• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.210-213
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• 2001

This study presents an effective variable forgetting factor method based on fuzzy logic to suppress frequency droop in extended integral load frequency control. The performance of the extended integral control is greatly dependent on the decaying factor. For an optimal or near optimal performance, it is necessary that the decaying factor as well as the feedback gains should be changed very quickly in response to changes in the system dynamics. However, because of its time-varing characteristic, the optimal decaying factor is difficult to be selected analytically. By adopting fuzzy set theory, the decaying factor can be determined quickly to respond to the variation of the feedback signals. This study builds a fuzzy rule base with use of the change of frequency and its rate as inputs. The computer simulation has been conducted for the single machine system. The simulation results show that the proposed fuzzy 1o81c based controller yields more improved control performance than the conventional PI controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.345-349
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• 2000

This paper presents an extended integral control with the PI controller by introducing the delay and decaying factors. The extended integral control scheme is developed by substituting the proportional convolution integral control for the PI(Proportional Integral) control. So far, the integral part of PI controller produces a signal that is proportional to the time integral of the input signal to the controller. The steady-state operation points are affected forever by errors in the past due to the input signal containing the information of the error in the past. These phenomena may cause some disturbances for other control purposes related to the given PI control. Introduction of forgetting factors to the error in the past can resolve the disturbance problems. Various forgetting factors are developed using the delay elements, the decaying factors, and the combination of the delay and decaying factors. The proposed various extended integral control schemes can be applicable to the corresponding PI control designs in which the error in the past may badly affect the current steady-state operation points and may cause some disturbances for other control purposes.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.270-276
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• 2020

In this paper, we analyze the buyer's joint pricing and lot-sizing model in a two-stage supply chain consisting of the supplier, the buyer and the customer. It is assumed that the supplier will permit a certain fixed period for settling the amount the buyer owes to him for the items supplied in order to stimulate the demand for the product. Generally, credit transactions would have a positive effect to the buyer. The availability of credit transactions from the supplier effectively reduces the cost of holding stocks for the buyer and therefore, the buyer has a lot of price options to choose his sales price for a customer in anticipation of increased the customer's demand and, as a result, it will appear to increase the buyer's inventory levels. On the other hand, in the case of decaying products in which their utility decay over time, the decaying rate with time may be expected to reduce inventory levels. In this regard, we need to analyze how much the length of credit period and the decaying rate affect the buyer's pricing and lot-sizing policy. For the analysis, we consider the situation where the customer's demand is represented as a linearly decreasing function of the buyer's sales price. From this perspective, we formulate the buyer's annual net profit and analyze the effect of the length of credit period and decaying rate of the product on the buyer's inventory policy numerically.

• Journal of the Korean Wood Science and Technology
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• v.24 no.1
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• pp.48-53
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• 1996

Brown rot fungus, Tyromyces palustris, has been reported to cause the loss of strength accelerated by oxalate, a non-enzymatic low molecular weight acid, with minute weight loss of decaying wood in early stage. The production of oxalate in relation to wood decaying and the presence of oxaloacetase. an oxalate producing enzyme, were identified during the process. Tyromyces palustris produced the largest amount of oxalate among brown rot fungi. In order to find out the cleavage of pulp fiber, we submerged pulp fiber in oxalate solution and the results showed that the number of short pulp fiber was highly increased, compared with control solution. The pH of decaying wood was decreased to 1.77 which was close to that of saturated oxalate solution, pH 1.2, Thus, the oxalate was thought to be accumulated in the decaying wood, The oxaloacetase which accelerates production of oxalate was derived from fungus, and the production of oxalate by the enzyme was determined by using on UV/Vis spectrophotometer. Therefore, the oxalate was found to be produced by oxaloacetase during decay. The oxalate may cause the acid-hydrolysis of cellulose and hemicellulose. The oxalate was thought to reduce the degree of polymerization and increase the enzyme activity, which resulted in rapid loss of strength in early stage-an identical feature of brown rot fungus.

• Journal of the Korean Wood Science and Technology
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• v.48 no.1
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• pp.50-60
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• 2020

Fungi are wood-decaying organisms, and this is an important trait that should be considered in wood utilization. When fungi attack wood, it decreases the quality of the wood. The use of metal screws has become an important part of woodworking. The ability of fungi to decay wood and damage metal screws that are embedded into wood is varied. In this study, eight fungal species were evaluated with respect to their ability to decay Parashorea smythiesii and P. tomentella wood. In addition, the effect of fungi on corroding metal screws was determined using the Kolle flask method. The evaluation showed that the fungal species Schizophyllum commune, Pycnoporus sanguineus, and Polyporus arcularius were highly capable of decaying Parashorea spp. woods. The greatest wood weight loss occurred with the heartwood of P. tomentella exposed to S. commune. Based on the classification of wood resistance against fungal attack, the two Parashorea spp. were classified as moderately resistant woods (class III). Schizophyllum commune was classified as highly capable of decaying wood that was embedded with metal screws and was highly capable of corroding metal screws placed in fungi-culture media. The greatest weight of rust powder formed because of screw corrosion was obtained from screw-embedded wood exposed to S. commune. Additionally, the most severe corrosion of metal screws that were embedded into woods was caused by the activities of P. arcularius. Moreover, the average weight loss of screw-embedded wood was greater than that of unscrewed wood.

• Korean Journal of Mathematics
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• v.21 no.2
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• pp.117-124
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• 2013

We investigate the existence of weak solutions for the biharmonic boundary value problem with nonlinear term decaying at the origin. We get a theorem which shows the existence of nontrivial solutions for the biharmonic boundary value problem with nonlinear term decaying at the origin. We obtain this result by reducing the biharmonic problem with nonlinear term to the biharmonic problem with bounded nonlinear term and then approaching the variational method and using the mountain pass geometry for the reduced biharmonic problem with bounded nonlinear term.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.39-41
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• 2003

n this paper, direct numerical simulation of decaying compressible turbulence with passive scalar is performed by using 7th order upwind difference scheme or 8th order group velocity control scheme. The start Reynolds number (defined by Taylor scale) is 72 and turbulent Mach numbers are 0.2-0.9. The Schmidt numbers of passive scalar are 2-10. The Batchelor k-1 range are found in scalar spectra, and the high wavenumber spectra decays faster with increasing turbulent Mach number. The extend self-similarity (ESS) is found in the passive scalar in compressible turbulence.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.315-319
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• 2015

We consider a late decaying dark matter model in which cold dark matter begins to decay into relativistic particles at a recent epoch ($z{\leqslant}1$). A complete set of Boltzmann equations for dark matter and other relevant particles particles is derived, which is necessary to calculate the evolution of the energy density and density perturbations. We show that the large entropy production and associated bulk viscosity from such decays leads to a recently accelerating cosmology consistent with observations. We determine the constraints on the decaying dark matter model with bulk viscosity by using a MCMC method combined with observational data of the CMB and type Ia supernovae.

• East Asian Economic Review
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• v.25 no.4
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.594-596
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• 2021

Future healthcare systems will heavily rely on ill-labeled data due to scarcity of the experts who are trained enough to label the data. Considering the contamination of the dataset, it is not desirable to make the neural network being overconfident to the dataset, but rather giving them some margins for the prediction is preferable. In this paper, we propose a novel epoch-wise decaying label-smoothing function to alleviate the model over-confidency, and it outperforms the neural network trained with conventional cross entropy by 6.0%.