• Interaction and multiscale mechanics
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• v.1 no.2
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• pp.211-230
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• 2008

Owing to the growing size of the eigenvalue problem and the growing number of eigenvalues desired, solution methods of iterative nature are becoming more popular than ever, which however suffer from low efficiency and lack of proper convergence criteria. In this paper, three efficient iterative eigenvalue algorithms are considered, i.e., subspace iteration method, iterative Ritz vector method and iterative Lanczos method based on the cell sparse fast solver and loop-unrolling. They are examined under the mode error criterion, i.e., the ratio of the out-of-balance nodal forces and the maximum elastic nodal point forces. Averagely speaking, the iterative Ritz vector method is the most efficient one among the three. Based on the mode error convergence criteria, the eigenvalue solvers are shown to be more stable than those based on eigenvalues only. Compared with ANSYS's subspace iteration and block Lanczos approaches, the subspace iteration presented here appears to be more efficient, while the Lanczos approach has roughly equal efficiency. The methods proposed are robust and efficient. Large size tests show that the improvement in terms of CPU time and storage is tremendous. Also reported is an aggressive shifting technique for the subspace iteration method, based on the mode error convergence criteria. A backward technique is introduced when the shift is not located in the right region. The efficiency of such a technique was demonstrated in the numerical tests.

• Macromolecular Research
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• v.14 no.3
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• pp.272-286
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• 2006

Dendritic hyperbranched poly(methyl methacrylate)s (PMMA)s, whose branched architectures resemble the 'dendron' part(s) of dendrimer, were synthesized by an iterative methodology consisting of two reactions in each iteration process: (a) a coupling reaction of u-functionalized, living, anionic PMMA having two tert-butyldimethylsilyloxymethylphenyl(SMP) groups with benzyl bromide(BnBr)-chain-end-functionalized PMMA, and (b) a transformation reaction of the introduced SMP groups into BnBr functionalities. These two reactions, (a) and (b), were repeated three times to afford a series of dendron-like, hyperbranched (PMMA)s up to third generation. Three dendron-like, hyperbranched (PMMA)s different in branched architecture were also synthesized by the same iterative methodology using a low molecular weight, functionalized 1,1-diphenylalkyl anion prepared from sec-BuLi and 1,1-bis(3-tert-butyldime-thylsilyloxymethylphenyl)ethylene in the reaction step (b) in each iterative process. Furthermore, structurally similar, dendron-like, hyperbranched block copolymers could be successfully synthesized by the iterative methodology using $\alpha$-functionalized, living, anionic poly(2-(perfluorobutyl) ethyl methacrylate) (PRfMA) in addition to $\alpha$-functionalized, living PMMA. Accordingly, the resulting block copolymers were comprised of both PMMA and PRfMA segments with different sequential orders. After the block copolymers were cast into films and annealed, their surface structures were characterized by angle-dependent XPS and contact angle measurements. All three samples showed significant segregation and enrichment of PRfMA segments at the surfaces.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.43-51
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• 1995

For the stress-strengh function, hierarchical Bayes estimations considered under squared error loss and entropy loss. In particular, the desired marginal postrior densities ate obtained via Gibbs sampler, an iterative Monte Carlo method, and Normal approximation (by Delta method). A simulation is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.373-376
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• 2006

In general, there are three kinds of methods in analyzing dynamic robust design experiment: loss model approach, response function approach, and response model approach. In this talk, we review the three modeling approaches in terms of several criteria in comparison. This talk also generalizes the response model approach based on a generalized linear model. We develop a generalized two-step optimization procedure to substantially reduce the process variance by dampening the effect of both explicit and hidden noise variables. The proposed method provides more reliable results through iterative modeling of the residuals from the fitted response model. The method is compared with three existing approaches in practical examples.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• Korean Management Science Review
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• v.24 no.1
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• pp.91-111
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• 2007

In this paper an effective two-phase approach adopting modified p-median mathematical model is proposed for grouping machines and parts in cellular manufacturing(CM). Unlike the conventional methods allowing machines and parts to be improperly assigned to cells and families, the proposed approach seeks to find the proper block diagonal solution where all the machines and parts are properly assigned to their most associated cells and families in term of the actual machine processing and part moves. Phase 1 uses the modified p-median formulation adopting new inter-machine similarity coefficient based on the non-binary production data-based part-machine incidence matrix(PMIM) that reflects both the operation sequences and production volumes for the parts to find machine cells. Phase 2 apollos iterative reassignment procedure to minimize inter-cell part moves and maximize within-cell machine utilization by reassigning improperly assigned machines and parts to their most associated cells and families. Computational experience with the data sets available on literature shows the proposed approach yields good-quality proper block diagonal solution.

• Proceedings of the KSRS Conference
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• v.1
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• pp.500-503
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• 2006

To adjust the discrepancy between Light Detection and Ranging (LIDAR) strips, previous researches generally have been conducted using conjugate features, which are called feature-based approaches. However, irrespective of the type of features used, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of employed methods to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these drawbacks, this paper presents a methodology using area-based algorithms. This approach is based on the scheme that discrepancies make complex the local height variations of LIDAR data whithin overlapping area. This scheme can be helpful to determine an appropriate transformation for adjustment in the way that minimizes the geographical complexity. During the process, the contour tree (CT) was used to represent the geological characteristics of LIDAR points in overlapping area and the Iterative Closest Points (ICP) algorithm was applied to automatically determine parameters of transformation. After transformation, discrepancies were measured again and the results were evaluated statistically. This research provides a robust methodology without restrictions involved in methods that employ conjugate features. Our method also makes the overall adjustment process generally applicable and automated.

• Environmental and Resource Economics Review
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• v.22 no.3
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• pp.499-520
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• 2013

This study proposes an iterative approach to the estimation of the marginal abatement costs of undesirable outputs by computing the slope of the efficient production possibilities frontier on the basis of the efficient projection points generated by the directional output distance function approach due to Fare et al. (2005) based on duality theory. In case of the latter methodology, the estimated marginal abatement costs differ significantly depending on the choice of the directional output vector. In addition, depending on the curvature of the underlying PPF the efficient projection points may be located at a significant distance away from their actually observed counterparts. While it would be more logical to estimate marginal abatement costs as a PPF slope at a point corresponding to the actually observed emissions level, the methodology based on duality theory is likely to produce unstable results due to the problems associated with applying the theorem of implicit function differentiation. Since our methodology is not based on duality theory, our results are immune to both of these problems. We apply our methodology to a sample of Western European countries for the period of 1995-2011 to illustrate our approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1148-1161
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• 2017

The success of a business process management system stands or falls on the quality of the business processes. Many experiments therefore have been devoting considerable attention to the modeling and analysis of business processes in process-centered organizations. One of those experiments is to apply the probabilistic theories to the analytical evaluations of business process models in order to improve their qualities. In this paper, we excogitate a conceptual way of applying a probability theory of proportions into modeling business processes. There are three types of routing patterns such as sequential, disjunctive, conjunctive and iterative routing patterns in modeling business processes, into which the proportion theory is applicable. This paper focuses on applying the proportion theory to the disjunctive routing patterns, in particular, and formally named proportional information control net that is the formal representation of a corresponding business process model. In this paper, we propose a conceptual approach to discover a proportional information control net from the enactment event histories of the corresponding business process, and describe the details of a series of procedural frameworks and operational mechanisms formally and graphically supporting the proposed approach. We strongly believe that the conceptual approach with the proportional information control net ought to be very useful to improve the quality of business processes by adapting to the reengineering and redesigning the corresponding business processes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.57-66
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• 1994

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algorithms need a special perfect position sensor or a priori information about error sources, while ours does not. to our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterativelearning algorithm does not have the drawbacks of the existing interativelearning control theories. To be more specivic, our algorithm learns an uncertain function itself rather than its special time-trajectory and does not reuquest the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.