• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.586-591
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• 2014

In this study, we introduce Radial Basis Function Neural Networks(RBFNNs) classifier using Artificial Bee Colony(ABC) algorithm in order to classify between precipitation event and non-precipitation event from given radar data. Input information data is rebuilt up through feature analysis of meteorological radar data used in Korea Meteorological Administration. In the condition phase of the proposed classifier, the values of fitness are obtained by using Fuzzy C-Mean clustering method, and the coefficients of polynomial function used in the conclusion phase are estimated by least square method. In the aggregation phase, the final output is obtained by using fuzzy inference method. The performance results of the proposed classifier are compared and analyzed by considering both QC(Quality control) data and CZ(corrected reflectivity) data being used in Korea Meteorological Administration.

• Journal of Sasang Constitutional Medicine
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• v.23 no.2
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• pp.194-207
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• 2011

1. Objectives: This study is about a development of Sasang constitutional classification algorithm using facial information. 2. Methods: We analysed the datum of middle aged (20~48) women collected by multi-center researchers in 2007. And this study analysed the data of the measurement of the face by 3D-AFRA (3-Dimensional Automatic Face Recognition Apparatus) and the items of impression by SDQ. We used multiple comparison, exploratory discriminant analysis and clinical decision to select optimal 3D facial variables which will be input in discriminant analysis model. And we used univariate F values and stepwise discriminant function analysis to choose best impression variables. 3. Results and Conclusions: In this study, derived discriminant function's explanation power was 39% in female group. Diagnostic accuracy rate was 66.0% in female group. And in test sample, Sasang constitutional diagnostic accuracy rate was 56.9%. In this process we could help improve the objectification of Sasang constitution diagnosis.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.2
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• pp.71-82
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• 1984

A programme, called BIPOLE, for the numerical analysis of twotimensional n-p-n bipolar transistors was developed. It has included the SRH and Auger recolnbination processes, the mobility dependence on the impurity density and the electric field, and the band-gap narrowing effect. The finite difference equations of the fundamental semiconductor equations are formulated using Newton's method for Poisson's equation and the divergence theorem for the hole and electron continuity equations without physical restrictions. The matrix of the linearized equations is sparse, symmetric M-matrix. For the solution of the linearized equations ICCG method and Gummel's algorithm have been employed. The programme BIPOLE has been applied to various kinds of the steady-state problems of n-p-n transistors. For the examples of applications the variations of common emitter current gain, emitter and diffusion capacitances, and input and output characteristics are calculated. Three-dimensional representations of some D.C. physical quantities such as potential and charge carrier distributions were displayed. This programme will be used for the nome,rical analysis of the distortion phenom ana of two-dimensional n-p-n transistors. The BIPOLE programme is available for everyone.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.55-63
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• 2011

This paper describes new moving target detection technique combining two algorithms to detect targets and reject clutters in video frame images for surveillance system: One obtains the region of moving target using phase correlation method using $N{\times}M$ sub-block images in frequency domain. The other uses adaptive threshold using learning weight for extracting target candidates in subtracted image. The block region with moving target can be obtained using the characteristics that the highest value of phase correlation depends on the movement of largest image in block. This technique can be used in camera motion environment calculating and compensating camera movement using FFT phase correlation between input video frame images. The experimental results show that the proposed algorithm accurately detects target(s) with a low false alarm rate in variety environment using the receiver operating characteristics (ROC) curve.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.55-63
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• 2008

This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.8
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• pp.75-84
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• 2004

In this paper, we proposed an efficient hardware architecture of line-based lifting algorithm for Motion JPEG2000. We proposed a new architecture of a lifting-based filtering cell which has an optimized and simplified structure. It was implemented in a hardware accommodating both (9,7) and (5,4) filter. Since the output rate is linearly proportional to the input rate, one can obtain the high throughput through parallel operation simply by adding the hardware units. It was implemented into both of ASIC and FPGA The 0.35${\mu}{\textrm}{m}$ CMOS library from Samsung was used for ASIC and Altera was the target for FRGA. In ASIC, the proposed architecture used 41,592 gates for the lifting arithmetic and 128 Kbit memory. For FPGA it used 6,520 LEs(Logic Elements) and 128 ESBs(Embedded System Blocks). The implementations were stably operated in the clock frequency of 128MHz and 52MHz, respectively.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.8
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• pp.453-464
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• 2004

In order to solve the well-known drawback of reduced flexibility that is associate with ASIC implementations, this paper proposes a novel arithmetic unit over GF(2$^{m}$ ) for field programmable gate arrays (FPGAs) implementations of elliptic curve cryptographic processor. The proposed arithmetic unit is based on the binary extended GCD algorithm and the MSB-first multiplication scheme, and designed as systolic architecture to remove global signals broadcasting. The proposed architecture can perform both division and multiplication in GF(2$^{m}$ ). In other word, when input data come in continuously, it produces division results at a rate of one per m clock cycles after an initial delay of 5m-2 in division mode and multiplication results at a rate of one per m clock cycles after an initial delay of 3m in multiplication mode respectively. Analysis shows that while previously proposed dividers have area complexity of Ο(m$^2$) or Ο(mㆍ(log$_2$$^{m}$ )), the Proposed architecture has area complexity of Ο(m), In addition, the proposed architecture has significantly less computational delay time compared with the divider which has area complexity of Ο(mㆍ(log$_2$$^{m}$ )). FPGA implementation results of the proposed arithmetic unit, in which Altera's EP2A70F1508C-7 was used as the target device, show that it ran at maximum 121MHz and utilized 52% of the chip area in GF(2$^{571}$ ). Therefore, when elliptic curve cryptographic processor is implemented on FPGAs, the proposed arithmetic unit is well suited for both division and multiplication circuit.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.329-338
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• 2003

Object tracking in a real time image is one of Interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.233-236
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• 1996

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are no quantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by auditory stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. The experiment was devised with seven experimental conditions, which are control and six different types of auditory stimulation. Twenty subjects were used to obtain EEGs while introducing auditory stimulation. Wavelet transformation was employed to analyze the EEG signals. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with negative and positive stimulus were found. This study could be extended to estabilish an algorithm which distinguishes psychophysiological states of the subjects exposed to the auditory stimulation.