• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5628-5636
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• 2012

Effective drying method of sewage sludge is researched in this study. To dry the sludge, chain crusher flash dryer was adopted to remove moisture content in the cell which is mostly responsible for the sludge moisture content. And Pilot plant experiment was conducted in real life sewage treatment plant to study effect and characteristics of operating conditions. Operating variables include sludge feeding rate, rotational speed of chain, process temperature and feed moisture content. As rotational speed of chain increased, product yield of sludge increased, and the performance of the testing system increased. And, as process temperature increased, the sludge drying efficiency increased. It is found that optimum feed moisture content is at 60% which shows the maximum sludge product yield and about 10 moisture content(%) of sludge product. Sludge feed rate showed optimal value, and when the sludge feed rate is exceeded, sludge product yield did not increased but the amount of residue increased. Pilot plant experiment results are as follow. The optimal condition for the rotational speed of chain 1600rpm(max. speed), final sludge discharge temperature $80^{\circ}C$, feed moisture content 60%, and feed rate 60kg/h. When the plant was operated at the optimal conditions, the final product showed fairly good results such as sludge product yield 85.5%, moisture content 11.0% and sludge drying efficiency 81.7%.

• Journal of the Korea Concrete Institute
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• v.16 no.6 s.84
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• pp.767-776
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• 2004

Polymer concrete shows excellent mechanical properties and chemical resistance compared with conventional normal cement concrete. The polymer concrete is drawing a strong interest as high-performance materials in the construction industry. Resins using recycled PET offer the possibility of a lower source cost of materials for making useful polymer concrete products. Also the recycling of PET in polymer concrete would help solve some of the solid waste problems posed by plastics and save energy. The purposed of this paper is to propose the model for the stress-strain relation of recycled-PET polymer concrete at monotonic uniaxial compression and is to investigate for the stress-strain behavior characteristics of recycled-PET polymer concrete with different variables(strength, resin contents, curing conditions, addition of silane and ages). The maximum stress and strain of recycled-PET polymer concrete was found to increase with an increase in resin content, however, it decreased beyond a particular level of resin content. A ascending and descending branch of stress-strain curve represented more sharply at high temperature curing more than normal temperature curing. Addition of silane increases compressive strength and postpeak ductility. In addition, results show that the proposed model accurately predicts the stress-strain relation of recycled-PET polymer concrete

• Journal of Environmental Science International
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• v.23 no.11
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• pp.1827-1833
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• 2014

This study has been carried out to present the valuation system of soil carbon sequestration potentials of soil in accordance with the new climate change scenarios(RCP). For that, by analyzing variation of soil carbon of the each type of agricultural land use, it aims to develop technology to increase the amount of carbon emissions and sequestration. Among the factors which affects the estimation of determining the soil carbon model and influence power after the measurement on soil organic carbon, under the center of a causal relationship between the explanatory variables this study were investigated. Chemical fertilizers (NPK) decreased with increasing the amount of soil organic carbon and as with the first experimental results, when cultivating rice than pepper, the fact that soil organic carbon content increased has been found out. The higher the carbon dioxide concentration, the higher the amount of organic carbon in the soil and this result is reliable under a 10% significance level. On the other hand, soil organic carbon, humus carbon and hot water extractable carbon has been found out that was not affected the soils depth, sames as the result of the first year. The higher concentration of carbon dioxide, the higher carbon content of humus and hot water extractable carbon content. According to IPCC 2006 Guidelines and the new climate change scenario RCP 4.5 and the measurement results of the total amount of soil organic carbon to the crops due to abnormal climate weather, 1% increase in atmospheric carbon dioxide concentration was found to be small when compared to the growing rate of increasing 0.01058% of organic carbon in the soil.

• Journal of the Korean Society of Food Science and Nutrition
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• v.29 no.6
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• pp.1090-1097
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• 2000

The aim of this study was to investigate the relationships among energy intakes, macronutrient intakes, macronutrient compositions, anthropometric and biochemical variables in natural environment of free-living female college students. The daily energy and macronutricnt intakes were analyzed by means of 3- week dictary records. The waist circumference and insulin level were best anthropometric and bio-chemical correlates with the energy, carbohydrate and protein intakes respectively. However, there were no relationships between waist circumference and insulin verse macronutrient compositions that macro-nutrient intakes were expressed as by the percentage of daily encrgy intakes. There were no relationships between BWI, weight, perccnt body fat and fat mass vs. energy and macronutrient intakes. However, BMI was positively related to the percentage of energy from fat and inversely related to the percentage of energy from carbohydrate in their habitual diet. Triglyceride was negatively correlated to the per-centage of energy from fat and fat intakes. Significant positive correlation was also observed bctween the percentage of energy from protein and HSL-cholcsterol.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1157-1168
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• 2012

In this study, we assess changes in water quality trends over time based on certain control measurements in order to identify and analyze the cause of the trend in water quality. The current water pollution in the Nakdong River was analyzed, as it suggests that the significant changes in water quality have occurred in between 2006 and 2010. Based on monthly average data, we have examined for trends of the Nakdong River watershed in water temperature, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP). Moreover, we have investigated seasonal variation of water quality of sites within the Nakdong River Basin by implementing further analyses such as, Correlation Coefficient, Regression Analysis, Hierarchical Clustering Method, and Time Series Analysis on SPSS. Geology and topography of the watershed, controlled by various conditions such as, climate, vegetation, topography, soil, and rain medium, have been affected by the non-homogeneity. Our study suggests that such variables could possibly cause eutrophication problems in the river. One possible way to overcome this particular problem is to lay up a ship on the river by increasing the nasal flow measurement of the Nakdong River during rainy season. Moreover, the water management requires arranging the measurement of the flow in order to secure the river while the numerous construction projects need to be continuously observed. However, the water is not flowing tributary of the reason for the timing to be flowing in a natural state of river water and industrial water intake because agriculture. Therefore, ongoing research is needed in addition to configuration of all observations.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.7
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• pp.1139-1146
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• 2004

The purpose of this study was to investigate the possibility of Meles meles oil as an functional resource. To assess the effects of Meles meles oil in 25 non-insulin dependent diabetes mellitus (DM) persons, we examined changes of fat intake level, hematological and chemical variables, serum DM indices and lipid contents during the Meles meles oil supplementation. Polyunsaturated fatty acid and $\omega$3 fatty acid intake were significantly increased by Meles meles oil intakes. The levels of LDL-cholesterol and triglyceride were significantly decreased while HDL-cholesterol was significantly increased. Iron status improved during Meles meles oil intakes. These results show that modest dose of Meles meles oil supplementation can decrease serum triglyceride, cholesterol level without any changes in blood glucose level in NIDDM patients. These results indicated that Meles meles oil diet is effective therapeutic regimen for the control of metabolic derangements in diabetes mellitus. Also, these results imply that Meles meles oil can be used as possible food resources and functional food materials. However, large amounts of Meles meles oil should be used cautiously in NIDDM patients.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• Journal of the Mineralogical Society of Korea
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• v.16 no.1
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• pp.1-17
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• 2003

The chemical composition of the arsenopyrite Ib adjoining“triple mutual contact”arsenopyrite + pyrite + hexagonal pyrrhotite may serve as a useful geothermometer in Stage II. In this study it corresponds to temperature T=33$0^{\circ}C$ and f( $S_2$)=10$^{-9.5}$ atm. And the pyrite-hexagonal pyrrhotite buffer curve indicates the probable range of the two variables; T= 315∼345$^{\circ}C$, and f( $S_2$)=10$^{-1}$0.5/∼10$^{-9}$ atm. The present antimony-bearing arsenopyrite (arsenopyrite Ic) is characterized by relatively high content of antimony, ranging from 4.95 to 8.91 percent Sb by weight and excess of iron and deficiency of anions are evident. Such a high antimonian arsenopyrite has never been known within single grain. But being the high content of antimony as in the arsenopyrite Ic, it does not serve as a geothermometer. The results of microprobe analyses for four pairs of asenopyrite and sphalerite in Stage III indicate the temperature range from 310 to 34$0^{\circ}C$, and sulphur fugacity range from 10$^{-10}$ ∼10$^{-9}$ atm. These values seem to correspond with those inferred from the Fe-As-S system.m..

• KSBB Journal
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• v.24 no.6
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• pp.527-532
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• 2009

Lignocellulose represents a key sustainable source of biomass for transformation into biofuels and bio-based products. Unfortunately, lignocellulosic biomass is highly recalcitrant to biotransformation, both microbial and enzymatic, which limits its use and prevents. As a result, effective pretreatment strategies are necessary. The vast majority of pretreatment strategies have focused on achieving a reduction of lignin content. In this work, an ethanosolv pretreatment has been evaluated for extracting lignin from barley straw. 75% ethanol was used as a pretreatment solvent to extract lignin from barley straw. The influence on delignification of three independent variables are temperature, time, catalyst (1 M $H_2SO_4$) dose. The best pretreatment condition observed was $180^{\circ}C$, 120 min, 0.2% $H_2SO_4$ and delignification was 38%. A combined roasting and ethanosolv, 2-step pretreatment, was developed in order to improve the delignification. Roasting didn't increase the delignification but reduced the pretreatment time. X-ray diffraction results indicated that these physical changes enhance the enzymatic digestibility in the ethanosolv treated barley straw. The cellulose in the pretreated barley straw becomes more crystalline without undergoing ethanosolv.