• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.25.4-25.4
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• 2011

Various estimation methods based on Kalman filter have been applied to the real-time satellite orbit determination. The most popular method is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The EKF is easy to implement and to use on orbit determination problem. However, the linearization process of the EKF can cause unstable solutions if the problem has the inaccurate reference orbit, sparse or insufficient observations. In this case, the UKF can be a good alternative because it does not contain linearization process. However, because both methods are based on Gaussian assumption, performance of estimation can become worse when the distribution of state parameters and process/measurement noise are non-Gaussian. In nonlinear/non-Gaussian problems the particle filter which is based on sequential Monte Carlo methods can guarantee more exact estimation results. This study develops and tests the particle filter for satellite orbit determination. The particle filter can be more effective methods for satellite orbit determination in nonlinear/non-Gaussian environment.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.21-28
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• 2016

In this paper, we propose a fast small target detection method using multiple filters, and describe system implementation using IPP libraries. To detect small targets in Infra-Red images, it is mandatory that you should apply a filter to eliminate a background and identify the target information. Moreover, by using a suitable algorithm for the environments and characteristics of the target, the filter must remove the background information while maintaining the target information as possible. For this reason, in the proposed method we have detected small targets by applying multi area(spatial) filters in a low luminous environment. In order to apply the multi spatial filters, the computation time can be increased exponentially in case of the sequential operation. To build this algorithm in real-time systems, we have applied IPP library to secure a software optimization and reduce the computation time. As a result of applying real environments, we have confirmed a detection rate more than 90%, also the computation time of the proposed algorithm have been improved about 90% than a typical sequential computation time.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.76-79
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• 2014

Face recognition is very challenging because of the unexpected changes of pose, expression, and illumination. Facial detection in the mobile environments has additional difficulty since the computational resources are very limited. This paper discusses face detection based on frequency domain matched filtering in the mobile environments. Face detection is performed by a linear or phase-only matched filter and sequential verification stages. The candidate window regions are selected by a number of peaks of the matched filtering outputs. The sequential stages comprise a skin-color test and an edge mask filtering tests, which aim to remove false alarms among selected candidate windows. The algorithms are built with JAVA language on the mobile device operated by the Android platform. The simulation and experimental results show that real-time face detection can be performed successfully in the mobile environments.

• ETRI Journal
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• v.39 no.3
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• pp.301-309
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• 2017

In this paper, we propose a parallelization method for a High Efficiency Video Coding (HEVC) deblocking filter with transform unit (TU) split information. HEVC employs a deblocking filter to boost perceptual quality and coding efficiency. The deblocking filter was designed for data-level parallelism. In this paper, we demonstrate a method of distributing equal workloads to all cores or threads by anticipating the deblocking filter complexity based on the coding unit depth and TU split information. We determined that the average time saving of our proposed deblocking filter parallelization method has a speed-up factor that is 2% better than that of the uniformly distributed parallel deblocking filter, and 6% better than that of coding tree unit row distribution parallelism. In addition, we determined that the speed-up factor of our proposed deblocking filter parallelization method, in terms of percentage run-time, is up to 3.1 compared to the run-time of the HEVC test model 12.0 deblocking filter with a sequential implementation.

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.30-36
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• 2014

BACKGROUND: Best management practices are often implemented to control nonpoint source pollutants. Best management practices need to be simulated and analyzed for effective Best management practices implementations. Filter strip is one of effective Best management practices in agricultural areas. METHODS AND RESULTS: Soil and Water Assessment Tool model was selected to explore the effectiveness of filter strip to control total phosphorous in Golji watershed. Soil and Water Assessment Tool model was calibrated for flow and total phosphorous by Sequential Uncertainty Fittin ver.2 algorithm provided in Soil and Water Assessment Tool-Calibration and Uncertainty Procedures. Three scenarios defined by filter strip width were applied. The filter strip width of 5 m was able to reduce the most amount of total phosphorous. In other words, the total phosphorous reduction by filter strip of 5 m was 28.0%, while the reduction was 17.5% by filter strip of 1 m. However, the reduction per unit filter strip width were 17.4%, 8.0%, and 4.5% for 1 m, 3 m, and 5 m of filter strips, respectively. CONCLUSION: Best management practices need to be simulated and analyzed so that the BMP scenario can be cost-effective. A large size of BMP might be able to control large amount of pollutants, however it would not be indicated as a cost-effective strategy.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.1
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• pp.16-24
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• 2005

Mathematical model was developed to verify a sequential particle removal taking place in a granular media gravity filter. Consequential multi-layer filtration cycle model was applied to verify the fraction of filter effluent particles that are filter influent particles that were never removed as well as the fraction of filter effluent particles that were detached after deposition were performed through laboratory experiments. Three sizes of marker particles were injected ahead of the filter column as a pulse in the presence of four sizes of polystyrene particles that were used as a primary source of particles in the raw suspension to investigate particle attachment alone in contrast to net removal from attachment and detachment. Microscopic counting of filter effluent particles was assumed to reflect attachment. Experimental results indicated that particle detachment is significant beginning from the early phase of filtration. For each size of fluorescent microspheres at one filter depth, fluorescent microsphere removal increased with filter runtime to a maximum due to ripening. The detached fraction of effluent particles increased with particle size and filter depth. The presence of detached particles and the increasing fraction of detached particles in deeper bed were confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2928-2947
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• 2015

Adaptive Gaussian filter (AGF) is a recently developed switching filter to remove salt and pepper noise. AGF first directly identifies pixels of gray levels 0 and 255 as noise pixels, and then only restored noise pixels using a Gaussian filter with adaptive variance based on the estimated noise density. AGF usually achieves better denoising effect in comparison with other filters. However, AGF still fails to obtain good denoising effect on images with noise-free pixels of gray levels 0 and 255, due to its severe false alarm in its noise detection stage. To alleviate this issue, a modified version of AGF is proposed in this paper. Specifically, the proposed filter first performs noise detection via an image block based noise density estimation and sequential noise density guided rectification on the noise detection result of AGF. Then, a modified Gaussian filter with adaptive variance and window size is used to restore the detected noise pixels. The proposed filter has been extensively evaluated on two representative grayscale images and the Berkeley image dataset BSDS300 with 300 images. Experimental results showed that the proposed filter achieved better denoising effect over the state-of-the-art filters, especially on images with noise-free pixels of gray levels 0 and 255.

• Journal of electromagnetic engineering and science
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• v.12 no.2
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• pp.148-154
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• 2012

In this paper, we propose an algorithm to conserve resources of the common control channel in a cognitive radio network by rejecting the redundant users using cooperative spectrum sensing. The proposed scheme is investigated under the paradigm of active spectrum sensing and a sequential detection technique. The algorithm is based on the J-divergence between the hypotheses of non primary user operation and the otherwise case. We select the most significant eigenvalues, which primarily affect the global statistical test. For the case where interference is from a secondary system transmission, a match filter is first employed to remove the degradation, and then the proposed algorithm is employed to remove the cooperative sensing nodes. Numerical results are provided and compared with conventional cases in order to validate the performance of the proposed algorithm.

• Mycobiology
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• v.37 no.4
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• pp.267-271
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• 2009

A fungal strain producing a high level of cellulase was selected from 320 fungal isolates and identified as Aspergillus sp. This strain was further improved for cellulase production by sequential treatments by two repeated rounds of $\gamma$-irradiation of $Co^{60}$, ultraviolet treatment and four repeated rounds of treatment with N-methyl-N'-nitro-N-nitrosoguanidine. The best mutant strain, Aspergillus sp. XTG-4, was selected after screening and the activities of carboxymethyl cellulase, filter paper cellulase and $\beta$-glucosidase of the cellulase were improved by 2.03-, 3.20-, and 1.80-fold, respectively, when compared to the wild type strain. After being subcultured 19 times, the enzyme production of the mutant Aspergillus sp. XTG-4s was stable.