• Microbiology and Biotechnology Letters
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• v.38 no.3
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• pp.283-288
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• 2010

Yam (Dioscorea spp.) has been used as important edible and medicinal natural resource in worldwide and D. alata L. is most popular nourishment among the yam. In this study the composition, color, antioxidation and antimicrobial activity of D. alata Gyeongbuk No. 6 (GB-6), which was established in Gyeongbuk Agricultural Research & Extension Services, Andong, Korea, was compared to those of D. batatas Gyeongbuk No. 1 (GB-1), a major domestic cultivation species. Water content of GB-6 was $78.02{\pm}0.16%$, which is slightly lower than that of GB-1 ($82.6{\pm}0.07%$). The contents of crude protein, crude fat, crude fiber and ash of GB-6 were 0.95, 0.26, 0.85 and 0.70%, whereas those of GB-1 were 1.58, 0.15, 1.39 and 0.88%, respectively. Analysis of color using colormeter showed that the GB-6 is slight dark-yellow than GB-1, and total polyphenol content of GB-6 was 2-fold higher compared than that of GB-1. Sequential organic solvent fractions from methanol extract of GB-6 showed that the ethylacetate fraction has highest total polyphenol ($144.1{\pm}3.20\;mg/g$). Determination of antioxidation activity showed that the ethylacete fraction and water fraction has strong DPPH radical scavenging activity ($IC_{50}=78.32\;{\mu}g/mL$) and reducing power, respectively. In antimicrobial activity assay, the n-hexane and ethylacetate fraction showed antibacterial activity against B. subtilis, L.monocytogenes, S. epidermidis, S. aureus, P. vulgaris, and S. typhimurium. These results provide the possibility of domestic cultivated D. alata GB-6 as a healthy food.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.81-90
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• 2013

During the past decade, many changes and attempts have been tried and are continued developing new technologies in the computing area. The brick wall in computing area, especially power wall, changes computing paradigm from computing hardwares including processor and system architecture to programming environment and application usage. The high performance computing (HPC) area, especially, has been experienced catastrophic changes, and it is now considered as a key to the national competitiveness. In the late 2000's, many leading countries rushed to develop Exascale supercomputing systems, and as a results tens of PetaFLOPS system are prevalent now. In Korea, ICT is well developed and Korea is considered as a one of leading countries in the world, but not for supercomputing area. In this paper, we describe architecture design of MAHA supercomputing system which is aimed to develop 300 TeraFLOPS system for bio-informatics applications like human genome analysis and protein-protein docking. MAHA supercomputing system is consists of four major parts - computing hardware, file system, system software and bio-applications. MAHA supercomputing system is designed to utilize heterogeneous computing accelerators (co-processors like GPGPUs and MICs) to get more performance/$, performance/area, and performance/power. To provide high speed data movement and large capacity, MAHA file system is designed to have asymmetric cluster architecture, and consists of metadata server, data server, and client file system on top of SSD and MAID storage servers. MAHA system softwares are designed to provide user-friendliness and easy-to-use based on integrated system management component - like Bio Workflow management, Integrated Cluster management and Heterogeneous Resource management. MAHA supercomputing system was first installed in Dec., 2011. The theoretical performance of MAHA system was 50 TeraFLOPS and measured performance of 30.3 TeraFLOPS with 32 computing nodes. MAHA system will be upgraded to have 100 TeraFLOPS performance at Jan., 2013.

• Food Engineering Progress
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• v.21 no.1
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• pp.57-63
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• 2017

This study investigated the effects of 27.12 MHz radio frequency (RF) heating on heat transfer phenomena during the thawing process of frozen food. To determine the velocity of the RF thawing machine, samples were frozen at $-80^{\circ}C$ and subjected to different power treatments. The phase change times (-5 to $0^{\circ}C$) of frozen radish were 30, 26, 13, and 8 min; those of pork sirloin were 38, 25, 11, and 5 min; those of rump were 23, 17, 11, and 6 min; those of chicken breast were 42, 29, 13, and 9 min; and those of tuna were 25, 23, 10, and 5 min at 50, 100, 200, and 400 W, respectively. The heating limit temperatures of the radish, pork sirloin, rump, chicken breast, and tuna samples were 19.5, 9.2, 21.8, 8.8, and $16.8^{\circ}C$ at 50 W; 23.5, 15.5, 27.3, 12.3, and $19^{\circ}C$ at 100 W; 42, 26.9, 45.7, 22.1, and $39.4^{\circ}C$ at 200 W; and 48.5, 54.7, 63.6, 57.3, and $44.9^{\circ}C$ at 400 W. These results suggest that high-power RF improves thawing velocity and heating limit temperatures, and that an improvement on the operation of the RF thawing machine, according to food temperatures, is needed.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.544-551
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• 2020

The aim of this study was to develop and validate a simultaneous analytical method for berberine and palmatine, which are representative substances of Phellodendron amurense, and to evaluate the antioxidant activity. We evaluated the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of analytical methods for berberine and palmatine using high-performance liquid chromatography. Our result showed that the correlation coefficients of the calibration curve for berberine and palmatine exhibited 0.9999. The LODs for berberine and palmatine were 0.32 to 0.35 µg/mL and the LOQs were 0.97 to 1.06 µg/mL, respectively. The inter-day and intra-day precision values for berberine and palmatine were from 0.12 to 1.93 and 0.19 to 2.89%, respectively. The inter-day and intra-day accuracies were 98.43-101.45% and 92.39-100.60%, respectively. In addition, the simultaneous analytical method was validated for the detection of berberine and palmatine. Moreover, we conducted FRAP and NaNO2 scavenging activity assays to measure the antioxidant activities of berberine and palmatine, and both showed antioxidant activity. These results suggest that P.amurense could be a potential natural resource for antioxidant activity and that the efficacy can be confirmed by investigating the content of the berberine and palmatine.

• Journal of Music and Human Behavior
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• v.5 no.1
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• pp.67-90
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• 2008

This case used MI techniques that give an imagery experience to depressed client's mental resource, and that makes in to verbalism. Also those images are supportive level therapy examples that apply to positive variation. MI is simple word of 'Music and Imagery' with one of psychology cure called GIM(Guided Imagery and Music). It makes client can through to the inner world and search, confront, discern and solve with suitable music. Supportive Level MI is only used from safety level music. Introduction of private session can associate specification feeling, subject, word or image. And those images are guide to positive experience. The First session step of MI program is a prelude that makes concrete goal like first interview. The Second step is a transition that can concretely express about client's story. The third step is induction and music listening. And it helps to associate imagery more easily by used tension relaxation. Also it can search and associate about various imagery from the music. The last step is process that process drawing imagery, talking about personal imagery experience in common with therapist that bring the power by expansion the positive experience. Client A case targets rapport forming(empathy, understanding and support), searching positive recourse(child hood, family), client's emotion and positive support. Music must be used simple tone, repetition melody, steady rhythm and organized by harmony music of what therapist and client's preference. The client used defense mechanism and couldn't control emotion by depression in 1 & 2 sessions. But the result was client A could experience about support and understanding after 3 sessions. After session 4 the client had stable, changed to positive emotion from the negative emotion and found her spontaneous. Therefore, at the session 6, the client recognized that she will have step of positive time at the future. About client B, she established rapport forming(empathy, understanding and support) and searching issues and positive recognition(child hood, family), expression and insight(present, future). The music was comfortable, organizational at the session 1 & 2, but after session 3, its development was getting bigger and the main melody changed variation with high and low of tune. Also it used the classic and romantic music. The client avoids bad personal relations to religious relationship. But at the session 1 & 2, client had supportive experience and empathy because of her favorite, supportive music. After session 3, client B recognized and face to face the present issue. But she had avoidance and face to face of ambivalence. The client B had a experience about emotion change according depression and face to face client's issues After session 4. At the session 5 & 6, client tried to have will power of healthy life and fairly attitude, train mental power and solution attitude in the future. On this wise, MI program had actuality and clients' issues solution more than GIM program. MI can solute the issue by client's based issue without approach to unconsciousness like GIM. Especially it can use variety music and listening time is shorter than GIM and structuralize. Also can express client's emotion very well. So it can use corrective and complement MI program to children, adolescent and adult.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.4-14
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• 2010

Collaboration strategies entail information sharing and other varied forms of cooperation that are mutually beneficial to the company and stakeholder groups. This study addresses the specific types of collaboration used in the fashion industry while also examining strategies that have been most successful for fashion companies and perceived benefits of collaboration from the customer perspective. In the present study we define fashion companies and brands as collaborators and their partners or stakeholders as collaboratees. We define collaboration as a cooperative relationship where more than two companies, brands or individuals provide customers with beneficial outcomes utilizing their own competitive advantages on an equal basis. Collaboration strategies entail information sharing and other varied forms of cooperation that are mutually beneficial to the company and stakeholder groups. Through collaboration, fashion companies have pursued both tangible differentiation, such as design and technology applications, and intangible differentiation such as emotional and psychological benefits to customers. As a result, collaboration within the fashion industry has become an important, value creating concept. This qualitative study utilized case studies and in-depth interview methodologies to examine customers' attitudes concerning collaboration in the fashion industry. A total of 173 collaboration cases were identified in Korean and international markets from 1998 through December 2008, focusing on fashion companies. Cases were collected from documented data including websites and industry data bases and top ranked portal search sites such as: Rankey.com; Naver, Daum, and Nate; and representative fashion information websites, Samsungdesignnet and Firstviewkorea. Cases were collected between November 2008 and February 2009. Cases were selected for the analysis where one or more partners were associated with the production of fashion products (excluding textile production), retail fashion products, or designer services. Additional collaboration case information was obtained from news articles, periodicals, internet portal sites and fashion information sites as conducted in prior studies (Jeong and Kim 2008; Park and Park 2004; Yoon 2005). In total, 173 cases were selected for analysis that clearly exhibited the benefits and outcomes of collaboration efforts and strategies between fashion companies and stakeholders. Findings show that the overall results show that for both partners (collaborator and collaboratee) participating in collaboration, that the major benefits are reduction of costs and risks by sharing resource such as design power, image, costs, technology and targets, and creation of synergy. Regarding types of collaboration outcomes, product/design was most important (55%), followed by promotion (21%), price (20%), and place (4%). This result shows that collaboration plays an important role in giving life to products and designs, particularly in the fashion industry which seeks for creative and newness. To be successful in collaboration efforts, results of the depth interviews in this study confirm that fashion companies should have a clear objective on why they are doing the collaboration. After setting the objective, they should select collaboratees that match their brand image and target market, make quality co-products that have definite concepts and differentiating factors, and also pay attention to increasing brand awareness. Based on depth interviews with customers, customer benefits were categorized into six factors: pursuit for individual character; pursuit for brand; pursuit for scarcity; pursuit for fashion; pursuit for economic efficiency; and pursuit for sociality. Customers also placed more importance on image, reputation, and trust of brands regarding the cases shown in the interviews. They also commented that strong branding should come first before other marketing strategies. However, success factors recognized by experts and customers in this study showed different results by subcategories. Thus, target customers and target market should be studied from various dimensions to develop appropriate strategies for successful collaboration.

• Journal of the Korean Recycled Construction Resources Institute
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• v.1 no.1
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• pp.89-97
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• 2005

Recently, for the problem solution of demand and supply imbalance of fine aggregate due to the shortage of natural fine aggregate resource and the environment regulation on sea sand extraction in the construction field, the studies for the application of recycled fine aggregate using waste concrete are being progressed versatilely. On the other hand, the treatment of fly-ashes that of industrial by-product originated in the steam power plant is discussed by the continuous increasing of origination quantities. In the ease of using fly-ash, advantages are the improvement of workability, viscosity and long-time strength, and the reduction of hydration heat under the early ages, as the admixtures for concrete, but the studies for the application of fly-ash as recycled concrete admixtures are inadequacy. There fore, in this study, through investigating the properties of fresh, hardened and durability according to the replacement of recycled fine aggregate and fly-ash, it is intended to propose the fundamental data for structural application of recycled concrete using recycled fine aggregate and fly-ash. As the result of this study, they arc shown that the engineering properties and durability, in the case of replacement ratio 100% of recycled fine aggregate, arc similar to those of concrete using natural fine aggregate, so it is considered that recycled fine aggregate could be used as the fine aggregate for concrete. Also, the performances of recycled concrete are improved by replacing fly-ash.

• Journal of Nutrition and Health
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• v.49 no.3
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• pp.135-143
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• 2016

Purpose: Ultraviolet (UV)-induced oxidative stress contributes to several adverse biological effects on skin. Many phenolic phytochemicals have been shown to have antioxidant properties and protect skin cells from UV-induced oxidative damage. In this study, we investigated whether or not Aralia elata (AE) has a protective effect against UVB-induced reactive oxygen species (ROS), ultimately leading to photoaging. Methods: Phenolic content of dried AE and antioxidant properties of AE extract in 70% ethanol weredetermined by measuring DPPH and ABTS radical scavenging activities and ferric reducing antioxidant power (FRAP). The effect of AE extract on cellular ROS generation and expression levels of oxidative stress-response proteins such as superoxide dismutase (SOD)-1, catalase, nuclear factor-erythroid 2-related factor (Nrf)-2, and heme oxygenase (HO)-1 in UVB-irradiated ($75mJ/cm^2$) human keratinocytes (HaCaT) were further determined by 2'-7'-dichlorofluoresceine diacetate assay and Western blotting, respectively. Results: The total phenolic and flavonoid contents of dried AE were 20.15 mg tannic acid/g and 18.75 mg rutin/g, respectively. The $IC_{50}$ of AE extract against DPPH radical was $98.5{\mu}g/mL$, and ABTS radical scavenging activity and FRAP upon treatment with $1,000{\mu}g/mL$ of AE extract were $41.8{\mu}g\;ascorbic\;acid\;(AA)\;eq./mL$ and $29.7{\mu}g\;AA\;eq./mL$,m respectively. Pretreatment with AE extract significantly reduced (p < 0.05) ROS generation compared to that in UVB-irradiated control HaCaT cells. Pretreatment with AE extract reversed reduction of Nrf-2 and SOD-1 protein expression and induction of HO-1 protein expression caused by UVB exposure in HaCaT cells, whereas it did not affect catalase expression. Conclusion: AE extract in 70% ethanol demonstrated a protective effect against UVB-induced oxidative stress and decreased expression of Nrf-2 and SOD-1 in human keratinocytes. These findings suggest that AE ethanol extract might have potential as a natural resource for a skin anti-photoaging product in the food and cosmetic industry.