• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.616-624
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• 2002

In satellite communication, which use the satellite, the protection of TT&C channel which controls the position, performance, and operation is required. In this thesis, we analyzed the weakness of authentication algorithm which is used for protection of TT&C generation and operation. Also, we proposed the authentication algorithm which complements key recovery attack structurely without increasing additional computational amount and verified its performance. The proposed authentication algorithm can satisfy Rivest's recommendation by increasing the computational complexity from $2^{55}$ operations to $2^{111}$ operations. In addition, it can be applied to the existing satellite system because the length of TT&C data and message authentication codes used for the input of authentication algorithm are unchanged.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.9-16
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• 2015

This paper proposes the parallel design of a shot change detection algorithm using frame segmentation and moving blocks. In the proposed approach, the high parallel processing components, such as frame histogram calculation, block histogram calculation, Otsu threshold setting function, frame moving operation, and block histogram comparison, are designed in parallel for NVIDIA GPU. In order to minimize memory access delay time and guarantee fast computation, the output of a GPU kernel becomes the input data of another kernel in a pipeline way using the shared memory of GPU. In addition, the optimal sizes of CUDA processing blocks and threads are estimated through the prior experiments. In the experimental test of the proposed shot change detection algorithm, the detection rate of the GPU based parallel algorithm is the same as that of the CPU based algorithm, but the average of processing time speeds up about 6~8 times.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.99-104
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• 2014

Nowadays, various researches fulfill in many communication engineering area for B4G (Beyond Forth Generation). Next LTE-A (Long Term Evolution Advanced), MU-MIMO (Multi-User Multi Input Multi Output) method raises to upgrade throughput performance. However, the method of user selection is not decided because of many types and discussions in MU-MIMO system. Many existing methods are powerful for enhancing performance but have various restrictions in practical implementation. Fairness problem is primary restriction in this area. Existing papers emphasis algorithm to increase sum-rate but we introduce an algorithm about dealing with fairness problem for real commercialization implementation. Therefore, this paper introduces new user selection method in MU-MIMO system. This method overcomes a fairness problem in SUS (Semiorthogonal User Selection) algorithm. We can use the method to get a similar sum-rate with SUS and a high fairness performance. And this paper uses a hybrid method with SC-SUS (Superposition Coding SUS) algorithm and SUS algorithm. We find a threshold value of optimal performance by experimental method. We show this performance by computer simulation with MATLAB and analysis that results. And we compare the results with another paper's that different way to solve fairness problem.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.8
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• pp.84-91
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• 2002

In this paper, we proposed a CLB-based CPLD technology mapping algorithm for power minimization under time constraint in combinational circuit. The main idea of our algorithm is to exploit the "cut enumeration and feasible cluster" technique to generate possible mapping solutions for the sub-circuit rooted at each node. In our technology mapping algorithm conducted a low power by calculating TD and EP of each node and decomposing them on the circuit composed of DAG. It also takes the number of input, output, and OR-term into account on condition that mapping can be done up to the base of CLB, and so it generates the feasible clusters to meet the condition of time constraint. Of the feasible clusters, we should first be mapping the one that h3s the least output for technology mapping of power minimization and choose to map the other to meet the condition of time constraint afterwards. To demonstrate the efficiency of our approach, we applied our algorithm to MCNC benchmarks and compared the results with those of the exiting algorithms. The experimental results show that our approach is shown a decrease of 46.79% compared with DDMAP and that of 24.38% for TEMPLA in the power consumption.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.54-62
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• 1999

Vectorizing for input processing of map is the most time and cost consuming task, and the quality of vector data depends on that processing result. Therefore, it is an important task to develop a good vectorizing system in the GIS. Thinning algorithm is the most important technology for deciding the quality of vector data in the vectorizing system. In this paper, as a suitable algorithm for map vectorizing we considered several algorithms that preserve topological and geometric characteristics, and have no distortion of the contour line. As a results, we implemented WPTA4 and well known thinning algorithm, and compared WPTA4 execution results with the others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.31-40
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• 2005

we propose an enhanced self-generation supervised algorithm that by combining an ART algorithm and the delta-bar-delta method. Form the input layer to the hidden layer, ART-1 and ART-2 are used to produce nodes, respectively. A winner-take-all method is adopted to the connection weight adaption so that a stored pattern for some pattern is updated. we test the recognition of student identification, a certificate of residence, and an identifier from container that require nodes of hidden layers in neural network. In simulation results, the proposed self-generation supervised learning algorithm reduces the possibility of local minima and improves learning speed and paralysis than conventional neural networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.403-412
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• 2008

This paper presents the methods which obtain the solution of Wiener-Hopf equation by LMS algorithm and get the coefficient of TDL filter in lattice filter directly. For this result, we apply an orthogonal input signal generated by lattice filter into an equivalent Wiener-Hopf equation and shows the scheme that can obtain the solution by using the MMSE algorithm. Conventionally, the method like aforementioned scheme can get an error and regression coefficient recursively. However, in this paper, we can obtain an error and the coefficients of TDL filter recursively. And, we make an theoretical analysis on the convergence characteristics of the proposed algorithm. Then we can see that the result is similar to conventional analysis. Also, by computer simulation, we can make sure that the proposed algorithm has an excellent performance.

• Journal of IKEEE
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• v.24 no.4
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• pp.1148-1155
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• 2020

Fire must be extinguished as quickly as possible because they cause a lot of economic loss and take away precious human lives. Especially, the detection of smoke, which tends to be found first in fire, is of great importance. Smoke detection based on image has many difficulties in algorithm research due to the irregular shape of smoke. In this study, we introduce a new real-time smoke detection algorithm that reduces the detection of false positives generated by irregular smoke shape based on faster r-cnn of factory-installed surveillance cameras. First, we compute the global frame similarity and mean squared error (MSE) to detect the movement of smoke from the input surveillance camera. Second, we use deep learning algorithm (Faster r-cnn) to extract deferred candidate regions. Third, the extracted candidate areas for acting are finally determined using space and temporal features as smoke area. In this study, we proposed a new algorithm using the space and temporal features of global and local frames, which are well-proposed object information, to reduce false positives based on deep learning techniques. The experimental results confirmed that the proposed algorithm has excellent performance by reducing false positives of about 99.0% while maintaining smoke detection performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1424-1430
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• 2020

In this paper, we propose an algorithm to remove AWGN by considering the characteristics of noise present in the image. The proposed algorithm uses block matching to calculate the output, and calculates an estimate by determining the similarity between the center mask and the matching mask. The output of the filter is calculated by adding or subtracting the estimated value and the input pixel value, and weighting is given according to the standard deviation of the center mask and the noise constant to obtain the final output. In order to evaluate the proposed algorithm, the simulation was performed in comparison with the existing methods, and analyzed through the enlarged image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves important characteristics of the image, and shows the performance of removing noise efficiently.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.49-57
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• 2010

This paper proposes a Korean document. categorization algorithm using Back Propagation Neural Network(BPNN) with Singular Value Decomposition(SVD). BPNN makes a network through its learning process and classifies documents using the network. The main difficulty in the application of BPNN to document categorization is high dimensionality of the feature space of the input documents. SVD projects the original high dimensional vector into low dimensional vector, makes the important associative relationship between terms and constructs the semantic vector space. The categorization algorithm is tested and compared on HKIB-20000/HKIB-40075 Korean Text Categorization Test Collections. Experimental results show that BPNN algorithm with SVD achieves high effectiveness for Korean document categorization.