• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.618-629
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• 2000

This study was carried out to investigate ecological niche of Quercus acuta communities in Bogildo-island from July to October, 1998. This island is occupied by a subtropical evergreen broad-leaved forests. The study on community ecology of Q. acuta, mostly dominant species of subtropical forests, is very important for successful forest management. Sampling areas were selected in 16 quadrats, dominated by Q. acuta to examine the vegetation characteristics(plant identification, D.B.H.) and environmental elements (microtopography, altitude, slope degree, aspect, illumination and soil physicochemical properties). On the basis of data from field surveys, importance values were calculated for the dominance of Q. acuta and volume growth was analyzed by tree ring widths. The results obtained were as follows ; 1. The lists of vascular plants in the investigations were identified as 54 families, 91 genera, 113 species, 9 varieties, 1 formae. It appeared that 45 kinds were evergreen, 6 kinds(Camellia japonica, Ligustrum japonicum, Eurya japonica, Smilax china, Trachelospermum asiaticum var. intermedium, Carex lanceolata) were commonly observed in all plots and 5 species(Cinnamomum japonicum, Ardisia japonica, Cymbidium goeringii, Dryopteris bissetiana, Viburnum erosum) were most highly observed in all plots(over 80%). 2. The dominating species per strata were, Quercus acuta, Castanopsis cuspidata sp. Quercus salicina, Pinus thunbergii, Prunus sargentii in tree layer, Camellia Japonica, Ligustrum japonicum, Quercus acuta, Eurya japonica, Castanopsis cuspidata sp. in subtree layer, Camellia japonica, Ligustrum japonicum, Smilax china, Cinnamomum japonicum, Viburnum erosum in shrub layer and Trachelospermum asiaticum var. intermedium, Ardisia japonica, Carex lanceolata, Camellia japonica(seedlings), Quercus acuta(seedlings) in herb layer, all in descending orders. 3. Quercus acuta could be suggested as shade intolerant tree, considering the distribution in southern, western, nothern and eastern slopes in the descending orders. 4. Mean relative illumination in the forest is 0.89 % and it is relatively low in brightness. 5. Sustainment of Quercus acuta community couldn't be confirmed by judging from their reverse J curve in even-aged forest, as shown in D.B.H. distribution analysis. 6. The result of annual ring width analysis(mean ; 2.44 mm) showed three stages, such as a gentle increasing(1~12 year ; 2.04 mm), a relatively steep increasing(13~22 year ; 2.95 mm) and decreasing or stagnating(23 year after ; 2.41 mm).

• 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 applied entomology
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• v.13 no.4 s.21
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• pp.181-204
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• 1974

The study has been carried out to investigate the occurrence, damage, host range, transmission and control of rice stripe virus in Korea since 1965. 1 Disease occur「once and damage : The virus infection during the seedling stage ranged from 1.3 to $8\%$. More symptom expression was found in regrowth of clipped rice than infected intact plants, and the greater infection took place in early seasonal culture than in ordinary seasonal culture. A higher incidence of the disease was found on the rows close to the bank, and gradually decreased toward the centre of the rice paddy. Disease occurrence and plant maturity was highly correlated in that the most japonica rice types were diseased when they were inoculated within 3 to 7 leaf stage, and$50\%$, $20\%$ and no diseaseb were found if they were inoculated at 9, 11 and 13 leaf stages, respectively. Symptom expression required 7-15 days when the plants were inoculated during 3-7 leaf stages, while it was 15-30days in the plants inoculated during 9-15 leaf stages. On Tongil variety the per cent disease was relatively higher when the plants were infected within 1.5-5 leaf stages than those at 9 leaf stage, and no disease was found on the plants infected after 15 leaf stage. The disease resulted in lowered growth rates, maturity and sterility of Tongil variety although the variety is known as tolerant to the virus. 2. Host range: Thirty five species of crops, pasture grasses and weeds were tested for their susceptibility to the virus. Twenty one out of 35 species tested were found to be susceptible. and 3 of them, Cyperus amuricus Maximowics var. laxus, Purcereus sanguinolentus Nees and Eriocaulon robustius Makino, were found as new hosts of the virus. 3. Transmission: The vector of the virus, Laodelphax striatellus, produces 5 generations a year. The peak of second generation adults occurred at June 20th and those of third was at about July 30th in Suweon area. In Jinju area the peak of second generation adult proceeded the peak at Suweon by 5-7 days. The peaak of third generation adult was higher than the second at Jinju, but at Suweon the reverse was true. The occurrence of viruliferous Laodelphax striatellus was 10-15, 9, 17, 8 and about $10\%$ from overwintered nymph, 1st generation nymph, 2nd generation adult, End generation nymph and the remaining generations, respectively. More viruliferous L. striatellus were found in the southern area than in the central area of Korea. The occurrence of viruliferous L. striatellus depended on the circumstances of the year. The per cent viruliferous vectors gin 2nd and 3rd generation adult, however, was consistantly higher than that of other generations. Matings of viruliferous L. striatellus resulted in $90\%$ viruliferous progenies, and the 3rd, 4th and 5th instars of the vector had higher infectiviey than the rest of the vector stages. The virus acquisition rate of non-viruliferous L. striatellus was $7-9\%$, These viruliferous L. striatellus, however, could not transmit the virus for more than 3 serial times. The optimum temperature for the transmission of the viru3 was $25-30^{\circ}C$, while rare transmission occurred when the temperature was below $15^{\circ}C$. The per cent of L. striatellus parasitization by Haplogonatopus atratus were $5-48\%$ during the period from June to the end of August, and the maximum parasitization was $32-48\%$ at around July 10. 4. Control: 1) Cultural practices; The deeper the depth of transplanting more the disease occurrence was found. The higher infection rate, $1.5-3.5\%$, was observed during the late stages of seedling beds, and the rate became lower, $1.0-2.0\%$, in the early period of paddy field in southern area. Early transplanting resulted in more infection than early seasonal culture, and the ordinary seasonal culture showed the lowest infection. The disease also was favored by earlier transplanting even under tile ordinary seasonal culture. The higher the nitrogen fertilizer level the more the disease occurrence was found in the paddy field. 2) Resistant varieties; Tongil varieties shelved the resistant reaction to the virus in greenhouse tests. In the tests for resistance on 955 varieties most japonica types shelved susceptible reactions, while the resistant varieties were found mostly from introduced varietal groups. 3) Chemical control; Earlier applications of chemicals, Disyston and Diazinon, showed better results when the test was made 4 days after inoculation in the greenhouse even though none of the insecticides shelved the complete control of the disease. Three serial applications of chemicals on June 14, June 20 and June 28 showed bettor results than one or two applications at any other dates under field conditions.