• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.105-111
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• 2017

This paper compares the SE-MMA (Signed Error-MMA) and QE-MMA (Quantized Error-MMA) adaptive equalization algorithm in order to compensates the intersymbol interference due to channel in the transmission of spectral efficient nonconstant modulus signal such as 16-QAM. In the currently MMA adaptive equalizer, the error signal is needed for the updating the tap coefficient. The SE-MMA uses the polarity of error signal for reduce the computational operation in that process, the QE-MMA consider the this polarity and finite bit power-of-2 quantized component in that process, so they has different equalization performance. In order to comparing these performance, the computer simulation was performed in the same channel and environment, the output signal constellation of equalizer, residual isi and maximum distortion, MSE, SER were applied. As a result of computer simulation, the QE-MMA have more superior performance than the SE-MMA in every performance index.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.113-118
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• 2017

This paper propose the NM-MMA (Novel Mixed-MMA) that is possible to improving the convergence speed of current MMA algorithm and reducing the high MSE of SE-MMA algorithm, and its equalization performance were analyzed. The cost function of the NM-MMA configured as the sum of appropriate weights of gradient vector of current MMA and SE-MMA, and then it used for the updating the tap coefficient of equalizer. The computer simulation was performed applying the same environment in the channel, step size and signal to noise ratio, and the same performance index in equalizer output signal constellation, residual isi, MSE, SER was used. As a result of computer simulation, the proposed NM-MMA has fast convergence time than MMA, and less in MSE and SER performance compared to SE-MMA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.513-521
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• 2002

This paper proposes a gamut mapping algorithm based on color space division for cross media color reproduction. As each color device has a limited range of producible colors, reproduced colors on a destination device are different from those of the original device. In order to reduce the color difference, the proposed method divides the whole gamut into parabolic shapes based on intersecting lightness by the just noticeable difference (JND) and the original device gamut boundary. Dividing the gamut with parabolic shapes and piecewise mapping of each region not only considers gamut characteristics but also provides for mapping uniformity. Also the lightness variations are more sensitive to the human visual system and by using lightness JND it can restrict lightness mapping variations that are unperceivable to enhance lightness contrast and chrominance. As a result, the proposed algorithm is able to reproduce high quality images using low-cost color devices.

• Journal of Venture Innovation
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• v.2 no.1
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• pp.23-31
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• 2019

The primary goal of this study is to develop proper indicators for evaluating and selecting an organization that contributes product safety in his industry. The indicators of product safety include input, process, and output in the sequences of product safety activities and systems. The indicators are proposed by the side of measurable and unmeasurable index. In detail, the indicators are consist of 3 parts - product safe management, efforts for product safety and the performance of product safety. The indicators are itemized by size of enterprise (large, medium and small size) due to the difference of their system and management capability of product safety. To get the indicators reasonably, the opinions of experts and VOC of the industrial field are considered. And the indicators are also divided by job position and level(an executive vs. worker). The items of indicators are 20 and the score is 200, that are the same whichever the case may be. The indicators are useful tools for selecting a person who serves the development of product safety in his industry.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.259-266
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• 2020

Magnetic gears have the same characteristics as mechanical gears, and each rotor does not come in contact, which is advantageous over mechanical gears in friction noise, heat generation, and maintenance. In addition, when the rotor using the coil-winding is applied, it is possible to control the output of the gear as well as to cut off its own drive in the emergency situation and to change its gear ratio. So the application of the magnetic gear is infinite. However, when the coil-winding rotor is used, cogging torque due to the attraction force between the permanent magnet and the iron core appears, which leads to an increase in the torque ripple component causing the rotor vibration. Therefore, in this paper, various shapes of the coil-winding rotor are analyzed to reduce the torque ripple of the rotor, and the optimum shape for reducing the torque ripple of the magnetic gear is presented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.3
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• pp.339-345
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• 2001

In this paper, FG-CPW (Finite-Ground Coplanar Wave-Guide) balanced diode mixer is presented. Frequency bandwidth is selected for a C-band, which is 5.72~5.82 GHz for RF, 5.58~5.68 GHz for LO, and 140 MHz for IF signals. A rat-race hybrid is designed for the accomplishment of single balanced type. A low pass filter (LPF) with CPW structure is used far good conversion loss and unwanted harmonics suppression. When LO signal with the power of 4 dBm at 5.635 GHz is injected, a conversion loss of 6.2 dB is obtained for the mixer. Also, the LO to RF and LO to IF isolation of 30 dB and 40 dB are obtained, respectively. This mixer can be used in the area on wireless LAN application.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.510-520
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• 2011

In this paper, we propose a new multiplication algorithm for primitive polynomial with all 1 of coefficient in case that m is odd and even on finite fields $GF(3^m)$, and compose the multiplier with parallel input-output module structure using the presented multiplication algorithm. The proposed multiplier is designed $(m+1)^2$ same basic cells that have a mod(3) addition gate and a mod(3) multiplication gate. Since the basic cells have no a latch circuit, the multiplicative circuit is very simple and is short the delay time $T_A+T_X$ per cell unit. The proposed multiplier is easy to extend the circuit with large m having regularity and modularity by cell array, and is suitable to the implementation of VLSI circuit.

• Journal of the Korean Institute of Gas
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• v.15 no.2
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• pp.63-68
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• 2011

As an effective utilization of biomass, organic wastes and coal, attention has been made to use syngas to a reciprocating engine to generate power. However, significant component variation of syngas depending upon origin and gasification conditions, and its lower heating value than that of LPG and CNG can create difficulties in stable engine operation. Thus it is necessary to address these issues in order to successfully develop power generation engines. As a primary step to resolve these problems, effects of H2 content variation in syngas on engine performance and emission characteristics were discussed in this study. The results show that as H2 % in syngas increases, more stable combustion was achieved with retarded MBT spark timing and engine efficiency becomes maximum with syngas of 10% H2. In addition, NOx emission increased while THC emission decreased as H2 % rises in the syngas.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.699-704
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• 2001

ABSTRACT In this paper, a new hybrid modular recurrent TDNN (time-delay neural network)-HMM (hidden Markov model) architecture for speech recognition has been studied. In TDNN, the recognition rate could be increased if the signal window is extended. To obtain this effect in the neural network, a high-level memory generated through a feedback within the first hidden layer of the neural network unit has been used. To increase the ability to deal with the temporal structure of phonemic features, the input layer of the network has been divided into multiple states in time sequence and has feature detector for each states. To expand the network from small recognition task to the full speech recognition system, modular construction method has been also used. Furthermore, the neural network and HMM are integrated by feeding output vectors from the neural network to HMM, and a new parameter smoothing method which can be applied to this hybrid system has been suggested.