• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1325-1344
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• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.287-292
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• 2022

In this paper, the stochastic distribution of the springback amount is investigated for the stamping process of a U-channel shaped-product with ultra-high strength steel. Using the reliability-based design optimization technique (RBDO), stochastic distribution of process parameters is considered in the analysis including material properties and process variation. Quantification of the springback scatters is carried out with the statistical analysis method according to the material strength. It is found that the scattering amount of springback decreases while the amount of springback increases as the tensile strength of the blank material increases, which is investigated by analyzing the strain and stress distribution of the punch and die shoulder. It is noted that the proposed scheme is capable of predicting and responding to the unavoidable scattering of springback in the sheet metal forming process.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.

• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.195-206
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• 2024

Shenzhen Innovation Light source Facility (SILF) is a 3.0 GeV fourth generation diffraction limited synchrotron light source currently under construction in Shenzhen. The SILF storage ring is proposed to use two 500 MHz single cell superconducting radio frequency (SRF) cavities to provide 2.4 MV RF voltage. In this study, we examined the geometric structure of mature CESR superconducting cavities and adopted a beam-pipe-type extraction scheme for high-order modes (HOM). One of the objectives of SRF cavity design and optimization in this study is to reduce E_p/E_acc and B_p/E_acc as much as possible to reduce power loss and ensure stable operation of the cavity. To reduce the risk of beam instability and thermal breakdown, the HOM and Multipacting (MP) are simulated. Moreover, the mechanical properties of the cavity are analyzed, including frequency sensitivity from pressure of liquid helium (LHe), stress, tuning, Lorentz force detuning (LFD), the microphone effect, and buckling. By comprehensive design and optimization of 500 MHz single-cell SRF cavities, a superconducting cavity for SILF storage ring was developed. This paper will detailed present the design and simulation.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.5
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• pp.640-645
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• 2016

The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (GEBV) as the selection criteria. The ZPLAN+ software was employed to calculate and compare the genetic gain, total cost, return and profit of each selection strategy. The first strategy reflected the current conventional breeding program, which was a progeny test system (CS). The second strategy was a selection scheme based strictly on genomic information (GS1). The third scenario was the same as GS1, but the selection by GEBV was further supplemented by the performance test (GS2). The last scenario was a mixture of genomic information and progeny tests (GS3). The results showed that the accuracy of the selection index of young boars of GS1 was 26% higher than that of CS. On the other hand, both GS2 and GS3 gave 31% higher accuracy than CS for young boars. The annual monetary genetic gain of GS1, GS2 and GS3 was 10%, 12%, and 11% higher, respectively, than that of CS. As expected, the discounted costs of genomic selection strategies were higher than those of CS. The costs of GS1, GS2 and GS3 were 35%, 73%, and 89% higher than those of CS, respectively, assuming a genotyping cost of $120. As a result, the discounted profit per animal of GS1 and GS2 was 8% and 2% higher, respectively, than that of CS while GS3 was 6% lower. Comparison among genomic breeding scenarios revealed that GS1 was more profitable than GS2 and GS3. The genomic selection schemes, especially GS1 and GS2, were clearly superior to the conventional scheme in terms of monetary genetic gain and profit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1255-1261
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• 2016

Recently, the energy harvesting technology in which energy is collected from the wireless signal which is transmitted by mobile communication devices, has been considered as a novel way to improve the life time of wireless sensors by mitigating the lack of power supply problem. In this paper, we consider the optimal sensing time and power allocation problem for cognitive radio systems, where the energy efficiency of secondary user is maximized while the constraint are satisfied, using the optimization technique. Based on the derived optimal solutions, we also have proposed an iterative resource allocation algorithm in which the optimal power and sensing time allocation can be found without excessive computations. The simulation results confirm that the proposed scheme achieves the optimal performance and it outperforms the conventional resource allocation schemes in terms of energy efficiency while the constraints are guaranteed to be satisfied.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.385-394
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• 2011

In this study, optimal parameters of diffusion-analogy GIUH were calculated by separating channel and hillslope from drainage structures in the basin. Parameters of the model were composed of channel and hillslope, each velocity($u_c$, $u_h$) and diffusion coefficient($D_c$, $D_h$). Tanbu subwatershed in Bocheong river basin as a target basin was classified as 4th rivers by Strahler's ordering scheme. The optimization technique was applied to the SCE-UA, the estimated optimal parameters are as follows. $u_c$ : 0.589 m/s, $u_h$ : 0.021 m/s, $D_c$ : $34.469m^2/s$, $D_h$ : $0.1333m^2/s$. As a verification for the estimated parameters, the error of average peak flow was about 11 % and the error of peaktime was 0.3 hr. By examining the variability of parameters, the channel diffusion coefficient didn't have significant effect on hydrological response function. by considering these results, the model is expected to be simplified in the future.