• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1317-1326
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• 2023

Today's computers, desktops and laptops were build with multi-core architecture. Developing and running serial programs in this multi-core architecture fritters away the resources and time. Parallel programming is the only solution for proper utilization of resources available in the modern computers. The major challenge in the multi-core environment is the designing of parallel algorithm and performance analysis. This paper describes the design and performance analysis of parallel algorithm by taking the Knight Tour problem as an example using OpenMP interface. Comparison has been made with performance of serial and parallel algorithm. The comparison shows that the proposed parallel algorithm achieves good performance compared to serial algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.70-80
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• 2008

This paper presents comparison of 18000-3 ASK and PJM mode RFID in terms of reading speed. This is accomplished by counting the occurrences of a few representative blocks which constitute the reader / tag interactions for each mode. To apply FS (frame slotted)-aloha protocol, four Q-algorithms, which are a Q-algorithm suggested in the standard document, a fixed Q-algorithm, a minimum Q-algorithm and the number of tag dependent Q-algorithm, are used. Through some simulations, we present the reading speed of each mode with respect to the Q-algorithm and the comparison of the reading speed between the two modes for each Q-algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.65-72
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• 2009

Laser interferometry is widely used as a measuring system in many fields because of its high resolution and its ability to measure a broad area in real-time all at once. In conventional laser interferometry, for example out-of-plane ESPI (Electronic Speckle Pattern Interferometry), in plane ESPI, shearography and holography, it uses PZT or other components as a phase shift instrumentation to extract 3-D deformation data, vibration mode and others. However, in most cases PZT has some disadvantages, which include nonlinear errors and limited time of use. In the present study, a new type of laser interferometry using a laser diode is proposed. Using Laser Diode Sinusoidal Phase Modulating (LD-SPM) interferometry, the phase modulation can be directly modulated by controlling the laser diode injection current thereby eliminating the need for PZT and its components. This makes the interferometry more compact. This paper reports on a new approach to the LD (Laser Diode) Modulating interferometry that involves four-frame phase shift method. This study proposes a four-frame phase mapping algorithm, which was developed to have a guaranteed application, to stabilize the system in the field and to be a user-friendly GUI. In this paper, the theory for LD wavelength modulation and sinusoidal phase modulation of LD modulating interferometry is shown. Using modulating laser and research of measurement algorithm does comparison with existent ESPI measurement algorithm. Algorithm measures using GPIB communication through most LabVIEW 8.2. GPIB communication does alteration through PC. Transformation of measurement object measures through modulating laser algorithm that develops. Comparison of algorithm of modulating laser developed newly with existent PZT algorithm compares transformation price through 3-D. Comparison of 4-frame phase mapping, unwrapping, 3-D is then introduced.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.127-144
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• 2006

The K-means algorithm is widely used at the initial stage of data analysis in data mining process, partly because of its low time complexity and the simplicity of practical implementation. Cluster validity indices are used along with the algorithm in order to determine the number of clusters as well as the clustering results of datasets. In this paper, we present a performance comparison of sixteen indices, which are selected from forty indices in literature, while considering their applicability to nonhierarchical clustering algorithms. Data sets used in the experiment are generated based on multivariate normal distribution. In particular, four error types including standardization, outlier generation, error perturbation, and noise dimension addition are considered in the comparison. Through the experiment the effects of varying number of points, attributes, and clusters on the performance are analyzed. The result of the simulation experiment shows that Calinski and Harabasz index performs the best through the all datasets and that Davis and Bouldin index becomes a strong competitor as the number of points increases in dataset.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1741-1751
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• 2007

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2699-2701
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• 2004

This paper describes a new algorithm for human sensibility evaluation using two personality-group templates of electroencephalogram (EEG) signals. EEG signals of two groups arc collected in relaxed state, comfortable state and uncomfortable state. First of all, the characteristics of EEGs in relaxed state for two groups are compared. After verification of the results, an algorithm for sensibility evaluation is developed. In comparison of the characteristics for two personality-group EEG signals. there are distinct difference between the EEG patterns of the extrovert and the introvert. Upon these findings, the algorithm for human sensibility evaluation is designed. The results of the algorithm showed 90.0% of coincidence with given tasks. This seems to be compromising results for subject independent sensibility evaluation using EEG signal.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.1
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• pp.1-9
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• 2006

Three categories such as the design of a machine, control and software are necessary in the development of the photomask inspection machine with high resolution. Among them, the design of a software detects inferiority through the comparison of CAD data and real data read by camera from photomask. The block matching algorithm is used since the domain is large and the comparison of data by pixel is accomplished. To correct the error arising from the assembly of a machine, calibration algorithm is used and prefocusing algorithm is suggested to correct the surface of the photomask.

• Journal of ILASS-Korea
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• v.28 no.4
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• pp.161-168
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• 2023

Droplet impingement on solid surfaces is pivotal for a range of spray and heat transfer processes. This study aims to optimize the cooling performance of single droplet impingement on heated textured surfaces. We focused on maximizing the cooling effectiveness or the total contact area at the droplet maximum spread. For efficient estimation of the optimal values of the unknown variables, we introduced an enhanced Genetic Algorithm (GA) and Particle swarm optimization algorithm (PSO). These novel algorithms incorporate its developed theoretical backgrounds to compare proper optimized results. The comparison, considering the peak values of objective functions, computation durations, and the count of penalty particles, confirmed that PSO method offers swifter and more efficient searches, compared to GA algorithm, contributing finding the effective way for the spray and droplet impingement process.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.25-30
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• 2003

Recently, development of digital technology is occupying a large part of multimedia information like character, voice, image, video, etc. Research about video indexing and retrieval progresses especially in research relative to video. In this paper, we propose new algorithm(Frame Feature Comparison) for MPEG video segmentation. Shot, Scene Change detection is basic and important works that segment it in MPEG video sequence. Generally, the segmentation algorithm that uses much has defect that occurs an error detection according to a flash of camera, movement of camera and fast movement of an object, because of comparing former frames with present frames. Therefore, we distinguish a scene change one more time using a scene change point detected in the conventional algorithm through comparing its mean value with abutted frames. In the result, we could detect more corrective scene change than the conventional algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.