• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.53-64
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• 2011

In this paper, we propose a channel estimation of side information method based received motion vectors for distributed video coding. The proposed decoder estimates motion vectors of side information and transmits it to the encoder. As the proposed encoder generates side information which is the same to one in the decoder with received motion vectors, accuracy of side information of the decoder is assessed and it is transmitted to decoder. The proposed decoder can also estimate accurate crossover probability with received error information. As the proposed method conducts correct belief propagation, computational complexity of the channel decoder decreases and error correction capability is significantly improved with the smaller amount of parity bits. Experimental results show that the proposed algorithm is better in rate-distortion performance and it is faster than several conventional distributed video coding methods.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1089-1099
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• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.8-16
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• 2016

In the field of computer vision and robotics, bin picking is an important application area in which object pose estimation is necessary. Different approaches, such as 2D feature tracking and 3D surface reconstruction, have been introduced to estimate the object pose accurately. We propose a new approach where we can use both 2D image features and 3D surface information to identify the target object and estimate its pose accurately. First, we introduce a label detection technique using Maximally Stable Extremal Regions (MSERs) where the label detection results are used to identify the target objects separately. Then, the 2D image features on the detected label areas are utilized to generate 3D surface information. Finally, we calculate the 3D position and the orientation of the target objects using the information of the 3D surface.

• Computers and Concrete
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• v.4 no.1
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• pp.1-18
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• 2007

Over the past decades, an enormous amount of effort has been expended in laboratory and field studies on concrete durability estimation. The results of this research are still either widely scattered in the journal literature or mentioned briefly in the standard textbooks. Moreover, the theoretical approaches of deterioration mechanisms with a predictive character are limited to some complicated mathematical models not widespread in practice. A significant step forward could be the development of appropriate software for computer-based estimation of concrete service life, including reliable mathematical models and adequate experimental data. In the present work, the basis for the development of a computer estimation of the concrete service life is presented. After the definition of concrete mix design and structure characteristics, as well as the consideration regarding the environmental conditions where the structure will be found, the concrete service life can be reliably predicted using fundamental mathematical models that simulate the deterioration mechanisms. The prediction is focused on the basic deterioration phenomena of reinforced concrete, such as carbonation and chloride penetration, that initiate the reinforcing bars corrosion. Aspects on concrete strength and the production cost are also considered. Field observations and data collection from existing structures are compared with predictions of service life using the above model. A first attempt to develop a database of service lives of different types of reinforced concrete structure exposed to varying environments is finally included.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.2
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• pp.131-137
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• 2021

The Angle-of-Arrival (AOA) estimation in real time is one of core technologies for the real-time tracking system, such as a radar or a satellite. Although AOA estimation algorithms for various antenna types have been studied, most of them are for the single-shaped array antenna suitable to the specific frequency. In this paper, we propose the cascade AOA estimation algorithm for the combined array antenna with Uniform Rectangular Frame Array (URFA) and Uniform Circular Array (UCA), with the excellent performance for various frequencies. The proposed technique is consisted of Capon for roughly finding AOA groups with multiple signal AOAs and Beamspace Multiple Signal Classification (MUSIC) for estimating the detailed signal AOA in the AOA group, for the combined array antenna. In addition, we provide computer simulation results for verifying the estimation performance of the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.99-102
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• 2003

A new interacting multiple model (IMM) method using genetic algorithm (GA)-based intelligent input estimation(IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The GA is utilized to optimize a fuzzy system fur a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation(IE) technique and the adaptive interacting multiple model (AIMM) method.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.659-668
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• 2017

The inverse Weibull distribution (IWD) can be readily applied to a wide range of situations including applications in medicines, reliability and ecology. It is generally known that the lifetimes of test items may not be recorded exactly. In this paper, therefore, we consider the maximum likelihood estimation (MLE) and Bayes estimation of the entropy of a IWD under generalized progressive hybrid censoring (GPHC) scheme. It is observed that the MLE of the entropy cannot be obtained in closed form, so we have to solve two non-linear equations simultaneously. Further, the Bayes estimators for the entropy of IWD based on squared error loss function (SELF), precautionary loss function (PLF), and linex loss function (LLF) are derived. Since the Bayes estimators cannot be obtained in closed form, we derive the Bayes estimates by revoking the Tierney and Kadane approximate method. We carried out Monte Carlo simulations to compare the classical and Bayes estimators. In addition, two real data sets based on GPHC scheme have been also analysed for illustrative purposes.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2610-2612
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• 2004

The polyphase filter-based orthogonal frequency division multiplexing (PF-OFDM) is proposed in [1]. It provides more efficient data transmission mechanism than the classical OFDM method. However, the channel estimation mechanism in the classical OFDM system such as the cyclic prefix can not be applied straightforwardly, since the received signal contains unpredictable terms. Therefore, the PF-OFDM system requires a complicated channel estimation scheme when it works on the multipath fading communication channel. In this paper, we proposed a pilot-symbol aided channel estimation algorithm suitable for the PF-OFDM system which efficiently deals with the unpredictable terms and verified its performance through a series of computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2057-2060
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• 2016

Range-based motion estimation of a moving object by using a camera is proposed. Whereas the existing results constrain the motion of an object for the motion estimation of an object, the constraints on the motion is relieved in the proposed method in that a more generally moving object motion can be handled. To this end, a nonlinear observer is designed based on the relative dynamics between the object and camera so that the object velocity and the unknown camera velocity can be estimated. Stability analysis and simulation results for the moving object are provided to show the effectiveness of the proposed method.