• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.137-140
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• 2011

A precoding strategy is one of the representative interference management techniques in cognitive radio (CR) network which is a typical interference-limited environment. The interference minimization approach to precoding is an appropriate scheme to mitigate the interference efficiently while it may cause the capacity loss of the desired channel. The precoding scheme for the maximal capacity of the desired channel improves the capacity of the desired channel while it increases the interference power and finally causes the capacity loss of the interfered users. Therefore, we propose a precoding scheme which satisfies these two conflicting goals and manages the interference signal in such an interference-limited environment. The proposed scheme consists of two steps. First, the precoder nulls out the largest singular value of the interference channel to mitigate the dominant interference signal based on the interference minimization approach. Second, the transmitter calculates the sum capacities per mode and selects a mode to maximize the sum capacity. In the second step, each mode consists of the right singular vectors corresponding to the singular values except the largest singular value eliminated in the first step. Simulation results show that the proposed precoding scheme not only efficiently mitigate the interference signal, but also has the best performance in terms of the sum capacity in a MIMO-based CR network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.252-256
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• 2011

We analyze the channel capacity with considering the effect of the loading conditions of indoor PLC networks on channel state information. We consider various numbers of load for two kinds of the networks with regular length branches and a deployed network of indoor PLC. For calculating the channel capacity degradation, two noise scenarios and impedances are considered. From the simulation results, we suggest the robust regression lines for modeling the channel capacity degradation. In the cases of 0 $\Omega$ and $Z_0$ loads, natural log and linear function curve show the best goodness of fit, respectively. For the deployed indoor PLC network with 0 $\Omega$ loads, compared with the networks with regular length branches, the goodness of fit decreases by the amount of 0.12 and 0.15 for low noise and high noise scenarios, respectively. Using the regression lines, we can estimate the channel capacity degradation without measurement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.465-467
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• 2010

This paper proposes MIMO two-way cooperative relay scheme to optimize the end to end capacity in wireless multi-hop mesh network. The basic idea is to perform data transmission via multi-hop relay nodes, in equidistant topology, this method is quite efficient. However, on one hand this topology is very rare in practical situation, on the other hand, in real practical situation where the topology is most likely non equidistant, the end to end capacity significantly degrades due to bottleneck link caused by uneven SNR. Moreover, the end to end capacity degrades at high SNR due to overreach interference from far nodes existing in multi-hop relay networks. In this paper, MIMO two-way cooperative relay in the region of non equidistant nodes is found efficient to improve the end to end capacity. The proposed scheme is validated using numerical simulation.

• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.671-680
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• 2022

The shear capacity of beams is an essential parameter in designing beams carrying shear loads. Precise estimation of the ultimate shear capacity typically requires comprehensive calculation methods. For steel fiber reinforced concrete (SFRC) beams, traditional design methods may not accurately predict the interaction between different parameters affecting ultimate shear capacity. In this study, artificial neural network (ANN) modeling was utilized to predict the ultimate shear capacity of SFRC beams using ten input parameters. The results demonstrated that the ANN with 30 neurons had the best performance based on the values of root mean square error (RMSE) and coefficient of determination (R²) compared to other ANN models with different neurons. Analysis of the ANN model has shown that the clear shear span to depth ratio significantly affects the predicted ultimate shear capacity, followed by the reinforcement steel tensile strength and steel fiber tensile strength. Moreover, a Genetic Algorithm (GA) was used to optimize the ANN model's input parameters, resulting in the least cost for the SFRC beams. Results have shown that SFRC beams' cost increased with the clear span to depth ratio. Increasing the clear span to depth ratio has increased the depth, height, steel, and fiber ratio needed to support the SFRC beams against shear failures. This study approach is considered among the earliest in the field of SFRC.

• Korea Trade Review
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• v.41 no.5
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• pp.325-351
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• 2016

This study empirically investigated the relationship among knowledge transfer, network(firm network and government network) and performance Korean MNCs' subsidiaries in terms of absorptive capacity and entry mode roles in China. For this, absorptive capacity was established as an independent variable, mediating variable, and moderating variable. And the entry mode was divided into single investment and joint venture and set to the moderating variable. Data for the analysis of actual proof was randomly selected from the companies which was established more than 3 years before KOTRA 'The overseas expansion Korean company directory (2014)'. Questionnaires to 138 Chinese subsidiaries of Korean MNCs were collected by FAX and E-mail. AMOS was utilized and collected data investigated the role of the absorption capacity and entry mode as the covariance structure analysis. The empirical analysis showed that absorption capacity has a direct influence on management performance as an independent variable with the network (firm network and government network). It only has a partial mediating role between enterprise networks and management performance, and no meaningful result was gained as its moderationg role bewteen the exogenous variable and management performance. And in terms of Korean companies' moderating role in entering China, they have a moderating role between government network, absorption capacity and management performance, but did not show a statistically significant result between knowledge transfer, enterprise network and management performance. Absorption capacity, as the variable affecting overseas subsidiary's management performance, should not be considered a mediating or moderating variable, but an independent variable. Since the joint venture is showing higher performance than single investment when going into the Chinese market, implication is provided for options in overseas expansion. But this research has the limitation in generalization because it is aiming at the subsidiaries of the Korean company investing in China. Therefore, it is more desirable in the future to conduct a study of the subsidiary of the Korean company entering several countries. It also has limitations in generalization, because the research was conducted using a limited number of variables, despite there are various factors affecting the management performance of Chinese subsidiaries.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2121-2123
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• 2003

Distributed Control Systems(DCS) arc used in a wide range of process applications such as power plants. This paper presents calculated network capacity of a DCS that developed for nuclear power plant. The network hierarchies are 3 layed of information network, control network and field network. The assumed total node number of maximum DCS network is 64. Worst case network utilization of the DCS is simulated and analyzed.

• Steel and Composite Structures
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• v.35 no.3
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• pp.415-437
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• 2020

Circular concrete filled steel tube (CFST) columns have an advantage over all other sections when they are used in compression members. This paper proposes a new approach for deriving a new empirical equation to predict the axial compressive capacity of circular CFST columns using the Artificial Neural Network (ANN). The developed ANN model uses 5 input parameters that include the diameter of circular steel tube, the length of the column, the thickness of steel tube, the steel yield strength and the compressive strength of concrete. The only output parameter is the axial compressive capacity. Training and testing the developed ANN model was carried out using 219 available sets of data collected from the experimental results in the literature. An empirical equation is then proposed as an important result of this study, which is practically used to predict the axial compressive capacity of a circular CFST column. To evaluate the performance of the developed ANN model and the proposed equation, the predicted results are compared with those of the empirical equations stated in the current design codes and other models. It is shown that the proposed equation can predict the axial compressive capacity of circular CFST columns more accurately than other methods. This is confirmed by the high accuracy of a large number of existing test results. Finally, the parametric study result is analyzed for the proposed ANN equation to consider the effect of the input parameters on axial compressive strength.

• Journal of the Korean Geotechnical Society
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• v.33 no.6
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• pp.27-36
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• 2017

Gravel compaction pile method has been widely used to improve the soft ground on the land or sea as one of the soft ground improvement technique. The ultimate bearing capacity of the ground reinforced by gravel compaction piles is affected by the soil strength, the replacement ratio of pile, construction conditions, and so on, and various prediction equations have been proposed to predict this. However, the prediction of the ultimate bearing capacity using the existing models has a very large error and variation, and it is not suitable for practical design. In this study, multiple regression analysis was performed using field loading test results to predict the ultimate bearing capacity of ground reinforced by gravel compaction pile, and the most efficient input variables are selected through evaluation of error by leave one out cross validation, and a multiple regression equation for the prediction of ultimate bearing capacity was proposed. In addition, the prediction error was evaluated by applying artificial neural network using the selected input variables, and the results were compared with those of the existing model.

• Journal of Communications and Networks
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• v.5 no.4
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• pp.290-302
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• 2003

Ultra wide band (UWB) radio has recently attracted increased attention due to its expected unlicensed operation, and potential to provide very high data rates at relatively short ranges. In this article we briefly describe some main candidate multiple access and modulation schemes for UWB communications, followed with their power spectral density calculation and properties. We also present some illustrative capacity results, and provide a discussion of the impact of network topology on multiple access capacity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.750-753
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• 2016

Quorum sensing (QS) is a bacterium-to-bacterium cell communication mechanism allowing bio-cell network construction but such mechanism is not well defined yet. We construct a QS-based multiple access network (MAN) and then numerically analyse its average uplink channel capacity as well as BER performance over diffusion-based 3-D molecular communication channels.