• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.724-732
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• 2013

In this paper, we analyze a performance of multiuser massive multiple-input and multiple-output (MIMO) system. We derive the ergodic cell capacity based on a downlink frame structure and analyze the ergodic cell capacity with respect to the number of base station (BS) antennas and the number of users. This paper shows that the ergodic cell capacity is a concave function with respect to the number of BS antennas and the number of users, and also derives the optimal numbers of BS antennas and users for the maximum cell capacity. The simulation results verify the derived analyses and show that the derived numbers of BS antennas and users provide the maximum cell capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3286-3301
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• 2014

Jung and Yoo proposed the first image interpolation-based reversible data hiding algorithm. Although their algorithm achieved superior interpolation results, the embedding capacity was insufficient. Lee and Huang proposed an improved algorithm to enhance the embedding capacity and the interpolation results. However, these algorithms present limitations to magnify the original image to any resolution and pixels in the boundary region of the magnified image are poorly manipulated. Furthermore, the capacity and the image quality can be improved further. This study modifies the pixel mapping scheme and adopts a bilinear interpolation to solve boundary artifacts. The modified reference pixel determination and an optimal pixel adjustment process can effectively enhance the embedding capacity and the image quality. The experimental results show our proposed algorithm achieves a higher embedding capacity under acceptable visual distortions, and can be applied to a magnified image at any resolution. Our proposed technique is feasible in reversible data hiding.

• Steel and Composite Structures
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• v.51 no.4
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• pp.417-440
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• 2024

Artificial neural networks (ANN) have been the focus of several studies when it comes to evaluating the pile's bearing capacity. Nonetheless, the principal drawbacks of employing this method are the sluggish rate of convergence and the constraints of ANN in locating global minima. The current work aimed to build four ANN-based prediction models enhanced with methods from the black hole algorithm (BHA), league championship algorithm (LCA), shuffled complex evolution (SCE), and symbiotic organisms search (SOS) to estimate the carrying capacity of piles in cold climates. To provide the crucial dataset required to build the model, fifty-eight concrete pile experiments were conducted. The pile geometrical properties, internal friction angle 𝛗 shaft, internal friction angle 𝛗 tip, pile length, pile area, and vertical effective stress were established as the network inputs, and the BHA, LCA, SCE, and SOS-based ANN models were set up to provide the pile bearing capacity as the output. Following a sensitivity analysis to determine the optimal BHA, LCA, SCE, and SOS parameters and a train and test procedure to determine the optimal network architecture or the number of hidden nodes, the best prediction approach was selected. The outcomes show a good agreement between the measured bearing capabilities and the pile bearing capacities forecasted by SCE-MLP. The testing dataset's respective mean square error and coefficient of determination, which are 0.91846 and 391.1539, indicate that using the SCE-MLP approach as a practical, efficient, and highly reliable technique to forecast the pile's bearing capacity is advantageous.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.696-703
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• 2000

This paper describes the capacity calculation of power supply system for light Rail Transit Three factors are considered for the design i.e. substation arrangements, line configuration and substation power capacity. In this study, we considered all of them for capacity calculation of power supply system for LRT. At first DC-fed-traction system is introduced on an outline, a characteristics of train and fed network, and design method of substation arrangements. Optimal design procedures are described, and program for capacity calculation of the system is presented. In addition, the computer simulated results are computed with the conventional simple calculation method.

• Journal of the Korea Society for Simulation
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• v.12 no.1
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• pp.35-48
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• 2003

This paper suggests the long-term strategy of the production distribution planning considering the capacity of factory production and the uncertain demand in a supply chain. This paper determines the near optimal capacity of factory production by using the advantages of mathematical and simulation models. Also, the relationship between the capacity from the suggested model and the strategy of production and distribution in a supply chain is studied. Arena is used for modeling and analysis.

• Journal of the Korean Society for Railway
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• v.5 no.2
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• pp.77-83
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• 2002

In this paper we present a nonlinear programming model for the train seat capacity distribution with a numerical example. The model finds the optimal capacity distribution methods which minimize the sum of the differences between the demands and the seat capacities. Also the model provides the information on the degree of the discrepancy between the demand and the seat capacities. One can use the model as a tool for planning train seat capacity planning.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.413-423
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• 2014

Recently, cloud computing has been affecting academic information system buildup. When university academic affairs information system is designed with cloud computing, it is very important to estimate the adequate processing capacity for the cloud computer taking into account a waste of resources and the quality of service. Cloud computer's processing capacity to meet the quality of service expected by users should be predicted based on users' transaction patterns and resource requirements characteristics. In this paper, we analyze actual traffic patterns occurring in university academic affairs business and propose a method to calculate the optimal processing capacity for cloud computer to satisfy the given average response time. To justify our research, we apply the research results to a real university academic affairs business case and obtain the optimal processing capacity for the integrated academic affairs business.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.341-358
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• 2021

Purpose: After product development, a Reliability Demonstration Test(RDT) is performed to confirm that the target life has been achieved. In the RDT, there are cases where the test equipment cannot accommodate all samples. Therefore, this study considers a test method to most economically demonstrate the target life of the product at a certain confidence level when the sample size is larger than the capacity of the test equipment. Methods: If the sample size is larger than the capacity of the test equipment, test equipments may be added or the test time of individual samples may be increased. So the test method is designed to cover this situation with limited capacity. A zero-failure test method is applied as a test method to RDT. To minimize the cost, the test cost is defined and the cost function is obtained. Finally, we obtain the optimal test plan. Results: A zero-failure test method is designed when the sample size is larger than the capacity of the test equipment, and the expected total cost is derived. In addition, the process of calculating the appropriate sample size, test time, and number of test equipment is illustrated through an example, and the effects of model parameters to the optimal solutions are investigated numerically. Conclusion: In this paper, we study a zero-failure RDT with test equipment that has limited capacity. The expected total cost is derived and the optimal sample size, test time, and number of test equipment are determined to minimize the expected total cost. We also studied numerical examples and for further studies, we can relax some restrictions in the test model and optimize the test method.

• Tribology and Lubricants
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• v.18 no.3
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• pp.181-186
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• 2002

A numerical analysis is undertaken to show the influence of bearing design parameters on the load capacity of air lubricated spiral grooved thrust bearing. The governing equation derived from the mass balance is solved by the finite difference method. Optimal values for various design parameters are obtained to maximize the load capacity. The design parameters are the groove angle, the groove width ratio, the groove height ratio, and the seal ratio.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.19-26
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• 1983

This paper deals with the problem of locating facilities with upper and lower capacity bounds in a single level physical distribution system at minimum total costs. Several known schemes for location problems with upper capacity bounds only are successfully extended to our case and then implemented into our branch ana bound solution procedure. Computational experiments with twelve test problems suggest the effectiveness of our approach by showing that only a small amount of additional computation is required for our problem as compared to that for the problems with upper capacity bounds.