• Steel and Composite Structures
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• v.39 no.3
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• pp.319-335
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• 2021

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R² = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R² = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.8
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• pp.39-45
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• 2012

This paper investigates the capacity for the secondary user with the primary full duplex relay (FDR) network in spectrum sharing systems. For sharing the spectrum of the primary user, sharing scheme under the various primary network should be investigated. However, the conventional works only consider the point-to-point primary communication system. When the FDR node is used for the primary networks, both primary relay and destination suffer the interference from the secondary transmitter simultaneously. Thus, the strict interference constraint should be considered to share the spectrum of the primary user. Therefore, we investigate the capacity of the secondary user with the primary FDR network under the average and peak received-power constraints. In addition, we analyze the performance degradation by the selection of the worst interference channels to consider interference constraint in this system. Through the numerical results, the capacities of the primary and secondary users under the average received-power is superior to the that under the peak received-power constraint.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3470-3493
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• 2019

IEEE 802.11s-based infrastructure Wireless Mesh Networks (iWMNs) are envisaged as a promising solution to provide ubiquitous wireless Internet access. The limited network capacity is a problem mainly caused by the medium contention between mesh users and the mesh access points (MAPs), which gets worst when the mesh clients employ the Transmission Control Protocol (TCP). To mitigate this problem, we use wireless network coding (WNC) in the MAPs. The aim of this proposal is to take advantage of the network topology around the MAPs, to alleviate the contention and maximize the use of the network capacity. We evaluate WNC when is used in MAPs. We model the formation of coding opportunities and, using computer simulations, we evaluate the formation of such coding opportunities. The results show that as the users density grows, the coding opportunities increase up to 70%; however, at the same time, the coding delay increments significantly. In order to reduce such delay, we propose to adaptively adjust the time that a packet can wait to catch a coding opportunity in an MAP. We assess the performance of moving-average estimation methods to forecast this adaptive sojourn time. We show that using moving-average estimation methods can significantly decrease the coding delay since they consider the traffic density conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.1-6
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• 2019

CCTV video recording system is recognized as evidence value of video data, and is widely used in real life for the purpose of security of facilities or security control, and it is developing in order to process high-resolution and high-capacity data in real time through network. However, there is no description of redundancy to prevent the loss of image data due to defects of unexpected equipment or external attack, and even if the redundancy is implemented, a high-capacity video stream is transmitted through the network, network overload can not avoided. In this paper, we propose and verify a failover method based on rules that can operate the redundancy scheme without inducing network overload in CCTV network video recording environment.

• Journal of Communications and Networks
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• v.15 no.6
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• pp.576-580
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• 2013

In this paper, we investigate the capacity of a multipoint-to-point cognitive radio network. In existing works, the asymptotic capacity is only obtained in the high peak power region at secondary transmitter (ST) or obtained without considering the interference from primary transmitter (PT) for easy analysis. Here, we analyze the asymptotic capacity by considering an arbitrary peak power at the ST and the interference from the PT based on extreme value theory. Simulation results show that our approximated capacity is well-matched to the exact capacity. Furthermore, the scaling law of our capacity is found to be double logarithm of the number of secondary users.

• Computers and Concrete
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• v.8 no.2
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• pp.125-142
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• 2011

In the present paper, a numerical simulation method based on mesoscopic composite structure of concrete, the truss network model, is developed to evaluate the diffusivity of concrete in order to account for the microstructure of concrete, the binding effect of chloride ions and the chloride concentration dependence. In the model, concrete is described as a three-phase composite, consisting of mortar, coarse aggregates and the interfacial transition zones (ITZs) between them. The advantage of the current model is that it can easily represent the movement of mass (e.g. water or chloride ions) through ITZs or the potential cracks within concrete. An analytical method to estimate the chloride diffusivity of mortar and ITZ, which are both treated as homogenious materials in the model, is introduced in terms of water-to-cement ratio (w/c) and sand volume fraction. Using the newly developed approaches, the effect of cracking of concrete on chloride diffusion is reflected by means of the similar process as that in the test. The results of calculation give close match with experimental observations. Furthermore, with consideration of the binding capacity of chloride ions to cement paste and the concentration dependence for diffusivity, the one-dimensional nonlinear diffusion equation is established, as well as its finite difference form in terms of the truss network model. A series of numerical analysises performed on the model find that the chloride diffusion is substantially influenced by the binding capacity and concentration dependence, which is same as that revealed in some experimental investigations. This indicates the necessity to take into account the binding capacity and chloride concentration dependence in the durability analysis and service life prediction of concrete structures.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.161-172
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• 2017

In the paper, a hybrid technique is proposed for detecting the location and capacity of distributed generation (DG) sources like wind and photovoltaic (PV) in power system. The novelty of the proposed method is the combined performance of both the Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) techniques. The mentioned techniques are the optimization techniques, which are used for optimizing the optimum location and capacity of the DG sources for radial distribution network. Initially, the Artificial Neural Network (ANN) is applied to obtain the available capacity of DG sources like wind and PV for 24 hours. The BBO algorithm requires radial distribution network voltage, real and power loss for determining the optimum location and capacity of the DG. Here, the BBO input parameters are classified into sub parameters and allowed as the PSO algorithm optimization process. The PSO synthesis the problem and develops the sub solution with the help of sub parameters. The BBO migration and mutation process is applied for the sub solution of PSO for identifying the optimum location and capacity of DG. For the analysis of the proposed method, the test case is considered. The IEEE standard bench mark 33 bus system is utilized for analyzing the effectiveness of the proposed method. Then the proposed technique is implemented in the MATLAB/simulink platform and the effectiveness is analyzed by comparing it with the BBO and PSO techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.89-97
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• 2007

We study the maximum integer multiflow problem and the minimum multicut problem in a ring network. Both problems in a general network are known to be NP-hard. In this paper, we develop polynomial time algorithms to solve the problems. We also prove that even In a ring network, maximum multiflow is not always integral, which implies that the amount of maximum integer flow does not always reach the minimum capacity of multicut.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.1-9
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• 2012

We consider a receiving node, located at the origin, and a Poisson point process (PPP) that models the locations of the desired transmitter as well as the interferers. Interference is known to be non-Gaussian in this scenario. The capacity bounds for additive non-Gaussian channels depend not only on the power of interference (i.e., up to second order statistics) but also on its entropy power which is influenced by higher order statistics as well. Therefore, a complete statistical characterization of interference is required to obtain the capacity bounds. While the statistics of sum of signal and interference is known in closed form, the statistics of interference highly depends on the location of the desired transmitter. In this paper, we show that there is a tradeoff between entropy power of interference on the one hand and signal and interference power on the other hand which have conflicting effects on the channel capacity. We obtain closed form results for the cumulants of the interference, when the desired transmitter node is an arbitrary neighbor of the receiver. We show that to find the cumulants, joint statistics of distances in the PPP will be required which we obtain in closed form. Using the cumulants, we approximate the interference entropy power and obtain bounds on the capacity of the channel between an arbitrary transmitter and the receiver. Our results provide insight and shed light on the capacity of links in a Poisson network. In particular, we show that, in a Poisson network, the closest hop is not necessarily the highest capacity link.