• Journal of the Microelectronics and Packaging Society
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• v.31 no.1
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• pp.16-22
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• 2024

Along with the high interest in electric vehicles and new renewable energy, there is a growing demand to apply lithium-ion batteries in the construction equipment industry. The capacity of heavy construction equipment that performs various tasks at construction sites is rapidly decreasing. Therefore, it is essential to accurately predict the state of batteries such as SOC (State of Charge) and SOH (State of Health). In this paper, the errors between actual electrochemical measurement data and estimated data were compared using the Dual Extended Kalman Filter (DEKF) algorithm that can estimate SOC and SOH at the same time. The prediction of battery charge state was analyzed by measuring OCV at SOC 5% intervals under 0.2C-rate conditions after the battery cell was fully charged, and the degradation state of the battery was predicted after 50 cycles of aging tests under various C-rate (0.2, 0.3, 0.5, 1.0, 1.5C rate) conditions. It was confirmed that the SOC and SOH estimation errors using DEKF tended to increase as the C-rate increased. It was confirmed that the SOC estimation using DEKF showed less than 6% at 0.2, 0.5, and 1C-rate. In addition, it was confirmed that the SOH estimation results showed good performance within the maximum error of 1.0% and 1.3% at 0.2 and 0.3C-rate, respectively. Also, it was confirmed that the estimation error also increased from 1.5% to 2% as the C-rate increased from 0.5 to 1.5C-rate. However, this result shows that all SOH estimation results using DEKF were excellent within about 2%.

• Applied Biological Chemistry
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• v.23 no.1
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• pp.64-72
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• 1980

Industrial wastes from pulp and food plants were treated with microorganisms to clarify organic waste-water and to produce cells as animal feed, and results were summarized as follows. (1) Waste-water from pulp, beer, bread yeast, and ethanol distillation plants contained $1.4{\sim}1.5%$ of total sugar, $0.25{\sim}0.35%$ nitrogen, and biological oxygen demand (BOD) was $400{\sim}25,000$, chemical oxygen demand (COD), $500{\sim}28,000$, and pH, $3.8{\sim}7.0$. The BOD and COD were highest in waste-water from ethanol distillation plants among others. (2) Bacterial and yeast counts were $4{\times}10^4-1{\times}10^9,\;2{\times}10^2-7{\times}10^4/ml$ in waste-water. (3) Bacteria grew better in pulp waste and yeasts in beer, bread yeast, and ethanol distillation waste. (4) Saccharomyces cerevisiae SAFM 1008 and Candida curvata SAFM 70 were the most suitable microorganisms for clarification of ethanol distillation waste. (5) When liquid and solid waste from ethanol distillation were treated with microbial cellulase, xylanase, and pectinase, solid waste was reduced by 36%, soluble waste was increased, and recuding sugar content was increased by 1.3 times which provided better medium than untreated waste for cultivation of yeasts. (6) Optimum growth conditions of the two species of yeast in ethanol distillation waste were pH 5.0, $30^{\circ}C$, and addition of 0.2% of urea, 0.1% of $KH_2PO_4$ and 0.02% of $MgSO_4$. (7) Minimum number of yeast for proper propagation was $1.8{\times}10^5/ml$. (8) C. curvata70 was better than cerevisae for the production of yeast cells from ethanol distillation waste treated with microbial enzymes. (9) S. cerevisiae produced 16 g of dried cell per 1,000ml of ethanol distillation waste and reduced BOD by 46%. C. curvata produced 17.6g of dried cell and reduced BOD by 52% at the same condition. (10) Yeast cells produced from the ethanol distillation waste contained 46-52% protein indicating suitability as a protein source for animal feed.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Life Science
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• v.21 no.6
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• pp.858-864
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• 2011

The phenolic compounds of walnut extracts by various solvents were shown to be 24.3 mg/g in hot water, 34.4 mg/g in ethanol, 32.5 mg/g in methanol and 15.1 mg/g in acetone. In a comparison of phenolic compounds from hot water and different concentrations of ethanol, which are harmless, 60% ethanol extract and hot water extract were 34.7 mg/g, 24.6 mg/g. The electron donating ability (EDA) of walnut extracts in hot water and 60% ethanol were 78.1% and 80.6%. According to ABTS radical cation decolorization for antioxidant activity, hot water and 60% ethanol extract showed high antioxidant activities of 98.1% and 98.3%. Antioxidant protection factor (PF) were $1.1{\pm}0.2$ PF and $1.1{\pm}0.4$ PF in hot water and 60% ethanol extract. In TBARs inhibitory activity, each extract showed high antioxidant activities at 60% and 75%. Anti-inflammation effects of walnut extract were tested, and inhibition of NO was 50% in 100 ${\mu}g/ml$ phenolics. Inhibitory activity against iNOS and COX-2 were shown, through Western blot, to be 10% in 100 ${\mu}g/ml$ phenolics. Tyrosine inhibitory activity of 60% ethanol extract was 43%, and astringent effect of 60% ethanol extract was 55%. These results suggest that walnut extracts are suitable for functional cosmetics requiring skin-whitening and anti-wrinkle activity.