• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.103-114
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• 2012

The many DE based data hiding schemes and the many data hiding schemes based on Histogram shifting are researched in spatial domain. The data hiding scheme based on Histogram shifting have an advantage of low distortion of the stego image. But the capacity is low than other schemes. On the other hands, the DE based data hiding schemes have an advantage of high capacity. But the quality of the stego image is low. In this paper, new data hiding scheme which has the similar capacity but the increased quality of the stego image is proposed. The prediction error is divided into blocks to embed the secret data in this scheme. The prediction errors in the block are scanned before the secret data is embedded. If one prediction error is low than the threshold at least, the block is changed to embed the secret data. Otherwise the secret data is not embedded. The distortion of the stego image is minimized by this method. But the block that the secret data embedded is marked in location map. So the additional information to extract the secret data and recover the cover image is needed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.42-48
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• 2002

Multiple description coding Is source coding for multiple channels such that a decoder which receives an arbitrary subset of the channels may produce a useful reconstruction. This paper presents an efficient multiple description coder using a newly designed EZW coding method. We first propose EZW coder which has expanded threshold and two subordinate passes. And then we present multiple description coder which has two coding channels using the proposed EZW coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare multiple description image coding results reported to date. Simulation results show that the proposed method has a better performance than the polyphase transform method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.10
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• pp.735-745
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• 2001

Processors require both intensive and extensive functional verification in their design phase due to their general purpose. The proposed random vector verification method for embedded control RISC cores meets this goal by contributing assistance for conventional methods. The proposed method proved its effectiveness during the design of CalmRISCTM-32 developed by Yonsei Univ. and Samsung. It adopts a cycle-accurate instruction level simulator as a reference model, runs simulation in both the reference and the target HDL and reports errors if any difference is found between them. Consequently, it successfully covers errors designers easily pass over and establishes other new error check points.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2975-2982
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• 2010

In this paper, embedded control system of segway robot using model based design is presented. Design of control program in embedded system can be implemented simply and easily by model based design method using MATLAB/SIMULINK. Segway robot is consisted of a NXT Mindstorms controller, two DC servo motors, a ultrasonic sensor, a gyro sensor, and a light sensor. It is a unstable nonlinear system and has a control problem of body pitch angle. So controller of segway robot is designed using state feedback LQR control. It is confirmed through design and experiment of controller that the model based design method, that is not depend on target processor, has merits compared with the text based design in aspects such as a program development, an error detection/modify, and an insight of software structure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.82-89
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• 2015

The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.9-17
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• 2022

As the COVID-19 pandemic situation worsens, the time spent indoors increases, and the exposure to indoor environmental pollution such as indoor air pollution and noise also increases, causing problems such as deterioration of human health, stress, and discord between neighbors. This paper designs and implements a system that measures and monitors indoor air quality and noise, which are representative evaluation criteria of the indoor environment. The system proposed in this paper consists of a particulate matter measurement subsystem that measures and corrects the concentration of particulate matters to monitor indoor air quality, and a noise measurement subsystem that detects changes in sound and converts it to a sound pressure level. The concentration of indoor particulate matters is measured using a laser-based light scattering method, and an error caused by temperature and humidity is compensated in this paper. For indoor noise measurement, the voltage measured through a microphone is basically measured, Fourier transform is performed to classify it by frequency, and then A-weighting is performed to correct loudness equality. Then, the RMS value is obtained, high-frequency noise is removed by performing time-weighting, and then SPL is obtained. Finally, the equivalent noise level for 1 minute and 5 minutes are calculated to show the indoor noise level. In order to classify noise into direct impact sound and air transmission noise, a piezo vibration sensors is mounted to determine the presence or absence of direct impact transmitted through the wall. For performance evaluation, the error of particulate matter measurement is analyzed through TSI's AM510 instrument. and compare the noise error with CEM's noise measurement system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.617-627
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• 2021

Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.506-513
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• 2021

The durability and safety of reinforced concrete structures significantly depend on the reinforcement conditions, concrete cover thickness, cracks, and concrete strength. There are two ways to accurately determine the information on reinforcing bars embedded in concrete - the local destructive method and the non-destructive rebar detection test. In general, the non-destructive rebar detection tests, such as the electromagnetic wave radar method, electromagnetic induction method, and radiation method, are adopted to avoid damage to the structural elements. The moisture content and temperature of concrete affect the dielectric constant, which is the electrical property of concrete, and cause interference in the non-destructive rebar detection test results. Therefore, in this study, the effects of the electromagnetic wave radar method and electromagnetic induction method have been analyzed according to the temperature and surface moisture content of concrete. Due to the technological advancement and development of equipment, the average error rate was less than 5% in the specimens at 24℃, irrespective of their operating principles. Among the tested methods, the electromagnetic induction method showed very high accuracy. The electromagnetic wave radar method indicated a relatively small error rate in the dry state than in the wet state, and exhibited a relatively high error rate at high temperatures. It was confirmed that the error could be reduced by applying the electromagnetic wave radar method when the temperature of the probe was low and in a dry state, and by using the electromagnetic induction method when the probe was in a wet state or at a high temperature.