• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

• Journal of the Korean Geotechnical Society
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• v.18 no.3
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• pp.33-41
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• 2002

Soil nailing type of retaining structures has been widely used in Korea far the purpose of the temporary and permanent support in excavations and slope stability. The important factors in application of soil nailing systems in urban excavation site nearby the existing structures are the displacement of the wall and tensile farce of the nails, etc. In this paper, the fled back analyses are carried out at 11 excavation sites to investigate the behavior of tensile farce of nails at stepwise excavation in the multi-layered strata including various rock layers. The results of the fled back analysis are less than about 50% of the measured ones. The distance of active zone by measurements are shown almost larger than that of fled back analysis when the distance of active Bone is defined from the surface of wall to the potential failure surface. And the results of fled back analysis are within the range proposed by the project CLOUTERRE and Cartier & Gigan (1983) which were 0.3$H_f$, and 0.5$H_f$, of the final excavation depth ($H_f$,) respectively, but the values of the measurement were larger than these values.

• Journal of Life Science
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• v.34 no.5
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• pp.304-312
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• 2024

This study was conducted to characterize strain Y10, isolated from discarded chicken feathers. Strain Y10 was identified as Bacillus amyloliquefaciens through phenotypic and 16S rRNA gene analysis. B. amyloliquefaciens Y10 exhibited plant growth-promoting activities, including the production of fungal cell-degrading enzymes (cellulase, lipase, protease, and pectinase), siderophores, ammonia, and indoleacetic acid. Furthermore, strain Y10 was able to inhibit the mycelial growth of several phytopathogenic fungi. When 0.1% sucrose as a carbon source and 0.05% casein as a nitrogen source were added to the basal medium, adjusted to pH 10, and cultured at 35℃, the degradation rate of chicken feathers by strain Y10 was about two times higher than that of the basal medium, with the feathers almost completely degraded in four days. Strain Y10 also degraded various keratin substrates, including duck feathers, wool, and human nails. It was confirmed that the feather hydrolyzates prepared using strain Y10 exhibited antioxidant activities, such as 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity (EC₅₀ = 0.38 mg/ml) and superoxide dismutase-like activity (EC₅₀ = 183.7 mg/ml). These results suggest that B. amyloliquefaciens Y10 is a potential candidate for the development of bioinoculants and feed additives applicable to the agricultural and livestock industries, as well as the microbiological treatment of keratin waste.