• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.43-54
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• 2003

Due to insufficient available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem has become increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model, which does not satisfy the requirements ity. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then designing a sequential branch-and-bound algorithm that is made to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching for better assignments. The proposed algorithms perform well based on experimental results and they were applied to the Taiwan Cellular Cooperation (TCC) in ChungLi city to find better assignments for its network.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.648-649
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• 2011

This Paper presents an efficient approach for solving the economic dispatch (ED) problems with valve-point effects using an combination of particle swarm optimization and harmony search. To reduce a premature convergence effect of PSO algorithm, We proposed PSO-HS algorithm considering evolutionary using harmony search algorithm. To prove the ability of the PSO-HS in solving nonlinear optimization problems, ED problems with non-convex solution spaces are solved with three different approach(PSO, HS, combination of PSO and HS)

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3121-3142
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• 2017

We present a method for 3D shape reconstruction of inextensible deformable surfaces from a single image. The key of our approach is to represent the surface as a 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which are designed to retain original lengths of mesh edges. We use a closed-form method to generate an initial structure, then refine this structure by solving the LP problem iteratively. Compared with previous methods, ours neither involves smoothness constraints nor temporal consistency, which enables us to recover shapes of surfaces with various deformations from a single image. The robustness and accuracy of our approach are evaluated quantitatively on synthetic data and qualitatively on real data.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.127-138
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• 1993

The Production Switching Heuristic (PSH) develope dby Mellichamp and Love (1978) has been suggested as a more realistic, practical and intuitively appealing approach to aggregate production planning (APP). In this researh, PSH has been modified to present a more sophisticated open grid search procedure for solving the APP problem. The effectiveness of this approach has been demonstrated by determining a better near-optimala solution to the classic paint factory problem. The performance of the modified production switching heuristic is then compared in the context of the paint factory problem with results obtained by other prominent APP models including LDR, PPP, and PSH to conclude that the modified PSH offers a better minimum cost solution than the original PSH model.

• Industrial Engineering and Management Systems
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• v.8 no.1
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• pp.14-21
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• 2009

We formulate a mathematical model of remanufacturing system as multi-stage reverse Logistics Network Problem (mrLNP) with minimizing the total costs for reverse logistics shipping cost and inventory holding cost at disassembly centers and processing centers over finite planning horizons. For solving this problem, in the 1st and the 2nd stages, we propose a Genetic Algorithm (GA) with priority-based encoding method combined with a new crossover operator called as Weight Mapping Crossover (WMX). A heuristic approach is applied in the 3rd stage where parts are transported from some processing centers to one manufacturer. Computer simulations show the effectiveness and efficiency of our approach. In numerical experiments, the results of the proposed method are better than pnGA (Prufer number-based GA).

• Journal of Information Technology Applications and Management
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• v.13 no.2
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• pp.29-39
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• 2006

There has been a tremendous need for dual homing cell switch assignment problems where calling volume and patterns are different at different times of the day. This problem of assigning cells to switches in the planning phase of mobile networks consists in finding an assignment plan which minimizes the communication costs taking into account some constraints such as capacity of switches. This optimization problem is known to be difficult to solve, such that heuristic methods are usually utilized to find good solutions in a reasonable amount of time. In this paper, we propose an evolutionary approach, based on the genetic algorithm paradigm, for solving this problem. Simulation results confirm the appropriateness and effectiveness of this approach which yields solutions of good quality.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.175-178
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• 2003

In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.2
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• pp.144-150
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• 1989

The competitive power extraction problem in a linear n-port network consisting of resistances and independent sources with the same frequency is solved. For solving the problem, the definition of the two-port image impedances is extended to the n-port image impedances. In a competitive power extraction from an n-port network, the load resistances eventually approach the image resistances been found to be between the reciprocal of the short circuit conductance and the open circuit resistance.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1149-1158
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• 2020

NPF Islamic banking needs to be resolved because it affects banking performance in terms of income and the quality of its productive assets. This study aims to solve problems of non-performing financing and assess and analyze whether the implementation of the Islamic Humanity model can reduce the problem of financing at Bank Syariah Mandiri Indonesia. The study uses qualitative method with Miles and Huberman approach for analizing data through four steps which are; (a) data collection (b) data reduction (c) data display, and (d) conclusion drawing/verification. The results of the study found non performing financing can be reduced with using a new approach namely the Islamic Humanity Approach, which is an interaction between several aspects, namely (a) spiritual aspects, (b) economic aspects, (c) social aspects, and (d) justice aspects. The Islamic humanity model carried out in problem-solving activities at Bank Syariah Mandiri Indonesia includes a friendly approach, communication and deliberation in a family, respect for people, empathy, the concept of justice, and the concept of prayer. Islamic humanity approach shows success in reducing non-performing financing. The research concluded Islamic humanity as a new approach to reduce non-performing financing at Bank Syariah Mandiri Indonesia and it can be implemented to all Islamic banking in Indonesia.