• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1211-1218
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• 2018

Within the framework of the modified factorization method, we solve the $Schr{\ddot{o}}dinger$ equation with the modified Yukawa potential. The energy spectrum is obtained using the Pekeris approximation scheme for the centrifugal term. The thermodynamic properties, including the vibrational partition function, vibrational mean energy, vibrational mean free energy, vibrational specific heat capacity and vibrational entropy, are calculated. As a special case, we compare our result with that work of Dong [Int. J. Quant. Chem. 107, 366 (2007)] and find good agreement.

• Bulletin of the Korean Chemical Society
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• v.6 no.6
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• pp.337-343
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• 1985

A statistical mechanical approach to elucidate the solvent effects on the high polymer solutions has been carried out on the basis of the simple model of liquids improved by Pak. In our works, the partition function of the polymer solutions is formulated by the lattice model and our simple treatment of liquid structures. For the ideal polymer solutions proposed by Flory, thermodynamic functions of the polymer solutions are obtained and equations of mixing properties and partial molar quantities are derived from the presented partition function of the polymer solutions. Partial molar quantities are calculated for the rubber solutions in carbon disulfide, benzene and carbon tetrachloride. Comparisons have been made between our equations and those of Flory's original paper for partial molar properties of the rubber-benzene system. Comparing the experimental data of the osmotic pressure of polystyrene-cyclohexane system with our calculated values and those of Flory's, our values fit to the agreeable degrees better than those of Flory's.

• Bulletin of the Korean Mathematical Society
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• v.60 no.4
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• pp.1017-1024
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• 2023

A celebrated result in the study of integer partitions is the identity due to Lehmer whereby the number of partitions of n with an even number of even parts minus the number of partitions of n with an odd number of even parts equals the number of partitions of n into distinct odd parts. Inspired by Lehmer's identity, we prove explicit formulas for evaluating generating functions for sequences that enumerate integer partitions of fixed width with an even/odd number of even parts. We introduce a technique for decomposing the even entries of a partition in such a way so as to evaluate, using a finite sum over q-binomial coefficients, the generating function for the sequence of partitions with an even number of even parts of fixed, odd width, and similarly for the other families of fixed-width partitions that we introduce.

• 연구논문집
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• s.28
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• pp.123-135
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• 1998

A shape function for element free Galerkin method is carved from Shepard interpolant of singular weight and consistency condition. Thus present shape function is an interpolation and has no singularities. The shape function is applied to cantilever bending problems and gives good results in comparison with beam theory. Finally it is shown that the coupling with finite element method is made easily without any additional treaties.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.1025-1032
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• 1990

We proposed a neural network energy function for the optimal graph partitioning and its optimization method using Boltzmann Machine. We composed a Boltzmann Machine with the proposed neural network energy function, and the simulation results show that we can obtain an optimal solution with the energy function parameters of A=50, B=5, c=14 and D=10, at the Boltzmann Machine parameters of To=80 and \ulcorner0.07 for a 6-node 3-partition problem. As a result, the proposed energy function and optimization parameters are proved to be feasible for the optimal graph partitioning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.861-872
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• 2006

The element free Galerkin method is extended by the local partition of unity method to model the cohesive cracks in two dimensional continuum. The shape function of a particle whose domain of influence is completely cut by a crack is enriched by the step enrichment function. If the domain of influence contains a crack tip inside, it is enriched by a branch enrichment function which does not have the LEFM stress singularity. The discrete equations are obtained directly from the standard Galerkin method since the enrichment is only for the displacement field, which satisfies the local partition of unity. Because only particles whose domains of influence are influenced by a crack are enriched, the system matrix is still sparse so that the increase of the computational cost is minimized. The condition for crack growth in dynamic problems is obtained from the material instability; when the acoustic tensor loses the positive definiteness, a cohesive crack is inserted to the point so as to change the continuum to a discontiuum. The crack speed is naturally obtained from the criterion. It is found that this method is more accurate and converges faster than the classical meshless methods which are based on the visibility concept. In this paper, several well-known static and dynamic problems were solved to verify the method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5464-5484
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• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.657-659
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• 1998

In order to optimize fuzzy modeling of nonlinear system, we proposed a optimal fuzzy model according to the characteristic of I/O relationship, HCM method, the genetic algorithm, and the objective function with weighting factor. A conventional fuzzy model has difficulty in definition of membership function. In order to solve its problem, the premise structure of the proposed fuzzy model is selected by both the partition of input space and the analysis of input-output relationship using the clustering algorithm. The premise parameters of the fuzzy model are optimized respectively by the genetic algorithm and the consequence parameters of the fuzzy model are identified by the standard least square method. Also, the objective function with weighting factor is proposed to achieve a balance between the performance results for the training and testing data.

• Korean Journal of Mathematics
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• v.22 no.2
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• pp.325-337
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• 2014

In 1911 Schur[6] derived degree and character formulas for projective representations of the symmetric groups remarkably similar to the corresponding formulas for ordinary representations. Morris[3] derived a recurrence for evaluation of spin characters and Stembridge[8] gave a combinatorial reformulation for Morris' recurrence. In this paper we give combinatorial interpretations for the orthogonality relations of spin characters based on Stembridge's combinatorial reformulation for Morris' rule.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.