• Korean Journal of Environmental Agriculture
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• v.23 no.4
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• pp.203-210
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• 2004

This study was conducted to assessment organic compound and bioassay (density of inhabited animal, fluctuation of predominant fungi, and survival ratio of earthworm) for finding damage on red pepper by heavily amount application of sludges in soil, which was treated with 3 pharmaceutical byproducts and a cosmetic industry wastewater sludge as raw materials of compost, and for establishing estimation method. HEM contents in the soil treated with pharmaceutical byproducts sludge2 (PS2) and cosmetic sludge (CS) were 0.51, 1.10 mg/kg respectively. PAHs content of PS2 treatment in the soil was 3406.8 ug/kg on July 8. In abundance of soil faunas, the pharmaceutical byproducts sludge2 treatment was the most highest. The next was decreased in the order of pig manure (PM) and the cosmetic sludge treatment. However the other pharmaceutical sludge treatments were remarkably reduced populations of soil inhabited animals. In upland soil treated with organic sludges, the numbers of bacteria and fungi of the pharmaceutical sludge treatment were 736, 909 cfu/g and those of the cosmetic sludge treatment were 440, 236 cfu/g, respectively. The pharmaceutical sludge treatments and the cosmetic sludge treatment in identification of predominant bacteria were not any tendency to compare with non fertilizer and pig manure treatments, but they had diverse bacteria than NPK treatment. In microcosm tests, the survival of the tiger earthworm in five soil samples was hardly affected against the soil of PSI (20%) after three months treated in the upland But after six months, survival of PS1 was 80%. At present, raw material of compost was authorized by contents of organic matter, heavy metal (8 elements), and product processing according to 'The specified gist on possible materials of using after analysis and investigation among raw materials of compost', however, for preparing to change regulation of raw material of compost and for considering to possibility of application, this study was conducted to investigate toxic organic compound and bioassay methods using inhabited animal, fungi, and earthworm without current regulation.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

• Korean Journal of Agricultural Science
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• v.5 no.2
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• pp.93-114
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• 1978

The purpose of the study was to find out possible ways for increasing farm income through the sheep and Korean native goats farming, and to investigate meat productivity, wool productivity; woolskin utility, physiological characteristics and correlation between economical college animal farm of the Chungnam National University and sample farms in the suburbs of Dae jeon City were selected for feeding 20 heads of Corriedale wethers and another 20 heads Korean native kids as research materials for the periods of 5th May-26th November, 1977. The data such as growth rate, carcass, viscera weight, blood picture and plamsa components, hebage intake and economic traits were obtained and analysed. The result of the study are summarized as follows: 1. Meat production and quality 1) After 196days of feeding, the body weight of sheep and Korean native goats was increased by two times of those at the beginning of the trial, i.e. 20kg and 8kg respectively. 2) There was no significance of growth rates of sheep in housing and grazing. 3) The growth rate of Korean native goats were excellent at the mountainous areas of Gong ju-Gun where infectious diseases were not found 4) Accroding to the body measurements of 18-month-old sheep, percentages of hip height, body length, rump length, chest depth, chest width, hip width, chest girth and forearm circumference to the withers height were 103,%, 104%, 33%, 44%, 31%, 23%, 135% and 15% respectively, and those of hip height, body length, chest depth and chest girth of 8-month-old native goats to the withers height were 106%, 109%, 46% and 122,% respecitively. As a result, it was found that the percentage of hip height, body length and chest depth of Korean native goats were higher than those of sheep while that of the chest girth of goats was lower. 5) In the carcass data, 47, $52{\pm}2.27%$ of carcass percentage, $34.61{\pm}1.62%$ of lean meat, $26.07{\pm}2.51%$ of viscera, $9.75{\pm}1.4%$ of bone, and $20.95%{\pm}2.14%$ of woolskin for sheep, and $45.58{\pm}5.63%$ of carcass percentage, $27.62{\p}3.81%$ of meat, $34.86{\pm}4.16%$ of viscera, $11.66{\pm}1.83%$ of bone, $3.63{\pm}1.61%$ of skull and $9.26{\pm}2.41%$ of woolskin for native goats were obtained. 6) The contents of moisture, crude protein, crude fat and crude ash in native goat meat were much similar in both plots of housing and grazing. It was, however, known that the contents of moisture and protein were higher in grazinrg than in housing, while fat content was lower in grazing plots. 7) The weights of visceral organs shown similar tendency for both of sheep and native goats. For the weights of liver, heart, kidney and spleen, significance was not reconized among the treatments. Those of rumen, reticulum, small and large intestine were heavier in grazing than in housing, while the amount of visceral fat was heavier in housing. 2. Wool productivity and woolskin 1) The wool production of sheep for 7 months was $3.88{\pm}1.02kg$, and wool percentage, staple length, straighten length, wool growth per day and number of crimps were $9.27{\pm}1.48%$, 8. $47{\pm}1.00cm$, $10.63{\pm}0.99cm$, $0.40{\pm}0.04cm$ and $2.78{\pm}0.40$ respecitively. 2) The tensile strength and tear strength of woolskin treated by alum tanning were highest on the skin obtained from rump, i.e. $1,351kg/mm^2$ and $2,252kg/mm^2$ respectively, and they are in order of loin and shoulder. 3. Utilization and improvement of pasture. 1) The difference of herbage intake of native goats was not recognized between grazing and tethering, but the intake in the afternoon was s lightly higher than that in the morning. However the hervage intake of sheep was superior in grazing and in the afternoon. 2) The cultivation effect was lower in the native goat plots due to their cultivation abilities, in other words, the establishment rates of pasture by hoof cultivation were 60.25% in the goat plots and 77.35% in the sheep plots. 4. Correlation among economical traits. 1) The correlation between live weight of sheep and daily gain was higher. On the other hand, the correlation between other traits was not significant except that live weight, daily gain and lean meat percentage to the length of thoracic vertebrae. The live weight of native goats and meat production were highly correlated, and high correlation was also found between weights of carcass and meat. However, negative correlation was shown between viscera weight and live weight as well as daily gain. 2) The correlatoin between fleece weight of sheep and other traits such as live weight, daily gain and fleece percentage is very high at the 1% siginficant level, and this means that rapid-growth individuals can produce much fleece. 3) The correlation between the factors such as weights of live body, lean meat and viscera of sheep and body measurements, i. e. chest girth and body length was highest, and weights, of carcass and lean meat was highly correlated to chest width and depth. It will be therefore reasonable that the meat productivity estimates will have to be made on the basis of chest girth and body length. The meat production traits of native goats were highly correlated to the most of body measurement data, and the correlation coefficient between chest girth and weights of live body, carcass, lean meat and bone percentage was very high, i. e. 0.992-0.974 in particular. The correlations of meat production traits to chest depth, forearm circumference, body length were 0.759-0.911, 0.759-0.909 and 0.708-0.872 respectively. Therefore, the meat production of native goats will have to be estimated on the basis of chest data. 5. Blood picture and plasma components. 1) The number of erythrocyte and MCHC of native goats were $12.93{\times}10^6/mm^3$ and 36.14%, and those of sheep were $10.68{\times}10^6/mm^3$ and 36.26 respectively. The values of native goats were significantly higher than those of sheep. 2) The hemoglobin concentration, PVC, MCV and MCR of native goats were 10.92 g/100ml, $23.40{\mu}^3$ and 10.94 pg, and those of sheep were 11.73 g/100ml, 36.25 ml/100ml, $33.97{\mu}^3$ and 30.2 ml/100ml 8.43 pg respectively. The values of native goats were significantly lower those of sheep. 3) The number of leukocytes of native goats was significantly higher than that of sheep, that is, $11.64{\times}10^3/mm^3$ in native goats and $9.32{\times}10^3/mm^3$ in sheep. 4) In differential count of leukocyte, neutrophil was significantly high in native goats while lympocyte in sheep. On the other hand, the basophil, eosinophil and monocyte were not significant between native goats and sheep. 5) The amounts of total protein and glucose in the plasma of native goats were 6.2g/100ml and 53.6mg/100ml, and those of sheep were 5.6g/100ml and 45.7mg/100ml, which means that the values of native goats were significantly higher that those of sheep. The amount of total-lipid of native goats(127.6mg/100ml) was significantly than that of sheep(149.6mg/100ml). 6) The amount of non-protein nitrogen, cholesterol, Ca, P, K, Na and Cl were not different between native goats and sheep. 6. Economic analysis. 1) The gross revenue of a farm which fed native goats and sheep was 4,000won per head and the optimum size for feeding them in a farm as a subsidiary work is 5-10 heads. 2) Since there was no difference between housing and grazing, they can be fed in group for farm's subsidiary work. 3) They can be also fed by youths and house wives in the suburbs of cities, because labour requirement is estimated as only two hours per days for feeding 5 heads of native goats and sheep.