• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.138-144
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• 2007

This paper introduces the design techniques of an IR module using the 2-D array un-cooled type infrared detector which is applied to the individual combat weapon. Considering the size and weight of the hand carried weapon system, we used a very small-sized detector and applied an adaptive temperature control algorithm so that the operation consumed with low power can be possible. We applied the AR(Auto Regressive) filter to improve the signal-to-noise ratio in a thermal image processing step. We also applied the plateau equalization and boundary enhancement techniques to improve the visibility for human visual system.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.303-329
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• 2004

Magnetostrictive materials are routinely employed as actuator and sensor elements in a wide variety of noise and vibration control problems. In infrastructural applications, other technologies such as hydraulic actuation, piezoelectric materials and more recently, magnetorheological fluids, are being favored for actuation and sensing purposes. These technologies have reached a degree of technical maturity and in some cases, cost effectiveness, which justify their broad use in infrastructural applications. Advanced civil structures present new challenges in the areas of condition monitoring and repair, reliability, and high-authority actuation which motivate the need to explore new methods and materials recently developed in the areas of materials science and transducer design. This paper provides an overview of a class of materials that because of the large force, displacement, and energy conversion effciency that it can provide is being considered in a growing number of quasistatic and dynamic applications. Since magnetostriction involves a bidirectional energy exchange between magnetic and elastic states, magnetostrictive materials provide mechanisms both for actuation and sensing. This paper provides an overview of materials, methods and applications with the goal to inspire novel solutions based on magnetostrictive materials for the design and control of advanced infrastructural systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.364-370
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• 1990

In this paper, we propose a self-tuning PID controller for unknown systems with time-varying delay. Using pole placement equations, we derive the controller that can be extended to the multi-step time delay case. The time-varying delays are estimated by a prediction error delay method using multiple predictors. Since the order of the estimation vector is not increased, the persistant exciting condition of control input is alleviated. Since the least square method gives biased parameter estimates for colored noise cases, the recursive instrumental variable method is used to estimate system parameters. The computational burden of the proposed method is less than the conventional adaptive methods. Computer simulations are performed to illustrate the efficiency of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.499-505
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• 1998

In developing an automated surface inspect algorithm, we have designed a hierarchical classifier using neural network. The defects which exist on the surface of cold mill strip have a scattering or singular distribution. We have considered three major problems, that is preprocessing, feature extraction and defect classification. In preprocessing, Top-hit transform, adaptive thresholding, thinning and noise rejection are used Especially, Top-hit transform using local minimax operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, and histogram ratio features are calculated. The histogram ratio feature is taken from the gray-level image. For defect classification, we suggest a hierarchical structure of which nodes are multilayer neural network classifiers. The proposed algorithm reduced error rate by comparing to one-stage structure.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.558-561
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding Process in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noise such spatter and arc light. The adaptive Hough transformation was used to extract the laser stripe and to obtain specific weld points In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of the Korean Institute of Telematics and Electronics
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• v.7 no.2
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• pp.26-32
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• 1970

Among the various methods used for determining control system dynamics, the method using cross-correlation function seems useful if the white noise can be available as a test signal. In this paper, results are reported of a M-sequence generator which was built by means of IC shift register as it designed by the authors. This signal appears very useful and promises future applications in adaptive control systems.

• Earthquakes and Structures
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• v.22 no.4
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• pp.421-430
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• 2022

This paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.51-57
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• 2022

The problem of optimal stochastic GA control of the system with uncertain parameters and unsure noise covariates is studied. First, without knowing the explicit form of the dynamic system, the open-loop determinism problem with path optimization is solved. Next, Gaussian linear quadratic controllers (LQG) are designed for linear systems that depend on the nominal path. A robust genetic neural network (NN) fuzzy controller is synthesized, which consists of a Kalman filter and an optimal controller to assure the asymptotic stability of the discrete control system. A simulation is performed to prove the suitability and performance of the recommended algorithm. The results indicated that the recommended method is a feasible method to improve the performance of active tuned mass damper (ATMD) shear buildings under random earthquake disturbances.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.80-86
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• 2006

The wireless communication based on LDPC and adaptive spatial-subcarrier coded modulation using MQAM for orthogonal frequency division multiplexing (OFDM) wireless transmission by using instantaneous channel state information and employing multiple antennas at both the transmitter and the receiver. Adaptive coded modulation is a promising idea for bandwidth-efficient transmission on time-varying, narrowband wireless channels. On power limited Additive White Gaussian Noise (AWGN) channels, low density parity check (LDPC) codes are a class of error control codes which have demonstrated impressive error correcting qualities, under some conditions performing even better than turbo codes. The paper demonstrates OFDM with LDPC and adaptive modulation applied to Multiple-Input Multiple-Output (MIMO) system. An optimization algorithm to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge is used. The experimental results are shown the potential of our proposed system.