• Korean Journal of Soil Science and Fertilizer
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• v.39 no.6
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• pp.380-385
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• 2006

To establish law-put fertilization technique and increase of fertilization efficiency during cultivation of vinyl mulching for plant, the improvement of soil properties, nutrition efficiency and yields by band spotty fertilization(BSF) using band spotty applicator was carried out at garlic(Alltuiti sativum L.) field in Honam Agricultural Research Institute from 2001 to 2002 for 2 years. The value of pH and the content of total nitrogen, organic matter, exchangeable potassium and calcium of soil after experiment were increased but the content of available phosphate was decreased than soil before experiment. Uptake amounts of nitrogen fertilized by plants were more than in BSF plots($89{\sim}111kg\;ha^{-1}$) compared to in CF(conventional fertilization) Plot ($76kg\;ha^{-1}$) and nitrogen use efficiency were high in BSF plots(42.9~58.2%) compared to in CF plot(34.9%). Also Uptake amounts of potassium fertilized by plants were more than in BSF plots($34{\sim}58kg\;ha^{-1}$) compared to in CF plot($33kg\;ha^{-1}$) and potassium use efficiency were high in BSF plots(21.6~41.2%) compared to in CF plot(19.4%). Residual amount of nitrogen fertilized on soil were more than in BSF plots($38{\sim}54kg\;ha^{-1}$) compared to in CF plot($22kg\;ha^{-1}$) while loss amount of nitrogen fertilized on soil were less than in BSF plots($32{\sim}53kg\;ha^{-1}$) compared to in CF plot($120kg\;ha^{-1}$). Also Residual amount of potassium fertilized on soil were more than in 100% BSF plot($109kg\;ha^{-1}$) compared to in CF plot($72kg\;ha^{-1}$) while loss amount of nitrogen fertilized on soil were less than in BSF plots($14{\sim}38kg\;ha^{-1}$) compared to in CF plot($113kg\;ha^{-1}$). The BSF plots were increased plant height, leaf number, leaf sheath diameter, bulb diameter and height compared to CF plot. The total yields of garlic were more increased 14~19% because of high large bulb rate, commercial yields in 70, 100% BSF plots compared to in CF plot($102.9Mg\;ha^{-1}$). It was found that 70% band spotty fertilization was more effective as fertilization method to reduce both environmental pollution and chemical nitrogen fertilizer in plastic film mulching cultivation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.115-133
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• 2021

This study examines the concept and related technologies of the 4th industrial revolution that has been mixed so far and examines the socio-economic changes and influences resulting from it, and the cases of responding to the 4th industrial revolution in major countries. Based on this, by deriving SWOT factors and calculating the importance of each factor for Korean venture companies to prepare for the forth industrial revolution, it was intended to help the government and policymakers in suggesting directions for establishing related policies. Furthermore, the purpose of this study was to suggest a direction for securing global competitiveness to Korean venture entrepreneurs and to help with basic and systematic analysis for further academic in-depth research. For this study, a total of 21 items derived through extensive literature research and data research to understand what are the necessary competency factors for internal and external environmental changes in order for Korean venture companies to have global competitiveness in the era of the 4th Industrial Revolution. After reviewing SWOT factors by three expert groups and confirming them through Delphi survey, the importance of each item was analyzed by using AHP, a systematic decision-making technique. As a result of the analysis, it was shown that Strength(48%), Opportunity(25%), Threat(16%), Weakness(11%) were considered important in order. In terms of sub-items, 'quick and flexible commercialization capability', 'platform/big data/non-face-to-face service activation', and 'ICT infrastructure and it's utilization' were shown to be of the comparatively high importance. On the other hand, in the lower three items, 'macro-economic stability and social infrastructure', 'difficulty in entering overseas markets due to global protectionism', and 'absolutely inferior in foreign investment' were found to have low priority. As a result of the correlation verification by item to see differences in opinions by industry, academia, and policy expert groups, there was no significant difference of opinion, as industry and academic experts showed a high correlation and industry experts and policy experts showed a moderate correlation. The correlation between the academic and policy experts was not statistically significant (p<0.01), so it was analyzed that there was a difference of opinion on importance. This was due to the fact that policy experts highly valued 'quick and flexible commercialization', which are strengths, and 'excellent educational system and high-quality manpower' and 'creation of new markets' which are opportunity items, while academic experts placed great importance on 'support part of government policy', which are strengths. The implication of this study is that in order for Korean venture companies to secure competitiveness in the field of the 4th industrial revolution, it is necessary to have a policy that preferentially supports the relevant items of strengths and opportunity factors. The difference in the details of strength factors and opportunity factors, which shows a high level of variability, suggests that it is necessary to actively review it and reflect it in the policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.29-37
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• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.339-345
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• 2018

The sugar beet cyst nematode (SBCN), Heterodera schachtii first detected in Taebaek, Gangwon-do in 2011, is one of the major plant parasitic nematodes that cause economic damage to the Chinese cabbage in highland regions. In addition, the distribution of clover cyst nematode (CCN), H. trifolii was confirmed in the highland Chinese cabbage cultivated regions in 2017. In order to investigate the spread of cyst nematodes, this study has been conducted since 2013 in the highland Chinese cabbage cultivation area. In addition, in 2017, the Real-Time PCR technique with the species-specific primer was used to investigate those two cyst nematodes and the soybean cyst nematode (SCN), H. glycines which is known for its distribution in Korea, focusing on the main production regions of highland Chinese cabbage cultivation. The number of infected fields in the Chinese cabbage plantation in highland increased every year to confirm distribution in Taebaek, Samcheok, Jeongseon and Gangneung in 2017, and the cumulative number of infection fields reached 245 by 2017. Of the 41 possible cyst nematode samples for PCR analysis, 61% were CCN, only 9.8% of the SBCN and 29.3% of the SCN were identified. Therefore, some of the previously known SBCN or CCN discoveries are likely to have been infected with SCN. It is believed that the CCN needs to be controlled in the future as CCN have been found to be dominant species in the highland Chinese cabbage plantation regions.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.201-220
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• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Korean Journal of Animal Reproduction
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• v.24 no.1
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• pp.89-95
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• 2000

This study was to establish an effective dilution technique in a vitrification of bovine blastocysts for the field trial. For vitrification, blastocysts were exposed in glycerol (G) and ethylene glycol (EG) mixture in m-DPBS supplemented with 10% FBS. Blastocysts were first exposed to 10% (v/v) G for 5 min, and subsequently were transferred to 10% G plus 20% EG (v/v) for 5 min. Finally, embryos were transferred to 25% G plus 25% EG (v/v) for 30 see and were placed in nitrogen vapor for 3 min, and then were plunged into L$N_2$. At thawing, the straw containing blastocysts was placed in air for 10 sec, and then plunged into a water bath at $25^{\circ}C$ until all ice had disappeared. They were placed in $25^{\circ}C$ and 36$^{\circ}C$ water according to treatment group for different time. Also, in vitro survival was assessed by the re-expansion and hatched rates at 24 hand 48 h postwarming, respectively. The results obtained in these experiments were summarized as follows; 1) In the survival rates of vitrified bovine blastocysts according to different dilution time at thawing, the data of 1 min group (86.6, 56.6%) were higher than those of other treatment groups (2 min; 93.5, 35.4%, 2.5 min; 76.9, 30.7%, 3 min; 88.8, 36.1% and 3.5 min; 83.7, 8.1%). 2) When the in vitro survival of vitrified groups according to different developmental stage was examined at 48 h after thawing using 1 min dilution method, the hatching rates of fast developed embryos (expanded blastocyst: 81.3%: early hatching blastocyst: 86.2%) were higher than that of delayed developed one (early blastocyst: 46.6%). 3) In addition, when the in vitro survival of vitrified groups according to different embryo age was compared, the hatched rates at 48 h after thawing of Day 7 (66.6%) and Day 8 embryos (60.0%) were significantly higher than that of Day 9 embryos (22.7%) (P＜0.05). These results demonstrate that vitrified bovine IVM/IVF/IVC blastocysts can be successfully survived in vitro using one-step dilution (1 min) method.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.172-203
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• 2023

<Cheongdamdo>(true-view landscape painting) was identified in this study to be a folding screen painting painted by Jeong Seon(a.k.a. Gyeomjae, 1676~1759) in the 32nd year of King Yeongjo(1756) while exploring the Cheongdam area located in Mt. Bukhansan near Seoul. Cheongdam Byeol-eop(Korean villa), consisting of Waunru Pavilion and Nongwolru Pavilion, was a cultural and artistic base at that time, where Nakron(Confucian political party) education took place and the Baegak Poetry Society met. <Cheongdamdo> is a painting that recalls a period of autumn rainfall in 1756 when Jeong Seon arrived in the Cheongdam valley with his disciple Kim Hee-sung(a.k.a. Bulyeomjae, 1723~1769) and met Hong Sang-han(1701~1769). It focuses on the valley flowing from Insubong peak to the village entrance. The title has a dual meaning, emphasizing "Cheongdam", a landscape feature that originated from the name of the area, while also referring to the whole scenery of the Cheongdam area. The technique of drastically brushing down(刷擦) wet pimajoon(hanging linen), the expression of soft horizontal points(米點), and the use of fine brush strokes reveal Jeong Seon's mature age. In particular, considering the contrast between the rock peak and the earthy mountain and symmetry of the numbers, the attempt to harmonize yin and yang sees it regarded as a unique Jingyeong painting(眞境術) that Jeong Seon, who was proficient in 『The Book of Changes』, presented at the final stage of his excursion. 「Cheongdamdongbugi」(Personal Anthology) of Eo Yu-bong(1673~1744) was referenced when Jeong Seon sought to understand and express the true scenery of Cheongdam and the physical properties of the main landscape features in the villa garden. The characteristics of this garden, which Jeong Seon clearly differentiated from the field, suppressed the view of water with transformed and exaggerated rocks(水口막이), elaborately creating a rain forest to cover the villa(裨補林), and adding new elements to help other landscape objects function. In addition, two trees were tilted to effectively close the garden like a gate, and an artificial mountain belt(造山帶), the boundary between the outer garden and the inner garden, was built solidly like a long fence connecting an interior azure dragon(內靑龍) and interior white tiger(內白虎). This is the Bibo-Yeomseung painting(裨補厭勝術) that Jeong Seon used to turn the poor location of the Cheongdam Byeol-eop into an auspicious site(明堂). It is interpreted as being devised to be a pungsu(feng shui) trick, and considered an iconographic embodiment of ideal traditional landscape architecture that was difficult to achieve in reality but which was possible through painting.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.