• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.111-125
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• 2015

In this study, the target detection using both high-resolution satellite SAR and Elecro-Optical (EO) images such as TerraSAR-X and WorldView-2 is performed, considering the characteristics of targets. The targets of our interest are featured by being stationary and appearing as cluster targets. After the target detection of SAR image by using Constant False Alarm Rate (CFAR) algorithm, a series of processes is performed in order to reduce false alarms, including pixel clustering, network clustering and coherence analysis. We extend further our algorithm by adopting the fast and effective ellipse detection in EO image using randomized hough transform, which is significantly reducing the number of false alarms. The performance of proposed algorithm has been tested and analyzed on TerraSAR-X SAR and WordView-2 EO images. As a result, the average false alarm for group of targets is 1.8 groups/$64km^2$ and the false alarms of single target range from 0.03 to 0.3 targets/$km^2$. The results show that groups of targets are successfully identified with very low false alarms.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.244-247
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• 2022

In this paper, the performance of the decoding schemes using linear MMSE filters in the frequency and time domains and the reinforcement Gauss-Seidel algorithm for the orthogonal time frequency space (OTFS) system that can improve robustness under high-speed mobile environments are compared. The reinforcement Gauss-Seidel algorithm can improve the bit error rate performance by suppressing the noise enhancement. The simulation results show that the performance of the decoding scheme using the linear MMSE filter in the frequency domain is severely degraded due to the effect of Doppler shift as the mobile speed increases. In addition, the decoding scheme using the reinforcement Gauss-Seidel algorithm under the channel environment with 120 km/h and 500 km/h speeds outperforms the decoding schemes using linear MMSE filters in the frequency and time domains.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.11-25
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• 2012

We present the method to infer Context-Free Grammars by applying genetic algorithm to the Binary Third-order Recurrent Neural Networks(BTRNN). BTRNN is a multiple-layered architecture of recurrent neural networks, each of which is corresponding to an input symbol, and is combined with external stack. All parameters of BTRNN are represented as binary numbers and each state transition is performed with any stack operation simultaneously. We apply Genetic Algorithm to BTRNN chromosomes and obtain the optimal BTRNN inferring context-free grammar of positive and negative input patterns. This proposed method infers BTRNN, which includes the number of its states equal to or less than those of existing methods of Discrete Recurrent Neural Networks, with less examples and less learning trials. Also BTRNN is superior to the recent method of chromosomes representing grammars at recognition time complexity because of performing deterministic state transitions and stack operations at parsing process. If the number of non-terminals is p, the number of terminals q, the length of an input string k, and the max number of BTRNN states m, the parallel processing time is O(k) and the sequential processing time is O(km).

• Journal of Navigation and Port Research
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• v.36 no.5
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• pp.371-378
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• 2012

This paper presents a timing recovery method using Gardner TED (Timing Error Detector) with a Peak Detector using Parabola Peak Interpolation in underwater acoustic communication. This method will have an eye to improve phase converge speed of timing recovery and reduced amount of Tx data. The OQPSK(Offset Quadrature Phase Shift Keying) modulation technique was considered. The proposed algorithm has faster recovery speed and more accurate than Gardner TED because the sampling values in the proposed algorithm are moved persistingly to maximum or minimum point using parabolic peak interpolation. when simulation performed using Preposed method, it improved BER (Bit Error Rate) performance about 23% And to evaluate the performances of the proposed algorithm the sea trial was performed in the Korean East Sea. And distance of a transmitter-receiver is 3 km each other. As a result, the proposed algorithm outperforms better BER performance about 20% of timing recovery than the Gardner method. Also Proposed method improved converge speed of timing recovery about 1.4 times better than Gardner method.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.37-45
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• 2000

Since being launched for ocean observing in 1997, the SeaWiFS sensor has supplied data on ocean chlorophyll distribution and environmental conditions of the atmosphere. Until now, a lot of SeaWiFS data have been archived and utilized for ocean monitoring and land observation. The SeaWiFS sensor has 1km spatial resolution, therefore, it is difficult to obtain data at the coastal zone. Since atmospheric correction algorithms at the coastal area have not been confirmed for chlorophyll algorithm, the ocean color data analysis for coastal zone is not common. In particular, domestic coastal areas have high suspended sediments concentrations and higher absorption influence of colored dissolved organic matter (CDOM), released from in-land, than open-sea. Thus, a useful algorithm for analysis of chlorophyll distribution in domestic coastal areas has not been developed. In this study, empirical algorithms, using data from the ocean color sensor, were developed for monitoring of chlorophyll distribution of coastal areas. In the process of the development of the algorithms, we can find that the red band (665nm) should be used for analyzing of domestic coastal areas near the Yellow Sea.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.547-557
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• 2012

This study purposed to estimate the forest biomass using k-Nearest Neighbor (k-NN) algorithm. Multiple data sources were used for the analysis such as forest type map, field survey data and Landsat TM data. The accuracy of forest biomass was evaluated with the forest stratification, horizontal reference area (HRA) and spatial filtering. Forests were divided into 3 types such as conifers, broadleaved, and Korean pine (Pinus koriansis) forests. The applied radii of HRA were 4 km, 5 km and 10 km, respectively. The estimated biomass and mean bias for conifers forest was 222 t/ha and 1.8 t/ha when the value of k=8, the radius of HRA was 4 km, and $5{\times}5$ modal was filtered. The estimated forest biomass of Korean pine was 245 t/ha when the value of k=8, the radius of HRA was 4km. The estimated mean biomass and mean bias for broadleaved forests were 251 t/ha and -1.6 t/ha, respectively, when the value of k=6, the radius of HRA was 10 km. The estimated total forest biomass by k-NN method was 799,000t and 237 t/ha. The estimated mean biomass by ${\kappa}NN$method was about 1t/ha more than that of filed survey data.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1207-1211
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• 2017

Long-Reach PON (LR-PON) is a broadband access network using passive optical network (PON) technology which the reach is extended to 100 km or higher. A major challenge in LR-PON is that the propagation delay between OLT and ONUs is increased by a very significant amount. To effectively and fairly distribute the upstream bandwidth dynamically in LR-PON, we propose a new periodic and multi-thread polling based dynamic bandwidth allocation (DBA) algorithm. We compare the proposed algorithm with traditional DBAs and show its advantage on average packet delay. Numerical results are analyzed under varying offered loads.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.2
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• pp.196-208
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• 2002

Since radio interference has occurred in the TRS frequency band in the south coastal area, Korea from 1994, similar interference has been observed in the mobile-cellular frequency band. Measurement showed that the sources of the radio interference are those from the base stations for digital cellular systems in Japan. This because the receiving frequency of the base stations in Korea is same as the transmitting frequency of the base stations in Japan. Since the distance between Korea and Japan is 240 ~ 300 km, we can conclude that the main reason of the interference is ducting. In this paper a ducting channel is modeled by split-step DMFT algorithm, and simulation results for measured index profile far east coast and west sea area are analyzed.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.29-33
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• 2015

The multidisciplinary design optimization (MDO) of a launch vehicle (LV) with a hybrid rocket engine (HRE) was carried out to investigate the ability of an HRE for a single-stage LV. The non-dominated sorting genetic algorithm-II (NSGA-II) was employed to solve two design problems. The design problems were formulated as two-objective cases involving maximization of the downrange distance over the target flight altitude and minimization of the gross weight, for two target altitudes: 50.0 km and 100.0 km. Each objective function was empirically estimated. Several non-dominated solutions were obtained using the NSGA-II for each design problem, and in each case, a trade-off was observed between the two objective functions. The results for the two design problem indicate that economical performance of the LV is limited with the HRE in terms of the maximum downrange distances achievable. The LV geometries determined from the non-dominated solutions were examined.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1469-1478
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• 2015

In this paper, The methodology of Type-2 fuzzy set-based Radial Basis Function Neural Network(T2RBFNN) is proposed for Sewage Treatment Process and the simulator is developed for application to the real-world sewage treatment plant by using the proposed model. The proposed model has robust characteristic than conventional RBFNN. architecture of network consist of three layers such as input layer, hidden layer and output layer of RBFNN, and Type-2 fuzzy set is applied to receptive field in contrast with conventional radial basis function. In addition, the connection weights of the proposed model are defined as linear polynomial function, and then are learned through Back-Propagation(BP). Type reduction is carried out by using Karnik and Mendel(KM) algorithm between hidden layer and output layer. Sewage treatment data obtained from real-world sewage treatment plant is employed to evaluate performance of the proposed model, and their results are analyzed as well as compared with those of conventional RBFNN.