• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.59-68
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• 2011

The analysis of optimal infiltration path is one of the representative fields in which the GIS technology can be useful for the military purpose. Usually the analysis of the optimal path is done with network data. However, for military purpose, it often needs to be done with raster data. Because raster data needs far more computation than network data, it is difficult to apply the methods usually used in network data, such as Dijkstra algorithm. The genetic algorithm, which has shown great outcomes in optimization problems, was applied. It was used to minimize the detection probability of infiltration route. 2D binary array genes and its crossover and mutation were suggested to solve this problem with raster data. 30 tests were performed for each population size, 500, 1000, 2000, and 3000. With each generation, more adoptable routes survived and made their children routes. Results indicate that as the generations increased, average detection probability decreased and the routes converged to the optimal path. Also, as the population size increases, more optimal routes were found. The suggested genetic algorithm successfully finds the optimal infiltration route, and it shows better performance with larger population.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.2
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• pp.191-197
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• 2015

The message passing interface (MPI) and hybrid programming models for the parallel computation of a pressure equation were compared in a distributed memory system. Both models were based on domain decomposition, and two numbers of the sub-domain were selected by considering the efficiency of the hybrid model. The parallel performances for various problem sizes were measured using up to 96 threads. It was found that in addition to the cache-memory size, the overhead of the MPI communication/OpenMP directives affected the parallel performance. For small problems, the parallel performance was low because the percentage of the overhead of the MPI communication/OpenMP directives increased as the number of threads increased, and MPI was better than the hybrid model because it had a smaller communication overhead. For large problems, the parallel performance was high because, in addition to the cache effect, the percentage of the communication overhead was relatively low compared to that for small problems, and the hybrid model was better than MPI because the communication overhead of MPI was more dominant than that of the OpenMP directives in the hybrid model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.4
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• pp.192-198
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• 2004

A numerical method is developed to solve a two-dimensional diffraction problem for a body located in a sediment pocket where a heavier muddy water is trapped. In the present study, the wave exciting forces acting on a submerged body in the water-sediment interface by an incident wave is investigate. It is assumed that the heavier mud is trapped locally in a sediment pocket. A mathematical formulation is made in the scope of the potential theory. The fluid is assumed to be inviscid, incompressible and its motion irrotational. The boundary conditions on the unknown free surface and interface are linearized. As a method of solution, the localized finite-element method is adopted. In the method, the computation domain is reduced by utilizing the complete set of analytic solutions known in the infinite subdomain to be truncated by introduction of an appropriate juncture conditions. The main advantage of this method is that any complex geometry of the boundaries can be easily accommodated. Computations are carried out for mono-chromatic plane progressive surface waves normally incident on the domain. Numerical results are compared with those obtained by Lassiter based on Schwingers variational method. Good Agreements are obtained in general. Another numerical computations are made for the cases with and without a body in the sediment pocket.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.99-104
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• 2012

The United States will proceed with the effort to modernize the GPS system, and one of its main content is to provide L5 signal. L5 will be transmitted in a radio band reserved exclusively for aviation safety services. And, L5, in combination with L1, will improve the position accuracy via ionospheric correction and robustness via signal redundancy. However, The acquisition processing time of L5 takes longer than that of L1 as the code length of L5 is 10 times longer than that of L1. To reduce this acquisition processing time, a higher number of correlators in the aquisition module should be used. However, there is a problem that this causes increase in the complexity of the correlator configuration and the computation power. So, in this paper, we propose L5 signal tracking scheme using tracking results in the GPS L1/L5 receiver. The proposed scheme could reduce the hardware complexity as the GPS L5 signal acquisition module is not needed, and provide fast and stable tracking of L5 signal by aiding L1 tracking results such as PRN, the code phase synchronization, and the Doppler frequency. The feasibility of the proposed scheme is demonstrated through simulation results.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.365-377
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• 2006

Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein interaction is intrinsic to most cellular processes, prediction of protein interaction is an important issue in post-genomic biology where abundant interaction data have been produced by many research groups. In this paper, we present an associative feature mining method to predict implicit protein-protein interactions of Saccharomyces cerevisiae from public protein interaction data. We discretized continuous-valued features by maximal interdependence-based discretization approach. We also employed feature dimension reduction filter (FDRF) method which is based on the information theory to select optimal informative features, to boost prediction accuracy and overall mining speed, and to overcome the dimensionality problem of conventional data mining approaches. We used association rule discovery algorithm for associative feature and rule mining to predict protein interaction. Using the discovered associative feature we predicted implicit protein interactions which have not been observed in training data. According to the experimental results, the proposed method accomplished about 96.5% prediction accuracy with reduced computation time which is about 29.4% faster than conventional method with no feature filter in association rule mining.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.99-110
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• 2017

Improving tracking performance by estimating the status of multiple targets using radar is important. In a clutter environment, a joint event occurs between the track and measurement in multiple target tracking using a tracking filter. As the number increases, the joint event increases exponentially. The problem to be considered when multiple target tracking filter design in such environments is that first, the tracking filter minimizes the rate of false track alarmsby eliminating the false track and quickly confirming the target track. The purpose is to increase the FTD performance. The second consideration is to improve the track maintenance performance by allocating each measurement to a track efficiently when an event occurs. Through two considerations, a single target tracking data association technique is extended to a multiple target tracking filter, and representative algorithms are JIPDAF and LM-IPDAF. In this study, a probabilistic evaluation of many hypotheses in the assignment of measurements was not performed, so that the computation amount does not increase nonlinearly according to the number of measurements and tracks, and the track existence probability based on the track density The LM-IPDAF algorithm was introduced. This paper also proposes a method to reduce the computational complexity by improving the clutter density estimation method for calculating the track existence probability of LM-IPDAF. The performance was verified by a comparison with the existing algorithm through simulation. As a result, it was possible to reduce the simulation processing time by approximately 20% while achieving equivalent performance on the position RMSE and Confirmed True Track.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.61-71
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• 2003

Existent DDHV draws and is calculating K coefficient. D coefficient from sum of traffic volume two-directions time. There is difference of design order and actuality order, error of DDHV estimation value, problem of irregular change etc. of DDHV thereby. In this study, among traffic volume of each other independent two direction(going up, going down), decide design target order in the directional traffic volume, presented way(way) applying without separating K coefficient and D coefficient at the same time. The result were analysis about national highway permanent count point 360 points 30 orders by existing DDHV estimation value method(separation plan) analysis wave and following variation appear. - design order and actuality order are collision at 357 agencies(99.2%) - actuality order special quality : Measuring efficiency of average 80 orders, maximum 1,027 order, minimum 2 orders - error distribution of design order and actuality order : inside 10 hours is(30$\pm$10hour) 106 points(29.4%), 254 points(70.6%) more than 30 orders and $\pm$10 orders error occurrence be - DDHV estimation value : Average 8.4%, maximum 46.7% The other side, average 50 orders. error improvement effect of DDHV 8.4% was analysed that is at design hourly volume computation by inseparability method in case of AADT premises correct thing because inseparability plan agrees actuality order at whole agency with design order and measuring efficiency of DDHV estimation value is "0".t;0".uot;.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.23-35
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• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.1-15
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• 2000

To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.