• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.125-132
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• 2007

We estimated the distribution of predator-prey interaction strengths for 12 species of herbivores (including amphipods, isopods, gastropods, and sea urchins) and made a regression model that may be applicable to other species. Laboratory experiments were used to determine per capita grazing rate (PCGR; g seaweeds/individual/day). Relationship between the biomass of individual grazers and fourth-root transformed PCGR was fitted to power curve ($y=0.2310x^{0.3290}$, r=0.8864). This finding supported that the grazing efficiency was not even as individual grazers increase in size (biomass). Therefore, the biomass-normalized PCGR was estimated and revealed that smaller size herbivores were more effective grazers. Grazing impact considering density of each taxon was calculated. The sea hare Aplysia kurodai had greatest grazing impact on the seaweed bed and the sea urchin Strongylocentrotus nudus and S. intermedius were ranked in descending order of the impact. The amount of seaweed grazed by the amphipod Elasmopus sp. (>4,000 $ind./m^2$) and Jassa falcata (>2,000 $ind./m^2$) were 3.435 and $1.697mg/m^2/day$ respectively. The combined grazing amount of herbivores was $5,045mg/m^2/day$ in the seaweed bed. Although sea hare and sea urchin had strong impacts on seaweeds, the effects of dense, smaller species could not be seen as negligible. Surprisingly, the calculated grazing potential of sea urchins with a mean density of 3 $ind./m^2$ exceeded the mean production of seaweed cultured in domestic coastal waters in Korea (ca., 5 ton/ha). Small crustaceans were also expected to consume up to 16% of the seaweed production if their densities were rising under weak predation conditions. Considering that the population density of herbivores are strongly controlled by fish, human interference like overfishing may have strong negative effects on persistence of seaweeds communities.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.5 no.1
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• pp.69-86
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• 1969

On the growing of the interspecific hybrid ginseng plant, the phenomena of hybrid vigoures are observed in the root, stem, and leaf, but it can not produce seeds favorably since the ovary is abortive in most cases in interspecific hybrid plants. The present investigation was undertaken in an attempt to elucidate the embryological dses of the seed failure in the interspecific hybrid of ginseng (Panax Ginseng ${\times}$ P. Quinque folium). And the results obtained may be summarized as follows. 1). The vegetative growth of the interspecific hybrid ginseng plant is normal or rather vigorous, but the generative growth is extremely obstructed. 2). Even though the generative growth is interrupted the normal development of ovary tissue of flower can be shown until the stage prior to meiosis. 3). The division of the male gameto-genetic cell and the female gameto-genetic cell are exceedingly irregular and some of them are constricted prior to meiosis. 4). At meiosis in the microspore mother cell of the interspecific hybrid, abnormal division is observed in that the univalent chromosome and chromosome bridge occure. And in most cases, metaphasic configuration is principally presented as 23 II+2I, though rarely 22II+4I is also found. 5). Through the process of microspore and pollen formation of F1, the various developmental phases occur even in an anther loclus. 6). Macro, micro and empty pollen grains occur and the functional pollen is very rare. 7). After the megaspore mother cell stage, the rate of ovule development is, on the whole, delayed but the ovary wall enlargement is nearly normal. 8). Degenerating phenomena of ovules occur from the megaspore mother cell stage to 8-nucleate embryo sac stage, and their beginning time of constricting shape is variously different. 9). The megaspore arrangement in the parent is principally of the linear type, though rarely the intermediate type is also observed, whereas various types, viz, linear, intermediate, Tshape, and I shape can be observed in hybrid. 10). After meiosis, three or five megaspore are some times counted. 11). Charazal end megaspore is generally functional in the parents, whereas, in F1, very rarely one of the center megaspores (the second of the third megaspore) grows as an embryo sac mother cell. 12). In accordance with the extent of irregularity or abnormality in meiosis, division of embryo sac nuclei and embryo sac formation cause more nucellus tissue to remain within th, embryo sac. 13). Even if one reached the stage of embryo sac formation, the embryo sac nuclei are always precarious and they can not be disposed to theil proper, respective position. 14). Within the embryo sac, which is lacking the endospermcell, the 4-celled proembryo, linear arrangement, is observed. 15). Through the above respects, the cause of sterile or seed failure of interspecific hybrid would be presumably as follows, By interspecific crossing gene reassortments takes place and the gene system influences the metabolism by the interference of certain enzyme as media. In the F1 plant, the quantity and quality of chemicals produced by the enzyme system and reaction system are entirely different from the case of the parents. Generally, in order to grow, form, and develop naw parts it is necessary to change the materials and energy with reasonable balance, whereas in the F1 plant the metabolic process becomes abnormal or irregular because of the breakdown of the balancing. Thus the changing of the gene-reaction system causes the alteration of the environmental condition of the gameto-genetic cells in the anther and ovule; the produced chemicals cause changes of oxidatio-reduction potential, PH value, protein denaturation and the polarity, etc. Then, the abnormal tissue growing in the ovule and emdryo sac, inhibition of normal development and storage of some chemicals, especially inhibitor, finally lead to sterility or seed failure. Inconclusion, we may presume that the first cause of sterile or seed abortion in interspecific hybrids is the gene reassortment, and the second is the irregularity of the metabolic system, storage of chemicals, especially inhibitor, the growth of abnormal tissue and the change of the polarity etc, and they finally lead to sexual defect, sterility and seed failure.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.