• KOREAN JOURNAL OF CROP SCIENCE
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• v.24 no.4
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• pp.83-114
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• 1979

These studies were, aimed at clarifying the relationship between the spring(winter) habits and the metabolism during the differentiation and development of young spike in naked barley. The pattern of change of nucleic phosphorus was paralleled to that of insoluble nitrogen in the normal heading type, showing their increase in the young spike and their decrease in the leaf at the stage of double ridges differentiation, respectively. However, in the rosetted type nucleic phosphorus remained at a constantly low level in both the young spike and the leaf, and insoluble nitrogen showed a considerably lower content in the young spike but a remarkable higher content in the leaf than that of the normal type. In addition to nucleic phosphorus and insoluble nitrogen, there were significant differences between the normal and the rosetted type in the content levels of PCA-soluble phosphorus, nonreducing sugar, crude starch and so on. Particularly, these differences were found even in the stage of bract differentiation, the vegetative phase, as well as in the reproductive phase. It appeared that nucleic phosphorus and insoluble nitrogen were closely concerned with the differentiation of double ridges, regardless of the varieties which are different in their spring habits.

• Korean Journal of Plant Resources
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• v.22 no.1
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• pp.49-70
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• 2009

Floral study on the vegetation of 8 mountains including Taehwa-san, Mugab-san, Haehyeob-san, Guksa-bong, Gwanggyo-san, Samseong-san, Suri-san, and 200m peak neighboring to Mulwang lake was carried out from April to October, 2007. They belong to the middle part of Gyeonggi Province, and located between Lat. $37^{\circ}$13' 31.19" ${\sim}37^{\circ}$33' 3.48", Long. $26^{\circ}$43' 04.1" ${\sim}127^{\circ}$26' 28.38". Vascular plants collected in these areas were total 447 taxa composed of 386 species, 5 subspecies, 46 varieties and 10 forms of 262 genera under 92 families. The area from which the most plentiful plants were found was Mt. Gwanggyo-san. The areas with comparatively excellent vegetation are easy slopes nearby valleys in Mt. Gwanggyo-san, Mt. Suri-san and Mt. Haehyeob-san. Forests of the examined areas are generally mixed of Pinus densiflora and Quercus plants, but herbaceous plants covering soil are becoming nearly extinct by air and soil pollutions except some sites. Families with abundant species are Compositae, Rosaceae, Liliaceae and Graminae, etc. Endemic plants found in these areas are 8 taxa of Clematis brachyura, Euonymus trapococcus, Viola seoulensis, Ajuga spectabilis, Scutellaria insignis, Weigela subsessilis, Aster koraiensis, Aconitum chiisanense and rare and endangered plants are 7 taxa of Arisaema heterophyllum, Iris odaesanensis, Eranthis stellata., Aconitum chiisanense, Prunus yedoensis (cultivar), Viola albida, and Syringa wolfi. As to useful plants, 192 taxa for the edible, 132 taxa for the medicinal, 130 taxa for the ornamental and 11 taxa for the staining were classified respectively. Among 17 taxa of specially designated plants, 5th degree plants are 2 taxa of Iris odaesanensis and Prunus yedoensis (cultivar), 4th degree plants are 2 taxa of Symplocarpus renifolius and Syringa wolfi, 3rd degree plants are 13 taxa of Dryopteris gymnophylla, Juniperus chinensis, Betula chinensis, Betula davurica, Diarrhena fauriei, Aconitum longecassidatum, Eranthis stellata, Spiraea salicifolia, Acer palmatum, Vaccinium koreanum, Scutellaria insignis, Weigela florida and Adoxa moschatellina.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.107-121
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• 2010

We conducted a sensitivity test of Joint UK Land Environment Simulator (JULES), in which the influence of biophysical parameters on the simulation of gross primary productivity (GPP) and ecosystem respiration (RE) was investigated for two typical ecosystems in Korea. For this test, we employed the whole-year observation of eddy-covariance fluxes measured in 2006 at two KoFlux sites: (1) a deciduous forest in complex terrain in Gwangneung and (2) a farmland with heterogeneous mosaic patches in Haenam. Our analysis showed that the simulated GPP was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration for both ecosystems. RE was sensitive to wood biomass parameter for the deciduous forest in Gwangneung. For the mixed farmland in Haenam, however, RE was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration like the simulated GPP. For both sites, the JULES model overestimated both GPP and RE when the default values of input parameters were adopted. Considering the fact that the leaf nitrogen concentration observed at the deciduous forest site was only about 60% of its default value, the significant portion of the model's overestimation can be attributed to such a discrepancy in the input parameters. Our finding demonstrates that the abovementioned key biophysical parameters of the two ecosystems should be evaluated carefully prior to any simulation and interpretation of ecosystem carbon exchange in Korea.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.11
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• pp.599-606
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• 2017

The effects of microbubble-oxygen physicochemical method for the removal of organic pollutants, nitrogen, and phosphorus contained in animal manure were investigated using a laboratory scale single reactor. The characteristics of used livestock manure were $36,894{\pm}5,024mg\;TCOD/L$, $22,031{\pm}2,018mg\;SCOD/L$, $4,150{\pm}35mg\;NH_4-N/L$, and $659{\pm}113mg\;PO_4-P/L$. It was confirmed that the amount of organic pollutants, nitrogen, and phosphorus removal was increased by the use of oxygen rather than air as the gas supplied with the microbubble, and by input of larger oxygen amount. When the oxygen was fed with 600 mL flow rate per minute, TCOD and phosphorus removal were 2.5 times and 5.6 times higher than those of air supplied. As the microbubble-oxygen reaction time was longer, the removal rate of nutrients increased gradually. The removal rates of ammonium and phosphorus reach to $41.03{\pm}0.20%$ and $65.49{\pm}1.39%$, respectively, after 24 hours. When the coagulation treatment method was applied to increase phosphorus removal rate from the effluent of microbubble-oxygen treatment, the phosphorus was removed up to 92.7%. However, the removal rate of organic pollutants (TCOD) was as small as $28.7{\pm}0.2%$ within the first 6 hours, and then the negligible removal of TCOD was recorded. This study suggests that microbubble-oxygen can be applied not only livestock manure but also aeration tank of various wastewater treatment plant, which can reduce the load on the associated unit process and produce stable high-quality effluent.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.479-488
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• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.131-143
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• 2021

In this study, the factors influencing the satisfaction of the online platform musical viewing method were investigated, and the effect of the satisfaction factors on the recommendation intention and rewatching intention of the online platform viewing method for musicals was investigated. In addition, the effect of the survey subjects' degree of involvement to musicals between the satisfaction of the online platform-based musical viewing method and recommendation intention, and rewatching intention was investigated. Satisfaction factors of online platform musicals, which are independent variables, were classified into image quality, convenience, economy, and interactivity, and dependent variables were classified into recommendation intention and rewatching intention of online platform musicals, and moderator variable was set to degree of involvement to musicals, and a total of 20 hypotheses were established. An online survey was conducted on 1,454 audiences who had experience watching musicals through the online platform from August 28 to September 7, 2021, and a total of 1,418 answers were used as valid samples. As a result of the analysis, the factors that make up the satisfaction of online platform musicals appeared in the order of convenience, video quality, economics, and interactivity. It was found that the satisfaction level of watching online platform musicals had a positive effect on the intention to recommend and rewatching online platform musicals in the path of all satisfaction factors. It was found that the moderating effect of the audience's involvement in musicals between online platform musical viewing satisfaction and recommendation intention and rewatching intention had a significant effect only between image quality and recommendation intention. It shows that audiences with high involvement in musicals have intention to recommend only when they are satisfied with the video quality of online platform musicals. Particularly important point is that the convenience factor was found to have the greatest influence on the satisfaction of online platform musical viewing method, but the image quality factor was found to have the greatest influence on the recommendation intention and rewatching intention of online platform musicals.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.30 no.3
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• pp.252-258
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• 1985

An experiment was conducted at the Yeongnam Crop Experiment Station to obtain basic informations about cultural techniques for high yielding by manipulating plant spacing using two rice cultivars, Samgangbyeo (Indica/Japonica type) and Nakdongbyeo (Japonica type), and four plant spacings, 10${\times}$10cm, 20${\times}$20cm 30${\times}$30cm and 40${\times}$40cm, with 4 kinds of seedling number per hill, 1,3,5 and 7, respectively. High photosynthetic efficiency (Eu) exhibited at the Samgangbyeo compared to Nakdongbyeo regardless of plant spacings and seedling numbers. For Samgangbyeo, Eu value was the highest at the 20${\times}$20cm plant spacing and five seedlings and seven seedlings per hill showed high Eu values at 10${\times}$10cm plant spacing and 20${\times}$20cm plant spacing, respectively, while other plant spacings were not significantly differed among seedling numbers. For Nakdongbyeo, however, one seedling plot obtained high Eu value at the 10${\times}$10cm plant spacing while this Eu value increased as the seedling number per hill increased in other plant spacings. There was a high positive correlation between rice grain yield and total competition index for both cultivars while kind of relationships differed in these two cultivars; linear relationship for Samgangbyeo and exponential relationship for Nakdongbyeo, respectively. Competition index between rice hill was more significant than within rice hill for Samgangbyeo while both competition indexs were important for Nakdongbyeo to increase rice yield.

• Korea Science and Art Forum
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• v.32
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• pp.319-334
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• 2018

This research is a case study to make sure the enhancement of students' imagination and creativity through developing and applying the Literature-Art-Science Integrated Education Program. Its research object was totally 25 persons of 29 students of the 1st to the 4 th Grades from Gunsan Sulsan Elementary School. Its research period lasted for 4 months from September to December, 2017, and I, as the research place, used the art room at Gunsan Sulsan Elementary School. The programs were totally 10 sessions with a unit of 1 session per each grade for 2 hours from 1:00 to 3:00 in the afternoon from Monday through Friday. I fixed ten themes of this program-eight plane modeling, and two solid modeling, and finished the work of storytelling during summer vacation. And I arranged their levels as low:middle:high(3:5:2) ones. The former was 'A Film of Monster Gorilla'(L), 'Learning the Spirit of Gyeongju Choi's Family'(M), 'A Tale of My Friend Made of Natural Materials'(L), 'The Reading of My Dream'(M), 'Gathering the Objects in My Mobile'(M), 'A Mock Trial of Marrying Off'(M), 'Painting My Favorite Children's Poem'(H), and 'Painting My Favorite Children's Song'(H), and the latter was 'Seeking for a Bluebird in My Mind'(L), and 'Making My Cherished Object' (M). Then I used the unique art expression technique per each theme, which were in sequence marbling, Korean paper art, combine painting, collage, imaginary painting, imaginary painting, play dough art, imaginary painting techniques. And I delivered to the students the scientific knowledge in terms of growing or manufacturing processes of materials used for making artworks. Prior to and after the processing this program, I surveyed about the students' ability of integrated thinking and emotional experience by 'Figure B Type' and 'Figure A Type' of The Torrance Tests of Creative Thinking, and took statistics with the resultant data. And I executed a paired t-test in order to verify the significance of mean difference in the result of investigation with those data. From the analyzed result according to the elements of creativity and the mean quotients of creativity, there showed a significant difference (t=3.47, p<.01) in 'fluency', and also a significant difference(t=3.59, p<.01) in 'creativity.' Judging from the statistic values of two fields such as the student's ability of integrated thinking and emotional experience, I estimate that over the majority of the students showed the enhancement in self-confident creative expression as well as higher interest and concern through this program. The result that I arranged and analyzed the making process of artworks, the photos of the resultant, etc. as such is as follows : Firstly, from this program being proceeded as art-centered STEAM class, the student's systematic problem-solving ability was improved in his ability of integrated thinking to transform the literary contents into artistic one. Secondly, the student obtained the emotional experience such as interest in the class, self-confidence, intellectual satisfaction, self-fulfillment, etc. through art-centered STEAM class using ten art expression techniques. Thirdly, the student's mind willing to cooperate, communicate with his friends, and care for them was ripened in the process of problem-solving. Fourth, the student's self-confidence was further instilled when presenting famous artists and their artworks in the introduction and finale of ten art expression techniques. Likewise, the statistic values on the fields of student's ability of integrated thinking and emotional experience illustrate that over the majority of the students showed improvement in the ability of creative expression with confidence as well as higher interest and concern upon this program.