• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.49-55
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• 2008

To address the convergence issue of power control algorithms, a number of algorithms have been developed hat shape the dynamics of up-link power control for cellular network. Power algorithms based on fixed point iterations can be accelerated by the use of various methods, one of the simplest being the use of Newton iterations, however, this method has the disadvantage which not only needs derivatives of the cost function but also may be weak to noisy environment. we showed performance of the power control schemes to solve the fixed point problem under static or stationary channel. They proved goof performance to solve the fixed point problem due to their predictor based optimal control and quadratic convergence rate. Here, we apply the proposed power control schemes to the problem of the dynamic channel or to dynamic time varying link gains. The rigorous simulation results demonstrated the validity of our approach.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.1027-1035
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• 2012

This paper proposes a new Levenberg-Marquardt algorithm that is accelerated by adjusting a Jacobian matrix and a quasi-Hessian matrix. The proposed method partitions the Jacobian matrix into block matrices and employs the inverse of a partitioned matrix to find the inverse of the quasi-Hessian matrix. Our method can avoid expensive operations and save memory in calculating the inverse of the quasi-Hessian matrix. It can shorten the training time for fast convergence. In our results tested in a large application, we were able to save about 20% of the training time than other algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.666-672
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• 2016

Recently the fingerprint is widely used as one of biometrics to improve the security of financial mobile applications, because of its user convenience and high recognition rate. However, in order to apply fingerprint algorithms to finance and security applications, the recognition rate and processing speed of the fingerprint algorithms have to be improved further. In this paper, we propose the parallel fingerprint enhancement algorithm on general-purpose computing on graphics processing unit (GPGPU) using OpenCL. We discuss the analysis of the parallelism in the fingerprint algorithm as well as the exploration of optimization parameters of the parallel fingerprint algorithm to improve the performance. The experimental results showed that the execution of parallel fingerprint enhancement algorithm on GPGPUs was accelerated from 29.4 upto 69.2 times compared with the execution of the original one on the host CPUs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.9-12
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• 2015

In this paper, we propose a new feature matching algorithm by modifying and combining the FAST(Features from Accelerated Segment Test) feature detector and SURF feature descriptor which is robust to the distortion of the given image. Scale space is generated to consider the variation of the scale and determine the candidate of features in the image robust to the noise. The original FAST algorithm results in many feature points along edges. To solve this problem, we apply the principal curvatures for refining it. We also use SURF descriptor to make it robust against the variations in the image by rotation. Through the experiments, it is shown that the proposed algorithm has better performance than the conventional feature matching algorithms even though it has much less computational load. Especially, it shows a strength for noisy images.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.271-276
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• 2016

In this paper, we propose robust face and eye detection algorithm under changing environmental condition such as lighting and pose variations. Generally, the eye detection process is performed followed by face detection and variations in pose and lighting affects the detection performance. Therefore, we have explored face detection based on Modified Census Transform algorithm. The eye has dominant features in face area and is sensitive to lighting condition and eye glasses, etc. To address these issues, we propose a robust eye detection method based on Gabor transformation and Features from Accelerated Segment Test algorithms. Proposed algorithm presents 27.4ms in detection speed with 98.4% correct detection rate, and 36.3ms face detection speed with 96.4% correct detection rate for eye detection performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.783-790
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• 2016

One of the main factors related to the deterioration of estimation accuracy in inertial measurement unit (IMU)-based orientation determination is the object's acceleration. This is because accelerometer signals under accelerated motion conditions cannot be longer reference vectors along the vertical axis. In order to deal with this issue, some orientation estimation algorithms adopt acceleration-compensating mechanisms. Such mechanisms include the simple switching techniques, mechanisms with adaptive estimation of acceleration, and acceleration model-based mechanisms. This paper compares these three mechanisms in terms of estimation accuracy. From experimental results under accelerated dynamic conditions, the following can be concluded. (1) A compensating mechanism is essential for an estimation algorithm to maintain accuracy under accelerated conditions. (2) Although the simple switching mechanism is effective to some extent, the other two mechanisms showed much higher accuracies, particularly when test conditions were severe.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.79-89
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• 2022

Images taken using drones have been applied to fields that require rapid decision-making as they can quickly construct high-quality 3D spatial information for small regions. To construct spatial information based on drone images, it is necessary to determine the relationship between images by extracting keypoints between adjacent drone images and performing image matching. Therefore, in this study, three study regions photographed using a drone were selected: a region where parking lots and a lake coexisted, a downtown region with buildings, and a field region of natural terrain, and the performance of AKAZE (Accelerated-KAZE), BRISK (Binary Robust Invariant Scalable Keypoints), KAZE, ORB (Oriented FAST and Rotated BRIEF), SIFT (Scale Invariant Feature Transform), and SURF (Speeded Up Robust Features) algorithms were analyzed. The performance of the keypoints extraction algorithms was compared with the distribution of extracted keypoints, distribution of matched points, processing time, and matching accuracy. In the region where the parking lot and lake coexist, the processing speed of the BRISK algorithm was fast, and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the downtown region with buildings, the processing speed of the AKAZE algorithm was fast and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the field region of natural terrain, the keypoints and matched points of the SURF algorithm were evenly distributed throughout the image taken by drone, but the AKAZE algorithm showed the highest matching accuracy and processing speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.97-103
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• 2010

There are many algorithms for 2D to 3D graphic conversion technology which have the high complexity and large scale of iterative computation. So in this paper propose parallel algorithm and high speed graphics accelerator architecture using Park's MAMS(Multiple Access Memory System) for Phong Shading, one of many 3D algorithms. The Proposed SIMD processor architecture is simulated by HDL and simulated and got 30 times faster result. It means any kinds of 3D algorithm can make parallel algorithm and accelerated by SIMD processor with Park's MAMS for real time processing.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.229-251
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• 2021

Arteriosclerosis is the leading cause of stroke, with a fatality rate surpassing that of ischemic heart disease. High-resolution vessel wall magnetic resonance imaging is generally recognized as a non-invasive and panoramic method for the evaluation of arterial plaque; however, this method requires improved signal-to-noise ratio and scanning speed. Recent advances in high-density head and neck coil arrays are characterized by broad coverage, multiple channels, and closefitting designs. This review analyzes fast magnetic resonance imaging from the perspective of accelerated algorithms for vessel wall imaging and demonstrates the need for effective algorithms for signal acquisition using advanced radiofrequency system. We summarize different phased-array structures under various experimental objectives and equipment conditions, introduce current research results, and propose prospective research studies in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.139-155
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• 2006

The facility location problem of this paper is distinguished from the maximal covering location problem and the flxed-charge facility location problem. We propose the maximal profiting location problem (MPLP) that is the facility location problem maximizing profit with multi-product. We apply to the simulated annealing algorithm, the stochastic evolution algorithm and the accelerated simulated annealing algorithm to solve this problem. Through a scale-down and extension experiment, the MPLP was validated and all the three algorithm enable the near optimal solution to produce. As the computational complexity is increased, it is shown that the simulated annealing algorithm' is able to find the best solution than the other two algorithms in a relatively short computational time.