• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.899-905
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• 2013

In this paper, we focus on how to calibrate multi-cameras easily and how to efficiently detect quad-copters with small-numbered particles. Each particle is a six dimensional vector that is composed of 3D position and 3D orientation of a quad-copter in the space. Due to curse of dimensionality, that leads to explosive computational costs with a large amount of high-dimensioned particles. To detect efficiently, we need to put more particles in very promising spaces and few particles in other spaces. Though computational cost is lowered by minimizing particles, in order to track a quad-copter with multiple cameras in real-time, multiple images from the cameras should be synchronized and analyzed. Therefore, lots of the computations still need to be done. Because of this, GPGPU(General-Purpose computing on Graphics Processing Units) is implemented for parallel computing. This method has been successfully tested and gives accurate results in practical situations.

• Korean Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.133-141
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• 1997

In the process of car body design, various surfaces are generated from the given boundary curves. Depending upon the method of the surface generation and the quality of the boundary curves provided, the resulting surfaces may have global or local irregularities in many cases. Thus it would be necessary for the designer to evaluate the surface quality and to modify the surface or to use the different generation method based on the evaluation results. This capability is very important because the defect of the surface quality detected in the production stage will require the rework of the dies and will cause a big loss in cost and time. A method of surface interrogation using reflection line is introduced. In this paper, We applied reflection mapping to generate reflection lines on the trimmed NURBS surface. Since reflection lines are obtained from reflection mapping that uses simple and physically acceptable mapping algorithm, they can be efficiently used to simulate the reflection test on the real part in the production line.

• ETRI Journal
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• v.38 no.2
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• pp.397-404
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• 2016

In group-oriented applications, it is often required to verify a group of signatures/messages. The individual verification of signed messages in such applications comes at a high cost in terms of computations and time. To improve computational efficiency and to speed up the verification process, a batch verification technique is a good alternative to individual verification. Such a technique is useful in many real-world applications, such as mail servers, e-commerce, banking transactions, and so on. In this work, we propose a new, efficient identity-based signature (IDS) scheme supporting batch verifications. We prove that the proposed IDS scheme and its various types of batch verifications is tightly related to the Computational Diffie.Hellman problem under a random oracle paradigm. We compare the efficiency of the proposed scheme with related schemes that support batch verifications.

• ETRI Journal
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• v.31 no.4
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• pp.454-456
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• 2009

The maximum likelihood linear spectral transformation (ML-LST) using a numerical iteration method has been previously proposed for robust speech recognition. The numerical iteration method is not appropriate for real-time applications due to its computational complexity. In order to reduce the computational cost, the objective function of the ML-LST is approximated and a closed-form solution is proposed in this paper. It is shown experimentally that the proposed closed-form solution for the ML-LST can provide rapid speaker and environment adaptation for robust speech recognition.

• Structural Engineering and Mechanics
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• v.52 no.4
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• pp.815-827
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• 2014

Buckling optimization of laminated composite plates is significant as they fail because of buckling under in-plane compressive loading. The plate is usually modeled without cutout so that the buckling strength is found analytically using classical laminate plate theory (CLPT). However in real world applications, the composite plates are modeled with cutouts for getting them assembled and to offer the provisions like windows, doors and control system. Finite element analysis (FEA) is used to analyze the buckling strength of the plate with cutouts and it leads to high computational cost when the plate is optimized. In this article, a genetic algorithm based optimization technique is used to optimize the composite plate with cutout. The computational time is highly reduced by replacing FEA with artificial neural network (ANN). The effectiveness of the proposed method is explored with two numerical examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.299-304
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• 2003

The design of an occupant protection equipment has been considered as the important process in developing a new car since the crash performance plays an important role on the market. The cost is increased when an unexpected real test is carried out in the proto-design stage. Thus, the exact prediction of a crash performance can reduce the number of full-car test. In this research, the robust design of an airbag system considering the frontal crash is suggested to predict the more reliable responses. On the contrary, most existing researches do not consider the uncertainties. The uncertainties treated in this research are the tolerances of the vent hole, the time to fire and the length of a strap in airbag and the tolerance of the load limiter load in seat belt. The Taguchi method is utilized to determine the robust optimum of each parameter

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1169-1193
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• 2010

In this paper, we present and compare two different multiple camera collaboration strategies to reduce false association in finding the correspondence of objects. Collaboration matrices are defined with the required minimum separation for an effective collaboration because homographic lines for objects association are ineffective with the insufficient separation. The first strategy uses the collaboration matrices to select the best pair out of many cameras having the maximum separation to efficiently collaborate on the object association. The association information in selected cameras is propagated to unselected cameras by the global information constructed from the associated targets. While the first strategy requires the long operation time to achieve the high association rate due to the limited view by the best pair, it reduces the computational cost using homographic lines. The second strategy initiates the collaboration process of objects association for all the pairing cases of cameras regardless of the separation. In each collaboration process, only crossed targets by a transformed homographic line from the other collaborating camera generate homographic lines. While the repetitive association processes improve the association performance, the transformation processes of homographic lines increase exponentially. The proposed methods are evaluated with real video sequences and compared in terms of the computational cost and the association performance. The simulation results demonstrate that the proposed methods effectively reduce the false association rate as compared with basic pair-wise collaboration.

• Advances in Computational Design
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• v.3 no.4
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• pp.385-404
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• 2018

The study investigated an area of sustainable structural design that is often overlooked in practical engineering applications. Specifically, a novel method to simultaneously optimise the cost and embodied carbon performance of steel building structures was explored in this paper. To achieve this, a parametric design model was developed to analyse code compliant structural configurations based on project specific constraints and rigorous testing of various steel beam sections, floor construction typologies (precast or composite) and column layouts that could not be performed manually by engineering practitioners. Detailed objective functions were embedded in the model to compute the cost and life cycle carbon emissions of the different material types used in the structure. Results from a comparative numerical analysis of a real case study illustrated that the proposed optimisation approach could guide structural engineers towards areas of the solution space with realistic design configurations, enabling them to effectively evaluate trade-offs between cost and carbon performance. This significant contribution implied that the optimisation model could reduce the time required for the design and analysis of multiple structural configurations especially during the early stages of a project. Overall, the paper suggested that the deployment of automated design procedures can enhance the quality as well as the efficiency of the optimisation analysis.

• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.484-494
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• 2017

In industrial plants such as nuclear power plants, system operations are performed by embedded controllers orchestrated by Supervisory Control and Data Acquisition (SCADA) software. A targeted attack (also termed a control aware attack) on the controller/SCADA software can lead a control system to operate in an unsafe mode or sometimes to complete shutdown of the plant. Such malware attacks can result in tremendous cost to the organization for recovery, cleanup, and maintenance activity. SCADA systems in operational mode generate huge log files. These files are useful in analysis of the plant behavior and diagnostics during an ongoing attack. However, they are bulky and difficult for manual inspection. Data mining techniques such as least squares approximation and computational methods can be used in the analysis of logs and to take proactive actions when required. This paper explores methodologies and algorithms so as to develop an effective monitoring scheme against control aware cyber attacks. It also explains soft computation techniques such as the computational geometric method and least squares approximation that can be effective in monitor design. This paper provides insights into diagnostic monitoring of its effectiveness by attack simulations on a four-tank model and using computation techniques to diagnose it. Cyber security of instrumentation and control systems used in nuclear power plants is of paramount importance and hence could be a possible target of such applications.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.171-177
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• 2011

In order to construct approximation functions for real data, it is necessary to remove the outliers from the measured raw data before constructing the model. Conventionally, visualization and maximum residual error have been used for outlier detection, but they often fail to detect outliers for nonlinear functions with multidimensional input. Although the standard support vector regression based outlier detection methods for nonlinear function with multidimensional input have achieved good performance, they have practical issues in computational cost and parameter adjustments. In this paper we propose a practical approach to outlier detection using support vector regression that reduces computational time and defines outlier threshold suitably. We apply this approach to real data examples for validity.