• Journal of Advanced Marine Engineering and Technology
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• v.22 no.3
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• pp.320-327
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• 1998

The purpose of this study is to design the intelligent speed control system for marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. Recently for the speed control of a diesel engine some methods using the advanced control techniques such as LQ control Fuzzy control or H$\infty$ control etc. have been reported. However most of speed controllers of a marine diesel engine developed are still using the PID control algorithm But the performance of a marine diesel engine depends highly on the parameter setting of the PID controllers. The authors proposed already a new method to tune efficiently the PID parameters by the Model Mathcing Method typically taking a marine diesel engine as a non-oscillatory second-order system. It was confirmed that the previously proposed method is superior to Ziegler & Nichols's method through simulations under the assumption that the parameters of a diesel engine are exactly known. But actually it is very difficult to find out the exact model of the diesel engine. Therefore when the model and the actual diesel engine are unmatched as an alternative to enhance the speed control characteristics this paper proposes a Model Refernce Adaptive Speed Control system of a diesel engine in which PID control system for the model of a diesel engine is adopted as the nominal model and a Fuzzy controller is adopted as the adaptive controller, And in the nominal model parameters of a diesel engine are adjusted using the Model Matching Method. it is confirmed that the proposed method gives better performance than the case of using only Model Matching Method through the analysis of the characteristics of indicial responses.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1398-1406
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• 2007

Providing natural and efficient access to the fast growing multimedia information is a critical aspect for content-based information system. Query by humming system allows the user to find a song by humming part of the tune form music database. Conventional music information retrieval systems use a high precision pitch extraction method. However, it is very difficult to extract true pitch perfectly. So, In this paper, we propose to use YIN parameter with applying the reliability to reduce the pitch extraction errors. And we describes developed music information retrieval method based on a query by humming system which uses reliable feature extraction. Developed system is based on a continuous dynamic programming algorithm with features including pitch, duration and energy along with their confidence measures. The experiment showed that the proposed method could reduce the errors of the top-10 7.2% and the top-1 9.1% compared with the cepsturm based multiple pitch candidate. The overall retrieval system achieved 92.8% correct retrieval in the top-10 rank list on a database of 155 songs.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.49-58
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• 2014

A low-swing differential near-ground signaling (NGS) transceiver for low-power high-speed mobile I/O interface is presented. The proposed transmitter adopts an on-chip regulated programmable-swing voltage-mode driver and a pre-driver with asymmetric rising/falling time. The proposed receiver utilizes a new multiple gain-path differential amplifier with feed-forward capacitors that boost high-frequency gain. Also, the receiver incorporates a new adaptive bias generator to compensate the input common-mode variation due to the variable output swing of the transmitter and to minimize the current mismatch of the receiver's input stage amplifier. The use of the new simple and effective impedance matching techniques applied in the transmitter and receiver results in good signal integrity and high power efficiency. The proposed transceiver designed in a 65-nm CMOS technology achieves a data rate of 13 Gbps/channel and 0.3 pJ/bit (= 0.3 mW/Gbps) high power efficiency over a 10 cm FR4 printed circuit board.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.451-456
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.75-81
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn`t make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.11-18
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• 2003

In this paper, we propose a fast variable block matching algorithm for motion estimation based on bit-patterns. Motion estimation in the proposed algorithm is peformed after the representation of image sequence is transformed 8-bit pixel values into 1-bit ones by the mean pixel value of search block, which brings a short searching time by reducing the computational complexity. Moreover, adaptive searching methods according to the motion information of the block make the procedure of motion estimation efficient by eliminating unnecessary searching processes of low motion block and deepening a searching procedure in high motion block. Experimental results show that the proposed algorithm provides bettor performance - average 0.5dB PSNR improvement and about 99% savings in the number of operations - than full search Hock matching algorithm with a fixed block size.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.175-183
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• 2015

In this paper, we propose a analyses the big data of students who are willing to find employment and thus presents strategy for their higher success rate of employment. The experiment covered in this paper is based on female two-year community college students who are yet unsure about their future employment. The primary flaw of pervious employment strategy was job opportunity was only based on simple factors such as student's grade, appearance, and personality due to employers and firms's demand. Therefore, students were less satisfied and often resign. In order to prevent these failures, this paper plans a strategy by analyzing the big data. Furthermore, this is proven by the comparison between 2014 employment statistics and those of previous years, and employment request has been 21.3 percent increased along with 81.4 percent increase in match rate between firms and graduating students. Most importantly, the final success rate of employment presented 63.1 percent increase compared to the previous year.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.127-132
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• 2019

In this paper, we propose a visual inspection method of automotive parts for injection molding to improve the appearance quality and productivity of automotive parts. Exterior inspection of existing injection molding automobile parts was generally done by manual sampling inspection by human. First, we applied the edge-tolerance vision inspection algorithm ([1] - [4]) for vision inspection of electronic components (TFT-LCD and PCB) And we propose a new visual inspection method to overcome the problem. In the proposed visual inspection, the inspection images of the parts to be inspected are aligned on the basis of the reference image of good quality. Then, after partial adaptive binarization, the binary block matching algorithm is used to compare the good binary image and the test binary image. We verified the effectiveness of the edge-tolerance vision check algorithm and the proposed appearance vision test method through various comparative experiments using actual developed equipment.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.561-568
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• 2022

Most deep learning-based video object segmentation methods perform the segmentation with past prediction information stored in external memory. In general, the more past information is stored in the memory, the better results can be obtained by accumulating evidence for various changes in the objects of interest. However, all information cannot be stored in the memory due to hardware limitations, resulting in performance degradation. In this paper, we propose a method of storing new information in the external memory without additional memory allocation. Specifically, after calculating the attention score between the existing memory and the information to be newly stored, new information is added to the corresponding memory according to each score. In this way, the method works robustly because the attention mechanism reflects the object changes well without using additional memory. In addition, the update rate is adaptively determined according to the accumulated number of matches in the memory so that the frequently updated samples store more information to maintain reliable information.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.325-332
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• 2006

In this paper. we Propose the noise suppressor with the Perceptual model and wavelet packet transform. The objective is to enhance speech corrupted colored or non-stationary noise. If corrupted noise is colored. subband approach would be more efficient than whole band one. To avoid serious residual noise and speech distortion, we must adjust the Wavelet Coefficient Threshold (WCT). In this Paper. the subband is designed matching with the critical band and WCT is adapted noise masking threshold (NMT) and segmental signal to noise ratio (seg_SNR). Consequently. it has similar Performance with EVRC in PESQ-MOS. But it's better than wavelet packet transform using universal threshold about 0.289 in PESQ-MOS. The important thing is that it's more useful than EVRC in coded speech. In coded speech. PESQ-MOS is higher than EVRC about 0.23.