• Korean Architects
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• s.631
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• pp.138-139
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• 2021

• Korean Architects
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• s.635
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• pp.118-119
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• 2022

• Korean Architects
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• s.647
• /
• pp.124-125
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• 2023

• Korean Architects
• /
• s.650
• /
• pp.124-127
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• 2023

• Korean Architects
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• s.661
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• pp.162-163
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• 2024

• Korean Circulation Journal
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• v.54 no.8
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• pp.466-467
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• 2024

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1-4
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• 2004

The dual-mode strategy has been adopted in many constrained MPC methods. The size of stabilizable regions of states of MPC methods depends on the size of underlying feasible and positively invariant set and number of control moves. These results, however, could be conservative because the definition of positive invariance does not allow temporal leave of states from the set, In this paper, a concept of periodic invariance is introduced in which states are allowed to leave a set temporarily but return into the set in finite steps. The periodic invariance can defined with respect to sets of different state feedback gains. These facts make it possible for the periodically invariant sets to considerably larger than ordinary invariant sets. The periodic invariance can be defined for systems with polyhedral model uncertainties. We derive a MPC method based on these periodically invariant sets. Some numerical examples are given to show that the use of periodic invariance yields considerably larger stabilizable sets than the case of using ordinary invariance.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.549-557
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• 2016

In this paper we propose multiclassification method for large data sets by ensembling least squares support vector machines (LS-SVM) with principal components instead of raw input vector. We use the revised one-vs-all method for multiclassification, which is one of voting scheme based on combining several binary classifications. The revised one-vs-all method is performed by using the hat matrix of LS-SVM ensemble, which is obtained by ensembling LS-SVMs trained using each random sample from the whole large training data. The leave-one-out cross validation (CV) function is used for the optimal values of hyper-parameters which affect the performance of multiclass LS-SVM ensemble. We present the generalized cross validation function to reduce computational burden of leave-one-out CV functions. Experimental results from real data sets are then obtained to illustrate the performance of the proposed multiclass LS-SVM ensemble.

• Journal of the Korean Society of Tobacco Science
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• v.10 no.1
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• pp.27-36
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• 1988

This experiment was tarried out to investigate the effect of plant spacing and amount of side dressing on the yield, quality and protein pattern in burley 21 and KB 101. The results obtained were summarized as follow. 1 Yield and alkaloid content are increased In high plant population and side dressing. 2 . Quality is not affected by plant population and side dressing. 3 . Nitrogen content is decreased by late growing stage. 4. The bands of burley 21 seed are fewer than KB 101 seed bands in protein pattern. 5. In protein pattern, the bands of KB 101s leave are thicker than that of burley21s leave between 18,000∼14,000 of molecular weight.

• Journal of Distribution Research
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• v.2 no.1
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• pp.115-141
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• 1997

This study examines the effects of economic and relational dimensions of supplier-distributor relationship on distributors intents to leave. A survey of 121 computer hardware distributors revealed that distributors commitment to the relationship and their transaction-specific investment would decrease directly the level of withdrawal intention. Other relational dimensions such as the procedural and distributive fairness, the morality of aspiration, and economic dimensions such as the transaction-specific investment made by the supplier and distributors expectations fo future performance increase indirectly the level of withdrawal intension via affecting either trust or commitment. The present study also found that perceived uncertainty and relative dependence might moderate the effects the economic and relational dimensions on distributors intents to leave. Relational dimensions, when compared to economic dimensions, tend to have stronger impacts on withdrawal intentions under high levels of uncertainty and relative dependence.