• Korean journal of applied entomology
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• v.14 no.3 s.24
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• pp.97-109
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• 1975

In an attempt to develop an effective integrated system of controlling blast disease of rice caused by Pyricularia oryzae Cav., the possibility of minimizing the disease incidence by proper application of fertilizers has been investigated. Thus the effect of silicate, nitrogen, phosphorus and potassium fertilizers on the development of blast disease as well as the correlation between the rice varieties an4 strains of P. oryzae were studied. The experiments were made in 1971 and 1973 by artificial inoculation and under natural development of the blast disease on rice plants. The results obtained are summarized as follows. 1. Application of silicate fertilizer resulted in the increase of silicate as well as total sugar and potassium content but decrease of total nitrogen and phosphorus in tile leaf blades of rice plants. 2. The ratios of total C/total N. $ SiO_2/total$ N, and $K_2O/total$ N in leaf blades of rice plants increased by the application of silicate fertilizers. There was high level of negative correlation between the ratios mentioned above and the incidence of rice blast disease. 3. Application of silicate fertilizer reduced the incidence of rice blast disease. 4. The over dressing of nitrogen fertilizer resulted in the increase of total nitrogen and decrease of silicate and total sugar content in leaf blades, thus disposing the rice plants more susceptible to blast disease. 5. Over dressing of phosphorus fertilizer resulted in the increase of both total nitrogen and Phosphorus, and decrease of silicate content in the leaf blades inducing the rice plants to become more susceptible to blast disease. 6. Increased dressing of potash resulted in the increase of silicate content and $K_2O/total$ N ratio but decrease of total nitrogen content in leaf blades. When potassium content is low in the leaf blades of rice plants, the additional dressing of potash to rice plant contributed to the increase of resistance to blast disease. However, there was no significant correlation between additional potassium application and the resistance to blast disease when the potassium content is already high in the leaf blades. 7. When four rice varieties were artificially inoculated with three strains of P. oryzae, the incidence of blast disease was most severe on Pungok, least severe on Jinheung and moderate on Pungkwang and Paltal varieties. 8. Disease incidence was most severe on the second leaf from top and less sever on top and there leaf regardless of the fertilizer application when 5-6 leaf stage rice seedlings of four rice varieties were artificially inoculated with three strains of P. oryzae. 9. The pathogenicity of three strains of P. oryzae was in the order of $P_1,\;P_2,\;and\;P_3$ in their virulence when inoculated to Jinheung, Paltal, Pungkwang varieties but not with Pungok. The interaction between strains of P. oryzae and rice varieties was significant.

• Journal of dental hygiene science
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• v.4 no.3
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• pp.103-109
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• 2004

The present study prepared 72 test samples - 24 made of amalgam alloy, 24 of Verabond (Ni-Cr alloy) for crown and 24 of Talladium $^{TM}alloy$ for denture - according to the manufacturers' manuals and general method in consideration of the width of the mesial-distal dental crown of the lower $1^{st}$ molar and MOD cavity in clinics, put them in a 200 ml beaker containing 80 ml of artificial saliva, and measured their galvanic corrosion at distances of 0 mm, 7 mm and 40 mm after 7 days. Isolated metals in the electrolyte such as Cu, Ag, Ni, Cr, Sn, Zn and Hg were quantitatively analyzed with Inductively Coupled Plasma - Atomic Emission Spectrometer (ICP-AES, JY-50P, VG Elemental Co. France), and from the results were drawn conclusions as follows. First, Cu, Sn, Ag, Hg and Zn were highly advantageous when amalgam contacted gold alloy compared to Ni-Cr alloy for crown and Talladium alloy for denture. In addition, although gold alloy was finest in terms of oral tissue and biocompatibility, it was most disadvantageous when it was with amalgam. Second, when amalgam contacted gold alloy, heavy metals such as Ni and Cr were not isolated at all because gold alloy did not contain such elements but Sn was isolated as much as $227.1{\pm}18.0035{\mu}g/cm^2$ although it was not included in the composition either. Hg was also isolated. These elements are assumed to have been isolated from amalgam itself. Third, when amalgam alloy was apart from gold alloy 0 mm, 7 mm and 40 mm, Cu and Ag showed significance but Hg did not. This suggests that gold alloy must not be used together with amalgam, and must not be used between dissimilar prostheses regardless of distance. Fourth, when amalgam alloy contacted Ni-Cr alloy for crown, Ag was not isolated from the amalgam, but Zn, Ni, Sn, Hg and Cu were isolated in order of quantity. Significance was observed according to distance - 0 mm, 7 mm and 40 mm. Hg was not isolated but heavy metals Ni and Cr were isolated. If amalgam alloy was in the opposite arch or it was apart from Ni-Cr alloy for crown, the isolation Hg was less than that when amalgam alloy contacted Ni-Cr alloy for crown. Fifth, when amalgam alloy contacted Talladium alloy for denture, significance was observed at distances of 0mm, 7 mm and 40 mm. Hg was not isolated but heavy metals Ni and Cr were isolated. If amalgam alloy was in the opposite arch or it was apart from Talladium alloy for denture, the isolation Hg was less than that when amalgam alloy contacted Talladium alloy for denture. Sixth, according to the result of ICPES test on Cu, Sn, Ag, Hg, Zn, Ni and Cr of amalgam alloy, gold ally, Verabond and Talladium alloy when these alloys contacted artificial saliva, significance was observed in Cu and Hg. Seventh, when amalgam alloy contracted two non-precious metals Ni-Cr alloy for crown and Talladium alloy for denture in artificial saliva, significance was observed in the isolated by-products of Hg, Ni and Cr according to distance.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.40-53
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• 2015

To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Korean Journal of Poultry Science
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• v.17 no.3
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• pp.141-156
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• 1990

The experiments were conducted to investigate the possibility of improving the effectiveness of the existing method to estimate the edible meat weight in the live broiler chicken. A total of 360 birds, five male and female chicks from each line were sacrificed at Trial 1 (body weight 900-1, 000g), Trial 2 (body weight 1.200-1, 400g), Trial 3(body weight 1, 600-1, 700), and Trial 4(body weight 2, 000g) in order to measure the body weight, edible meat weight of breast, thigh and drumsticks, and various components of body weight. Each line was reared at the Poultry Breeding Farm, Seoul National University from the second of july, 1987 to the thirteenth of September, 1987. The results obtained from this study were summarized as follows ： 1. The average body weights of each line( H. T, M, A) were $2150.5\pm$34.9, $2133.0\pm$26.2, $1960.0\pm$23.1, and $2319.3\pm$27.9, respectively. at 7 weeks of age. The feed to body weight eain ratio for each line chicks was 2.55, 2.13, 2.08, and 2.03, respectively, for 0 to 7 weeks of age. The viability of each line was 99.7. 99.7, 100.0, and 100.0%, respectively, for 0 to 7 weeks of age.01 was noticed that A Line chicks grow significantly heavier than did T, H, M line chic ks from 0 to 7 weeks of age. The regression coefficients of growth curves from each line chicks were bA＝1.015, bH＝0.265, bM＝0.950 and bT＝0.242, respectively. 2. Among the body weight components, the feather. abdominal fat, breast, and thigh and drumsticks increased in their weight percentage as the birds grew older, while neck. head, giblets and inedible viscera decreased. No difference wat apparent in shank, wings and hack. 3. The weight percentages of breast in edible part for each line thicks were 19.2, 19.0, 19.9 and 19.0% at Trial 4, respectively. The weight percentages of thigh and drumsticks in edible part for each line chicks were 23.1, 23.3, 22.8, and 23.0% at Trial 4. respective1y. 4. The values for the percentage meat yield from breast were 77.2. 78.9 73.5 and 74.8% at Trial 4 in H, T, M and A Line chicks. respectively. For thigh and drumstick, the values of 80.3, 78.4. 79.7 and 80.2% were obtained. These data indicate that the percentage meat yield increase as the birds grow older. 5. The correlation coefficients between body weight and blood. head, shanks. breast. thigh-drumstick were high. The degree if correlation between abdominal fat(%) and percentage of edible meat were extremely low at all times, but those between abdominal fat (%) and inedible viscera were significantly high.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.

• Journal of The Korean Society of Grassland and Forage Science
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• v.5 no.3
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• pp.200-206
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• 1985

This field experiment was undertaken to assess the effects of three levels of inclination ($10^{\circ},\;20^{\circ},\;and\;30^{\circ}$) and four rates of $N-P_2O_5-K_2O$ (0-0-0-, 14-10-10, 28-25-25, and 42-40-40kg/10a) on establishment, yield and quality, and botanical compositions of mixed grass-clover sward. This second part is concerned with the soil chemical properties, concentrations and uptake of mineral nutrients, and percent recovery and efficiency of NPK. The results obtained after a two-year experiment are summarized as follows: 1. The pH, exchangeable Mg and Na, and base saturation in the surface soils were decreased by increasing the grade of inclination, whereas organic matter and available $P_2O_5$ tended to be increased. However, the changes in the Ca content and equivalent ratio of $K\sqrt{Ca+Mg}$ were not significant. The pH, exchangeable Ca and Mg, and base saturation were reduced by increasing the NPK rate, whereas available $P_2O_5$, exchangeable K, and equivalent ratio of $K\sqrt{Ca+Mg}$ tended to be increased. 2. The concentrations of mineral nutrients in grasses and weeds were not significantly affected by increasing the grade of slope in hilly pasture, whereas the concentrations of N, K, and Mg in legume were the lowest with the steep slope, which seemed to be related to the low legume yield. The Mg concentrations of all forage species were below the critical level for good forage growth and likelihood of grass tetany. 3. The increase of NPK rate resulted in the increment of N, K and Na concentrations, and the decrease of Mg and Ca in grasses. The P concentration was increased with P application, but there were no differences in that among the P rates applied. It resulted also in a slight increase of K, and a decrease of Mg in legume, but the contents of N, Ca, and Na were not affected by that. On the other hand, it has not affected the mineral contents in weeds except a somewhat increase of N. The mixed forages showed a increase of N and K contents, a decrease of Ca and Mg, and a slight change in P and Na. 4. The percent recovery of N, P and K by mixed forages were greatly decreased by increasing the grade of inclination and NPK rate. They were high in the order; K>N>P. The efficiency of mixed NPK applications was decreased by that. The efficiency of mixed NPK fertilizers absorbed was slightly decreased by the increased rate of NPK, but it was not affected by the grade of inclination.

• Korean journal of food and cookery science
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• v.25 no.4
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• pp.488-495
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• 2009

Pork cutlet is a favorite deep fat fried food item among Korean children, and an excellent protein-containing food, and as well as a simple and economical cuisine. However, the frying process adds a significant amount of calories. We added MC (Methylcellulose) and HPMC (Hydroxypropyl Methylcellulose) to the batter in an effort to reduce oil uptake in prepared pork cutlets. After additions of MC and HPMC at concentrations of 0.5, 1, and 1.5% respectively, we assessed the viscosity of batter, color after frying, the increases in moisture retention and oil uptake, and sensory characteristics, comparing each quality. The viscosity of batter with 0.5% HPMC added (w/w) was similar to that of the controls, but the viscosity of all the batter with added MC was so much higher that it was difficult to use the batter for coating at the same temperature, leading to a failure even to prepare a sample. After frying, the batter with added HPMC provided significantly less oil uptake and more moisture retention than the batter to which MC was added. Additionally, with regard to color and sensory characteristics, the pork cutlet with 0.5% added HPMC was superior to the other samples. According to these results, we concluded that when cellulose derivatives are added in order to reduce oil uptake and to raise the moisture retention of the batter of pork cutlet, HPMC is more useful in this regard than MC. Additionally, the batter with 0.5% HPMC added appears to be the best of the tested choices, for three reasons: first, the viscosity of the batter is similar to that of the controls; second, the taste is not greasy after frying as the result of the reduced oil uptake and higher moisture retention; and third, the sensory characteristics of this sample, such as, color, crispiness, and hardness were the best among samples.

• Journal of Korean Historical Folklife
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• no.52
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• pp.7-46
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• 2017

The elderly in the Joseon Dynasty consistently attracted attention from the national herb as objects of social respect. Based on the Confucian ideology, the old man was considered to be a receiving body, since he was a person with complete character as a man. The elderly, who have the character of being a slave, transcended their status, and both the souls and the people were transcended beyond their identities and attributes and became objects of respect. The perception of the elderly is divided by age. The persons who are 50 years old and start to be in physical decline were regarded as senior citizens. However, this was just mentioned as an inflection point between the prime of manhood and senior citizens and was not defined as the elderly. As a public duty called a national work ends when they are 60 years old, the age is truly the lowest limit of senior citizens who are applicable to all the social beings. However, because their public duties end when they are 60 years old and they were regarded as general members of society, special benefits were not granted to them. In the caste system and bureaucratic society, senior citizens' treatment were differently done by age. For the senior citizens who are 70 years old, various benefits were just granted to high government officials. Bokho(復戶) and Seojeong were first given to them. And the retirement age of government officials was not specially set. It was done in the way to treat Jonno with exceptional respect by Chisa(致仕: regular retirement). It is the most respectful treatment given to high government officials and ministers. For the senior citizens who are 80 years old, Yangnoyeon(養老宴) was held for both of Yangmin and Cheonmin as an measure to treat them considerately. In addition, official ranks(官品) with social value were allowed by giving them Noinjik (老人職). Official ranks given to Seoin and Cheonin were the best Jonno(尊老) policy. However, the Jonno policy related to senior citizens was different according to position and official ranks as follows: Kings were subjected to social treatment when they were 60 years old. High government officials and royal relatives of the senior grade of the second court rank were subjected to social treatment when they were 70 years old. And general Seoin and slaves were subjected to social treatment when they were respectively 80 and 90 years old. Senior citizens were individually supported. However, social value was granted because the nation supervised it. As Bokho and Sijeong were assigned according to position and official ranks and kinds of things were different, the social limit was clearly shown. Social order was put above the ideology called Jonno thought. However, Jonno acts by age and position did not stay at the individual level and the nation took care of the senior citizens who are the members of society in various ways based on Jonno thought. Society tried to take care of the senior citizens who had difficulties in their activities because of being in physical decline. The nation increased the existence value of the senior citizens by giving things(賜物) including chairs, rice, meat, and ice economically, exoneration(免罪), the reduction system, and wergild legally, and Noinjik called Gaja(加資) socially to them and changing them to the members of society. Yangnoyeon and Gaja held targeting people of every class by transcending position and official ranks make the point that the senior citizens who are more than 80 years old are subject to social jonno clear. That is, the senior citizens were subject to respect for the elderly as the persons who were socially respected transcending their position when they got to be 80 years old.