• International Journal of Precision Engineering and Manufacturing
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• v.5 no.2
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• pp.60-67
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• 2004

For improving the motion accuracy of hydrostatic tables, a corrective machining algorithm is proposed in this paper. The algorithm consists of three main processes. The reverse analysis is performed firstly to estimate the rail profile from the measured linear and angular motion error, in the algorithm. For the next step, the corrective machining information is obtained based upon the estimated rail pronto. Finally, the motion errors on the correctively machined rail are analyzed by using the motion error analysis method. These processes are iterated until the analyzed motion errors are satisfactory within the target accuracy. In order to verify the validity of the algorithm theoretically, the motion errors calculated by the estimated rail after the corrective machining process, are compared with those by the true rail which is previously assumed as the initially measured value. The motion errors calculated using the estimated rail show good agreement with the assumed values, and it is shown that the algorithm is effective in acquiring the corrective machining information to improve the accuracy of hydrostatic tables.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.169-185
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• 2017

This study proposes a novel recommendation algorithm that reflects the results from trust/distrust network analysis as a solution to enhance prediction accuracy of recommender systems. The recommendation algorithm of our study is based on memory-based collaborative filtering (CF), which is the most popular recommendation algorithm. But, unlike conventional CF, our proposed algorithm considers not only the correlation of the rating patterns between users, but also the results from trust/distrust relationship network analysis (e.g. who are the most trusted/distrusted users?, whom are the target user trust or distrust?) when calculating the similarity between users. To validate the performance of the proposed algorithm, we applied it to a real-world dataset that contained the trust/distrust relationships among users as well as their numeric ratings on movies. As a result, we found that the proposed algorithm outperformed the conventional CF with statistical significance. Also, we found that distrust relationship was more important than trust relationship in measuring similarities between users. This implies that we need to be more careful about negative relationship rather than positive one when tracking and managing social relationships among users.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.501-508
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• 2004

In this paper, a coordinated scheduling algorithm is proposed to reduce end-to-end delay in distributed control of systems. For the algorithm, the analysis of practical end-to-end delay in the worst case is performed priory with considering implementation of the systems. The end-to-end delay is composed of the delay caused by multi-task scheduling of operating systems, the delay caused by network communications, and the delay caused by asynchronous timing between operating systems and network communications. Through some simulation tests based on CAN(Controller Area Network), the proposed worst case end-to-end delay analysis is validated. Through the simulation tests, it is also shown that a real-time distributed control system designed to existing worst case delay cannot guarantee end-to-end time constraints. With the analysis, a coordinated scheduling algorithm is proposed here. The coordinated scheduling algorithm is focused on the reduction of the delay caused by asynchronous timing between operating systems and network communications. Online deadline assignment strategy is proposed for the scheduling. The performance enhancement of the distributed control systems by the scheduling algorithm is shown through simulation tests.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.180-188
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• 2016

In this paper, we propose a fire detection algorithm based on motion information and color information analysis. Conventional fire detection algorithms have as main problem the difficulty to detect fire due to external light, intensity, background image complexity, and little fire diffusion. So we propose a fire detection algorithm that accurate and fast. First, it analyzes the motion information in video data and then set the first candidate. Second, it determines this domain after analyzing the color and the domain. This algorithm assures a fast fire detection and a high accuracy compared with conventional fire detection algorithms. Our algorithm will be useful to real-time fire detection in real world.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.2
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• pp.164-176
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• 1996

The main intention of this paper is to develop and compare the algorithm based on finite element procedures for nonlinear transient dynamic analysis which has combined effects of material and geometric nonlinearities. Incremental equilibrium equations based on the principle of virtual work are derived by the finite element approach. For the elasto - plastic large deformation analysis of shells and the determination of the displacement-time configuration under time-varying loads, the explicit, implicit and combined explicit-implicit time integration algorithm is adopted. In the time structure is selected and the results are compared with each others. Isoparametric 8-noded quadrilateral curved elements are used for shell structure in the analysis and for geometrically nonlinear elastic behaviour, a total Lagrangian coordinate system was adopted. On the other hands, material nonlinearity is based on elasto-plastic models with Von-Mises yield criteria. Thus, the combined explicit-implicit time integration algorithm is benefit in general case of shell structure, which is the result of this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.307-314
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• 2000

A parallel condensation algorithm for efficient dynamic analysis of three-dimensional large-scale structures is presented. The algorithm is developed for a user-friendly and cost effective high-performance computing system on a collection of Pentium processors connected via a 100 Mb/s Ethernet LAN. To harness the parallelism in the computing system effectively, a large-scale structure is partitioned into a number of substructures equal to the number of computers in the computing system Then, for reduction in the size of an eigenvalue problem the computations required for static condensation of each substructure is processed concurrently on each slave computer. The performance of th proposed parallel algorithm is demonstrated by applying to dynamic analysis of a three dimensional structure. The results show that how the parallel algorithm facilitates the efficient use of a small number of low-cost personal computers for dynamic analysis of large-scale structures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.654-661
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• 2011

This paper is about a personal identification algorithm using an ECG that has been studied by a few researchers recently. Previously published algorithm can be classified as two methods. One is the method that analyzes of ECG features and the other is the morphological analysis of ECG. The main characteristic of proposed algorithm can be classified the method of analysis ECG features. Proposed algorithm adopts DSTW(Down Slope Trace Wave) for extracting ECG features, and applies SVM(Support Vector Machine) to training and testing as a classifier algorithm. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating of algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 93.89% heartbeat recognition rate and 100% ECG recognition rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1361-1369
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• 1996

Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.995-1000
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• 2017

In this paper, we present an electrical arc detection algorithm using the mash-up analysis technique which is the core technology for the autonomous electrical safety management system(AESMS) of the multi-unit dwellings. The mash-up analysis technique analyzes the voltage, load current, zero phase current data simultaneously to judge arc faults. In order to develop the arc fault detection algorithm, the characteristics of series arc and parallel arc were analyzed. Also, we propose the mash-up analysis technique that analyzes waveforms of voltage, load current, and zero phase current at the same time. The arc fault detection algorithm was developed using the mash-up analysis technique. The developed algorithm can prevent electrical disasters in an effective way through accident prediction, and it will be used as a basic technology to introduce an autonomous electrical safety management system.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.1-11
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• 2009

This paper proposes an algorithm capable of detecting vehicles in front or in rear using a monocular camera installed in a vehicle. The vehicle detection has been regarded as an important part of intelligent vehicle technologies. The proposed algorithm is mainly composed of two parts: 1)hypothesis generation of vehicles, and 2)hypothesis verification. The hypotheses of vehicles are generated by the analysis of vertical and horizontal edges and the detection of symmetry axis. The hypothesis verification, which determines vehicles among hypotheses, is done by the AdaBoost algorithm. The proposed algorithm is proven to be effective through experiments performed on various images captured on the roads.