• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.23-30
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• 2022

The active phased array antenna system performs beam steering, multi-beam formation and adaptive beam forming by controlling the amplitude and phase of signals fed to each radiating element. In order to obtain the desired radiation characteristics using an active phased array antenna system, the accurate amplitude and phase of the signal must be fed to each radiating element; however, due to various causes, the signal errors occurs in each radiating element. In this paper, a signal error estimation method of each radiating element is proposed. The proposed method simplifies the process of signal error estimation, and can quickly and accurately calculate the signal error.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.339-340
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• 2010

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.271-273
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• 2006

Because effect of value elevation is great as it is fast that construction VE is enforcement, VE at the design phase is more and more important more than construction process phase. But, is exerting negative impact for construction process phase by various problem that happen at design phase, and is causing discord to between project partners. Therefore, quality security in design phase is important first of all. Hereupon, this study emphasized that need VE at the design phase of extension plan forward more and more because achieved process that derive conceptional estimation by quantitative value calculating value index (V) through provision of design function point (F) and LCC expense (C) by comparison method of construction and chooses optimum method of construction through VE/LCC analysis example in improvement of soft soil ground method choice process of design phase.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.200-202
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• 2005

In this paper, improved rotor position estimation for position sensorless control system of the SRM (Switched Reluctance Motor) is presented. For more accurate rotor position estimation, the PLL (Phase Locked Loop) based position interpolation is adapted. In the current-flux-rotor position lookup table based rotor position estimation, the inherent current and flux-linkage ripple can cause the position estimation error. Instead of the conventional low-pass filter, the PLL based position interpolation technique is used for the better dynamic performance. The developed rotor position estimation scheme is realized using TMS320F2812 digital signal processor and prototype 1-hp SRM.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.485-496
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• 2023

Precise construction cost estimation is paramount to determining the total construction expense of a project prior to the initiation of the construction phase. Despite this, manual quantification and cost estimation methods, which continue to be widely used, may result in imprecise estimation and subsequent financial loss. Given the fast-paced and efficiency-demanding nature of the construction industry, trustworthy quantity and cost estimation is essential. To mitigate these obstacles, this research is focused on establishing an automated quantity estimation algorithm, particularly designed for the main rebar of beams which are recognized for their complicated reinforcement configurations. The exact quantity derived from the proposed algorithm is compared to the manually approximated quantity, reflecting a variance of 10.27%. As a result, significant errors and impending financial loss can be averted. The implementation of the findings from this research holds the potential to significantly assist construction firms in quickly and accurately estimating rebar quantities while adhering strictly to applicable specifications and regulatory requirements.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.419-425
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• 2013

Recently AEC industry has required construction automation according to becoming large and complex. Thus BIM-based construction project is increased and used in whole fields of AEC industry. Quantity take-off and estimation fields are important factor for decision-making in conceptual and schematic design stages of construction projects. The purpose of this study improves reliability of the estimation through QTO based on Open BIM. Scope and method to apply QTO is to select conceptual design stage through LoD(Level of Detail) in AEC field and to extract information from BIM model through analysis of IFC structure. This study proceeds three step to make BIM model and check the model quality and calculate QTO. The methodology of QTO using IFC is to verify of result in this study and expects utilizing in design stage of construction projects. The result from this study is expected to decrease the risk factor and time of estimation in the project early phase through improving reliability of schematic estimation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1070-1079
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• 2016

In this paper, the design of recursive radial basis function neural networks based on incremental fuzzy c-means is introduced for processing the big data. Radial basis function neural networks consist of condition, conclusion and inference phase. Gaussian function is generally used as the activation function of the condition phase, but in this study, incremental fuzzy clustering is considered for the activation function of radial basis function neural networks, which could effectively do big data processing. In the conclusion phase, the connection weights of networks are given as the linear function. And then the connection weights are calculated by recursive least square estimation. In the inference phase, a final output is obtained by fuzzy inference method. Machine Learning datasets are employed to demonstrate the superiority of the proposed classifier, and their results are described from the viewpoint of the algorithm complexity and performance index.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.625-628
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• 2007

We present an efficient and robust technique to estimate the velocity of moving targets from a single SAR image. In SAR images, azimuth image shift is a well known phenomenon, which is observed in moving targets having slant-range velocity. Most methods estimated the velocity of moving targets from the distance difference between the road and moving targets or between ship and the ship wake. However, the methods could not be always applied to moving targets because it is difficult to find the road and the ship wake. We adopted a method estimating the velocity of moving targets from azimuth differentials of range-compressed image. This method is based on an assumption that Doppler center frequency shift of moving target causes a phase difference in azimuth differential values. The phase difference is linearly distorted by Doppler rate due to the geometry of SAR image. The linear distortion is eliminated from phase removal procedure, and the constant phase difference is estimated. Finally, range velocity estimates for moving targets are retrieved. This technique is tested using an ENVISAT ASAR image in which several unknown ships are presented. The theoretical accuracy of this technique is discussed by SAR simulation. The advantages and disadvantages of this method over the conventional method are also discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.959-966
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• 2010

Quantitative ultrasound analysis provides fundamental information of various ultrasound parameters using spectral information of the short-gated radiofrequency(RF) data. Therefore, accurate extraction of spectral information from backscattered RF signal is crucial for further analysis of medical ultrasound parameters. In this paper, we propose two techniques for calculating a more accurate power spectrum which are based on the phase-compensation using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio(SNR). The simulation results demonstrate that the proposed method estimates better results with 10% smaller estimation variances compared to the conventional methods.