• Journal of Industrial Technology
• /
• v.10
• /
• pp.9-13
• /
• 1990

The approximation of the radial distribution functions(RDF) of mixture plays an important role in deriving the mixing rules for the corresponding states principle(CSP). The mean density approximation(MDA), one of the most successful approximations, fails to predict the radial distribution functions when the size ratio in terms of the Lennard-Jones size parameters is greater than 1.5. To get a better prediction of important structural integrals over the radial distribution functions that arise in the asymmetrical attraction contribution of the perturbaton theory, the new type of mean density approximation(NTMDA) is proposed. With this NTMDA, quite reliable results for those integrals for systems with comparatively large ratio of the size parameters are obtained.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.12
• /
• pp.1736-1738
• /
• 2016

In modern digital communication systems adapting high-order modulation and high performance channel code, log-likelihood ratios involving the repeated calculations of the logarithm of sum of exponential functions are necessary for demodulation and decoding. In this paper, the approximation methods called Min and MinC are applied to demodulation and decoding together and their complexity and joint performance are analyzed.

• ETRI Journal
• /
• v.37 no.4
• /
• pp.727-735
• /
• 2015

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first-order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second-order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first-order Taylor approximation to suit higher-order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first-order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal-to-noise ratio conditions, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.10
• /
• pp.2303-2308
• /
• 2012

In this paper, we deal with the problem of scheduling parallel tasks with deadlines. Parallel tasks can be simultaneously executed on various machines and specially, we consider the malleable tasks, that is, the tasks whose execution time is given by a function of the number of machines on which they are executed. The goal of the problem is to maximize the throughput of tasks completed within their deadlines. This problem is well-known as NP-hard problem. Thus we will find an approximation algorithm, and its performance is compared with that of the optimal algorithm and analyzed by finding the approximation ratio. In particular, the algorithm has more resources, that is, more machines, than the optimal algorithm. This is called the resource augmentation analysis. We propose an algorithm to guarantee the approximation ratio of 3.67 using 1.5 times machines.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1994.10a
• /
• pp.133-140
• /
• 1994

In this paper, we have proposed a new method to determine the initial billet for the forged products using a function approximation in neural networks. the architecture of neural network is a three-layer neural network and the back propagation algorithm is employed to train the network. By utilizing the ability of function approximation of neural network, an optimal billet is determined by applying nonlinear mathematical relationship between shape ratio in the initial billet and the final products. A volume of incomplete filling in the die is measured by the rigid-plastic finite element method. The neural network is trained with the initial billet shape ratio and that of the un-filled volume. After learning, the system is able to predict the filling region which are exactly the same or slightly different to results of finite element method. It is found that the prediction of the filling shape ratio region can be made successfully and the finite element method results are represented better by the neural network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.405-409
• /
• 2009

In this paper, the effects of LLR (Log-Likelihood Ratio) approximation on LDPC (Low-Density Parity-Check) decoder performance are analyzed, and optimal design conditions of LDPC decoder are derived. The min-sum LDPC decoding algorithm which is based on an approximation of LLR sum-product algorithm is modeled and simulated by MATLAB, and it is analyzed that the effects of LLR approximation bit-width and maximum iteration cycles on the bit error rate (BER) performance of LDCP decoder. The parity check matrix for IEEE 802.11n standard which has block length of 1,944 bits and code rate of 1/2 is used, and AWGN channel with QPSK modulation is assumed. The simulation results show that optimal BER performance is achieved for 7 iteration cycles and LLR bit-width of (7,5).

• Journal of the Korean Data and Information Science Society
• /
• v.10 no.1
• /
• pp.29-36
• /
• 1999

We propose a new method of asymptotic inference on the odds ratio (or cross-product ratio) in $2{\times}2$ contingency table. Saddlepoint approximations to the conditional tail probability we used in this procedure. We assess the accuracy of the suggested method by comparing with the exact one. To obtain the exact values, we need very complicated calculations containing the cumulative probabilities of non-central hypergeometric distribution. The suggested method in this paper is very accurate even for small or moderate sample sizes as well as simple and easy to use. Example with a real data is also considered.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.11
• /
• pp.19-26
• /
• 2019

To construct buildings on limited land, the size of the building is important. The development process needs to be minimized because determining the size of a structurally safe building at the planning stage incurs considerable time and cost. This study proposes the Limit Slenderness Ratio Approximation Equation. This study examined an outrigger structure system among several systems proposed for controlling the lateral displacement in tall buildings. This study compared the Limit Slenderness Ratio Approximation Equation with the approximate equation by changing the variables of the building model, and examined the size of the building using the approximate Equation. As an analysis program, the MAIDAS architectural structural analysis program was used to conduct model-specific analysis. The appropriate scale of the building to minimize the error between the approximate value calculated by the Limit Slenderness Ratio Approximation Equation and the analysis result of the structural analysis program is as follows. As the number of outrigger installation increases, the error can be reduced; the ratio of the cores is reasonable, from 20% to 30%, and the arrangement of the column is suitable only for the outer column without an internal column.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2298-2304
• /
• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• Nuclear Engineering and Technology
• /
• v.20 no.3
• /
• pp.197-202
• /
• 1988

A finite slab approximation method was developed to predict the long-term teachability. It is based on the assumption that the diffusional characteristics of radionuclides in a waste matrix are not dependent on matrix geometry but dependent on volume to surface ratio V/S) and diffusion coefficient. Consequently it can be expressed as the solution of the equations obtained from a finite slab with an equal V/S ratio (imaginary diffusion length). The calculational results by the finite slab approximation method have been compared with the results obtained for finite cylinder and sphere with corresponding diffusional analysis. The results of this simple model have showed a good agreement and presented a general applicability for the long-term prediction of the radionuclide leaching behavior.