• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1101-1107
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• 2017

In this paper, a robust and fast grid synchronization method of a three-phase power converter is proposed. The amplitude and phase information of grid voltages are essential for power converters to be properly connected into the utility. The phase-lock-loop in synchronous reference frame has been widely adopted for the three-phase converter system since it shows a satisfactory performance under balanced grid voltages. However, power converters often operate under abnormal grid conditions, i.e. unbalanced by grid faults and frequency variations, and thus a proper active and reactive power control cannot be guaranteed. The proposed method adopts a second order generalized integrator in synchronous reference frame to detect positive sequence components under unbalanced grid voltages. The proposed method has a fast and robust performance due to its higher gain and frequency adaptive capability. Simulation and experimental results show the verification of the proposed synchronization algorithm and the effectiveness to detect positive sequence voltage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.2
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• pp.223-230
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• 1998

This paper describes a phase-shift pulse-width modulation and pulse-frequency modulation series resonant high-frequency inverter using IGBT(Insulated-Gated Bipolar Transistor) for the power control of high-frequency induction heating using neuro-fuzzy, which is practically applied for 20KHz~500KHz induction-heating and melting power supply in industrial fields. The adaptive frequency tracking based phase-shifting PWM(Pulse-Width Modulation) regulation scheme is presented in order to minimize switching losses. The trially-produced breadboards using IGBT are successfully demonstrated and discussed.

• Smart Media Journal
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• v.5 no.1
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• pp.55-60
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• 2016

Mobility of the sensor networks proposed a new way to the efficient design of sensor networks and improvement of network system performance. Mobility results in a number of functional changes in the MAC protocol and routing protocol. Especially, the mobility of the nodes may occur the increase of the overhead of transmission or disconnection of the link. Therefore, the study of the energy efficient transmission is very important in mobile sensor networks. This paper proposed adaptive transmission mechanism on the distance-based power control. The proposed mechanism was analyzed better than conventional method in the average energy consumption and network life by simulation results.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.581-594
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• 2011

Due to the recent advancement of networking and high-performance computing technologies, scientists can easily access large-scale data captured by scientific measurement devices through a network, and use huge computational power harnessed on the Internet for their analyses of scientific data. However, visualization technology, which plays a role of great importance for scientists to intuitively understand the analysis results of such scientific data, is not fully utilized so that it can seamlessly benefit from recent high-performance and networking technologies. One of such visualization technologies is SAGE (Scalable Adaptive Graphics Environment), which allows people to build an arbitrarily sized tiled display wall and is expected to be applied to scientific research. In this paper, we present a multi-application controller for SAGE, which we have developed, in the hope that it will help scientists efficiently perform scientific research requiring high-performance computing and visualization. The evaluation in this paper indicates that the efficiency of completing a comparison task among multiple data is increased by our system.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1225-1235
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• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• BMB Reports
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• v.55 no.2
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• pp.57-64
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• 2022

Autoimmune disease is known to be caused by unregulated self-antigen-specific T cells, causing tissue damage. Although antigen specificity is an important mechanism of the adaptive immune system, antigen non-related T cells have been found in the inflamed tissues in various conditions. Bystander T cell activation refers to the activation of T cells without antigen recognition. During an immune response to a pathogen, bystander activation of self-reactive T cells via inflammatory mediators such as cytokines can trigger autoimmune diseases. Other antigen-specific T cells can also be bystander-activated to induce innate immune response resulting in autoimmune disease pathogenesis along with self-antigen-specific T cells. In this review, we summarize previous studies investigating bystander activation of various T cell types (NKT, γδ T cells, MAIT cells, conventional CD4⁺, and CD8⁺ T cells) and discuss the role of innate-like T cell response in autoimmune diseases. In addition, we also review previous findings of bystander T cell function in infection and cancer. A better understanding of bystander-activated T cells versus antigen-stimulated T cells provides a novel insight to control autoimmune disease pathogenesis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.53-60
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• 2010

This paper presents a novel gain control system composed of a feedback circuit, Two stage Low Noise Amplifier (LNA) using 0.18 um CMOS technology for 5.2 GHz. The feedback circuit consists of the seven function blocks: peak detector, comparator, ADC, IVE(Initial Voltage Elimination) circuit, switch, storage, and current controller. We focus on detecting signal and designing storage circuit that store the previous state. The power consumption of the feedback circuit in the system can be reduced without sacrificing the gain by inserting the storage circuit. The adaptive front-end system with the feedback circuit exhibits 11.39~22.74 dB gain, and has excellent noise performance at high gain mode. Variable gain LNA consumes 5.68~6.75 mW from a 1.8 V supply voltage.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.248-261
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• 2002

In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.