• Horticultural Science & Technology
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• v.30 no.6
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• pp.650-656
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• 2012

The aims of the experiment, conducted over three years in the Central Europe field conditions, were (1) to investigate the effect of growing period (plantings in the middle and at the end of August: $1^{st}$ and $2^{nd}$ term, respectively) on yield and chemical composition of the non-heading Chinese cabbage (Brassica rapa var. chinensis) cultivars 'Taisai', 'Pak Choy White', and 'Green Fortune', and (2) to develop regression models to evaluate the changes in crop yields as a function of weather conditions. A highest marketable yield was obtained from 'Taisai' (65.71 and 77.20 $t{\cdot}ha^{-1}$), especially in the $2^{nd}$ term of production. Low yield, observed for 'Pak Choy White' was due to its premature bolting. Almost 39% ($1^{st}$ term) and 70% ($2^{nd}$ term) of plants of this cultivar formed inflorescence shoots before harvest. The highest dry matter level was observed in the leaf petioles of 'Taisai', while 'Green Fortune' was the most abundant of carotenoids and L-ascorbic acid. The content of soluble sugars was the lowest for 'Pak Choy White'. In a phase of harvest maturity, more of the analyzed constituents were gathered by plants from earlier plantings, and differences were as follows: 4.7% (dry matter), 26.3% (carotenoids) and 22.1% (L-ascorbic acid), in comparison to $2^{nd}$ term of production. Significant increase of soluble sugars level was observed for plants from later harvest. The regression model for marketable yield of Chinese cabbage cultivar 'Taisai' as a function of maximum air temperature can predict the yield with accuracy 68%. The models for yield or bolting of 'Pak Choy White', based on extreme air temperatures and sunshine duration, were more precise (98%). It should be pointed out that Taisai could be recommended for later growing period in Central Europe conditions with regard to maximum yield potential. 'Green Fortune' was notable for its uniform yielding. To obtained plants of higher nutritional value, earlier time of cultivation should be suggested. Described models can be successfully applied for an approximate simulation of Chinese cabbage yielding.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.304-304
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• 2017

In semi-arid countries such as Namibia, the flooding unexpectedly happens in a rainy season, causing losses in the yield of upland-adapted cereal crop. In flooding conditions, rice roots sequentially form aerenchyma and a barrier to radial oxygen loss (ROL), and oxygen is released into the rhizosphere near the root tips. Iijima et al. (2016) and Awala et al. (2016) reported that close mixed-planting with rice can mitigate the flood stress of co-growing upland-adapted cereal crop by modifying their rhizosphere microenvironments via the oxygen released from the rice roots. Moreover, by using the model system of hydroponic culture, it was confirmed that oxygen from rice roots was transferred to co-growing upland-adapted cereal crop in close mixed planting system (Kawato et al., 2016). However, it is not sure whether the ability of oxygen release varies among rice cultivars, because Kawato et al. (2016) used only one japonica cultivar, Nipponbare (Oryza sativa). The objective of this study was to compare the ability of oxygen release in rhizosphere among rice cultivars. The experiment was conducted in a climate chamber in Kindai University. We used 10 rice cultivars from three different rice species (O. sativa (var. japonica (2), var. indica (3)), Oryza glaberrima Steud. (2) and their interspecific progenies (3)) to compare the ability of oxygen release from the roots. According to the method by Kawato et al. (2016), the dissolved oxygen concentration of phase I (with shoot) and phase II (without shoot) were measured by a fiber optic oxygen-sensing probe. The oxygen released from rice roots was calculated from the difference of the measurements between phase I and phase II. The result in this study indicated that all of the rice cultivars released oxygen from their roots, and the amount of released oxygen was significantly correlated with the above-ground biomass (r = 0.710). The ability of oxygen release (the amount of the oxygen release per fresh root weight) of indica cultivars (O. sativa) tended to be higher as compared with the other cultivars. On the other hand, that of African rice (O. glaberrima) and the interspecific progenies tended to be lower. These results suggested that the ability of oxygen release widely varies among rice cultivars, and some of indica cultivars (O. sativa) may be suitable for close mixed-planting to mitigate flood stress of upland-adapted cereal crop.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.535-545
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• 2019

If the real estate auction market indicators are relevant and meaningful, they can be meaningful information to the real estate market in connection with general real estate. The purpose of this study is to examine whether time-supply logic is applied in auction market by identifying time series correlations for the number of auctions, the auction rate, and the auction price rate, which are major indicators of real estate auction market. The real estate types were classified into three categories: residential real estate, land, and commercial real estate. The monthly time series of auctions in the metropolitan real estate were compiled for 96 months. Based on this data, the auction market model for each type was established and the mutual influences between the indicators were analyzed. As a result, the supply and demand indicators, the number of auctions and the auction rate, showed the nature of supply and demand according to the supply and demand logic of the market. However, the correlation was high for residential real estate and relatively low for commercial real estate. the auction rate has a long-term impact on price indicators, especially residential real estate, which is quantitatively explanatory and significant. The three auction-related indicators differ in degree, but there is a correlation, especially for residential real estate, which can be useful information for policy making.

• Journal of Korea Foresty Energy
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• v.22 no.2
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• pp.1-17
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• 2003

Populus species have been as a model species in tree breeding and we have enormous varieties resulting from the poplar breeding because of their fast growth performance and short rotation age. New varieties developed in Korea are common italian poplar(P euramericana, I-214, I-476), P euramericana“Eco 28”(Italian poplar No.1) and p. deltoides“Lux”(Italian poplar No.2), which were introduced from foreign countries. As hybrid polars, Hyun-Sasi(p. alba ${\times}$ P. glandulosa No.1, No.2, No.3, No4.), P. nigra x P. maximowiczii and P. koreana x P. nigra val. italica, were developed, and P. davidiana was selected as the result of selection breeding The total plantation areas covered with the new varieties are 935,162ha that include 745,773ha of P. euramericana, 184,636ha of P. alba x P. glandulosa, and other new varieties are 4,735ha. The new poplars are contributed to increase farmer's income as well as bare land tree-planting in Korea. The technologies associated with the poplar species were developed, such as the determination of optimum site for new the poplar species, the crossing method between incompatible poplar species, and the vegetative mass propagation. In the future, poplar species will be considered for phytoremediation species at contaminated areas such as landfill sites or with lives stock's waste water as well as wood production, a shade tree like road-side tree and public park tree.

• Korean journal of applied entomology
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• v.50 no.4
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• pp.289-293
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• 2011

This study was conducted to develop economic injury level (EIL) of onion thrips, Thrips tabaci, on welsh onion (Allium fistulosum L. var) in the early transplanting stage. The changes of welsh onion biomass, yield loss, and T. tabaci density were investigated according to the inoculation periods of T. tabaci. In the early transplanting stage of welsh onion, the yield loss (%) increased with increasing inoculation periods: 17.0, 53.3, 38.4, and 80.8% yield loss in 5, 10, 15, and 20 d inoculation periods, respectively. The relationship between Cumulative Insect Days (CID) of T. tabaci and yield loss (%) of welsh onion was well described by a nonlinear logistic equation. Using the estimated equation, EIL of T. tabaci on welsh onion was estimated to 30 CID per plant based on the yield loss 12% (an empirical gain threshold 5% + marketable rate 93% of welsh onion). ET was calculated to 24 CID, which corresponds to 80% of EIL. Until a more defined EIL-model is developed, the present results should be useful for T. tabaci management in early growth stage of welsh onion. The effect of T. tabaci attack on the yield of welsh onion in late growing season (120 days after transplanting) was also examined. The yield of welsh onion increased at a low population density of T. tabaci and decreased at higher densities, showing a typical over-compensatory response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.5-5
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• 2019

DMZ는 살아있는 생물다양성의 보고로 지난 60여년동안 자연적으로 재생이 일어나고 환경적인 강제 보존 영향으로 높은 생태학적인 가치가 유지되고 있으며, 최근에는 남북교류에 대한 활발한 의지로 DMZ생태자원의 남북공동활용 방안에 대한 이슈가 급부상하고 있다. 이에 본 연구진은 3년전부터 DMZ에서 자생하는 식물에 대한 조사를 진행하여 총 200여종 이상의 자생식물의 표본과 추출물들을 보유하고 있으며, 이 추출물들을 활용 in vitro 와 in vivo 평가를 통해 비임상 평가에서 유효한 효과를 나타내는 후보물질들을 다수 찾아낼 수 있었다. 그 중 조팝나무(Spiraea prunifolia var. simpliciflora)는 쌍떡잎식물 장미과에 속하는 낙엽활엽관목으로 동북아시아 지역에 널리 분포되며 우리나라에서는 중부지방에 주로 서식한다고 알려져 있다. 예로부터 해열 및 소염, 신경통완화 치료등에 이용해왔다고 알려져 있으며 그 속에는 다양한 terpenoids, flavonoid 및 phenolic 화합물이 다량 함유되어 있다고 알려져 있다. 본 연구에서는 조팝나무 추출물을 이용하여 전구지방세포에서의 지방세포분화 억제 및 관련 유전자들의 활성을 확인한 후 고지방식이로 유도된 high-fat diet mouse model을 이용하여 체지방 감소 및 내장지방감소, 간 조직내의 지방량 감소등을 확인하였으며, 혈액분석을 통해 총콜레스테롤과 고중성지방등 동맥경화와 심혈관계 질환을 유도시킬수 있는 지표들에서 억제 활성도 확인하였다. 특히 내장 지방의 경우는 Micro-CT를 통해 정밀한 분석을 진행하였고, 체지방뿐만 아니라 전체 체중감소도 나타나는 것을 확인하였다. 현재 실험을 통해 적출된 간 조직과 지방조직을 이용하여 항 비만 활성의 작용기전을 지속적으로 확인하고 있으며, 이 결과는 국제적인 연구저널에 보고되어 향후 체지방 감소 또는 항 비만 치료제로 개발되는 비임상 연구자료로 활용될 계획이다. 이미 조팝나무에 대한 연구결과는 특허로 출원이 완료되어 PCT출원까지 진행중에 있으며 개별인정형 건강기능식품 개발 기업에 기술이전이 될 예정이다. 또한 원활한 원료 수급을 위해 기초단체 소속 농업기술센터와 원료 재배 및 대량 수급에 관한 논의를 마친 상태로 접경지역 근처 농가소득 증대로도 이어지는 제품화 사례이기도 하다. 이는 접경지역에서 자생하는 원료의 활성을 과학적으로 검증하여 기업과의 연계를 통해 기초시군 단체의 농가 소득과도 연계한 우수한 제품개발 사례로 향후에도 이와 같은 연구성과가 지속적으로 도출되기를 기대해본다.

• Management & Information Systems Review
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• v.33 no.1
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• pp.139-155
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• 2014

This study is to examine the linkage of volatility between changes in the stock market of India and other countries through the integration of the world economy. The results were as follows: First, autocorrelation or serial correlation did not exist in the classic RS model, but long-term memory was present in the modified RS model. Second, unit root did not exist in the unit root test for all periods, and the series were a stable explanatory power and a long-term memory with the normal conditions in the ARFIMA model. Third, in the multivariate asymmetric BEKK and VAR model before the financial crisis, it showed that there was a strong influence of the own market of Taiwan and UK in the conditional mean equation, and a strong spillover effect from Japan to India, from Taiwan to China(Korea, US), from US(Japan) to UK in one direction. In the conditional variance equation, GARCH showed a strong spillover effect that indicated the same direction as the result of ARCH coefficient of the market itself. Asymmetric effects in three home markets and between markets existed. Fourth, after the financial crisis, in the conditional mean equation, only the domestic market in Taiwan showed strong influences, and strong spillover effects existed from India to US, from Taiwan to Japan, from Korea to Germany in one direction. In the conditional variance equation, strong spillover effects were the same as the result of the pre-crisis and asymmetric effect in the domestic market in UK was present, and one-way asymmetric effect existed in Germany from Taiwan. Therefore, the results of this study presented the linkage between the volatilities of the stock market of India and other countries through the integration of the world economy, observing and confirming the asymmetric reactions and return(volatility) spillover effects between the stock market of India and other countries.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.68-76
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• 2006

A thermal time-based two-step phenological model was used to project flowering dates of Japanese cherry in South Korea from 1941 to 2100. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. Daily maximum and minimum temperature are used to calculate daily chill units until a pre-determined chilling requirement for rest release is met. After the projected rest release date, daily heat units (growing degree days) are accumulated until a pre-determined heating requirement for flowering is achieved. Model calculations using daily temperature data at 18 synoptic stations during 1955-2004 were compared with the observed blooming dates and resulted in 3.9 days mean absolute error, 5.1 days root mean squared error, and a correlation coefficient of 0.86. Considering that the phonology observation has never been fully standardized in Korea, this result seems reasonable. Gridded data sets of daily maximum and minimum temperature with a 270 m grid spacing were prepared for the climatological years 1941-1970 and 1971-2000 from observations at 56 synoptic stations by using a spatial interpolation scheme for correcting urban heat island effect as well as elevation effect. A 25km-resolution temperature data set covering the Korean Peninsula, prepared by the Meteorological Research Institute of Korea Meteorological Administration under the condition of Inter-governmental Panel on Climate Change-Special Report on Emission Scenarios A2, was converted to 270 m gridded data for the climatological years 2011-2040, 2041-2070 and 2071-2100. The model was run by the gridded daily maximum and minimum temperature data sets, each representing a climatological normal year for 1941-1970, 1971-2000, 2011-2040, 2041-2070, and 2071-2100. According to the model calculation, the spatially averaged flowering date for the 1971-2000 normal is shorter than that for 1941-1970 by 5.2 days. Compared with the current normal (1971-2000), flowering of Japanese cherry is expected to be earlier by 9, 21, and 29 days in the future normal years 2011-2040, 2041-2070, and 2071-2100, respectively. Southern coastal areas might experience springs with incomplete or even no Japanese cherry flowering caused by insufficient chilling for breaking bud dormancy.