• Clean Technology
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• v.28 no.4
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• pp.269-277
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• 2022

With the recent development of the biological enzymatic reaction industry, lactic acid (LA) can be mass-produced from biomass sources. In particular, a catalytic process that converts LA into acrylic acid (AA) is receiving much attention because AA is used widely in the petrochemical industry as a monomer for superabsorbent polymers (SAP) and as an adhesive for displays. In the LA conversion process, NaY zeolites have been previously shown to be a high-activity catalyst, which improves AA selectivity and long-term stability. However, NaY zeolites suffer from fast deactivation due to severe coking. Therefore, the aim of this study is to modify the acid-base properties of the NaY zeolite to address this shortcoming. First, base promoters, Ca ions, were introduced to the NaY zeolites to tune their acidity and basicity via ion exchange (IE) and incipient wetness impregnation (IWI). The IWI method showed superior catalyst selectivity and stability compared to the IE method, maintaining a high AA yield of approximately 40% during the 16 h reaction. Based on the NH₃- and CO₂-TPD results, the calcium salts that impregnated into the NaY zeolites were proposed to exit as an oxide form mainly at the exterior surface of NaY and act as additional base sites to promote the dehydration of LA to AA. The NaY zeolites were further treated with KOH before calcium impregnation to reduce the total acidity and improve the dispersion of calcium through the mesopores formed by KOH-induced desilication. However, this KOH treatment did not lead to enhanced AA selectivity. Finally, calcium loading was increased from 1wt% to 5wt% to maximize the amount of base sites. The increased basicity improved the AA selectivity substantially to 65% at 100% conversion while maintaining high activity during a 24 h reaction. Our results suggest that controlling the basicity of the catalyst is key to obtaining high AA selectivity and high catalyst stability.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Korean Journal of Food Science and Technology
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• v.42 no.2
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• pp.233-239
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• 2010

This study was conducted to examine the anticancer activities of Berberis koreana extracts according to different extraction processes. The highest extraction yield obtained was 8.26% following extraction by ultrasonification at 60 kHz and $60^{\circ}C$ followed by high pressure at 500MPa. Generally, the extracts from the ultrasonification process showed relatively low cytotoxicities against the human normal cell line, HEK293 showing as low as 15%. This extract inhibited the growth of the digestive related organs cell lines, human stomach adenocarcimoma cell and human epithelial adenocarcinoma cell by up to 80% when administered at 1.0 mg/mL, and showed 2.5-3.5 of selectivity. It was also found that this extract induced the production of nitric oxide levels as high $37.87\;{\mu}M$ from macrophages. For the in vivo experiment using ICR mice, the total serum IgG levels of mice treated with B. koreana extracts from ultrasonification extraction were increased by up to 57 ng/mL. The survival time of this group was longer than that of the other group after the injection of Sarcoma-180 and the increment of their body weights was also greatly suppressed. In addition, the extract showed the highest tumor inhibition activities, leading to a reduction of 78.47%. These results indicate that the highest activities of B. koreana associated with this extraction process can be significantly improved.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.104-109
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• 2010

Purpose: $[^{18}F]$Fallypride plays an effective radiotracer for the study of dopamine $D_2/D_3$ receptor occupancy, neuropsychiatric disorders and aging in humans. This tracer has the potential for clinical use, but automated labeling efficiency showed low radiochemical yields about 5~20% with relatively long labelling time of fluorine-18. In present study, we describe an improved automatic synthesis of [$^{18}F$]Fallypride using different base concentration for routine clinical use. Materials and Methods: Fully automated synthetic process of [$^{18}F$]Fallypride was perform using the TracerLab $FX_{FN}$ synthesizer under various labeling conditions and tosyl-fallypride was used as a precursor. [$^{18}F$]Fluoride was extracted with various concentration of $K_{2.2.2.}/K_2CO_3$ from $^{18}O$-enriched water trapped on the ion exchange cartridge. After azeotropic drying, the labeling reaction proceeded in $CH_3CN$ at $100^{\circ}C$ for 10 or 30 min. The reaction mixture was purified by reverse phase HPLC and collected organic solution was exchanged by tc-18 Sep-Pak for the clinically available solution. Results: The optimal labeling condition of [$^{18}F$]Fallypride in the automatic production was that 2 mg of tosyl-fallypride in acetonitrile (1 mL) was incubated at $100^{\circ}C$ for 10 min with $K_{2.2.2.}/K_2CO_3$ (11/0.8 mg). [$^{18}F$]Fallypride was obtained with high radiochemical yield about $66{\pm}1.4%$ (decay-corrected, n=28) within $51{\pm}1.2$ min including HPLC purification and solid-phase purification for the final formulation. Conclusion: [$^{18}F$]Fallypride was prepared with a significantly improved radiochemical yield with high specific activity and shorten synthetic time. In addition, this automated procedure provides the high reproducibility with no synthesis failures (n=28).

• Resources Recycling
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• v.2 no.2
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• pp.27-38
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• 1993

In this study, we investigated the grinding and sedimentation(elutriation) process of the dusts for the effective separation of high purity iron and iron oxides. For characterization of the dust, particle size distribution and chemical composition, were examined. The results obtained in this study may be summarized as follows : 1. The converter CF(clarifier) dust of the Pohang 1st, 2nd steel making factory and EC(Evaporation Cooler), EP(Eltrostatic precititator) dust of the Kwangyang 2nd steel making factory are composed $\alpha$-Fe(21~50%), FeO(wustite)$Fe_3$$O_4$(magnetite), $Fe_2$$O_3$, CaO, $Al_2$$O_3$, $SiO_2$, and etc. 2. Pure iron has ductile characteristic in nature, particle size of the pure iron increase by increasing the grinding time. On the other hand, it is conformed that bo고 particles of hematite and magnetite become less than 325 mesh after 10 minutes grinding. 3. By applying the elutriation technique for the EC dust of the Kwangyang 2nd steel making factory, the iron powder of high content more than 99.17% of pure Fe was recovered with 37.8% yield at grinding time for 40 minutes. 4. By applying the elutriation technique for the CF dust of the Pohang 2nd steel making factory, the iron powder of high content more than 98.38% of pure Fe was recovered with 44.42% yield at grinding time for 40 minutes. 5. When magnetic separation was performed using plastic bonding magnet of 70 gauss, more than 98% Fe grade of iron powder was recovered in the size range +65 -200 mesh but the recovery of it was low.

• Korean Chemical Engineering Research
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• v.51 no.2
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• pp.189-194
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• 2013

A sulfonated activated carbon (AC-$SO_3H$) was used as a solid acid catalyst for dehydration of sorbitol to isosorbide and its catalytic performance was compared with the commercial solid acid such as acidic ion exchange resin, Amberlyst-36, and sulfated copper oxide. The catalytic performance with 100% sorbitol conversion and 52% isosorbide selectivity was obtained over AC-$SO_3H$ at 423.15 K. Although AC-$SO_3H$ possessed only 0.5 mmol/g of sulfur content, it showed the similar dehydration activity of sorbitol to isosorbide with Amberlyst-36 (5.4 mmol/g) at 423.15 K. Based on the high thermal and chemical stability of AC-$SO_3H$, one-step reactive distillation, where isosorbide separation can be carried out simultaneously with sorbitol dehydration, was tried to increase the recovery yield of isosobide from sorbitol. The reactive distillation process using AC-$SO_3H$, the turnover number of AC-$SO_3H$ was 4 times higher than the conventional two-step process using sulfuric acid.

• Applied Chemistry for Engineering
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• v.26 no.2
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• pp.224-228
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• 2015

The carbon precursor pitch from pyrolyzed fuel oil (PFO), by-product of Naphta cracking process (NCC), was prepared through heat and UV irradiation treatments with various concentrations of $AlCl_3$, which is a new pitch preparation method. The reformed pitches were characterized by measuring their elemental composition, chemical structure of components, molecular weight distribution, and softening point. The oxygen contents of reformed pitch increased as increasing $AlCl_3$ amounts on the other hand, the carbon and hydrogen contents were not nearly changed. UV irradiated reformed pitches were composed of more aromatic carbon compounds than that of using only heat-treatment without any UV irradiation. The addition of $AlCl_3$ catalyst was ineffective on the aromaticity of reformed pitches. The softening point of prepared pitches was in the range of $103.3{\sim}168.9^{\circ}C$. Also the yield of prepared pitch increased from 48% to 80% when 5 wt% of $AlCl_3$ was added during the heat and UV irradiation reforming. It is expected that the UV irradiation reforming method can be practical and helpful to produce high yields of pitches with diverse properties.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.12
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• pp.1113-1122
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• 2009

In order to find the way to solve the problem of sewage sludge discharge into the ocean, the sludge solubilization by ultrasonic and the improvement methods of wastewater treatment process were studied. In the membrane bioreactor the sludge retention time was stepwise increased from 5.1 day to 442 days where the biomass average concentration has been increased from $c_B$=3.4 $gTSSL^{-1}$ to $c_B$=14.5 $gTSSL^{-1}$ respectively. At the same time, the biomass yield coefficients were reduced from 0.5-0.7 at SRT=5.1 day to 0.005-0.007 at SRT=442 days which means the reduction of sludge production. Oxygen mass transfer coefficients and ${\alpha}$-factor were investigated with changing stirrer speed to find the relation between the high biomass concentration and aeration efficiency in the propeller loop reactor. As a result of sludge solubilization, the solubilization of sludge by ultrasound was increased with increasing energy input and it led to improved anaerobic digestion rate with more biogas production than that of nonsolubilized sewage sludge.

• Korean Chemical Engineering Research
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• v.53 no.1
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• pp.1-5
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• 2015

Lactic acid, the most widely occurring hydroxy-carboxylic acid, has traditionally been used as food, cosmetic, pharmaceutical, and chemical industries. Even though it has tremendous potential for large scale production and use in a wide variety of applications, high cost lactic acid materials are primarily problems. Lactic acid can be obtained on either by fermentation or chemical synthesis. In recent years, the fermentation approach has become more successful because of the increasing market demand for naturally produced lactic acid. Generally, lactic acid was produced from pure starch or from glucose. As an alternative, biomass which is the most abundant renewable resources on earth have been considered for conversion to readily utilizable hydrolysate. In this study, we conducted the fermentation method to produce L(+)-lactic acid production from pretreated hydrolysate was investigated by Lactobacillus rhamnosus ATCC 10863. The hydrolysate was obtained from pretreatment process of biomass using Ammonia percolation process (AP) followed by enzymatic hydrolysis. In order to effectively enhance lactic acid conversion and product yield, controlled medium, temperature, glucose concentration was conducted under pure glucose conditions. The optimum conditions of lactic acid production was investigated and compared with those of hydrolysate.

• The Journal of Information Systems
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• v.24 no.3
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• pp.133-154
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• 2015

Purpose This study re-analyzes Jung 2012's data using the time interval based analysis to examine if the process of idea generation is in good currency throughout the ideation sessions. In this way, the relationship between extraversion-introversion personality trait and ideation performance in the context of computer-mediated idea generation can be better understood. Design/methodology/approach A $2{\times}4$ factorial design was used, crossing personality differences (extraversion and introversion) with the degree of stimuli (0, 20, 40, and 80 high-quality ideas). Participants were randomly assigned to one of eight treatment conditions. The group simulator is used to measure individual level performance. The number of unique ideas generated by individuals and the exact time stamp when each idea was submitted were analyzed to compare performances. Findings The results show that introverts' performances significantly drops after about the middle stage of the ideation session, whereas extraverts do not seem to feel time constraints throughout the ideation session, resulting in superior divergent thinking, which is a major key to understand creative productivity in the problem-solving process. Since extraverts tend to yield a larger pool of ideas, another interpretation is that group composition with extraverts compared with introverts may create a logically larger group, which is important to improve the performance of idea generation group.