• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.641-644
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• 2016

Unlike wired networks, broadcasting in wireless networks can transmit data at once to several nodes with a single transmission. For omnidirectional broadcast to a node in wireless networks, all adjacent nodes receive the data at the same time. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem of minimizing the total transmit power on broadcasting in wireless networks. We apply two matrices to the proposed algorithm: one is a distance matrix that represents the distance between each node, the other is an adjacency matrix having the number of adjacency nodes. Among the nodes that receive the data, a node that has the greatest number of the adjacent node transmits data to neighbor preferential. We compare the performance of the proposed algorithm with random method through computer simulation in terms of transmitting power of nodes. Experiment results show that the proposed algorithm outperforms better than the random method.

• Composites Research
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• v.36 no.6
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• pp.416-421
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• 2023

Multifunctional composite materials capable of both load-carrying and energy functions are promising innovative candidates for the advancement of contemporary technologies owing to their relative feasibility, cost-effectiveness, and optimized performance. Carbon fiber (CF)-based structural batteries utilize the graphitic inherent structure to enable the employment of carbon fibers as electrodes, current collectors, and reinforcement, while the matrix system is an ion-conduction and load transfer medium. Although it is possible to enhance performance through the modification of constituents, there remains a need for a systematic design methodology scheme to streamline the commercialization of structural batteries. In this work, a bi-phasic epoxy-based ionic liquid (IL) modified structural battery electrolyte (SBE) was developed via thermally initiated phase separation. The polymer's morphological, mechanical, and electrochemical characteristics were studied. In addition, the interfacial shear strength (IFSS) between CF/SBE was investigated via microdroplet tests. The results accentuated the significance of considering IFSS and matrix plasticity in designing composite structural batteries. This approach is expected to lay the foundation for realizing smart structures with optimized performance while minimizing the need for extensive trial and error, by paving the way for a streamlined computational design scheme in the future.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.43-62
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• 2004

Conventionally the estimation method of the origin-destination Matrix has been developed by implementing the expansion of sampled data obtained from roadside interview and household travel survey. In the survey process, the bigger the sample size is, the higher the level of limitation, due to taking time for an error test for a cost and a time. Estimating the O-D matrix from observed traffic count data has been applied as methods of over-coming this limitation, and a gradient model is known as one of the most popular techniques. However, in case of the gradient model, although it may be capable of minimizing the error between the observed and estimated traffic volumes, a prior O-D matrix structure cannot maintained exactly. That is to say, unwanted changes may be occurred. For this reason, this study adopts a conjugate gradient algorithm to take into account two factors: estimation of the O-D matrix from the conjugate gradient algorithm while reflecting the prior O-D matrix structure maintained. This development of the O-D matrix estimation model is to minimize the error between observed and estimated traffic volumes. This study validates the model using the simple network, and then applies it to a large scale network. There are several findings through the tests. First, as the consequence of consistency, it is apparent that the upper level of this model plays a key role by the internal relationship with lower level. Secondly, as the respect of estimation precision, the estimation error is lied within the tolerance interval. Furthermore, the structure of the estimated O-D matrix has not changed too much, and even still has conserved some attributes.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.999-1011
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• 2013

In this research, we propose a document recommendation method which can find documents that are relatively important to a specific document based on citation information. The key idea is parameter tuning in the Neumann kernal which is an intermediate between a measure of importance (HITS) and of relatedness (co-citation). Our method properly selects the tuning parameter ${\gamma}$ in the Neumann kernal minimizing the prediction error in future citation. We also discuss some comutational issues needed for analysing large citation data. Finally, results of analyzing patents data from the US Patent Office are given.

• Steel and Composite Structures
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• v.27 no.1
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• pp.13-25
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• 2018

The main objective of this study is to develop a dual approach for geometrically nonlinear finite element analysis of plane truss structures. The geometric nonlinearity is considered using the Total Lagrangian formulation. The nonlinear solution is obtained by introducing and minimizing an objective function subjected to displacement-type constraints. The proposed method can fully trace the whole equilibrium path of geometrically nonlinear plane truss structures not only before the limit point but also after it. No stiffness matrix is used in the main approach and the solution is acquired only based on the direct classical stress-strain formulations. As a result, produced errors caused by linearization and approximation of the main equilibrium equation will be eliminated. The suggested algorithm can predict both pre- and post-buckling behavior of the steel plane truss structures as well as any arbitrary point of equilibrium path. In addition, an equilibrium path with multiple limit points and snap-back phenomenon can be followed in this approach. To demonstrate the accuracy, efficiency and robustness of the proposed procedure, numerical results of the suggested approach are compared with theoretical solution, modified arc-length method, and those of reported in the literature.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.38-49
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• 2016

This paper proposes a mathematical model-based solution for sourcing decisions with an objective of minimizing the manufacturer's total cost in the two-echelon supply chain with supply capacity risk. The risk impact is represented by uniform, beta, and triangular distributions. For the mathematical model, the probability vector of normal, risk, and recovery statuses are developed by using the status transition probability matrix and the equations for estimating the supply capacity under risk and recovery statuses are derived for each of the three probability distributions. Those formulas derived are validated using the sampling method. The results of the simulation study on the test problem show that the sourcing decisions using the proposed solution reduce the total cost by 1.6~3.7%, compared with the ones without a consideration of supply capacity risk. The total cost reduction increases approximately in a linear fashion as the probability of risk occurrence or reduction rate of supply capacity due to risk events is increased.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.37-48
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• 1995

This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1207-1212
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• 2013

Arithmetic operations over finite fields are widely used in coding theory and cryptography. In both of these applications, there is a need to design low complexity finite field arithmetic units. The complexity of such a unit largely depends on how the field elements are represented. Among them, representation of elements using a optimal normal basis is quite attractive. Using an algorithm minimizing the number of 1's of multiplication matrix, in this paper, we propose a multiplier which is time and area efficient over finite fields with optimal normal basis.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.98-107
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• 2008

The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.