• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2439-2442
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• 2000

This paper presents a practical On-The-Fly(OTF) integer ambiguity resolution algorithm for real-time precise positioning with low cost, $L_1$ single frequency, conventional C/A code GPS receiver. A state reconfiguration scheme is adopted in the Kalman filter to deal with the variation of ambiguity states caused by varying sets of visible GPS satellites. The proposed algorithm reduces the ambiguity search space from the coarse m-level C/A code pseudorange measurements of the conventional C/A code reciever, thereby reducing the computational time. Simulation results are presented to show that the algorithm achieves a cm-level accuracy.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.28-35
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• 2010

This paper presents new Adaptive Linear Combination Structure (ADALINE) for tracking/estimating voltage-current phasor and frequency of power system. To estimate the phasors and frequency from sampled data, the algorithm assumes that orthogonal coefficients and speed of angular frequency of power system are unknown parameters. With adequate sampled data, the estimation problem can be considered as a linear weighted least squares (LMS) problem. In addition to determining the phasors (orthogonal coefficients), the procedure estimates the power system frequency. The main algorithm is verified through a computer simulation and data from field. The proposed algorithm is tested with transient and dynamic behaviors during power swing, a step change of frequency upon islanding of small generators and disconnection of load. The algorithm shows a very high accuracy, robustness, fast response time and adaptive performance over a wide range of frequency, from 10 to 2000 Hz.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3482-3497
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• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• 한국정보전자통신기술학회논문지
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• 제13권2호
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• pp.153-158
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• 2020

본 논문에서는 무선 통신 환경에서 잡음 및 간섭을 제거하여 원하는 목표물을 추정하는 알고리즘을 연구하였다. 잡음과 간섭이 포함된 정보신호가 수신기에 입사하면 원하는 목표물을 정확히 추정하기 어렵기 때문에 잡음 및 간섭 신호를 제거하는 방법이 필수적이다. 수신 신호영역을 두 공간으로 분리하기 위해서 상관행렬, 공분산, 고유특성벡터, 고유치를 분석하여 전력 스펙트럼을 획득한다. 제안한 전력 스펙트럼은 잡음을 제거할 수 있는 알고리즘으로서 목표물 추정성능을 분석하기 위해서 기존의 알고리즘과 모의실험을 통해서 확인한다. 모의실험 결과로, 기존 알고리즘의 목표물방향 추정 분해능은 10°이상이지만, 제안 알고리즘의 분해능은 10°미만을 나타내었다. 제안 알고리즘이 기존 알고리즘보다 약 5°의 분해능이 향상 되었다. 본 연구에서 제안된 알고리즘이 목표물 추정 정확도와 분해능이 기존 알고리즘보다 우수함을 입증하였다.

• 한국CDE학회논문집
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• 제4권3호
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• pp.247-258
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• 1999

With the contemporary CAD/CAM system, where the tool path is generated and verified purely based on the geometric operation, geometric accuracy of the machined surface cannot be guaranteed dut to the cutting mechanics, meaning that the cutting mechanics should be incorporated in some fashion. In this paper, we incorporate the instantaneous cutting force and the tool deflection phenomena in predicting the machined surface for the finish-cut and milling operation. For the given NC dat including cutting conditions, the developed algorithm computes cutting force and deflection amount along the tool trajectory, and outputs the 3D graphic model of the machined surface together with error analysis. The validity and accuracy of the presented method has been tested by the actual cutting experiments. Experimental results and accuracy enhancement method together with implementing architecture of the VMCS (Virtual Machining CAM System) are discussed in the paper.

• 응용통계연구
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• 제23권2호
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• pp.357-366
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• 2010

Many tree algorithms have been developed for regression problems. Although they are regarded as good algorithms, most of them suffer from loss of prediction accuracy when there are many noise variables. To handle this problem, we propose the multi-step GUIDE, which is a regression tree algorithm with a variable selection process. The multi-step GUIDE performs better than some of the well-known algorithms such as Random Forest and MARS. The results based on simulation study shows that the multi-step GUIDE outperforms other algorithms in terms of variable selection and prediction accuracy. It generally selects the important variables correctly with relatively few noise variables and eventually gives good prediction accuracy.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3764-3771
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• 2021

Based on the convolutional neural network (CNN), a novel technique is investigated for lost gamma source detection in a room. The CNN is trained with the result of a GEANT4 simulation containing a gamma source inside a meshed room. The dataset for the training process is the deposited energy in the meshes of different n-step paths. The neural network is optimized with parameters such as the number of input data and path length. Based on the proposed method, the place of the gamma source can be recognized with reasonable accuracy without human intervention. The results show that only by 5 measurements of the energy deposited in a 5-step path, (5 sequential points 50 cm apart within 1600 meshes), the gamma source location can be estimated with 94% accuracy. Also, the method is tested for the room geometry containing the interior walls. The results show 90% accuracy with the energy deposition measurement in the meshes of a 5-step path.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1993년도 가을 학술발표회논문집
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• pp.248-255
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• 1993

Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.

• Journal of the Optical Society of Korea
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• 제19권1호
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• pp.84-87
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• 2015

For large optical elements which are tested by many sub-apertures, it takes too much time for a sub-aperture stitching algorithm to get the stitching result. To solve this problem, we propose a fast sub-aperture stitching algorithm to quickly compensate for piston, tilt, and defocus errors. Moreover, the new algorithm is easy to understand and program. We use partial derivatives of measurement data to separately solve piston, tilt, and defocus errors. First, we show that the new algorithm has a lower time complexity than the currently used algorithm. Although simulation results indicate that the accuracy of the new algorithm is lower than the current algorithm in all 20 simulations, our experimental results validate the algorithm and show it is sufficiently accurate for general use.