required. The widely used current way for train position detection is the one of using track circuits. The track circuit has a simple structure, and has a high level of reliability. However trains can be detected only on track circuits, which have to be installed on all ground sections, and much amount of cost for its installation and maintenance is needed. In addition, for the track circuit, only discontinuous position detection is possible because of the features of the closed circuit loop configuration. As the recent advances in telecommunication technologies and high-tech vehicle-based control equipments, for the train position detection, the method to detect positions directly from on trains is being studied. Vehicle-based position detection method is to estimate train positions, speed, timing data continuously, and to use them as the control information. In this paper, the features of GPS navigation and DR navigation are analyzed, and the navigation filters are designed by constructing vehicle-based train position detection method by combining GPS navigation and DR navigation for their complementary cooperation, and by using kalman filter. The position estimation performance of the proposed method is also confirmed by simulations.

• Korean Chemical Engineering Research
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• v.56 no.2
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• pp.281-290
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• 2018

As the internal combustion engine vehicles of high fuel efficiency and low emission are demanded, it becomes important to procure technologies for improving low-temperature performance of automotive catalyst systems. In this study, we showed that the combustion rate of diesel particulate matter is greatly enhanced at low temperature by applying fuel-borne catalyst and perovskite catalyst concurrently. It was tried to examine the correlation between elemental composition of perovskite catalyst and combustion activity of mixed catalyst system. To achieve this goal, we applied temperature-programmed oxidation technique in testing the combustion behavior of perovskite-mixed particulate matter bed which contained the element of fuel-borne catalyst or not. We tried to explain the synergetic action of two catalyst components by comparing the trends of concentrations of carbon dioxide and nitrogen oxide in temperature-programmed oxidation results.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.147-156
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• 2011

This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI's DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.

• Journal of Astronomy and Space Sciences
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• v.26 no.2
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• pp.229-236
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• 2009

KOorea Multi-purpose SATellite(KOMPSAT)-5 will be launched at 550km altitude in 2010. Accurate satellite position(20 cm) and velocity(0.03 cm/s) are required to treat highly precise Synthetic Aperture Radar(SAR) image processing. Ionosphere delay was eliminated using dual frequency GPS data and double differenced GPS measurement removed common clock errors of both GPS satellites and receiver. SAC-C carrier phase data with 0.1 Hz sampling rate was used to achieve precise orbit determination(POD) with ETRI GNSS Precise Orbit Determination(EGPOD) software, which was developed by ETRI. Dynamic model approach was used and satellite's position, velocity, and the coefficients of solar radiation pressure and drag were adjusted once per arc using Batch Least Square Estimator(BLSE) filter. Empirical accelerations for sinusoidal radial, along-track, and cross track terms were also estimated once per revolution for unmodeled dynamics. Additionally piece-wise constant acceleration for cross-track direction was estimated once per arc. The performance of POD was validated by comparing with JPL's Precise Orbit Ephemeris(POE).

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.567-584
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• 2004

As XML becomes popular as the way of presenting information on the web, how to secure XML data becomes an important issue. So far study on XML security has focused on security of data communications by using digital sign or encryption technology. But, it now requires not just to communicate secure XML data on communication but also to manage query process to access XML data since XML data becomes more complicated and bigger. We can manage XML data queries by access control technique. Right now current XML data access control only deals with read operation. This approach has no option to process update XML queries. In this paper, we present XML access control model and technique that can support both read and update operations. In this paper, we will propose the operation for XML document update. Also, We will define action type as a new concept to manage authorization information and process update queries. It results in both minimizing access control steps and reducing memory cost. In addition, we can filter queries that have no access rights at the XML data, which it can reduce unnecessary tasks for processing unauthorized query. As a result of the performance evaluation, we show our access control model is proved to be better than other access control model in update query. But it has a little overhead to decide action type in select query.