• Journal of Bio-Environment Control
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• v.19 no.4
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• pp.351-359
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• 2010

To establish the optimum artificial light illumination method for baby leaf lettuce in closed plant factory system, the effects of red/blue light quality and short-term light quality conversion on growth and anthocyanin content were investigated. The growth of 'Hongha' lettuce was most favorable under red single wavelength LED light after 23 days of treatment, sequentially followed by the growth under red/blue mixed light, blue light, and fluorescent light. Total anthocyanin content in the mixed red/blue light (R57-B43) was 4.1-fold and 6.9-fold increased compared to the red LED and fluorescent light, respectively. With increasing the blue light ratio to 43%, the growth of lettuce was significantly decreased, while the relative chlorophyll content and Hunter's $a^*$ value was increased, indicating that the red/blue light ratio inversely affects on growth and anthocyanin pigment development. By changing light quality from red to red/blue mixed light source (R57-B43) for 9 days before harvest, the growth rate decreased compared to the continuous red light illumination, while the anthocyanin content dramatically increased compared to either red LED or fluorescent light. Whereas, when the light source was changed to red light, the growth rate was increased but anthocyanin content was reversely decreased. The result demonstrated that both growth and anthocyanin expression could be effectively regulated by shifting of light quality between red and red/blue mixed light source at a specific growth stage of lettuce in a plant factory.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.121-131
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• 2009

In recent years, microtremor array observations have been used for estimation of shear-wave velocity structures. One of the methods is the conventional spatial autocorrelation (SPAC) method, which requires simultaneous recording at least with three or four sensors. Modified SPAC methods such as 2sSPAC, and linear array methods, allow estimating shear-wave structures by using only two sensors, but suffer from instability of the spatial autocorrelation coefficient for frequency ranges higher than 1.0 Hz. Based on microtremor measurements from four different size triangular arrays and four same-size triangular and linear arrays, we have demonstrated the stability of SPAC coefficient for the frequency range from 2 to 4 or 5 Hz. The phase velocities, obtained by fitting the SPAC coefficients to the Bessel function, are also consistent up to the frequency 5 Hz. All data were processed by the SPAC method, with the exception of the spatial averaging for the linear array cases. The arrays were deployed sequentially at different times, near a site having existing Parallel Seismic (PS) borehole logging data. We also used the imaginary part of the SPAC coefficients as a data-quality indicator. Based on perturbations of the autocorrelation spectrum (and in some cases on visual examination of the record waveforms) we divided data into so-called 'reliable' and 'unreliable' categories. We then calculated the imaginary part of the SPAC spectrum for 'reliable', 'unreliable', and complete (i.e. 'reliable' and 'unreliable' datasets combined) datasets for each array, and compared the results. In the case of insufficient azimuthal distribution of the stations (the linear array) the imaginary curve shows some instability and can therefore be regarded as an indicator of insufficient spatial averaging. However, in the case of low coherency of the wavefield the imaginary curve does not show any significant instability.

• Korean Journal of Plant Resources
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• v.28 no.5
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• pp.574-581
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• 2015

This study describes a preliminary evaluation of the anti-inflammatory activity of Acrosorium yendoi Yamada extracts. A. yendoi Yamada was extracted using 80% ethanol and then fractionated sequentially with n-hexane, ethyl acetate and butanol. To screen for anti-inflammatory agents effectively, we first examined the inhibitory effect of 80% EtOH extract and solvent fractions of A. yendoi Yamada on the production of pro-inflammatory factors and cytokines stimulated with lipopolysaccharide. In addition, we examined the inhibitory effect of 80% EtOH extract and solvent fractions of A. yendoi Yamada on pro-inflammatory mediators (NO, iNOS, PGE₂, and COX-2) in RAW 264.7 cells. In the sequential fractions of n-hexane and EtOAc inhibited the NO and PGE₂ production and the protein level of iNOS and COX-2, and protein expression of pro-inflammatory cytokines (TNF-α, and IL-6). These results suggest that A. yendoi Yamada may have significant effects on inflammatory factors and may be provided as possible anti-inflammatory therapeutic seaweed.

• Journal of Life Science
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• v.32 no.12
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• pp.929-937
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• 2022

To investigate the anti-inflammatory activity of the grains of sorghum, three Sorghum bicolor (L.) Moench variants (Hwanggeumchal, Huinchal, and Chal) being cultivated in Korea, the 80% ethanol (EtOH) extracts of individual sorghum grains were compared for their inhibitory activity against nitric oxide (NO) production in lipopolysaccharide (LPS)-stimulated RAW264.7 murine macrophage cell line. Among them, the EtOH extract of sorghum Hwanggeumchal grains could exert the highest inhibitory effect on the LPS-induced NO production. However, under these conditions, the viability of RAW264.7 cells was not affected. When the EtOH extract of sorghum Hwanggeumchal grains was sequentially fractionated with n-hexane, methylene chloride (MC), ethyl acetate (EtOAc), and n-butanol, the anti-NO production activity was predominantly detected in both MC and EtOAc fractions. In particular, treatment with the MC fraction reduced dose-dependently the expression levels of iNOS, COX-2 and pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) in LPS-stimulated RAW264.7 cells. Simultaneously, the MC fraction could prevent LPS-induced activating phosphorylation of p38 mitogen-activated protein kinase (MAPK), c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK). HPLC analysis of the MC fraction showed gentisic acid and naringenin as the major phenolic components. Both gentisic acid and naringenin commonly exhibited a potent inhibitory activity against LPS-induced NO production in RAW264.7 cells. Together, these results provide the evidence of the inhibitory activity of Hwanggeumchal grains on LPS-induce inflammatory responses in RAW264.7 murine macrophage cells and also suggest that sorghum grains possess beneficial health effects which can be applicable in development of the grain-based functional foods.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.14 no.1
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• pp.12-25
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• 2003

Objectives：As increasing number of new antidepressants have been being introduced in clinical practice, pharmacological understanding has been broadened. These changes mandate new information and theories to be incorporated into the treatment process of children with depressive disorders. In light of newly coming knowledge, this review intended to recapitulate the characteristics of new antidepressants and to consider the pivotal issues to develope guidelines for the treatment of depression in childhood and adolescence. Methods：Searching the Pub-Med online database for the articles with the key words of 'new', 'antidepressants' and 'children' ninety-seven headings of review articles were obtained. The author selected the articles of pertinent subjects in terms of either treatment guideline or psychopharmacology of new antidepressants. When required, articles about the clinical effectiveness of individual antidepressants were separatedly searched. In addition, the safety information of new antidepressants was acquired by browsing the official sites of the United States Food and Drugs Administration and Department of Health and Human Services. Results：1) For the clinical course, treatment phase, and treatment outcome, the reviews or treatment guidelines adopted the information from adult treatment guidelines. 2) Systematic and critical reviews unambiguously concluded that selective serotonin reuptake inhibitors(SSRIs) excelled tricyclic antidepressants( TCAs) for both efficacy and side effect profiles, and were recommend for the first-line choice for the treatment of children with depressive disorders. 3) New antidepressants generally lacked treatment experiences and randomized controlled clinical trials. 4) SSRIs and other new antidepressants, when used together, might result in pharmacokinetic and/or pharmacodynamic drug-to-drug interaction. 5) The difference of the clinical effectiveness of antidepressants between children and adults should be addressed from developmental aspects, which required further evidence. Conclusion：Treatment guidelines for the pharmacological treatment of childhood and adolescence depression could be constructed on the basis of clinical trial findings and practical experiences. Treatment guidelines are to best serve as the frame of reference for a clinician to make reasonable decisions for a particular therapeutic situation. In order to fulfill this role, guidelines should be updated as soon as new research data become available.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.929-936
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• 2005

The purpose of this study was to examine the ability of alkaline phosphatase (ALP) synthesis of MC3T3-E1 cells when above edible sources, Solidago virga-aurea var. gigantea Miq. root (SVR) extracts, were supplimented. MC3T3-E1 cells were cultured with $\alpha-MEM$(vehicle control), dexamethasone and genestein (positive control), and SVR extracts for 27 days. The effects of SVR MeOH extracts and its fractions on cell proliferation were measured by MTT assay. At 10, 100${\mu}g/mL$ of SVR methanol extract treated, that were elevated of cell proliferation to 140 and $120\%$ via vehicle control, respectively. And then ALP synthesis was measured by spectrophotometer for enzyme activity and by naphthol AS-BI staining for morphometry at 3, 9, 18, and 27th day. As the results, every extracts and fractions were promoted ALP activity by time course at 1, 10, 100${\mu}g/mL$, except n-hexane and chloroform fractions. Remarkably, the MeOH extracts were increased ALP activity more than 4.4 times compared with vehicle control, 2.2 times via positive control at 27th day (p<0.05). The SVR MeOH extracts treated cells, especially at a concentration of 10${\mu}g/mL$, showed remarkably higher than vehicle-treated control cells of mineralization which were checked by Alizarin red staining. These results indicate that SVR methanol extract have an induction ability of proliferation and differentiation on osteoblast.

• Journal of Agricultural Extension & Community Development
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• v.21 no.1
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• pp.35-82
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• 2014

It was main objectives to find the learners characteristics and educational effects of cyber agricultural technology courses in RDA. For the research, it was followed by literature reviews and internet based survey methods. In internet based survey, two staged stratified sampling method was adopted from cyber training members database in RDA along with some key word as open course or certificate course, and enrollment years. Instrument was composed through literature reviews about cyber education effects and educational effect factors. And learner characteristics items were added in survey documents. It was sent to sampled persons by e-mail and 316 data was returned via google survey systems. Through the data cleaning, 303 data were analysed by chi-square, t-test and F-test. It's significance level was .05. The results of the research were as followed; First, the respondent was composed of mainly man(77.9%), and monthly income group was mainly 2,000,000 or 3,000,000 won(24%), bachelor degree(48%), fifty or forty age group was shared to 75%, and their job was changed after learning(12.2%). So major respondents' job was not changed. Their major was not mainly agriculture. Learners' learning style were composed of two or more types as concrete-sequential, mixing, abstract-random, so e-learning course should be developed for the students' type. Second, it was attended at 3.2 days a week, 53.53 minutes a class, totally 172.63 minutes a week. They were very eager or generally eager to study, and attended two or more subjects. The cyber education motives was for farming knowledge, personal competency development, job performance enlarging. They selected subjects along with their interest. A subject person couldn't choose more subjects for little time, others, non interesting subject, but more subject persons were for job performance benefits and previous subjects effectiveness. Most learner was finished their subject, but a fourth was not finished for busy (26.7%). And their entrying behavior was not enough to learn e-course and computer or internet using ability was middle level as software using. And they thought RDA cyber course was comfort in non time or space limit, knowledge acquisition, and personal competency development. Cyber learning group was composed of open course only (12.5%), certificate only(25.7%), both(36.3%). Third, satisfaction and academic achievement of e-learning learners were good, and educational service offering for doing job in learning application category was good, but effect of cyber education was not good, especially, agricultural income increasing was not good because major learner group was not farmer, so they couldn't apply their knowledge to farming. And content structure and design, content comprehension, content amount were good. The more learning subject group responded to good in effects, and both open course and certificate course group satisfied more than open course only group. Based on the results, recommendation was offered as cyber course specialization before main course in RDA training system, support staff and faculty enlargement, building blended learning system with local RDA office, introducing cyber tutor system.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• The Korean Journal of Air & Space Law and Policy
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• v.19 no.2
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• pp.9-53
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• 2004

This paper described the contents of theme entitled "Domestic Legislative Problems on the Civil Liability of Air Carrier in Korea" including the current example of fourteen countries' legislation ((1) Great Britain, (2) United States of America, (3) Canada, (4)European Union), (5) Germany, (6) France, (7) Italy, (8) Spain, (9) Swiss, (10) Australia, (11) Japan, (12) People's Republic of China, (13) Taiwan, (14) North Korea) relating to the aviation law or air transport law. Though the Korean and Japanese aviation act has provided only the public items such as (1) registration of aircraft, (2) persons engaged in aviation, (3) operation of aircraft, (4) aviation facilities including airport, (5) air transport business, (6) investigate of aircraft accidents etc., but they could not regulated the private items such as the legal relations of the air transport contract (1) air passenger ticket, (2) air luggage ticket, (3) airway bill, (4) liability of air carrier, (5) amount of compensation for damage caused by aircraft accidents, (6)jurisdiction, (7) arbitration, (8) limitation of action, (9) combined carriage, (10) carriage by air performed by an actual carrier other than contracting carrier, damage caused by aircraft to the third parties etc. in their aviation act until now. In order to solve speedily the legal problems on the limitation of air carrier's liability and long law suit and disputes between wrongdoers and survivors etc, it is necessary and desirable for us to enact a new "Draft for the Air Transport Act" including the abovementioned private items. I would like to propose personally and strongly the legislation of "Draft for the Air Transport Act" in Korea in emphasizing the importance of ensuring protection of the interests of consumers air passengers and shippers in carriage by air and the need for equitable compensation between air carriers and survivors caused by the aircraft accidents such as the German Air Transport Act (Luftverkerhrsgesetz).