• Journal of electromagnetic engineering and science
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• v.15 no.1
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• pp.53-58
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• 2015

For the testing of nonlinear power amplifiers, this paper suggests an approach to design optimized multisine signals that could be substituted for the original modulated signal. In the design of multisines, complex coefficients should be determined to mimic the target signal as much as possible, but very few methods have been adopted as general solutions to the coefficients. Furthermore, no solid method for the phase of coefficients has been proven to show the best resemblance to the original. Therefore, in order to determine the phase of multisine coefficients, a time-domain nonlinear optimization method is suggested. A frequency-domain-method based on the spectral response of the target signal is also suggested for the magnitude of the coefficients. For the verification, multisine signals are designed to emulate the LTE downlink signal of 10 MHz bandwidth and are used to test a nonlinear amplifier at 1.9 GHz. The suggested phase-optimized multisine had a lower normalized error by 0.163 dB when N = 100, and the measurement results showed that the suggested multisine achieved more accurate adjacent-channel leakage ratio (ACLR) estimation by as much as 12 dB compared to that of the conventional iterative method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.112-116
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• 2002

A sensorless control strategy for permanent magnet synchronous motors is presented in this paper. A speed control scheme based on the measurement and observation of stator current, voltage. and flux vector is proposed. Two phase voltages and two stator currents are measured and processed in discrete form in DSP. The rotor position and speed are estimated through the stator flux and its derivative estimation. Flux and its derivative are calculated in the stationary reference frame and used to estimate the speed and position. The rotor position angle is then used in a microcontroller to produce the appropriate stator current command signals for the hysteresis current controller of the inverter. The closed-loop speed control has been shown to be effective from standstill to rated speed. Moreover, a flux drift problem caused by the integration can be eliminated so that a stable sensorless starting and running operation can be achieved. Computer simulation and experimental results are presented to demonstrate the effectiveness of the proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.762-770
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• 2014

Tangible Space Initiative (TSI) is a new framework that can provide a more natural and intuitive Human Computer Interface for users. This is composed of three cooperative components: a Tangible Interface, Responsive Cyber Space, and Tangible Agent. In this paper we present a Tangible Tele-Meeting system in TSI, which allows people to communicate with each other without any spatial limitation. In addition, we introduce a method for registering a Tangible Avatar with a Tangible Agent. The suggested method is based on relative pose estimation between the user and the Tangible Agent. Experimental results show that the user can experience an interaction environment that is more natural and intelligent than that provided by conventional tele-meeting systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2032-2038
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• 2006

The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle Inter and apply the MATLAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.702-707
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• 2004

This article is concerned with container pose estimation using CCD a camera and a range sensor. In particular, the issues of characteristic point extraction and image noise reduction are described. The Euler-Lagrange equation for gaussian and random noise reduction is introduced. The alternating direction implicit(ADI) method for solving Euler-Lagrange equation based on partial differential equation(PDE) is applied. The vertex points as characteristic points of a container and a spreader are founded using k order curvature calculation algorithm since the golden and the bisection section algorithm can't solve the local minimum and maximum problems. The proposed algorithm in image preprocess is effective in image denoise. Furthermore, this proposed system using a camera and a range sensor is very low price since the previous system can be used without reconstruction.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.3
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• pp.103-110
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• 2013

Logical Effort [1, 2] is a simple hand-calculated method that measures quick delay estimation. It has the advantage of reducing the design cycle time. However, it has shortcomings in designing a path for minimum area or power under a fixed-delay constraint. The method of overcoming the shortcomings is shown in [3], but it is constrained for a single logical path. This paper presents an advanced gate sizing method in multiple logical paths based on the equal delay model. According to the results of the simulation, the power dissipation for both the existing logical effort method and proposed method is almost equal. However, compared with the existing logical effort method, it is about 52 (%) more efficient in space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2396-2413
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• 2018

Trust management is one of the most challenging issues for the highly heterogeneous Internet of Things (IoT). In the context of the IoT, it is difficult to evaluate the node's trustworthiness in the same trust model when a node provides different services. Guaranteeing the availability of the trust management service is another significant challenge because of the dynamic nature of IoT environments. With these issues in mind, this paper propose a robust and adaptive trust management system for the IoT that is able to measure the trustworthiness of nodes based on feedbacks collected from participants in a specific context and ensure the availability of trust management services. The main contributions of our system are: 1) Proposing a partly decentralized trust management framework, which improves the resiliency of the trust mechanism; 2) Proposing an adaptive trust evaluation scheme and a three-dimensional context representation makes trust evaluation more accurate and specific; 3) Enhancing the adaptive trust evaluation scheme by incorporating a bad behavior factor in trust estimation, which efficiently distinguishes misleading feedbacks from On-Off attacks. Simulation results show the good performance of the proposed system and especially show effectiveness against On-Off attacks compared to other trust mechanisms.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1182-1189
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• 2009

A potential advantage of computer-based education is individualized instruction. In this regard, issues regarding how to evaluate individual learners fast and accurately in order to implement customized instruction program and to open education are raised. In this study, we suggest through a simulation study a way to reach an optimal decision by complementing the insufficient point of the way of the decision of the existing SPRT(Sequential Probability Ratio Testing) in which the number of questions in a test decreases while decision on pass or fail is relatively exact. For the purpose, the data of the examinees obtained from actual tests were used in this study and we present that simulation to verify the accuracy of decision and Multilevel SPRT decision standard for initial set point for optimal SPRT decision and evaluate the ground of the same through simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.102-107
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• 2019

This paper proposes a method to improve the mass spectral detection performance of the residual gas analyzer. By improving the mode estimation method for setting the threshold value and improving the additive noise elimination method, it is possible to detect mass spectrums having low peak values of the threshold level difficult to distinguish from noise. Ion signal blocks for each mass index with noise removed by the improved method are effective for eliminating invalid ion signals based on the linear and quadratic fittings. The mass spectrum can be obtained from the quadratic fitted curves for the reconstructed ion signal block using only the valid ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed method, computer simulations were performed using real ion signals obtained from the residual gas analysis system under development. The simulation results show that the proposed method is valid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.180-194
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• 2021

For small image registration, feature-based approaches are likely to fail as feature detectors cannot detect enough feature points from low-resolution images. The classic FFT approach's prediction accuracy is high, but the registration time can be relatively long, about several seconds to register one image pair. To achieve real-time and high-precision rigid registration for small images, we apply deep neural networks for supervised rigid transformation prediction, which directly predicts the transformation parameters. We train deep registration models with rigidly transformed CIFAR-10 images and STL-10 images, and evaluate the generalization ability of deep registration models with transformed CIFAR-10 images, STL-10 images, and randomly generated images. Experimental results show that the deep registration models we propose can achieve comparable accuracy to the classic FFT approach for small CIFAR-10 images (32×32) and our LSTM registration model takes less than 1ms to register one pair of images. For moderate size STL-10 images (96×96), FFT significantly outperforms deep registration models in terms of accuracy but is also considerably slower. Our results suggest that deep registration models have competitive advantages over conventional approaches, at least for small images.