• Bulletin of the Korean Chemical Society
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• v.29 no.5
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• pp.1051-1054
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• 2008

The entropy production in a non-equilibrium state based on the reversible Oregonator model of the Belousov-Zhabotinskii (BZ) reaction system has been studied. The reaction affinity and the reaction rate for the individual steps have been calculated by varying the concentrations of key variables in the system. The result shows a linear relationship between the reaction affinity and the reaction rate in the given concentration range. However, the overall entropy calculated on the basic assumption that the entropy in a reaction system corresponds to the summation of a product of reaction affinity and reaction rate of individual steps shows a nonlinearity of the reaction system. The results well agrees with the fact that the entropy production is not linear or complicated function in a non-linear reaction system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.9
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• pp.671-678
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• 2012

The objective of this study is to analyze theoretically the performance of an open air-cycle refrigeration system in which environmental concerns increase. The pressure ratio of the external compressor and efficiencies of the components that compose of the system are selected as important parameters. As the pressure ratio of the external compressor increases, the pressure ratio of the ACM compressor is determined high, the refrigerating temperature and capacity increase, the COP decreases, and the total entropy production rate increases. The effect of heat exchanger effectiveness and turbine efficiency on the performance are greater than that of the ACM compressor efficiency. Also the performance of the air-cycle refrigeration system with two heat exchangers has been enhanced like high COP and low total entropy production rate, compared to the system with one heat exchanger.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.11
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• pp.504-511
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• 2014

The objective of this study is to theoretically analyze the performance of an open wet air-cycle refrigeration system, which nowadays is increasingly generating environmental concern. The temperature and relative humidity of the outside air are selected as the most important parameters. As the temperature and relative humidity of the outside air increase, the pressure ratio of the ACM compressor is determined to be nearly constant, the air temperature at the exit of the system increases, and the amount of condensed water, the cooling capacity, the COP, and the total entropy production rate increase overall. The effects of the effectiveness of the heat exchanger and the efficiency of the turbine on the performance are greater than that of the efficiency of the ACM compressor. Also, the performance of the wet air-cycle refrigeration system with two heat exchangers is enhanced, with a high COP and low total entropy production rate, compared to the system with a single heat exchanger.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1579-1602
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• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.365-371
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• 2013

Pine mushroom (Tricholoma matsutake) is one of the most profitable forest products in Korea. We postulated a hypothesis that a high rate of returns to labor input could make the harvest of pine mushroom off the optimum level. In the view of developing a sustainable production strategy for pine mushroom producers, production of pine mushroom collectors and pine mushroom growth function were estimated using maximum entropy method. Annual pine mushroom production and labor input were the data used in the estimation of production function of pine mushroom collectors and pine mushroom growth function. The level of sustainable maximum production derived from the estimated function. The production function estimated shows that production of pine mushroom is affected more by the resource of pine mushroom stocked in the forests than by labor that households put in forestry business. The production function of mushroom collectors and the estimated growth function indicate that pine mushroom harvests for the period of 2005-2011 did not reach the potential level of maximum sustainable production. Therefore, we suggest that pine mushroom harvest should be controlled until the resource stock of pine mushroom in the forests increases to the level of maximum sustainable production.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.1
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• pp.18-28
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• 2013

It was compared the estimated parameters by the surplus production from three different models, i.e., three types (Schaefer, Gulland, and Schnute) of the traditional surplus production models, a stock production model incorporating covariates (ASPIC) model and a maximum entropy (ME) model. We also evaluated the performance of models in the estimation of their parameters. The maximum sustainable yield (MSY) of small yellow croaker (Pseudosciaena polyactis) in Korean waters ranged from 35,061 metric tons (mt) by Gulland model to 44,844mt by ME model, and fishing effort at MSY ($f_{MSY}$) ranged from 262,188hauls by Schnute model to 355,200hauls by ME model. The lowest root mean square error (RMSE) for small yellow croaker was obtained from the Gulland surplus production model, while the highest RMSE was from Schnute model. However, the highest coefficient of determination ($R^2$) was from the ME model, but the ASPIC model yielded the lowest coefficient. On the other hand, the MSY of Kapenta (Limnothrissa miodon) ranged from 16,880 mt by ASPIC model to 25,373mt by ME model, and $f_{MSY}$, from 94,580hauls by ASPIC model to 225,490hauls by Schnute model. In this case, both the lowest root mean square error (RMSE) and the highest coefficient of determination ($R^2$) were obtained from the ME model, which showed relatively better fits of data to the model, indicating that the ME model is statistically more stable and robust than other models. Moreover, the ME model could provide additional ecologically useful parameters such as, biomass at MSY ($B_{MSY}$), carrying capacity of the population (K), catchability coefficient (q) and the intrinsic rate of population growth (r).

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.53-59
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• 2018

In this paper, we propose a sequence mining based manufacturing process using a decision model in cognitive factory. The proposed model is a method to increase the production efficiency by applying the sequence mining decision model in a small scale production process. The data appearing in the production process is composed of the input variables. And the output variable is composed the production rate and the defect rate per hour. We use the GSP algorithm and the REPTree algorithm to generate rules and models using the variables with high significance level through t-test. As a result, the defect rate are improved by 0.38% and the average hourly production rate was increased by 1.89. This has a meaning results for improving the production efficiency through data mining analysis in the small scale production of the cognitive factory.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.3
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• pp.217-223
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• 2018

Overfishing capacity has become a global issue due to over-exploitation of fisheries resources, which result from excessive fishing intensity since the 1980s. In the case of Korea, the fishing effort has been quantified and used as an quantified index of fishing intensity. Fisheries resources of coastal fisheries in the Korean waters of the East Sea tend to decrease productivity due to deterioration in the quality of ecosystem, which result from the excessive overfishing activities according to the development of fishing gear and engine performance of vessels. In order to manage sustainable and reasonable fisheries resources, it is important to understand the fluctuation of biomass and predict the future biomass. Therefore, in this study, we forecasted biomass in the Korean waters of the East Sea for the next two decades (2017~2036) according to the changes in fishing intensity using four fishing effort scenarios; $f_{current}$, $f_{PY}$, $0.5{\times}f_{current}$ and $1.5{\times}f_{current}$. For forecasting biomass in the Korean waters of the East Sea, parameters such as exploitable carrying capacity (ECC), intrinsic rate of natural increase (r) and catchability (q) estimated by maximum entropy (ME) model was utilized and logistic function was used. In addition, coefficient of variation (CV) by the Jackknife re-sampling method was used for estimation of coefficient of variation about exploitable carrying capacity ($CV_{ECC}$). As a result, future biomass can be fluctuated below the $B_{PY}$ level when the current level of fishing effort in 2016 maintains. The results of this study are expected to be utilized as useful data to suggest direction of establishment of fisheries resources management plan for sustainable use of fisheries resources in the future.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.513-525
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• 2017

In the estimation of the exploitable carrying capacity (ECC) in the Korean water of the East China Sea, two approaches, which are the ecosystem modeling method (EMM) and the holistic production method (HPM), were applied. The EMM is accomplished by Ecopath with Ecosim model using a number of ecological data and fishery catch for each species group, which was categorized by a self-organizing mapping (SOM) based on eight biological characteristics of species. In this method, the converged value during the Ecosim simulation by setting the instantaneous rate of fishing mortality (F) as zero was estimated as the ECC of each group. The HPM is to use surplus production models for estimateing ECC. The ECC estimates were 4.6 and 5.1 million mt (mmt) from EMM and HPM, respectiverly. The estimate from the EMM has a considerable uncertainty due to the lack of confidence in input ecological parameters, especially production/biomass ratio (P/B) and consumption/biomass ratio (Q/B). However, ECC from the HPM was estimated on the basis of relatively fewer assumptions and long time-series fishery data as input, so the estimate from the HPM is regarded as more reasonable estimate of ECC, although the ECC estimate could be considerd as a preliminary one. The quality of input data should be improved for the future study of the ECC to obtain more reliable estimate.