• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.91-98
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• 2008

This work was performed to develop a model possible to predict the influent flow and influent components, which are one of main disturbances causing process problems at the operation of municipal wastewater treatment plant. In this study, artificial neural network (ANN) was used in order to develop a model that was able to predict the influent flow, $COD_{Mn}$, SS, TN 1 day-ahead, 2day-ahead and 3 day ahead. Multi-layer feed-forward back-propagation network was chosen as neural network type, and tanh-sigmoid function was used as activation function to transport signal at the neural network. And Levenberg-Marquart (LM) algorithm was used as learning algorithm to train neural network. Among 420 data sets except missing data, which were collected between 2005 and 2006 at field plant, 210 data sets were used for training, and other 210 data sets were used for validation. As result of it, ANN model for predicting the influent flow and components 1-3day ahead could be developed successfully. It is expected that this developed model can be practically used as follows: Detecting the fault related to effluent concentration that can be happened in the future by combining with other models to predict process performance in advance, and minimization of the process fault through the establishment of various control strategies based on the detection result.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.125-132
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• 2010

The authors have investigated the acoustic field analysis using the Constrained Interpolation Profile(CIP) Method recently proposed by Yabe. This study has examined the calculation accuracy of the three-dimensional(3-D) acoustic field analysis using the type C CIP method. In this paper we show phase error of type C CIP method and the dependence on the wave-propagation direction in the type C CIP acoustic field analysis, and then demonstrate that it gives less-diffusive results than conventional analysis. Moreover, in comparison between type C-1 CIP, type C-2 CIP, type M CIP and FDTD, reports the memory requirements and calculation time of each method.

• Geotechnical Engineering
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• v.10 no.3
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• pp.79-96
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• 1994

A tunnel design expert system entitled NESTED is developed using the artificial neural network. The expert system includes three neural network computer models designed for the stability assessment of underground openings and the estimation of correlation between the RMR and Q systems. The expert system consists of the three models and the computerized rock mass classification programs that could be driven under the same user interface. As the structure of the neural network, a multi -layer neural network which adopts an or ror back-propagation learning algorithm is used. To set up its knowledge base from the prior case histories, an engineering database which can control the incomplete and erroneous information by learning process is developed. A series of experiments comparing the results of the neural network with the actual field observations have demonstrated the inferring capabilities of the neural network to identify the possible failure modes and the support timing. The neural network expert system thus complements the incomplete geological data and provides suitable support recommendations for preliminary design of tunnels in rock masses.

• The Journal of Information Technology
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• v.5 no.4
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• pp.1-8
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• 2002

This thesis is about power line communication(PLC) over the low voltage grid. The main advantage with power line communication is the use of an existing infrastructure. The PLC channel can be modeled as having multi-path propagation with frequency-selective fading, typical power lines exhibit signal attenuation increasing with length and frequency. OFDM(Orthogonal Frequency Division Multiplexing) is a modulation technique where multiple low data rate carriers are combined by a transmitter to form a composite high data rate transmission. To implement the multiple carrier scheme using a bank of parallel modulators would not be very efficient in analog hardware. Each carrier in an OFDM is a sinusoid with a frequency that is an integer multiple of a base or fundamental sinusoid frequency. Therefore, each carrier is a like a Fourier series component of the composite signal. In fact, it will be shown later that an OFDM signal is created in the frequency domain, and then transformed into the time domain via the Discrete Fourier Transform(DFT).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.563-574
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• 2006

This paper implements SCM(Spatial Channel Model), a kind of ray-tracing method which has characteristics similar to realistic wave propagation environments, for link-level performance analysis of OFDM(Orthogonal Frequency Division Multiplexing) based multiple antenna systems. The SCM is proposed by 3GPP & 3GPP2 Spatial Channel AHG(Ad-hoc Group) for system-level performance validation. In this paper, we modify the system level parameters and channel coefficient of SCM to compare the link-level performances of OFDM based multiple antenna systems. Through computer simulations, we manifest the implemented SCM channel characteristics. We analyze a realistic link-level performance of OFDM based conventional MIMO(Multiple Input Multiple Output) system and smart antenna system in the implemented channel. We also include the link-level performance of OFDM based multiple antenna systems in I-METRA(Intelligent Multi Element Transmit and Receive Antenna) and independent channel environments with the same system parameters. We suggest appropriate multiple antenna system in the given environment by comparing the link-level performance in the spatial channels that have different channel correlation values.

• Computers and Concrete
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• v.22 no.2
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• pp.249-259
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• 2018

This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi-Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.73-81
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• 2007

This paper presents how to recognize the new-type vehicle license plate using multi-link recognizer after extract the features from characters. In order to assist this task, this paper proposed FE-MCBP to recognize each character that got through image preprocess, extract range of vehicle license plate and extract process of each character. FE-MCBP is the recognizer based on the features of the character, The recognizer is employed to identify the new-type vehicle licence plates which have both the hangul and the arabic numeral characters. And its recognition rate is improved 9.7 percent than the back propagation recognizer before. Also it makes use of extract of linear component and region coordinate generation technology to normalize a image of the tilted vehicle license plate. The recognition system of the new-type vehicle license plate make possible recognize a image of the tilted vehicle license plate when using this system. Also, this system can recognize the tilted or imperfect vehicle licence plates.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.157-166
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• 2011

As underwater environment monitoring system's interest has increased, the research is proceeding about underwater acoustic sensor network. Underwater sensor network can be applicable to many fields, such as underwater environment monitoring, underwater resource exploration, oceanic data collection, military purposes, etc. It is essential to define the PHY-MAC protocol for revitalization of the underwater acoustic sensor network which is available utilization in a variety of fields. However, underwater acoustic sensor network has to implement by consideration of underwater environmental characteristics, such as limited bandwidth, multi-path, fading, long propagation delay caused by low acoustic speed. In this paper, we define frequency of adjusted PHY protocol, network topology, MAC protocol, PHY-MAC interface, data frame format by consideration of underwater environmental characteristics. We also present system configuration of our implementation and evaluate performance based on our implementation with test in real underwater field.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.124-131
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• 2015

In this paper, we proposed indoor positioning system using RSS(Received Signal Strength) positioning method and TSS(Transmission Signal Strength). The main point in the paper is to improve reliability of accuracy positioning with the area recognition algorithm and probabilistic algorithm, which can be effectively used indoor. In the test in 1-dimensional or 2-dimensional spaces, also we checked effective positioning system considered environment of propagation that is changed by reflection, refraction and multipath in according to space form. It is necessary to find place where urgent situation happen and quickly to respond the situation for patients or the weak. Therefore, we expect the positioning system proposed can apply to the field of traffic IT.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.179-189
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• 2000

Recently, due to the increasing interests in deep sea development, all possible efforts to the development of underwater unmanned working vehicles such as AUV(Autonomous Underwater Vehicle) or underwater robot are exerted. This paper proposes a new efficient acoustic-based underwater image data communication system, which ensures a certain level of maximum throughput regardless of the propagation delay of ultrasonic and allowsfast data transmission through the multiple ultrasonic communication channel. Proposed system consists of an acoustic transducer which operates at 136kHz center frequency and it's 10kHz bandwidth, pre-amplifier, $\pi/4 QPSK$(Quadrature Phase Shift Keying) modulation/demodu-lation method, image compressing method using JPEG technique and modified Stop & Wait protocol. The experimental result of the system make it possible to transfer the underwater image as a high throughput at the basin test. The results of test are also verified which allows to desirable transmission performance compared with the existing developed system and the possibility to put the practical use of survey and investigation in the water.