• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.211-218
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• 2019

Purpose: The purpose of the present study was to compare the accuracy of four different metal copings fabricated by CAD/CAM technology and to evaluate clinical effectiveness. Materials and methods: Composite resin tooth of the maxillary central incisor was prepared for a metal ceramic crown and duplicated metal die was fabricated. Then scan the metal die for 12 times to obtain STL files using a confocal microscopy type oral scanner. Metal copings with a thickness of 0.5 mm and a cement space of $50{\mu}m$ were designed on a CAD program. The Co-Cr metal copings were fabricated by the following four methods: Wax pattern milling & Casting (WM), Resin pattern 3D Printing & casting (RP), Milling & Sintering (MS), Selective laser melting (SLM). Silicone replica technique was used to measure marginal and internal discrepancies. The data was statistically analyzed with One-way analysis of variance and appropriate post hoc test (Scheffe test) (${\alpha}=.05$). Results: Mean marginal discrepancy was significantly smaller in the Group WM ($27.66{\pm}9.85{\mu}m$) and Group MS ($28.88{\pm}10.13{\mu}m$) than in the Group RP ($38.09{\pm}11.14{\mu}m$). Mean cervical discrepancy was significantly smaller in the Group MS than in the Group RP. Mean axial discrepancy was significantly smaller in the Group WM and Group MS then in the Group RP and Group SLM. Mean incisal discrepancies was significantly smaller in the Group RP than in all other groups. Conclusion: The marginal and axial discrepancies of the Co-Cr coping fabricated by the Wax pattern milling and Milling/Sintering method were better than those of the other groups. The marginal, cervical and axial fit of Co-Cr copings in all groups are within a clinically acceptable range.

• Korean Journal of Poultry Science
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• v.48 no.1
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• pp.13-22
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• 2021

The present experiment was conducted to evaluate the effect of stocking density on the growth performance, immune status, and meat quality of broilers. In total, 385 one-day-old Ross 308 broilers were randomly assigned to one of four distinct stocking densities: 26 birds/㎡, 22 birds/㎡, 19 birds/㎡, and 16 birds/㎡. They were fed the diet ad libitum for 5 weeks. Immunoglobulin (Ig) and corticosterone levels were evaluated, and growth performance, blood parameters, and breast meat quality were determined. It was observed that the weight gain and feed intake of growers (21~35 d) and broilers (0~35 d) were significantly reduced as the stocking density increased (P<0.05). However, the feed intake of starters (0~21 d) significantly increased as the stocking density increased (P<0.05). There were no significant differences in the biochemical profiles among the four different stock densities. Furthermore, no significant differences were observed in the stress parameters: (heterophils / lymphocytes ratio and corticosterone), IgA, and IgM; however, IgG significantly increased with stocking density (P<0.05). The pH, water holding capacity, and cooking loss of the muscle were all unaffected by the stocking density, but the shear force (tenderness) increased slightly as the density increased. The findings of this study suggest that a lower stocking density (16 birds/㎡) significantly improved the shear force of breast meat and IgG in broilers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.9-16
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• 2022

Rice is one of the most important staple foods in Wnju, Jeonbuk, South Korea. However, rice consumption has dramatically decreased as eating habits have diversified owing to rapid economic growth. Recently, floury endosperm rice varieties have been developed to invigorate the rice processing industry, because dry-milled rice flour is economically and environmentally suitable for massive rice flour distribution. The National Institute of Crop Science has developed 'AromaT', an early-maturing black rice with floury-endosperm, suitable for tea and dry milling. 'AromaT' was derived from a cross between 'Suweon542' as the floury endosperm source and 'Heugjinju' as the black and aromatic source. In this study, 'AromaT' and its parents, 'Suweon542' and 'Heugjinju', were analyzed for agronomic traits, anthocyanin content, and their major physicochemical properties by different planting date. The field experiment was conducted in Wanju, Jeollabuk-do Province, South Korea, in 2019. The transplanting dates were May 30 (ordinary season), June 25 (double-cropping season), and July 10 (late season). The yield performance of brown rice 'AromaT' was 330 kg/10 a in the double-cropping cultivation method and was the highest among the transplanting dates. The floury endosperm of 'AromaT' was derived from 'Suweon542' containing 'flo7', located on chromosome 5 and known to control floury endosperm. With the late planting date, the anthocyanin content of 'AromaT' was 570.5 mg/100 g, much higher than that of 'Heugjinju' (376.3 mg/100 mg). The brown rice of 'AromaT' also exhibited the pop-corn-flavoring 2-acetyl-1-pyrroline, exclusively detected in aroma rice varieties. The average particle sizes of 'AromaT' and 'Suweon542' were 67.12 ㎛ and 70.9 ㎛, respectively, lower than that of 'Heugjinju' (95.5 ㎛) with a black transparent endosperm. The average damaged starch content of 'AromaT' was 8.1%, lower than that of 'Heugjinju' (10.05%) and Suweon542 (9.5%). As a result, 'AromaT' with high anthocyanin content, fine particle size, and low damaged starch content is expected to provide a new rice material in various processing fields.

• Journal of the Korean Applied Science and Technology
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• v.40 no.3
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• pp.534-546
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• 2023

In this study, we investigated the antioxidant and anti-winkle activity in human fibroblast cell (CCD-986sk) of Persimmon Leaves (PL) as a cosmetic ingredient. As a result of investigating antioxidant activity through electron-donating ability and ABTS⁺ radical scavenging assay, the PL showed concentration-dependent antioxidant activity similar to ascorbic acid, a control group, at a concentration of 1,000 ㎍/ml. As a result of investigating the anti-wrinkle effect through elastase inhibition and collagenase inhibition assay, the PL showed concentration-dependent antioxidant activity similar to epigallocatechin gallate, a control group, at a concentration of 1,000 ㎍/ml. As a result of measuring the synthesis rate of pro-collagen type I and the inhibition rate of MMP-1 in UVB-induced CCD-986sk cells, the control group EGCG showed a 90.2% pro-collagen synthesis rate at 20 ㎍/ml and PL showed an 88.5% synthesis rate at 30 ㎍/ml. In addition, the inhibition rate of MMP-1 of 33.0% and 40.8% were confirmed in EGCG 20 ㎍/ml and PL 30 ㎍/ml, respectively. As a result of measuring the protein expression of pro-collagen type I and MMP-1 in the PL through western blot, it was confirmed that the protein expression of pro-collagen type I increased, and MMP-1 decreased when the PL was treated together compared to the UVB alone group. According to the above experimental results, it is expected to be used as a natural product material for cosmetics by confirming that the PL prevent photoaging caused by UVB stimulation and have antioxidant and anti-wrinkle effects.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.123-130
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• 2023

Salmonella spp. are prevalent foodborne pathogens that are infective at relatively low concentrations, thus posing a serious health threat, especially to young children and the elderly. In several countries, the management and regulation of Salmonella spp. in food, including seafood, adhere to a negative detection standard. The risk of infection is particularly high when seafood is consumed raw, which underscores the importance of timely detection of pathogenic microorganisms, such as Salmonella. Accordingly, this study aimed to develop a combined pre-treatment and detection method that includes pre-culture and DNA extraction in order to detect five species of Salmonella at concentrations below 10 CFU/mL in seafood. The effectiveness of the proposed method was assessed in terms of the composition of the enrichment (pre-culture) medium, minimum incubation time, and minimum cell concentration for pathogen detection. Furthermore, a practical DNA extraction method capable of effectively handling high salt conditions was tested and found to be successful. Through polymerase chain reaction, Salmonella spp. Were detected and positively identified in shellfish samples at cell concentrations below 10 CFU/g. Thus, the proposed method, combining sample pre-treatment and cell culture with DNA extraction, was shown to be an effective strategy for detecting low cellular concentrations of harmful bacteria. The proposed methodology is suitable as an economical and practical in situ pre-treatment for effective detection of Salmonella spp. in seafood.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.6
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• pp.909-919
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• 2010

The purpose of this study was to investigate the demand and use of fresh-cut produce in school foodservice and restaurant industries. The subjects of this survey study were 200 school nutritionists and 70 cooks or managers in the restaurant industry nationwide. The data were collected by means of self-administered or e-mail questionnaires. Data analysis was completed using the SPSS window (ver. 12.0) program including frequency, $\chi^2$-test and t-test. Survey questions assessed the general characteristic of respondents, and the supply, use, and demand of fresh-cut produce in school foodservice and restaurant industries. Over 74% of the subjects have used fresh-cut produce. Most of the school foodservice (84.0%) kept fresh-cut produce for one day, while restaurant industry (28.3%) kept them up to three days. The nutritionists of school foodservice and managers of restaurant industry considered origin and date of production as the most important factor, respectively, when fresh-cut produce were being used. Fresh-cut root vegetable, such as potato and carrot was used mostly. The main reason not to use the fresh cut produce was due to the distrust of the fresh-cut produce safety in school foodservice and cost in restaurant industry. The main problem in fresh-cut produce use was the need of rewashing (29.9%) in school foodservice and irregular size (39.0%) in restaurant industry. These results indicate that the quality standard and size specification must be prepared with production guideline of safe fresh-cut produce.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Korean Journal of Organic Agriculture
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• v.21 no.3
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• pp.451-465
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• 2013

This study was conducted to estimate Hanwoo carrying capacity when whole crop barley, rye, wheat and tritcale as winter forage crops was grown on different applying sources (chemical fertilizer, cattle or organic fertilizer) and mixed sowing combination with hairy vetch or forage pea during the period of 2011~2012. The experimental plots within whole crop barley or rye were consisted of 7 treatments, which were non-fertilizer, chemical fertilizer (P+K), chemical fertilizer (N+P+K), organic fertilizer, cattle slurry, cattle slurry with hairy vetch, and cattle slurry with forage pea. Each plot was triplicates and experimental treatments were allocated in the randomized complete block design. For whole crop barley, annual mean dry matter (DM) and total digestible nutrients (TDN) yields were the highest in N+P+K plots, but there were no significant differences among organic fertilizer, cattle slurry and mixed sowing with legumes. The TDN were the highest in mixed sowing plots of forage pea plus cattle slurry application. As 450 kg Hanwoo heifers were fed diets included 70% whole crop barley, organic fertilizer, cattle slurry application and mixed sowing plots of forage pea is capable of raising average 2.8 to 3.1 heads/ha a year. For whole crop rye, annual mean DM were the highest in N+P+K plots, but there were no significant differences among cattle slurry. Organic fertilizer application significantly increased TDN and relative feed value (RFV) in comparison with treatments of N+P+K fertilization as chemical fertilizers. In case of 450 kg Hanwoo heifers fed diets included 70% forage rye, it is estimated that cattle slurry application (mixed sowing with legumes) plots can rear average 2.8~ 3.2 heads/ha a year. For whole crop wheat, annual DM, crude protein, and TDN yields of application groups and mixed sowing treatment with legumes showed 6.90~7.44, 0.53~0.60 and 4.35~5.04 ton/ha, respectively. In case of 450 kg Hanwoo heifers fed diets included 70% forage rye, it is estimated that cattle slurry application (mixed sowing with legumes) plots can rear average 3.1~3.7 heads/ha a year. For Triticale, TDN yield was significantly (P<0.05) higher N+P+K plots, organic ferilizer, cattle slurry, cattle slurry with legumes than for no fertilizer and N+P+K plots. The Crude protein (CP) contents were the highest in mixed sowing plots of forage pea plus cattle slurry application. In case of 450 kg Hanwoo heifers fed diets included 70% forage triticale, it is estimated that cattle slurry application (mixed sowing with legumes) plots can rear average 3.4~3.7 heads/ha a year. It can be concluded that, on the basis of DM yield, not only mixed sowing with legumes by applying cattle slurry rather than single sowing of whole crop barley or whole crop rye enhanced production yield and feed values, but also it could be a substitute for imported grains as dietary protein sources in the case of feeding Hanwoo.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.