• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.217-224
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• 1986

In case of VLSI design, the shuffle-exchange graph is useful for optimal layout. HOEY and LEISERSON proposed the method of drawing a N-nodes shuffle-exchange graph on O(N2/log N) layout area by using the complex plane digram. [2] In this paper, a new algorithm for drawing the shuffle-exchange graph is proposed. This algorithm is not by using the complex plane diabram, but the table of e decimal represented nodes of shuffle-edge relations. And the structural properties for optimal layout of the graph are summarized and verified. By using this more simplified algorithm, a FORTRAN program which can be treated faster is written. Aimed near optimal shuffle-exchange graphs are printed out by giving inputs` the number of nodes.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1852-1861
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• 2016

Drowsy driving is a significant factor in traffic accidents, so driver drowsiness detection system based on computer vision for convenience and safety has been actively studied. However, it is difficult to accurately detect the driver drowsiness in complex background and environmental change. In this paper, it proposed the driver drowsiness detection algorithm to determine whether the driver is drowsy through the measurement standard of a yawn, eyes drowsy status, and nod based on facial features. The proposed algorithm detect the driver drowsiness in the complex background, and it is robust to changes in the environment. The algorithm can be applied in real time because of the processing speed faster. Throughout the experiment, we confirmed that the algorithm reliably detected driver drowsiness. The processing speed of the proposed algorithm is about 0.084ms. Also, the proposed algorithm can achieve an average detection rate of 98.48% and 97.37% for a yawn, drowsy eyes, and nod in the daytime and nighttime.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.295-299
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• 2004

In this paper, we compare and analyze the LMS ard RLS algorithm of IEEE802.15.3(HDR-WPAN) system. The LMS algorithm have two merits that easily embody and not complex, but convergence speed is slow. The RLS algorithm have fast convergence speed, but very complex. When equalization using LMS algorithm, it can achieve adaptive equalization after 250 sample in fading environment, but case of RLS algorithm can achieve adaptive equalization after just 50 sampls. The computer simulation proved that adaptive equalizer to fast equalization and stability of HDR-WPAN system is more effective using RLS algorithm then LMS algorithm.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.83-88
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• 1989

This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively.

• Kyungpook Mathematical Journal
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• v.28 no.1
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• pp.45-50
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• 1988

Circulant and multiblock circulant matrices have many important applications, and therefore their inverses are of considerable interest. A simple recursive algorithm is presented to compute the inverse of a multiblock circulant matrix. The algorithm only uses complex variables, roots of unity and normal matrix/vector operations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.194-199
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• 2005

Body-on-frame type vehicle has a set of frame bushes which are installed between body and frame fur vibration Isolation. Such frame bushes are important vibration transmission paths to passenger space. In order to reduce the vibration level of passenger space, therefore, the change of complex stiffness of the frame bushes is more efficient than modification of other parts of the vehicle such as body, frame and suspension. The purpose of this study is to reduce the vibration level for ride comfort by optimization of complex stiffness of frame bushes. In order to do this end, simple finite element vehicle model was constructed and the complex stiffness of frame bushes was set to be design variable. Objective function was defined to reflect passenger ride comfort and genetic algorithm and sub-structure synthesis were applied for minimization of the objective function.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.6 s.111
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• pp.619-626
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• 2006

Body-on-frame type vehicle has a set of frame bushes between body and frame for vibration isolation. Such frame bushes are important vibration transmission paths to passenger space for excitations during driving. In order to reduce the vibration level of passenger space, therefore, change of complex stiffness of the frame bushes is more efficient than modification of other parts of the vehicle such as body, frame and suspension. The purpose of this study is to reduce the vibration level for ride comfort by optimization of complex stiffness of frame bushes. In order to do this, a simple finite element vehicle model was constructed and complex stiffness of the frame bushes was set to be design variables. The objective function was defined to reflect frequency dependence of passenger ride comfort. Genetic algorithm and sub-structure synthesis were applied for minimization of the objective function. After optimization level at a position of interest on the car body was reduced by about 43.7 % in RMS value. Causes for optimization results are discussed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.127-140
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• 2003

This paper develops a novel algorithm of computing 2 Dimensional Discrete Cosine Transform (2D-DCT) via Polynomial Transform (PT) converting 2D-DCT to the sum of 1D-DCTs. In computing N${\times}$M size 2D-DCT, the conventional row-column algorithm needs 3/2NMlog$_2$(NM)-2NM＋N＋M additions and 1/2NMlog$_2$(NM) additions and 1/2NMlog$_2$(NM) multiplications, while the proposed algorithm needs 3/2NMlog$_2$M＋NMlog$_2$N-M-N/2＋2 additions and 1/2NMlog$_2$M multiplications The previous polynomial transform needs complex operations because it applies the Euler equation to DCT. Since the suggested algorithm exploits the modular regularity embedded in DCT and directly decomposes 2D DCT into the sum of ID DCTs, the suggested algorithm does not require any complex operations.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.11-15
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• 2015

In this study, we present the architecture design of data control system in water hazard information platform with analyzing the complexity of the data processing. Generally, data control systems in data collection and analysis platforms base on the constant data-algorithm data processing meaning that data processing between data and algorithm is fixed. But the number of data processing in data control system is rapidly increasing because of increasing of complexity of system. To hold down the number of data processing, dynamic data-algorithm data processing is able to be applied to data control system. After comparison each data-algorithm data processing method, we suggest design method of the data control system optimizing water hazard information platform.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.255-263
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• 2022

3D object detection pipelines often incorporate RGB-based object detection methods such as YOLO, which detects the object classes and bounding boxes from the RGB image. However, in complex environments where objects are heavily cluttered, bounding box approaches may show degraded performance due to the overlapping bounding boxes. Mask based methods such as Mask R-CNN can handle such situation better thanks to their detailed object masks, but they require much longer time for data preparation compared to bounding box-based approaches. In this paper, we present a 3D object recognition pipeline which uses either the YOLO or Mask R-CNN real-time object detection algorithm, K-nearest clustering algorithm, mask reduction algorithm and finally Principal Component Analysis (PCA) alg orithm to efficiently detect 3D poses of objects in a complex environment. Furthermore, we also present an improved YOLO based 3D object detection algorithm that uses a prioritized heightmap clustering algorithm to handle overlapping bounding boxes. The suggested algorithms have successfully been used at the Artificial-Intelligence Robot Challenge (ARC) 2021 competition with excellent results.