• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.571-578
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• 1998

In this paper, we deal with a node weighted Steiner Ring Problem (SRP) arising from the deployment of Synchronous Optical Networks (SONET), a standard of transmission using optical fiber technology. The problem is to find a minimum weight cycle (ring) covering a subset of nodes in the network considering node and link weights. We have developed two mathematical models, one of which is stronger than the other in terms of LP bounds, whereas the number of constraints of the weaker one is polynomially bounded. In order to solve the problem optimally, we have developed some preprocessing rules and valid inequalities. We have also prescribed an effective heuristic procedure for providing tight upper bounds. Computational results show that the stronger model is better in terms of computation time, and valid inequalities and preprocessing rules are effective for solving the problem optimally.

• Journal of the Korean Statistical Society
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• v.10
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• pp.91-96
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• 1981

The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

• Journal of the Korean Mathematical Society
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• v.31 no.4
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• pp.633-643
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• 1994

Let us consider the initial-value problem of dimension m: $$ \frac{d\tau}{d}y(\tau) = f(\tau, Y(\tau)), y(0) = y_0, \tau \geq 0, (1.1) $$ Where $ = (f_1, f_2, \cdots, f_m) and y = (y_1, y_2, \cdots, y_m)$.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.96-99
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• 1987

In the way of perception and depth finding of 3-D scene stereo vision is one of the best ways. Matching is important problem of stereo vision. In this paper we develop an algorithm that is adaptable to errors and computation time. And we demonstrate the way of matching.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1428-1434
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• 2006

In this paper, we propose the scheme solving privacy infringement in RFID systems with improving the scalability of back-end server. With RFID/USN becoming important subject, many approaches have been proposed and applied. However, limits of RFID, low computation power and storage, make the protection of privacy difficult. The Hash Chain scheme has been known as one guaranteeing forward security, confidentiality and indistinguishability. In spite of that, it is a problem that requires much of computation to identify tags in Back-End server. In this paper, we introduce an efficient key search method, the Hellman Method, to reduce computing complexity in Back-End server. Hellman Method algorism progresses pre-computation and (re)search. In this paper, after applying Hellman Method to Hash chain theory, We compared Preservation and key reference to analyze and apply to parallel With guaranteeing requistes of security for existing privacy protecting Comparing key reference reduced computation time of server to reduce computation complex from O(m) to $O(\frac{m{^2/3}}{w})$ than the existing form.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.56-63
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• 2016

For air express service providers offering various express delivery services such as overnight delivery and next-business day delivery services, establishing quickly cargo loading plans is one of important issues owing to the characteristics of air express business, i.e., a short amount of time is available to complete all cargo loading operations before flight departure after receiving air express containers, pallets and bulks. On the other hand, one of major concerns in the air cargo loading planning is to make a plan that insures the stability of an aircraft to avoid take-off, flight, and landing accidents. To this end, this paper considers an air cargo loading planning problem, which is the problem of determining locations in the aircraft cargo space where air containers, pallets and bulks to be loaded while insuring the aircraft stability, motivated from DHL and Air Hong Kong. The objective of the problem is to maximize the total revenue gained from loading air express containers, pallets and bulks. To solve the problem, this paper suggests a simulated annealing algorithm to overcome impracticality of the integer programming model developed by a previous study requiring excessive computation time. The results of computational experiments show that the heuristic algorithm is a viable tool for establishing express cargo loading plans as giving robust and good solutions in a short amount of computation time. Scenario analyses are performed to investigate the effect of the current activities of air express carriers on the revenue change and to draw practical implications for air express service providers.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.117-126
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• 2003

GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.2
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• pp.41-50
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• 2003

In this paper, nonlinear parallel structural analyses are introduced by using the parallel multifrontal solver and damage localization for 2D and 3D crack models is presented as the application of nonlinear parallel computation. The parallel algorithms related with nonliear reduce the amount of memory used is carried out because many variables should be utilized for this highly nonlinear damage analysis. Also, Riks' continuation method is parallelized to search the solution when strain softening occurs due to damage evolution. For damage localization problem, several computational models having up to around 1-million degree of freedoms are used. The parallel performance in this nonlinear parallel algorithm is shown through these examples and the local variation of damage at crack tip is compared among the models with different degree of freedoms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.103-108
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• 2016

In communication systems the solution of the problem of maximizing the mutual information between the input and output of a channel composed of several subchannels under total power constraint has a waterfilling structure. OFDM and MIMO can be decomposed into parallel subchannels with CSI. Waterfilling solves the problem of optimal power allocation to these subchannels to achieve the rate approaching the channel capacity under total power constraint. In waterfilling, more power is alloted to good channels(high SNR) and less or no power to bad channels to increase the rate of good channels, resulting in channel capacity. Waterfilling finds the exact water level satisfying the power constraint employing an iterative algorithm to estimate and update the water level. In this process computation of partial sums of inverse of square of subchannel gain is repeatedly required. In this paper we reduced the computation time of waterfilling algorithm by replacing the partial sum computation with reference to an array which contains the precomputed partial sums in initialization phase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.842-849
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• 2022

With the development of deep learning technology, there are many cases of using DNNs in embedded systems such as unmanned vehicles, drones, and robotics. Typically, in the case of an autonomous driving system, it is crucial to run several DNNs which have high accuracy results and large computation amount at the same time. However, running multiple DNNs simultaneously in an embedded system with relatively low performance increases the time required for the inference. This phenomenon may cause a problem of performing an abnormal function because the operation according to the inference result is not performed in time. To solve this problem, the solution proposed in this paper first reduces the computation by applying the Tucker decomposition to DNN models with big computation amount, and then, make DNN models run in parallel as much as possible in the unit of hidden layer inside the GPU. The experimental result shows that the DNN inference time decreases by up to 75.6% compared to the case before applying the proposed technique.