• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.65-68
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• 2000

It is well-known that the decision rule in the mini-mum mean-squares-error decision feedback equalizer(MMSE-DFE) is biased, and therefore suboptimum with respect to error probability. We present a new family of algorithms that solve the bias problem in the adaptive DFE. A novel constraint, called the constant-norm con-straint, is introduced unifying the quadratic constraint and the monic one. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of unbiased adaptive DFE. The simula-tion results demonstrate that the proposed method in-deed produce unbiased solution in the presence of noise while keeping very simple both in computation and im-plementation.

• IE interfaces
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• v.12 no.4
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• pp.617-624
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• 1999

In order to maximize an availability of machine and utilization of space, the parallel machines scheduling problem with space limit is frequently discussed in the industrial field. In this paper, we consider a scheduling problem for assembly machine in ship engine assembly shop. This paper considers the parallel machine scheduling problem in which n jobs having different release times, due dates and space limits are to be scheduled on m parallel machines. The objective function is to minimize the sum of earliness and tardiness. To solve this problem, a heuristic is developed. The proposed heuristic is divided into three modules hierarchically: job selection, machine selection and job sequencing, solution improvement. To illustrate its effectiveness, a proposed heuristic is evaluated with a large number of randomly generated test problems based on the field situation. Through the computational experiment, we determine the job selection rule that is suitable to the problem situation considered in this paper and show the effectiveness of our heuristic.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.954-961
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• 2018

In this paper, a chatbot for emotional stress recognition and management using rule-based method and NLP is designed and developed to tackle various emotional stresses of people through questionnaire. For this, Dialogflow as open chatbot development platform and Facebook messenger as chatting platform are used. We can build natural and resourceful conversational experiences through predefined questions by using powerful tools of Dialogflow, and can use developed chatbot on the Facebook page messenger. Developed chatbot perceives emotional stresses of user by user-input which is either text or choice of predefined answer. It also gives user questions according to the user's feeling, and assess the strength of the emotional stresses, and provide a solution to the user. Further research can improve the developed chatbot by using open Korean NLP library and database of emotions and stresses.

• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.8-14
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• 2016

The optimal estimation of a bearing only target tracking problem be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Recently, a nonlinear filtering algorithm using a direct quadrature method of moments in which the associated Fokker-Planck equation can be propagated efficiently and accurately was proposed. Although this approach has demonstrated its promising in the field of nonlinear filtering in several examples, the "degeneracy" phenomenon, similar to that which exists in a typical particle filter, occasionally appears because only the weights are updated in the modified Bayesian rule in this algorithm. Therefore, in this paper to enhance the performance, a more stable measurement update process based upon the update equation in the Extended Kalman filters and a more accurate initialization and re-sampling strategy for weight and abscissas are proposed. Simulations are used to show the effectiveness of the proposed filter and the obtained results are promising.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.342-349
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• 2011

This paper considers the inbound and outbound truck scheduling problem in a cross docking terminal. The unloading process from inbound trucks and loading process to outbound trucks are assumed to be performed within a time window. If some items are not able to be loaded to their scheduled outbound trucks within the time window, they are stored in the terminal and shipped using the truck visiting the next time window. The objective of this paper is to schedule inbound and outbound trucks to minimize the number of items unable to ship within the time window. A mathematical model for an optimal solution is derived, and a rule-based local search heuristic algorithm and genetic algorithm (GA) are proposed. The performance of the algorithms are evaluated using randomly generated several examples.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.789-795
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• 2000

Free-surface flows with an arbitrary deformation, induced by a submerged hydrofoil, are simulated numerically, considering two-fluid flows of both water and air. The computation is performed by a finite volume method using unstructured meshes and an interface capturing scheme to determine the shape of the free surface. The method uses control volumes with an arbitrary number of faces and allows cell wise local mesh refinement. The integration in space is of second order, based on midpoint rule integration and linear interpolation. The method is fully implicit and uses quadratic interpolation in time through three time levels. The linear equations are solved by conjugate gradient type solvers, and the non-linearity of equations is accounted for through Picard iterations. The solution method is of pressure-correction type and solves sequentially the linearized momentum equations, the continuity equation, the conservation equation of one species, and the equations for two turbulence quantities. Finally, a comparison is quantitatively made at the same speed between the computation and experiment in which the grid sensitivity is numerically checked.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.205-213
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• 2006

This paper considers testing for the ratio of two exponential means. We propose a solution based on a Bayesian decision rule to this problem in which no subjective input is considered. The criterion for testing is the Bayesian reference criterion (Bernardo, 1999). We derive the Bayesian reference criterion for testing the ratio of two exponential means. Simulation study and a real data example are provided.

• Computers and Concrete
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• v.22 no.2
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• pp.161-166
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• 2018

This paper deals with the instability analysis of concrete pipes conveying viscous fluid-nanoparticle mixture. The fluid is mixed by $AL_2O_3$ nanoparticles where the effective material properties of fluid are obtained by mixture rule. The applied force by the internal fluid is calculated by Navier-Stokes equation. The structure is simulated by classical cylindrical shell theory and using energy method and Hamilton's principle, the motion equations are derived. Based on Navier method, the critical fluid velocity of the structure is calculated and the effects of different parameters such as fluid velocity, volume percent of nanoparticle in fluid and geometrical parameters of the pipe are considered. The results present that with increasing the volume percent of nanoparticle in fluid, the critical fluid velocity increase.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1183-1188
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• 2004

The inverse heat conduction problem (IHCP) is a problem of estimating boundary condition from temperature measurement at one or more interior points. Neural networks are general information processing systems inspired by the connectionist theory of human brain. By properly training the network by the learning rule, the neural network method can handle many non-linear or other complex problems. In this work, neural network is applied to complicated inverse heat conduction problems. Efficiency of the procedure is enhanced by incorporating the radial basis functions (RBF). The RBF is trained faster than other neural network and can find smooth solution. In order to demonstrate the effectiveness of the current scheme, a typical one-dimensional IHCP is considered. At one surface, the temperature as well as the heat flux is known. The unknown temperature of interest is estimated on the other side of the slab. The results from the proposed method based on RBF neural network are compared with the conventional method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.04a
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• pp.71-78
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• 1997

The high precision analysis by the p-version of the finite element method are fairly well established as highly efficient method for linear elastic problems, especially in the presence of stress singularity. It has been noted that the merits of p-version are accuracy, modeling simplicity, robustness, and savings in user's and CPU time. However, little has been done to exploit their benefits in elasto-plastic analysis. In this paper, the p-version finite element model is proposed for the materially nonlinear analysis that is based on the incremental theory of plasticity, the associated flow rule, and von-Mises yield criteria. To obtain the solution of nonlinear equation, the Newton-Raphson method and initial stiffness method, etc are used. Several numerical examples are tested with the help of the square plates with cutout, the thick-walled cylinder under internal pressure, and the center cracked plate under tensile loading. Those results are compared with the there cal solutions and the numerical solutions of ADINA software.