• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.1-6
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• 1999

We propose a new algorithm for pattern classification by extracting feature vectors based on Gibbs distributions which are well suited for representing the characteristic of an images. The extracted feature vectors are comprised of 2-D moments which are invariant under translation rotation, and scale of the image less sensitive to noise. This implementation contains two puts: feature extraction and pattern classification First of all, we extract feature vector which consists of an improved 2-D moments on the basis of estimated Gibbs distribution Next, in the classification phase the minimization of the discrimination cost function for a specific pattern determines the corresponding template pattern. In order to evaluate the performance of the proposed scheme, classification experiments with training document sets of characters have been carried out on SUN ULTRA 10 Workstation Experiment results reveal that the proposed scheme had high classification rate over 98%.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.44-50
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• 1999

This paper presents a set of techniques to automatically find rate optimal or near rate optimal implementation of shift-invariant flow graphs on pipelined processor, in which pipeline processor has multiple accumulators and internal datapaths. In such case, the problem to be addressed is the scheduling of multiple instruction streams which control all of the pipeline stages. The goal of an automatic scheduler in this context is to rearrange the order of instructions such that they are executed with minimum iteration period between successive iteration of defining flow graphs. The scheduling algorithm described in this paper also focuses on the problem of removing the hazards due to inter-instruction dependencies.

• Molecules and Cells
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• v.37 no.5
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• pp.365-371
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• 2014

Recent findings, notably on adipokines and adipose tissue inflammation, have revised the concept of adipose tissues being a mere storage depot for body energy. Instead, adipose tissues are emerging as endocrine and immunologically active organs with multiple effects on the regulation of systemic energy homeostasis. Notably, compared with other metabolic organs such as liver and muscle, various inflammatory responses are dynamically regulated in adipose tissues and most of the immune cells in adipose tissues are involved in obesity-mediated metabolic complications, including insulin resistance. Here, we summarize recent findings on the key roles of innate (neutrophils, macrophages, mast cells, eosinophils) and adaptive (regulatory T cells, type 1 helper T cells, CD8 T cells, B cells) immune cells in adipose tissue inflammation and metabolic dysregulation in obesity. In particular, the roles of natural killer T cells, one type of innate lymphocyte, in adipose tissue inflammation will be discussed. Finally, a new role of adipocytes as antigen presenting cells to modulate T cell activity and subsequent adipose tissue inflammation will be proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.267-274
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• 2015

In this paper the optimal structure of a neural network based on OpenCV for a golf ball recognition and the intensity of ROI(Region Of Interest) are calculated. The system is composed of preprocess, image processing and machine learning, and a learning model is obtained by multi-layer perceptron using the inputs of 7 Hu's invariant moments, box ration extracted by vertical and horizontal length or ${\pi}$ calculated by area of ROI. Simulation results show that optimal numbers of hidden layer and the node of neuron are selected to 2 and 9 respectively considering the recognition rate and running time, and optimal intensity of ROI is selected to 200.

• Geomechanics and Engineering
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• v.5 no.1
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• pp.71-86
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• 2013

For rock materials, a transversely isotropic failure criterion established through the extended Lade-Duncan failure criterion incorporating an anisotropic state scalar parameter, which is a joint invariant of deviatoric microstructure fabric tensor and normalized deviatoric stress tensor, is verified with the results of triaxial compressive data on Tournemire shale. For torsional shear mode with $0{\leq}b{\leq}0.75$, rock shear strengths decrease with ${\alpha}$ increasing until the rock shear strength approaches minimum value at ${\alpha}{\approx}40^{\circ}$, and after this point, the rock shear strengths increase as ${\alpha}$ increases further. For the torsional shear mode with b > 0.75, rock shear strengths are almost constant for ${\alpha}{\leq}40^{\circ}$, but it increases with increase in ${\alpha}$ afterwards. The rock shear strength variation against ${\alpha}$ agrees with shear strength changing tendency of heavily OCR natural London Clays tested before. Prediction results show that the transversely isotropic failure criterion proposed in the paper is reasonable.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.119-127
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• 1999

In this paper, a robust direct adaptive contrdler is presented in a linear time-invariant. Continuous systems with unmodeded dynamics and bounded disturbance using a rmdified control law and the adaptive law to Compensate for the drawback of ${\sigma}$-modification algorithm. The proposed algorithm is awlied to a plant with unrmdeled dynamics represented as a singular perturbation. Boundness of all signals in overall system is guaranteed with mathematical analysis. simulation results are presented the effectiveness foc the first-order plant even in the presence of unmodelled dynamics or bounded disturbance simulatneousIy.eousIy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.283-290
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• 2006

The cellular neural networks have the structure that consists of an array of the same cell which is a simple processing element, and each of the cells has local connectivity and space invariant template properties. So, it has a very suitable structure for the hardware implementation. But, it is impossible to have a one-to-one mapping between the CNN hardware processors and the pixels of the practical large image. In this paper, a $5{\times}5$ CNN hardware processor with pipeline input and output that can be applied to the time-multiplexing processing scheme, which processes the large image with a small CNN cell block, is designed. the operation of the implemented $5{\times}5$ CNN hardware processor is verified from the edge detection and the shadow detection experimentations.

• Journal of KIISE:Software and Applications
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• v.28 no.8
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• pp.570-581
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• 2001

본 논문에서는 윤곽선(edge) 기반의 형태 정보와 웨이브렛 변환(wavelet transform)에 의한 방향(direction) 정보를 사요하는데 2단계 상표 영상 검색 시스템을 제안한다. 1 단계에서는 후보 상표 영상을 추출하기 위해 영상의 전반적인 정보로 원 상표 영상(original trademark image)을 웨이브렛 변환하여 얻은 X, Y 방향 고주파(high frequency) 성분으로부터 구한 방향 정보와 영상의 윤곽선에 대해 모멘트를 구하는 향상된 불변 모멘트(improved invariant moment)를 이용한다. 2단계에서는 후부 영상들에 대해 영상의 세부 정보인 윤곽선 각도(edge angle)와 윤곽선 반지름(edge radius) 정보를 추출하여 유사도 측정 알고리즘을 통해 결과 영상을 산출하게 된다. 본 상표 영상 검색 시스템은 문자 색인으로는 색인이 용이 하지 않은 기하학적도형 상표 영상만을 사용하였다. 본 시스템에서는 색상과는 상관없는 특징인 형태 정보와 방향 정보만을 이용하므로 같은 색상 구성을 가진 유사 영상뿐만 아니라, 유사하지만 바탕이 반전된 영상이나 색상이 다른 유사 영상에 대해서도 바르게 검색할 수 있으며, 각 특징을 일반화해줌으로 이동.회전.크기 변화에도 불변하는 견고성을 가진다. 또한 효율적인 검색을 위해 2단계의 구조를 사용하였으며, 각 단계마다 계산량을 줄여 검색 시간을 감소시키도록 설계되었다.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.481-486
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• 2012

Accurate and efficient estimation of the number of sources is critical for providing the parameter of targets in problems of array signal processing and blind source separation among other such problems. When conventional estimators work in unfavorable scenarios, e.g., at low signal-to-noise ratio (SNR), with a small number of snapshots, or for sources with a different strength, it is challenging to maintain good performance. In this paper, the detection limit of the minimum description length (MDL) estimator and the signal strength required for reliable detection are first discussed. Though a comparison, we analyze the reason that performances of classical estimators deteriorate completely in unfavorable scenarios. After discussing the limiting distribution of eigenvalues of the sample covariance matrix, we propose a new approach for estimating the number of sources which is based on a sequential hypothesis test. The new estimator performs better in unfavorable scenarios and is consistent in the traditional asymptotic sense. Finally, numerical evaluations indicate that the proposed estimator performs well when compared with other traditional estimators at low SNR and in the finite sample size case, especially when weak signals are superimposed on the strong signals.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.20-23
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• 2006

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTI) plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with the specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller. Furthermore, the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.