• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.10 no.1
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• pp.284-305
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• 1997

A Literatural study on the etiological factors, classification, prescription of hemorrhoids and hemorrhoids complicated by anal fistula following results were obtained. 1. The cause of hemorrhoids are long time sit, long time gate, overfatigue, overeating, imbalance of stool( constipation or diarrhea), pregnant fertility(overfatigue after childbirth, insufficiency of middle warmer energy), uncontrol sexual excess, pathgenic factors of wetness, heat, wind, dry, genetic cause, excess of anxiety, pile up of heat poison, weakness of entrails and viscera. The cause of hemorrhoid complicated by anal fistula are attack of external wind, heatness, dry, fire, wetness(pathgenic factors), inapporiate treatment and chronic disease, greasy diet, excess of anxiety, constipation, uncontrol sexual excess, obstacle of circulation of vital energy and blood on anal site. 2. Classification of hemorrhoids are female hemorrhoids, male hemorrhoids, pulse hemorrhoids, intestines hemorrhoids, vital energy hemorrhoids, wine hemorrhoids, blood hemonhoids, flowing hemorrhoids. Classification with other method are external hemorrhoids, internal hemorrhoids, mixed hemorrhoids, excrescence hemorrhoids, nipple homorrhoids. External hemorrhoids is classified of varicosis of hemorrhoidal vein, connective tissue form, thrombus form. Classification of hemorrhoid complicated by anal fistula are simple lower hemorrhoid, lower mixed hemorrhoid, deep hemorrhoid, outer of one hole hemorrhoid, a horseshoe hemorrhoids. Once more classificated of four are space of sphincter muscle form, penetration sphincter muscle form, upper of sphincter muscle form, outer of sphincter muscle form. 3. Therapy method of hermorrhoid and hemorrhoid complicated by anal fistula are internal method, fumigation method method, ointment, method of close with medicine, necrotizing method, hot medicated compress( gxternal method), injection, insertion, bind, (operation) and acupuncture therapy (the others method) 4. Herb medicine for many used of internal method are Scutellaria baikalensis George(黃芩), Coptis japonia Makino(黃連), Rehmania giutinosa Liboschitz ex Fischer & Meyer(生地黃), Poncirus trifoliata Refinesque(枳殼), Sanguisorba officinalis Linne(地楡), Sophora japonica L.(槐花), Cnidium officinale Makino (川芎), Astragalus membranaceus Bunge(황기), Angelica gigas Nakai (當歸). 5. Herb medicine for many used of fumigation are Schlechtendalia Chinesis J. Bell (五倍子), Artemisia Vulgaris L. var indica Maxim(艾葉), Poncirus trifoliata Refinesque (枳殼), Nepeta japonica Maximowicy(荊芥), And herb medicine for many used of ointment are Calomelas(輕粉), Alum(白礬), Boswellia carterii Birdwood(乳香), Os Draconis Fossilia Ossis Mastodi(龍骨).

• Korean Journal of Agricultural Science
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• v.5 no.1
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• pp.35-41
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• 1978

Extensive selection works on wild yeasts of fruits were carried cut to obtain strains which are applicable to apple wine making. Among the total number of 1,358 yeast strains which were isolated from various fruit samples collected from the vicinity of Daejeon and other regions cf Korea, the strains SH-49, SH-129 and SH-338 were found to be useful. Then experiments on their morphological and physiological characteristics, and on the aspects of practical use in apple wine making were proceeded. The results obtained were as follows: 1. The strains SH-49 and SH-129, particularly SH-49, were appeared to have good fermentation ability, tolerance to sulfur dioxide and to produce fine quality of apple wine. 2. Apple wines made by using the strain, SH-49 and SH-129 contained less amount of total acids than those by other strains. 3. Apple wines of SH-49 and SH-129 were clarified rapidly during the primary fermentation period, and their absorbancy at 430 nm after 45 days of storage were approximately half of others. 4. Apple wine of SH-338 contained higher amount of residual sugar and its quality was superior to others. It is considered that this strain could be used in the production of apple wine of a characteristic quality. 5. The strains SH-49 and SH-338 were identified as a Saccharomyces cerevisiae according to Taxanomic Study of Yeasts by Lodder, however, classification of SH-129 was suspended for further study.

• Journal of Dairy Science and Biotechnology
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• v.38 no.4
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• pp.230-236
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• 2020

Heat treatment is a fundamental processing technology in the dairy industry. The main purpose of heat treatment is to destroy pathogenic and spoilage promoting microorganisms to ensure milk safety and shelf life. Despite the development of alternative technologies, such as high-pressure processing and pulse field technology for microbial destruction, heat treatment is widely used in the dairy industry and in other food processes to destroy microorganisms. Heat treatment has contributed greatly to the success of food preservation since Pasteur's early discovery that heat treatment of wine and beer could prevent their deterioration, and since the introduction of milk pasteurization in the 1890s. In Korea, food labeling standards do not stratify heat treatments into low temperature, high temperature, and ultra-high temperature methods. Most milk is produced in Korea by pasteurization, with extended shelf life (ESL : 125--140℃ / 1-10 s). Classification based on temperature (i.e. low, high, and ultra-high), is meaningless.

• Korean journal of food and cookery science
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• v.21 no.5
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• pp.607-615
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• 2005

The purpose of this study was to analyze the characteristics of Chinese foods in main ingredients, sauces, and cooking methods, and to assess the applicability of kochujang in Chinese foods. Twenty Chinese foods and commercial kochujang were selected by a Chinese head cook. The main ingredients were 24 kinds such as pork, chicken, shrimp, bok choy, bean curd, Chinese noodles etc., which were generally used in Korean foods. The main Chinese sauces were 11 kinds, and soy sauce was used in 12 foods, shang loo tau soy sauce in 2, wine in 8, oyster sauce in 7, rice wine in 6. The classification of cooking units in all Chinese foods was performed and the cooking frequency was deep frying>pan frying>boiling>stir frying>steaming>roasting. The proper amount of kochujang (weight ratio) was decided by pre-test of the Chinese head cook and Chinese food added kochujang was assessed by a Chinese focus group. The overall preference of Chinese food added kochujang was assessed highly and was related to the kinds of sauces, and to the kinds of main ingredients. The foods which used soy sauce or shang loa tau soy sauce were preferred. Sweetness by using kochujang wasn't preferred in several foods. Saltiness and aftertaste by using kochujang didn't affect the food preference, and the intensity of color and pungency were evaluated as a moderate level. An increased amount of kochujang would be possible in several foods. However, the increase in the amount of kochujang for intensive color and pungency in Chinese foods was directly related to the increase of sweetness, which had been discussed as the main problem in lowering the preference. Therefore, the screening of various Chinese foods harmonized with kochujang and the determination of the proper mixing ratio with Chinese sauces are very important. The results of this study could be used as basic data for the promotion of kochujang consumption in the Chinese market.

• Korean Journal of Food Science and Technology
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• v.46 no.3
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• pp.352-357
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• 2014

In this study, 100 consumers (men, 50; women, 50; age group, 20-50 years) rated their overall preferences for 24 Korean raspberry wines by using a 9-point hedonic scale. The analysis of variance was constructed to evaluate the effect of gender, age, and samples on the preference scores of the wine products. Significant differences were observed in overall preferences for the 24 samples; however, no interactions based on preferences by age and gender groups were noted. Cluster analysis was performed to determine sample clustering based on the frequencies from the preference data. Three clusters were obtained; these three clusters were well separated based on the mean overall preference scores for the samples. Discriminant analysis based on the three clusters also confirmed the same grouping of samples with 100% accuracy.

• Journal of KIISE
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• v.42 no.7
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• pp.852-859
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• 2015

As the amount of knowledge information significantly increases, a lot of progress has been made in the studies focusing on how to reason large scale ontology effectively at the level of RDFS or OWL. These reasoning methods are divided into TBox classifications and ABox realizations. A TBox classification mainly deals with integrity and dependencies in schema, whereas an ABox realization mainly handles a variety of issues in instances. Therefore, the ABox realization is very important in practical applications. In this paper, we propose a realization method for analyzing the constraint of the specified class, so that the reasoning system automatically infers the classes to which instances belong. Unlike conventional methods that take advantage of the object oriented language based distributed file system, we propose a large scale ontology reasoning method using spark, which is a functional programming-based in-memory system. To verify the effectiveness of the proposed method, we used instances created from the Wine ontology by W3C(120 to 600 million triples). The proposed system processed the largest 600 million triples and generated 951 million triples in 51 minutes (696 K triple / sec) in our largest experiment.

• Korean Journal of Human Ecology
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• v.12 no.4
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• pp.539-552
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• 2003

The purpose of this study was to find out the proper evaluative words and colors according to various fashion images and to classify the fashion images according to certain criteria. 13 books which included the content of the fashion images were selected to draw evaluative words and colors. Evaluative words and colors were found out as follows: classic image-traditional, classical, conservative and brown, wine, dark yellow, modem image-intelligent, rational, westernized and achromatic color, cool colors, elegance image-dignified, graceful, chic and greyish tone, pale tone, romantic image-cute, lovely, girlish, natural image-natural, comfortable, gently and brown, ivory beige, khaki, casual image-energetic, comfortable, active and red, yellow, blue family. The classification of fashion images according to various criteria were as follows. According to sex: feminine-elegance, romantic, pretty and masculine-mannish, dandy, military. According to time: past-conservative, traditional, classical, and present-modern, contemporary, sophisticate. According to formality: formal-formal wear of classic, elegance, mannish, dandy style and informal-natural, casual. According to intelligence, the elite style-modern, elegance, classic, sophisticate and the public style-casual, natural.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Mycobiology
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• v.41 no.3
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• pp.139-144
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• 2013

Makgeolli is a traditional cloudy-white Korean rice wine with an alcohol content of 6~7%. The present study investigated the morphological characteristics, carbon-utilizing ability, fatty acid composition, alcohol resistance, glucose tolerance, and flocculence of Saccharomyces cerevisiae Y98-5 and Pichia anomala Y197-13, non-S. cerevisiae isolated from Nuruk, which is used in brewing Makgeolli. Similar morphological characteristics were observed for both isolated wild yeast strains; and the carbon source assimilation of Y197-13 differed from that of other P. anomala strains. Strain Y197-13 was negative for D-trehalose, mannitol, arbutin, I-erythritol, and succinic acid. The major cellular fatty acids of strain Y197-13 included C18:2n6c (33.94%), C18:1n9c (26.97%) and C16:0 (20.57%). Strain Y197-13 was Crabtree-negative, with 60% cell viability at 12% (v/v) ethanol. The flocculation level of strain Y197-13 was 8.38%, resulting in its classification as a non-flocculent yeast.

• Horticultural Science & Technology
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• v.29 no.2
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• pp.116-122
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• 2011

In this study, we report the generation and analysis of 1,392 expressed sequence tags (ESTs) from Korean Stewartia (Stewartia koreana Nakai). A cDNA library was generated from the young leaf tissue and a total of 1,392 cDNA were partially sequenced. EST and unigene sequence quality were determined by computational filtering, manual review, and BLAST analyses. Finally, 1,301 ESTs were acquired after the removal of the vector sequence and filtering over a minimum length 100 nucleotides. A total of 893 unigene, consisting of 150 contigs and 743 singletons, was identified after assembling. Also, we identified 95 new microsatellite-containing sequences from the unigenes and classified the structure according to their repeat unit. According to homology search with BLASTX against the NCBI database, 65% of ESTs were homologous with known function and 11.6% of ESTs were matched with putative or unknown function. The remaining 23.2% of ESTs showed no significant similarity to any protein sequences found in the public database. Annotation based searches against multiple databases including wine grape and populus sequences helped to identify putative functions of ESTs and unigenes. Gene ontology (GO) classification showed that the most abundant GO terms were transport, nucleotide binding, plastid, in terms biological process, molecular function and cellular component, respectively. The sequence data will be used to characterize potential roles of new genes in Stewartia and provided for the useful tools as a genetic resource.