• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.95-105
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• 2005

As the security system using facial recognition, the recognition performance depends on the environments (e. g. face expression, hair style, age and make-up etc.) For the revision of easily changeable environment, it's generally used to set up the threshold, replace the face image which covers the threshold into images already registered, and update the face images additionally. However, this usage has the weakness of inaccuracy matching results or can easily active by analogous face images. So, we propose the genetic algorithm which absorbs greatly the facial similarity degree and the recognition target variety, and has excellence studying capacity to avoid registering inaccuracy. We experimented variable and similar face images (each 30 face images per one, total 300 images) and performed inherent face images based on ingredient analysis as face recognition technique. The proposed method resulted in not only the recognition improvement of a dominant gene but also decreasing the reaction rate to a recessive gene.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.1-10
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• 2000

This paper proposes a novel video coding system with rate control based on fractal algorithm To overcome the demerits of excessive amounts of coded bit generated by previous fractal coding methodology. the proposed system classifies the Image into three classes such as background, motion compensation, and fractal coding area. The motion vector for motion compensation, and the fractal offset value that is difference value between the predicted offset and the least-square approximated value are coded with variable length code The decision method which determines threshold value of partitioning quadtree is applied to the bit-rate control algorithm considering the quantity of currently generated bits and fixed channel bandwidth Experimental result shows that the proposed system enhances compression ratio 1.8 times higher than previous method for the same image quality, and performs efficient rate control for fixed channel bandwidth.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.100-105
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• 2011

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.39-45
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• 2012

Recently the convergence of healthcare technology is used for daily life healthcare monitoring. Cardiac arrhythmia is presented by the state of the heart irregularity. Abnormal heart's electrical signal pathway or heart's tissue disorder could be the cause of cardiac arrhythmia. Fatal arrhythmia could put patient's life at risk. Therefore arrhythmia detection is very important. Previous studies on the detection of arrhythmia in various ECG analysis and classification methods had been carried out. In this paper, an ECG signal processing techniques to detect abnormal ECG based on DTW minimum accumulation distance through the template matching for normalized data and variable threshold method for ECG R-peak detection. Signal processing techniques able to determine the occurrence of normal ECG and abnormal ECG. Abnormal ECG detection algorithm using DTW minimum accumulation distance method is performed using MITBIH database for performance evaluation. Experiment result shows the average percentage accuracy of using the propose method for Rpeak detection is 99.63 % and abnormal detection is 99.60 %.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.227-235
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• 2006

In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1378-1383
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• 1999

In this paper, an effective variable-block-based image compression technique using wavelet transform is proposed. Since the statistical property of each wavelet subband is different, we apply the adaptive quantization to each wavelet subband. In the proposed algorithm, each subband is divided into non-overlapping variable-sized blocks based on directional properties. In addition, we remove wavelet coefficients which are below a certain threshold value for coding efficiency. To compress the transformed data, the proposed algorithm quantizes the wavelet coefficients using scalar quantizer in LL subband and vector quantizers for other subbands to increase compression ratio. The proposed algorithm shows improvements in compression ratio as well as PSNR compared with the existing block-based compression algorithms. In addition, it does not cause any blocking artifacts in very low bit rates even though it is also a block-based method. The proposed algorithm also has advantage in computational complexity over the existing wavelet-based compression algorithms since it is a block-based algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1333-1340
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• 2015

IEEE 802.11 MAC(Media Access Control) defines DCF(Distributed Coordination Function) for data transmission control. BEB(Binary Exponential Backoff) algorithm of DCF has a problem that if the number of stations connected are over a certain threshold, it degrades network performance because of packet collisions caused from the minimum contention window size. To cope with this problem, we proposed a novel algorithm, named as VBS(Variable Backoff Stage) algorithm, which adjusts the rate of backoff stage increment depending on the number of stations associated with an AP(Access Point). Analytic model of proposed algorithm was derived and simulations on the BEB and the VBS algorithms have been conducted on the OFDM (Orthogonal Frequency Division Multiplexing) method. Simulation results showed that when the rate of backoff state increment was 5 and 10, the number of retransmission were reduced to 1/5 and 1/10 comparing to that of BEB, respectively. Our algorithm showed improvement of 19% and 18% in network utilization, respectively. Packet delay was reduced into 1/12.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.357-369
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• 2020

Different from the conventional planar fracture and simplified Newton model, for power-law slurries with a lower water-cement ratio commonly used in grouting engineering, flow model in geological rough fractures is built based on ten standard profiles from Barton (1977) in this study. The numerical algorithm is validated by experimental results. The flow mechanism, grout superiority, and water plugging of pseudo plastic slurry are revealed. The representations of hydraulic grouting properties for JRCs are obtained. The results show that effective plugging is based on the mechanical mechanisms of the fluctuant structural surface and higher viscosity at the middle of the fissure. The formulas of grouting parameters are always variable with the roughness and shear movement, which play a key role in grouting. The roughness can only be neglected after reaching a threshold. Grouting pressure increases with increasing roughness and has variable responses for different apertures within standard profiles. The whole process can be divided into three stationary zones and three transition zones, and there is a mutation region (10 < JRCs < 14) in smaller geological fractures. The fitting equations of different JRCs are obtained of power-law models satisfying the condition of -2 < coefficient < 0. The effects of small apertures and moderate to larger roughness (JRCs > 10.8) on the permeability of surfaces cannot be underestimated. The determination of grouting parameters depends on the slurry groutability in terms of its weakest link with discontinuous streamlines. For grouting water plugging, the water-cement ratio, grouting pressure and grouting additives should be determined by combining the flow conditions and the apparent widths of the main fracture and rough surface. This study provides a calculation method of grouting parameters for variable cement-based slurries. And the findings can help for better understanding of fluid flow and diffusion in geological fractures.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Advances in nano research
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• v.3 no.3
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• pp.143-168
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• 2015

Initiation of crack and its growth simulation requires accurate model of traction - separation law. Accurate modeling of traction-separation law remains always a great challenge. Atomistic simulations based prediction has great potential in arriving at accurate traction-separation law. The present paper is aimed at establishing a method to address the above problem. A method for traction-separation law prediction via utilizing atomistic simulations data has been proposed. In this direction, firstly, a simpler approach of common neighbor analysis (CNA) for the prediction of crack growth has been proposed and results have been compared with previously used approach of threshold potential energy. Next, a scheme for prediction of crack speed has been demonstrated based on the stable crack growth criteria. Also, an algorithm has been proposed that utilizes a variable relaxation time period for the computation of crack growth, accurate stress behavior, and traction-separation atomistic law. An understanding has been established for the generation of smoother traction-separation law (including the effect of free surface) from a huge amount of raw atomistic data. A new curve fit has also been proposed for predicting traction-separation data generated from the molecular dynamics simulations. The proposed traction-separation law has also been compared with the polynomial and exponential model used earlier for the prediction of traction-separation law for the bulk materials.