• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.141-144
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• 2001

In this paper, we proposed a neural network controller with a fuzzy compensator which compensate a output of neural network controller. Even if learn by neural network controller, it can occur a bad results from disturbance or load variations. So in order to adjust above case. we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning an inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. In order to confirm a performance of the proposed controller, we implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.233-237
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• 2012

In this paper, We propose a control system which compensate a output of a main Neual Network using a RTDNN(Recurrent Time Delayed Neural Network) with a FLC(Fuzzy Logic Controller)After a learn of main neural network, it can occur a Over shoot or Under shoot from a disturbance or a load variations. In order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. We can confirm good response characteristics of proposed neural network controller by the results of simulation.

• Coupled systems mechanics
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• v.7 no.2
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• pp.233-254
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• 2018

In order to reduce the dependency on fossil fuels, a policy to increase the production capacity of wind turbine is set up. This can be achieved with increasing the dimensions of offshore wind turbine blades. However, this increase in size implies serious problems of stability and durability. Considering the cost of large turbines and financial consequences of their premature failure, it is imperative to carry out numerical simulations over long periods. Here, an energy-conserving time-stepping scheme is proposed in order to ensure the satisfying computation of long-term response. The proposed scheme is implemented for three-dimensional solid based on Biot strain measures, which is used for modeling flexible blades. The simulations are performed at full spatial scale. For reliable design process, the wind loads should be represented as realistically as possible, including the fluid-structure interaction (FSI) dynamic effects on wind turbine blades. However, full-scale 3D FSI simulations for long-term wind loading remain of prohibitive computation cost. Thus, the model to quantify the wind loads proposed here is a simple, but not too simple to be representative for preliminary design studies.

• Structural Engineering and Mechanics
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• v.55 no.2
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• pp.435-459
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• 2015

Parametric resonance of shear deformable composite skew plates subjected to non-uniform (parabolic) and linearly varying periodic edge loading is studied for different boundary conditions. The skew plate structural model is based on higher order shear deformation theory (HSDT), which accurately predicts the numerical results for thick skew plate. The total energy functional is derived for the skew plates from total potential energy and kinetic energy of the plate. The strain energy which is the part of total potential energy contains membrane energy, bending energy, additional bending energy due to additional change in curvature and shear energy due to shear deformation, respectively. The total energy functional is solved using Rayleigh-Ritz method in conjunction with boundary characteristics orthonormal polynomials (BCOPs) functions. The orthonormal polynomials are generated for unit square domain using Gram-Schmidt orthogonalization process. Bolotin method is followed to obtain the boundaries of parametric resonance region with higher order approximation. These boundaries are traced by the periodic solution of Mathieu-Hill equations with period T and 2T. Effect of various parameters like skew angle, span-to-thickness ratio, aspect ratio, boundary conditions, static load factor on parametric resonance of skew plate have been investigated. The investigation also includes influence of different types of linearly varying loading and parabolically varying bi-axial loading.

• International Journal of Railway
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• v.7 no.1
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• pp.16-23
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• 2014

Reduction in railway-induced vibrations in urban areas is a very challenging task in railway transportation. Many mitigation measures can be considered and applied. Among these, a little attention has been paid to trenches. In this study, a numerical investigation on the effectiveness of in-filled trenches with pipes in reducing railway vibrations due to passing trains is presented. Particularly, a series of two-dimensional dynamic analysis was performed to model the behavior of ballasted railway track under harmonic load with ABAQUS software as a Finite Element method. In so doing, two types of in-filled trenches with pipes with steel and concrete materials have been investigated in this paper. In addition, effectiveness of pipes made of steel and concrete, filled with loose sand and clay in railway-induced vibration reduction has been assessed. The results point out that using in-filled trench with pipes does not effective a lot on railway-induced vibration reduction in comparison to other railway-induced vibration reduction methods. However, in-filled trenches with steel pipes are much more effective than in-filled trenches with concrete pipes. Moreover, filling pipes with loose sand and clay does not have any effect on vibration reduction efficiency of these in-filled trenches.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.3
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• pp.119-126
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• 2017

Recently, ground source heat pump systems are being used in buildings for cooling and heating to reduce greenhouse gas and save energy. However, ground source heat pump systems mainly use the vertical closed-loop geothermal system design rather than the open-loop geothermal system design. This is due to a lack of knowledge and few research feasibility studies. In this research, a dynamic thermal analysis numerical simulation based on a standard house model was conducted for an open-loop geothermal system. Based on heating load analysis results, the life cycle costs of a standard house using an open two-well geothermal system were analyzed and compared with a vertical closed-loop geothermal system, and a diesel boiler. As a result, it was found that using an open two-well geothermal system shows economic return on investment after three years.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.9
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• pp.515-521
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• 2002

This paper presents the scheme that improves control responsibility and stability of the controlled-PM electromagnet levitation system with zero Power controller. A magnetically levitation system is used widely because friction can almost be disappeared. But it is difficult to control due to restraint of controllable area and nonlinear characteristics of electromagnetic force, which is proportioned to a square of the magnetic flux density and is in inverse proportion to a square of the air-gap. So, the application of observer theory in which the levitation system is considered to be a linear dynamic model has resulted in omitting the time dependence on mover's speed. Consequently, the performance of the observer is quite poor during transients. Therefore, this paper proposed the controlled-PM electro-magnetic levitation control method in which the variable load is estimated by using the reduced order extended luenverger observer and its system is controlled at a new zero power equilibrium air-gap position. It is also verified that the proposed control method improve the control performance through simulation and experiment.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.54-60
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• 2002

In this paper, we proposed a hybrid neural network-fuzzy controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of loaming a inverse model neural network of Plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed speed controller get a good response compare with a neural network controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of Power System Engineering
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• v.2 no.1
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• pp.67-72
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• 1998

In crane control system, it is required that the travelling time of crane must be reduced as much as possible and there is no the swing of load at the end and starting points. In this paper, we present a hybrid control method which includes two control methods of the optimal regulator and the velocity pattern control in order to realize high performance of the anti-sway. To implement the control algorithm, the dynamic equation is linearlized at an equilibrium point, so that the linear time invariant state equation can be obtained. A 1/10 sized model crane of the usual gantry cranes is made and used to show the applicability of the developed hybrid control method. The effectiveness of developed hybrid control method is proved by experimental results which show us good performance for anti-sway control comparing to conventional velocity pattern control. Practically, it is expected that the proposed control system will make an important contribution to the automatic crane control system of the industrial fields.