• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2058-2074
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• 2017

Dense Heterogeneous Cellular Networks(HCNs) offer a promising approach to meet the target of 1000x increase in aggregate data rates in 5G wireless communication systems. However how to best utilize the available radio resources at densely deployed small cells remains an open problem as those small cells are typically unplanned. In this paper we focus on balancing loads across macro cells and small cells by offloading users to small cells, as well as dynamically switching off underutilized small cells. We propose a joint user association and base station(BS) sleep mangement(UA-BSM) scheme that proactively offloads users to a fraction of the densely deployed small cells. We propose a heuristic algorithm that iteratively solves the user association problem and puts BSs with low loads into sleep. An interference relation matrix(IRM) is constructed to help us identify the candidate BSs that can be put into sleep. User associations are then aggregated to selected small cells that remain active. Simulation results show that our proposed approach achieves load balancing across macro and small cells and reduces the number of active BSs. Numerical results show user signal to interference ratio(SINR) can be improved by small cell sleep control.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.207-211
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• 2004

The final goal of this research is to establish the relative dangerousness D/B for factors on seakeeping performance. This D/B is essential to develope the seakeeping performance evaluation system built-on-ship. The system is composed of the apparatus for measuring a vertical acceleration to be generated by the ship's motions, computer for calculating the synthetic seakeeping performance index and monitor for displaying the evaluating diagram of navigational safety of ship. In this paper, a methodology on the establishment of the relative dangerousness D/B for factors on seakeeping performance is presented by a numerical simulations, playing an important role on the algorithm of the program for calculating the synthetic seakeeping performance index. Finally, It is investigated whether the relative dangerousness D/B can be realized an accurate values according to the loading conditions, weather conditions, wave directions end present ship's speed of a model ship.

• KIEAE Journal
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• v.16 no.3
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• pp.89-94
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• 2016

Purpose: This study aimed at developing an artificial neural network (ANN) model to predict the optimal start moment of the setback temperature during the normal occupied period of a building. Method: For achieving this objective, three major steps were conducted: the development of an initial ANN model, optimization of the initial model, and performance tests of the optimized model. The development and performance testing of the ANN model were conducted through numerical simulation methods using transient systems simulation (TRNSYS) and matrix laboratory (MATLAB) software. Result: The results analysis in the development and test processes revealed that the indoor temperature, outdoor temperature, and temperature difference from the setback temperature presented strong relationship with the optimal start moment of the setback temperature; thus, these variables were used as input neurons in the ANN model. The optimal values for the number of hidden layers, number of hidden neurons, learning rate, and moment were found to be 4, 9, 0.6, and 0.9, respectively, and these values were applied to the optimized ANN model. The optimized model proved its prediction accuracy with the very storing statistical correlation between the predicted values from the ANN model and the simulated values in the TRNSYS model. Thus, the optimized model showed its potential to be applied in the control algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7A
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• pp.757-767
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• 2008

Start Ongoing next generation networks are expected to be deployed over current existing networks, in the form of overlayed heterogeneous networks, in particular, in hot spot areas. Therefore, it will be necessary to develop an interworking technique such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load balancing mechanism termed 'soft' load balancing where the IP(Internet Protocol) traffic of a user is divided into sub-traffic, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load sharing and handover techniques. Through a numerical analysis, we obtain an optimal LBR (Load Balancing Ratio) for determining the volume of traffic delivered to each network over an overlayed multi-cell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by reducing the outage probability efficiently for a given user traffic.

• Journal of the Korea Computer Graphics Society
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• v.24 no.2
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• pp.11-20
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• 2018

We propose a new method particle-based method that explicitly preserves thin liquid sheets for animating liquids on CPU-GPU heterogeneous computing framework. Our primary contribution is a particle-based framework that splits at thin points and collapses at dense points to prevent the breakup of liquid on GPU. In contrast to existing surface tracking methods, the our method does not suffer from numerical diffusion or tangles, and robustly handles topology changes on CPU-GPU framework. The thin features are detected by examining stretches of distributions of neighboring particles by performing PCA(Principle component analysis), which is used to reconstruct thin surfaces with anisotropic kernels. The efficiency of the candidate position extraction process to calculate the position of the fluid particle was rapidly improved based on the CPU-GPU heterogeneous computing techniques. Proposed algorithm is intuitively implemented, easy to parallelize and capable of producing quickly detailed thin liquid animations.

• Journal of IKEEE
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• v.14 no.3
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• pp.173-181
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• 2010

The high flowability performance evaluation device for the concrete is the device which was designed to compensate from the incorrect data detection of the viscosimetry examination of the existing concrete. As for the existing concrete viscosimetry method, the measuring data for a viscosity are very irregular by the point of view of an experimenter and a supervisor, Therefore there were some problems to have many different opinions by a small numerical value difference according to the job characteristic. In this paper, we suggested some mechanism to compensate the problem and some driving electronics including the related algorithm, and the communication structure with wireless sensor network between the devices and users are also presented. The effectiveness of the suggested method was verified with a real experiment.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of The Korean Astronomical Society
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• v.48 no.1
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• pp.57-66
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• 2015

Monte-Carlo radiative models of the diffuse Galactic light (DGL) in our Galaxy are calculated using the dust radiative transfer code MoCafe, which is three-dimensional and takes full account of multiple scattering. The code is recently updated to use a fast voxel traversal algorithm, which has dramatically increased the computing speed. The radiative transfer models are calculated with the generally accepted dust scale-height of 0.1 kpc. The stellar scale-heights are assumed to be 0.1 or 0.35 kpc, appropriate for far-ultraviolet (FUV) and optical wavelengths, respectively. The face-on optical depth, measured perpendicular to the Galactic plane, is also varied from 0.2 to 0.6, suitable to the optical to FUV wavelengths, respectively. We find that the DGL at high Galactic latitudes is mostly due to backward or large-angle scattering of starlight originating from the local stars within a radial distance of r < 0.5 kpc from the Earth. On the other hand, the DGL measured in the Galactic plane is mostly due to stars at a distance range that corresponds to an optical depth of $${\sim_\sim}$$ 1 measured from the Earth. Therefore, the low-latitude DGL at the FUV wavelength band would be mostly caused by the stars located at a distance of $r{\leq}0.5$ kpc and the optical DGL near the Galactic plane mainly originates from stars within a distance range of $1{\leq}r{\leq}2kpc$. We also calculate the radiative transfer models in a clumpy two-phase medium. The clumpy two-phase models provide lower intensities at high Galactic latitudes compared to the uniform density models, because of the lower effective optical depth in clumpy media. However, no significant difference in the intensity at the Galactic plane is found.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.11
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• pp.1039-1048
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• 2008

new computational procedure for the Non-Linear Vortex Lattice Method (NLVLM) is suggested in this work. Conventional procedures suggested so far usually involves inner iteration loop to update free vortex shape and an under-relaxation based iteration loop to determine the free vortex shape. In this present work, we suggest a new formula based on quasi-steady concept to fix free vortex shape which eliminates the need for inner iteration loop. Further, the ensemble averaging of the induced velocities for a given free vortex segment evaluated at each iteration significantly improves the convergence property of the algorithm without resorting to the under-relaxation technique. Numerical experiments over several low aspect ratio wings are carried out to obtain optimal empirical parameters such as the length of the free vortex segment, the vortex core radius, and the rolled-up wake length.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.33-40
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• 1989

In the design of reinforced concrete framed structures, which consist of various design variables, the objective and the constraint functions are formulated in complicated forms. Usually iterative methods have been used to optimize the design variables. In this paper, multilevel formulation is adopted, and design variables are selected in reduced numbers at each level, to reduce the iterative cycle and to accelerate the convergence rate. At level 1, elastic analysis is performed to get the upper and lower bounds of the redistributed design moments due to inelastic behavior of the frame. Then the design moments are taken as design variables and optimized at level 2, and the sizing variables are optimized at level 3. The optimization of redistributed moments is performed using the design sensitivity obtained at the level 2, and force approximation technique is used to reflect the variation of design variables in the lower level to the upper level. The design variables are selected in reduced numbers at each level, and the optimization formulation is simplified effectively. A cost function is taken as the objective function, and the constraints of the stress of the structures are derived from BSI CP 110 following limit state theory. Numerical examples are included to prove the effectiveness of the developed algorithm.