• Environmental Analysis Health and Toxicology
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• v.28
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• pp.16.1-16.8
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• 2013

Objectives Fish vitellogenin (VTG) is produced in the female liver during oogenesis through the estradiol cycle and produced in the male liver by endocrine disrupting chemicals (EDCs) such as alkylphenols. In this study, we propose that the VTG concentration in the pale chub could be detected using monoclonal antibodies and polyclonal antibodies against vitellin (Vn) in a VTG enzyme-linked immunosorbent assay (ELISA) system. Methods Monoclonal antibodies and polyclonal antibodies were produced using the Vn extracted from the matured ovum of the ovary. The VTG was extracted from the plasma of the male pale chub. The Vn and VTG were confirmed by measuring the molecular weight of their proteins using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and the specificity of the antibodies was checked through western blotting methods. The assay system was validated with respect to optimal assay concentrations, specificity, recovery, and intra- and inter-assay variations. Results The Vn consisted of two protein bands with apparent molecular weights of 64 and 37 kDa. The SDS-PAGE indicated protein weights of 146 and 77 kDa in the VTG. The assay range was 15.6 ng/mL to 2,000 ng/mL, and the value of the intra- and inter-assay variations were within 10.0% and 14.7%, respectively. The recovery rate was $99.5{\pm}5.5%$. Conclusions A sandwich ELISA was developed that could be used to qualify the VTG of pale chub in screening for EDCs. Pale chub is an ideal species for observing estrogen activity in the environment because of its extensive habitat and extensive food chain. The ELISA developed here would be more favorable than those for other species for determining the effect of long-term food chain accumulation of EDCs in aquatic environments.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.149-154
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• 2017

The MCT-Adaboost algorithm chooses an optimal set of features in each rounds. On each round, it chooses the best feature by calculate minimizing error rate using feature index and MCT kernel distribution. The involved process of weak classification executed by a hard decision. This decision occurs some problems when it chooses ambiguous kernel feature. In this paper, we propose the modified MCT-Adaboost classification using soft decision. The typical MCT-Adaboost assigns a same initial weights to each datum. This is because, they assume that all information of database is blind. We assign different initial weights with our propose new algorithm using some statistical properties of involved features. In experimental results, we confirm that our method shows better performance than the traditional one.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.32 no.4
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• pp.66-73
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• 2000

Alkaline sulfite-anthraquinone(AS-AQ) cooking process has been applied to unground pine bark. The properties of the spent liquor such as molecular weight distributions, sulfonic equivalent weights, degree of sulfonation, phenolic hydroxyl groups and kaolin dispersing ability have been investigated to evaluate the possibility of using this liquor as concrete additives or binders. In the case of ground bark meal, more than 90% delignification was achieved at the optimal cooking conditions. However, applying these conditions on unground bark the delignification was slightly retarded. The decrease in the degree of delignification may be attributed to less penetration and diffusion of chemicals during the cooking of the bark. Increasing the cooking temperature only by $5^{\circ}C$ improved the delignification of the bark and about 90% delignification can be achieved. These results indicate that bark can be used successfully during AS-AQ cooking without any mechanical or physical pretreatment. The properties of lignin or polyphenol sulfonates in the spent liquor after AS-AQ cooking of the bark were compared with Sunflo-R, which is commercial lignosulfonate(CLS) prepared from wood. The weight average molecular weights(Mws) estimated by gel-filteration chromatography was found to be ranging from 1,200~1,800. These are considerably lower than those in CLS. Lignin or polyphenol sulfonates in the spent liquor of bark and CLS have similar degree of sulfonation, but the phenolic hydroxyl group was 1.8 times higher than CLS. Moreover, the dispersing abilities of the spent liquors were better than that of CLS, especially after 0.1% addition to kaolin suspension.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.739-748
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• 2012

In this paper we propose a mixed effects least squares support vector machine (LS-SVM) for the censored data which are observed from different groups. We use weights by which the randomly right censoring is taken into account in the nonlinear regression. The weights are formed with Kaplan-Meier estimates of censoring distribution. In the proposed model a random effects term representing inter-group variation is included. Furthermore generalized cross validation function is proposed for the selection of the optimal values of hyper-parameters. Experimental results are then presented which indicate the performance of the proposed LS-SVM by comparing with a standard LS-SVM for the censored data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1743-1750
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• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.04b
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• pp.39-40
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• 2001

This experiment was conducted to investigate the effect of root zone heating on the growth of cut minirose Rosa hybrida L. ′Little Marble′ in winter season. Effects of four different root zone temperatures of 16, 20, 24$^{\circ}C$ and non-heating control on the growth and productivity were compared. Harvested cut-flowers were measured for stem length, stem diameter, fresh and dry weights, numbers of leaves, stems and flowers, days to flower, and chlorophyll concentration. The results showed that mean height was the greatest at 16$^{\circ}C$. Days to flower was the shortest at 24$^{\circ}C$. Fresh and dry weights of top (shoot＋leaf＋flower), shoot and leaf were the greatest at 2$0^{\circ}C$. Stem and flower numbers were the greatest at 16$^{\circ}C$, but leaf number was the greatest at 2$0^{\circ}C$. Mean cut flower yield was the greatest at 16$^{\circ}C$. Chlorophyll concentration was slightly higher at 16$^{\circ}C$, but was not significantly different among the treatments. Stem diameter was the greatest at 2$0^{\circ}C$. Dry matter was the greatest at 24$^{\circ}C$. Total yield of cut rose stems increased with increasing temperature. Combined heating could save 24% in fuel cost as compared to the air heating alone. The results obtained suggested that optimal root zone temperature for the growth of cut rose "Little Marble" was 2$0^{\circ}C$, and the greenhouse heating energy can be saved by minimal air heating combined with root zone heating to 2$0^{\circ}C$.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.67-77
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• 2010

Growth of oil and chemical industries has been remarkable during recent years. Hazardous materials (Hazmat) make frequent use in the wide range of industries. It increases the frequency of Hazmat transport and it leads to increase the number of accidents. Optimal Hazmat routes can reduce damage. Thus, the objective of this study is to minimize the areas impacted by Hazmat accidents by adopting experts' opinion in planning the route. We calculated weights using AHP (Analytic Hierarchy Process) and deduced the best route by applying this weights. Results showed that in the case of shortest route versus weighted route, the percentage of population damage has been decreased by 33.4% in the comparison between shortest route and optimally weighted route. And the percentage of environmental damage also has been decreased by 21.8%. Social damage has been decreased by 1521.7%. In the case of none weighted route versus weighted route, the percentage of population damage has been decreased by 2.6% when we adopted weighted route. Consequently, the recommended route with weighted risk assessment avoids densely populated area comparing with none weighted route. Further research needs to be carried out in order to figure out the specific cost-effectiveness analysis applying the equal cost unit for each factor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Horticultural Science & Technology
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• v.34 no.3
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• pp.405-413
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• 2016

Quinoa (Chenopodium quinoa Willd.) is a plant native to the Andean region that has become increasing popular as a food source due to its high nutritional content. This study determined the optimal photoperiod, light intensity, and electrical conductivity (EC) of the nutrient solution for growth and yield of quinoa in a closed-type plant factory system. The photoperiod effects were first analyzed in a growth chamber using three different light cycles, 8/16, 14/10, and 16/8 hours (day/night). Further studies, performed in a closed-type plant factory system, evaluated nutrient solutions with EC (salinity) levels of 1.0, 2.0 or $3.0dS{\cdot}m^{-1}$. These experiments were assayed with two light intensities (120 and $143{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$) under a 12/12 and 14/10 hours (day/night) photoperiod. The plants grown under the 16/8 hours photoperiod did not flower, suggesting that a long-day photoperiod delays flowering and that quinoa is a short-day plant. Under a 12/12 h photoperiod, the best shoot yield (both fresh and dry weights) was observed at an EC of $2.0dS{\cdot}m^{-1}$ and a photosynthetic photon flux density (PPFD) of $120{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$. With a 14/10 h photoperiod, the shoot yield (both fresh and dry weights), plant height, leaf area, and light use efficiency were higher when grown with an EC of $2.0dS{\cdot}m^{-1}$ and a PPFD of $143{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$. Overall, the optimal conditions for producing quinoa as a leafy vegetable, in a closed-type plant factory system, were a 16/8 h (day/night) photoperiod with an EC of $2.0dS{\cdot}m^{-1}$ and a PPFD of $143{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$.

• Membrane and Water Treatment
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• v.14 no.2
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.