• Transactions of the Korean hydrogen and new energy society
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• v.21 no.1
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• pp.1-11
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• 2010

Current distribution measurement technique based on a segmented bipolar plate (BP) has been widely adopted to visualize the distribution of current density in a polymer electrolyte membrane. However, a concern is raised how closely the current density of a segmented BP can approach that of a corresponding non-segmented membrane. Therefore, in this paper, the accuracy of the measurement technique is numerically evaluated by applying a three-dimensional, two-phase fuel cell model to a $100\;cm^2$ area fuel cell geometry in which segmented BPs and non-segmented membrane are combined together. The simulation results reveal that the errors between the current densities of the segmented BPs and non-segmented membrane indeed exist, predicting the maximum relative error of 33% near the U-turn regions of the flow-field. The numerical study further illustrates that the erroneous result originates from the BPs segmented non-symmetrically based on the flow channels that allows some currents bypassing flow channels to flow into its neighboring segment. Finally, this paper suggests the optimal way for bipolar plate segmentation that can minimize the deviation of current measured in a segmented BP from that of a corresponding membrane region.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.816-819
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• 2005

This paper proposes a coordinate correction technique using the transformation of 3D parabolic coordinate function and BP(Back Propagation) neural network in order to solve space distortion problem caused by using catadioptric camera. Although Catadioptric camera can obtain omni-directional image at all directions of 360 degrees, it makes an image distorted because of an external form of lens itself. Accordingly, To obtain transformed ideal distance coordinate information from distorted image on 3 dimensional space, we use coordinate transformation function that uses coordinates of a focus at mirror in the shape of parabolic plane and another one which projected into the shape of parabolic from input image. An error of this course is modified by BP neural network algorithm.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.92-100
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• 2020

Satellite-based argumentation systems (SBAS) is a system that enhances the accuracy, integrity, availability and continuity of GNSS navigation users by using geostationary orbit (GEO) satellites to send correction information and the failures of global navigation satellite system (GNSS) satellites in the form of messages. The correction information provided by SBAS is pseudorange error, satellite orbit error, clock error, and ionospheric delay error at 250 bps. Therefore, A lot of message processing are required for the SBAS navigation. There is a need to reduce SBAS time to first fix (TTFF) for using SBAS navigation in systems with short operating time. In this paper, A-SGNSS operation method was proposed for reducing SBAS TTFF. Also, A-SGNSS TTFF and availability were analyzed.

• Journal of Acupuncture Research
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• v.24 no.5
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• pp.207-217
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• 2007

Objectives: We investigated the safty of distilled Astragali Radix Herbal Acupuncture, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture on vital sign -BP, pulse, resperation-in adult man. Methods : We investigated on 106 healthy volunteers consisted of each 30 subjects in experiment (distilled Astragali Radix Herbal Acupuncture, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture) group and 30 subjects in control(Normal Saline) group. Study form was a randomized, placebo-controlled, double-blind clinical trial. 30 subjects in each experiment group were injected distilled Astragali Radix Herbal Acupuncture, Wild Ginseng Herbal Acupuncture, Rehmannia glutinosa Herbal Acupuncture at $GB_{21}$(Kyonjong) and 30 subjects in control group were injected Normal Saline at $GB_{21}$ (Kyonjong). except of 2 subjects(in control group) who can't be measured and 10 subjects(6 in experiment group and 4 in control group) who move or make unforceable error during measuring. Finally each 25. subject, subject, subject in experiment group and 24 subject in control group are studied. We measured resperation by PolyG-I and BP & pulse by electric manometer on 5 times : before injection per 5 minutes during and after injection per 10 minutes during 35 minutes. The SPSS 13.0 for windows was used to analyze the data and the Student t test(between two groups) were used to verify the result. Results : 1. After distilled Astragali Radix Herbal Acupuncture injection, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture , systolic BP is not significantly change in all experiment time. 2. After distilled Astragali Radix Herbal Acupuncture injection, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture , diastolic BP is not significantly change in all experiment time. 3. After distilled Astragali Radix Herbal Acupuncture injection, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture , pulse is not significantly change in all experiment time. 4. After distilled Astragali Radix Herbal Acupuncture injection, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture , resperation is not significantly change in all experiment time. Conclusions : The results suggest that distilled Astragali Radix Herbal Acupuncture, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture in healthy adult man don't influence vital sign within normal range. This result is derived from that distilled Astragali Radix Herbal Acupuncture, Wild Ginseng Herbal Acupuncture and Rehmannia glutinosa Herbal Acupuncture in healthy adult man are safety.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.3
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• pp.582-590
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• 1994

This paper introduce a highly verstile and simple data transmission system designed for commercial power distribution lines. The system operates on the DSSS principle but utilizes two independent carrier frequencies each represents polarity of DS MODEM outiputs. At the receiving terminal, outputs of two envelope detectors are directly applied to separate DS correlators before the two components are compared. The recovered signals which represents data and line noise are then compared at comparator. With the noise power greatly rudused at the correlator, the error rate of the data observed at comparator desplays great improvement comparing to the conventional FSK-DS system in which the detector output are compared before the correlator stage. Despite its simplest structure, the prototype MODEM transmitts 2400 bps with the error rate 10 , about 10dB improved compared to conventional FSK system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.4
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• pp.10-15
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• 1983

In this paper effective methods of demodulation and equalization in a 9600 bps modem have been studied. To reduce the number of multiplications required per symbol in demodula-tion, the method of using a decimation filter is presented. In the equalizer the optimum step size and the steady state mean-squared error (MSE) are obtained from computer simulation results. The performance of the first-order carrier phase tracking loop is compared with that of the second-order loop when carrier frequency offset exists. In addition, the finite word length effects in the equalizer are studied.

• Computers and Concrete
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• v.28 no.6
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• pp.635-642
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• 2021

In this paper, soft learning techniques are used to predict the ultimate torsional capacity of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. Soft computing techniques, namely Artificial Neural Network, trained by various back propagation algorithms, and Particle Swarm Optimization (PSO) algorithm, have been used to model and predict the torsional strength of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. The performance of each model has been evaluated by using statistical parameters such as coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The hybrid PSO NN model resulted in an R² of 0.9292 with an RMSE of 5.35 for training and an R² of 0.9328 with an RMSE of 4.57 for testing. Another model, ANN BP, produced an R² of 0.9125 with an RMSE of 6.17 for training and an R² of 0.8951 with an RMSE of 5.79 for testing. The results of the PSO NN model were in close agreement with the experimental values. Thus, the PSO NN model can be used to predict the ultimate torsional capacity of RC beams strengthened with FRP with greater acceptable accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.45-51
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• 2015

In this paper, we discuss the belief propagation decoding algorithm for polar codes. The performance of Polar codes for shorter lengths is not satisfactory. Motivated by this, we propose a novel technique to improve its performance at short lengths. We showed that the probability of messages passed along the factor graph of polar codes, can be increased by multiplying the current message of nodes with their previous message. This is like a feedback path in which the present signal is updated by multiplying with its previous signal. Thus the experimental results show that performance of belief propagation polar decoder can be improved using this proposed technique. Simulation results in binary-input additive white Gaussian noise channel (BI-AWGNC) show that the proposed belief propagation polar decoder can provide significant gain of 2 dB over the original belief propagation polar decoder with code rate 0.5 and code length 128 at the bit error rate (BER) of $10^{-4}$.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.151-155
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbance and performance improvement with the on-line learning in the position control of excavator attachment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.383-386
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• 1997

In this paper, We proposed a parallel structure of the Neural Network model to nonlinear complex system. Neural Network was used as basic model which has learning ability and high tolerence level. This paper, we used Neural Network which has BP(Error Back Propagation Algorithm) model. But it sometimes has difficulty to append characteristic of input data to nonlinear system. So that, I used HCM(hard c-Means) method of clustering technique to append property of input data. Clustering Algorithms are used extensively not only to organized categorize data, but are also useful for data compression and model construction. Gas furance, a sewage treatment process are used to evaluate the performance of the proposed model and then obtained higher accuracy than other previous medels.