• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2420-2435
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• 2010

This study presented estimation framework that consider website pattern and user use purpose for website estimation improvement. Also, analyzed and evaluated existing website using estimation framework. In this study, divided by general user and company user and analyzed relative importance between each estimation factors in estimation framework and secured reliability of website estimation model because applies AHP method and presented key factors to website construction, operation, administration. Through this study, projected necessity of weight calculation between estimation area by site type to website estimation field researchers and differentiate contents offered that follow in user type(individual, company) to website planners and operators, projected guideline that can provide more efficient and strategic service.

• Journal of the Korean Society of Systems Engineering
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• v.8 no.2
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• pp.57-67
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• 2012

It is the sensitivity and confidentiality of nuclear power plant decommissioning cost that prevent detailed cost information to be released to the public, which causes some limitation to analyze and reuse the costs. This limitation to access cost information means that the lessons learned from preceding cost estimating may not systematically feed back into following cost estimates. As an alternative, decommissioning cost estimation framework is indispensable to reflecting available experience and knowledge for decommission costs. This study provides the cost estimation framework including data flow and structuralization based on engineering and bottom up approach to enhance decommissioning cost estimation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.779-782
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• 2017

OpenBR is a framework for researching new facial recognition methods, improving existing algorithms, interacting with commercial systems, measuring perceived performance, and deploying automated biometric systems. Designed to facilitate rapid algorithm prototyping, it features a mature core framework, flexible plug-in system, and open and closed source development support. The established algorithms can be used for specific forms such as face recognition, age estimation, and gender estimation. In this paper, we describe the framework of OpenBR and implement facial recognition, gender estimation, and age estimation using supported programs.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.209-215
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• 2022

This paper proposes a novel approach for training an unsupervised depth estimation algorithm. The objective of unsupervised depth estimation is to estimate pixel-wise distances from camera without external supervision. While most previous works focus on model architectures, loss functions, and masking methods for considering dynamic objects, this paper focuses on the training framework to effectively use depth cue. The main loss function of unsupervised depth estimation algorithms is known as the photometric error. In this paper, we claim that direct depth cue is more effective than the photometric error. To obtain the direct depth cue, we adopt the technique of knowledge distillation which is a teacher-student learning framework. We train a teacher network based on a previous unsupervised method, and its depth predictions are utilized as pseudo labels. The pseudo labels are employed to train a student network. In experiments, our proposed algorithm shows a comparable performance with the state-of-the-art algorithm, and we demonstrate that our teacher-student framework is effective in the problem of unsupervised depth estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.559-575
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• 2023

3D human pose estimation is widely applied in various fields, including action recognition, sports analysis, and human-computer interaction. 3D human pose estimation has achieved significant progress with the introduction of convolutional neural network (CNN). Recently, several researches have proposed the use of multiview approaches to avoid occlusions in single-view approaches. However, as the number of cameras increases, a 3D pose estimation system relying on a CNN may lack in computational resources. In addition, when a single host system uses multiple cameras, the data transition speed becomes inadequate owing to bandwidth limitations. To address this problem, we propose a distributed real-time 3D pose estimation framework based on asynchronous multiple cameras. The proposed framework comprises a central server and multiple edge devices. Each multiple-edge device estimates a 2D human pose from its view and sendsit to the central server. Subsequently, the central server synchronizes the received 2D human pose data based on the timestamps. Finally, the central server reconstructs a 3D human pose using geometrical triangulation. We demonstrate that the proposed framework increases the percentage of detected joints and successfully estimates 3D human poses in real-time.

• ETRI Journal
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• v.36 no.3
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• pp.460-468
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• 2014

This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra-wideband systems with a two-antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter-estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint-estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.607-612
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• 2007

Early cost estimation promote efficient budget plan by comparing alternatives and presenting cost information However it is hard to predict accurate cost because of vague cost standard and lack of available information in the early stage. The precious cost model has limitations in the accuracy because they are simple linear model which uses the unit cost per kilometer. This study presents the framework of early cost estimation for road construction projects to overcome the limitation of previous cost model. This study analyzed domestic and foreign cost model and cost data of previous road construction project to present method of cost model framework.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.641-650
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• 2017

In order to include the design capability for a compound rotorcraft in a helicopter conceptual design and optimization framework, relevant further improvement was planned and conducted. Previously, a certain conceptual design optimization framework was developed by the present authors to design a modern rotorcraft with single main and tail rotor. The previously developed framework was further improved to expand its capability for a compound rotorcraft. Specifically, its power estimation algorithm was upgraded by using a comprehensive rotorcraft analysis program, CAMRAD II. The presently improved conceptual design and optimization framework was validated using data of the XH-59A aircraft.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1078-1090
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• 2022

The distribution patterns of battery usage time data per battery level are able to affect the performance of estimating battery remaining time in mobile devices. Outliers may mainly affect the estimation performance of statistical regression methods. In this paper, we propose a software framework that detects and processes outliers to improve the estimation performance of statistical regression methods. The proposed framework first detects outliers that degrade the estimation performance. The proposed framework replaces outliers with smoothed data. The difference between an outlier and its replaced data will be properly distributed into individual data. Finally, individual data are reinforced to improve the estimation performance. The numerical results obtained by experimenting the proposed framework confirmed that it yielded good performance of estimating battery remaining time.

• Computers and Concrete
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• v.33 no.5
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.