• Korean journal of applied entomology
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• v.60 no.2
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• pp.221-228
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• 2021

The fall armyworm (FAW), Spodoptera frugiperda (Smith), is a notorious invasive migratory pest native to the tropics that has recently invaded South Korea with subsequent damage to cornfields. This study was conducted to evaluate the damage patterns on corn plants caused by the migratory and subsequent generations of FAW. The early migrant generation-related infestation rates reached an average of 13.2%, ranging from a minimum of 4.3% ('Allog-i') to a maximum of 33.0% ('Chodang'), depending on the corn cultivar. The proportion of FAW larvae-infested corn plants, in which the FAW survived until the pupal stage was 19.3%. The subsequent FAW generation caused considerable damage to the ears, resulting in 60% of ears with damaged kernels. This damage was markedly different from the nearly negligible damage caused by the migratory generation. The FAW larval dispersion was the most dynamic during the second instar stage and occurred along the same cornrow in line. In addition, we discuss the development of corn pant damage patterns caused by FAW. In summary, the results of the present study would provide useful basic information for the damage analysis of this pest for future studies.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.112-120
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• 2019

The purpose of this study is to explore educational methods for elementary, middle and high schools using school forests via IT convergence. To this aim, we reviewed the previous literature on education using school forests to identify the problems with the existing education using school forests, and conducted interviews with experts to analyze the demands. we proposed an educational method that can utilize the school forests via IT convergence, and explored its validity through content reviews conducted by experts. The findings of this study are as follows. First, we proposed the IT convergence instruction focused on hands-on activities on top of the existing educational contents. Second, we proposed IT convergence instruction that incorporates diverse materials, physical computing tools, and programming tools. Third, we presented methods for utilizing such IT convergence instruction in connection with various elements of the 2015 Revised Curriculum as well as with various other activities such as middle school free semester activities and after-school activities. The school forest is a crucial learning space for the areas related to agriculture and biotechnology. Thus, we anticipate that the IT convergence instruction proposed in this study will lead to the re-discovery and re-evaluation of a value of school forests as an educational space that contributes to fulfilling the objective of the 2015 Revised Curriculum to nurture creative convergent talent.

• Korean Journal of Poultry Science
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• v.20 no.4
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• pp.177-188
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• 1993

This study was performed to find out the reasonable sexing methods In the chicken, obtain the basic information for the mechanisms related to chicken sexual differentiation and identify the genes which known to involved in chicken sex differentiation. The chromosome analysis of chicken embryonic fibroblast was a simple method to determine sex of chicken by means of Z and W chromosome identification. The bands of female chicken genomic DNA digested with Xho Ⅰ and Eco RI restriction endonuclease showed to be useful in direct sex determination and these repetitive sequences of Xho Ⅰ and Eco RI families were proposed to be very homologous in their sequences by colony hybridization analysis. Seven of 150 random primers were selected to amplify the W chromosome-specific band by using arbitrary primed PCR and three of them were useful to identify the sex of chicken. To identify the sex differentiation genes in the chicken, PCR for the amplification of ZFY and SRY sequences was performed. ZFY and SRY sequences were amplified successfully in the chicken genome, implying that chicken genome might have the sex-related conserved sequences similar to mammalian ones. The PCR products of ZFY amplification were the same in both sexes, suggesting that these sequences may be located on autosome or Z chromosome. The profile of PCR amplification for SRY sequences showed variation between sexes, but this result was not enough to specify whether the SRY gene in chicken is on the autosome or sex chromosome.

• Journal of the Korean Geographical Society
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• v.47 no.1
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• pp.60-78
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• 2012

The main objective of this study is to conduct subnational population projections of Korea based on a Myriad Things" (萬物門), which is part of Seongho's representative work entitled $Miscellaneous$ $Explanations$ $of$ $Seongho$ (星湖僿說), has been in this paper in order to understand Seongho's "thinking on geography". To do so, contents related to geography were selected and these were discussed and interpreted in terms of the classification system of today's geographical knowledge. Following is the result of this research. First, information on astronomical geography and natural geography such as uplift, tornado, structure of soil, and the $yut$ board as well as humangeographical topics such as wild $ginseng$, cigarettes, hot pepper, traditional fruits and nuts (chestnuts, jujubes, and persimmons), Goryeo paper (Korean paper), mulberry trees, cotton plants, natural dye, policy about horses, magnetic compass needles, and farming implements for rice transplantation are mentioned in "Myriad Things" in relation to geography. Second, the depth of information described varies from topic to topic, but the topics on tornado and magnetic compass needles, horses, wild ginseng, traditional fruits and nuts, and $yut$ board are described in depth and in detail. Third, authenticity of the contents on these topics are "true" insofar as bibliographical information and citations are provided for support. Fourth, these topics reflect the interests and circumstances that are related to the "economic improvement of common people's livelihood" in those days, such as agriculture, crops, and transportation of goods. Fifth, the bibliography and citations explaining all instances reveal that China (Qing) is a great civilization of the advanced world and that the scholarship of Joseon relied on and accepted it. Sixth, except for horse raising and management, farming implements for rice transplantation, sericulture, and natural dying of cloth, most of the topics are useful even today. In short, theres is a profound aspect to the content that makes it possible to estimate the "geographical thinking". In general, the focus of the content of this book directly linked to the practical agricultural economy of the common people.

• Journal of Korean Society of Forest Science
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• v.75 no.1
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• pp.1-18
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• 1986

This study was initiated to estimate productivity of Quercus variabilis stand. However the practical objective of this study was to provide some information to establish the basis of selecting the suitable site for Quercus variabilis. The productivity measured in terms of DBH, height, basal area and stem volume was hypothesized, respectively, to be a function of a group of factors. This study considered 32 factors, 20 of which were related to the forest environmental factors such as tree age, latitude, percent slope, etc. and the rest of which were related to soil factors such as soil moisture, total nitrogen, available $P_2O_5$, etc. The data on 4 productivity measurements of Quercus variabilis growth and related factors cited were collected from 99 sample plots in Kyeongbook and chungbook provinces. Some factors considered were, in nature, discrete variables and the others continuous variables. Each kind of factor was classified into 3 or 4 categories and total numbers of such categories were eventually amounted to 110. Then each category was treated as an independent variable. This is amounted to saying that individual variable was treated a dummy variable and assigned a value 1 or 0. However the first category of each factor was deleted from the normal equation for statistical consideration. First of all, each of 4 productivity measurements of Quercus variabilis growth was regressed and, at the same time, those 110 categories. Secondly, the partial correlation coefficients were measured between each pair of 4 productivity measurements and 32 individual foctors. Finally, the relative scores were estimated in order to derive the category ranges. The result of these statistical analyses could be summarized as follows: 1) Growth measurement in terms of height seems to be a more significant criterion for estimation of productivity of Quercus variabilis. 2) Productivity of forest on stocked land may better be estimated in terms of forest environmental factors, on the other hand, that of unstocked land may be estimated in terms of physio-chemical factors of soil. 3) The factors that a strongly positive relation to all growth factors of tree are age group, effective soil, soil moisture, etc. This implies that these factors might effectively be used for criteria for selecting the suitable site for Quercus variabilis. 4) Parent rock, latitude, total nitrogen, age group, effective soil depth, soil moisture, organic matter, etc., had more significant category range for tree growth. Therefore, the suitable site for Quercus variabilis may be selected, based on this information. In conclusion, the above results obtained by the multivariable analysis can be not only the important criteria for estimating the growth of Quercus variabilis but also the useful guidance for selecting the suitable sites and performing the rational of Quercus variabilis forest.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Korean Journal of Environmental Agriculture
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• v.15 no.1
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• pp.46-69
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• 1996

The studies were conducted to obtain the basic information of the effects of pollutants on plant species and to select the plant species showing specific responses to the pollutants. For these purposes, paraquat, ammonium, and cadmium as a source of oxidative stress, nitrogen toxicity, and heavy metal toxicity respectively were treated to the plant species. Among the tested plants, Lamiaceae, Brassicaceae, and Caryophyllaceae were tolerant to paraquat, whereas Poaceae and Asteraceae were sensitive. Especially Mosla dianthera of Lamiaceae, Hemistepta lyrata and Aster pilosus of Asteraceae, and Paspalum thunbergii of Poaceae showed higher tolerance than others. Paraquat resistance was related with life style, overwintering capacity, so perennial and biennial species showed higher tolerance than annual species. In response to ammonium, Poaceae showed higher resistance while Fabaceae and Caryophyllaceae showed sensitiveness. Weed species having tolerance to ammonium were Echinochloa crus-galli var. praticola, Panicum dichotomiflorum, Setaria glauca, Chenopodium album, and Solanum nigrum, while Mosla dianthera, Arenaria serpyllifolia and Perilla frutescens var. japonica showed sensitiveness. In the response of plant species to cadmium, Digitaria sanguinalis, Amaranthus lividus showed higher resistance, whereas Galinsoga parviflora, Plantago asiatica, Ambrosia trifida, and Paspalum thunbergii showed sensitiveness. The injured degree on germination stage by pollutants did not related with injured degree on matured stage. During germination, the root elongation was more sensitive than shoot elongation by pollutants, paraquat, ammonium, and cadmium.

• Korean Journal of Environmental Agriculture
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• v.30 no.3
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• pp.252-260
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• 2011

BACKGROUND: Currently, national biomass inventory are being established for efficient management of the potential energy sources. Among the various types of biomass, agricultural wastes are considered to take the biggest portion of the total annual biomass generated in Korea, implying its importance. However, the currently estimated amount is not reliable because the old reference data are still used to estimate total annual amount of agricultural wastes. METHODS AND RESULTS: Therefore, to provide reliable estimation data, a correct conversion factor obtained by taking into account the current situation is required. For this, the current study was conducted to provide the conversion factors for each representative 8 crop through a field cultivation study. Also conversion factors for 18 crops were calculated using the average amount of each crop produced during 2004 and 2008, subsequently; total amount of agricultural wastes generated in 2009 was estimated using these conversion factors. The total biomass of rice straw and rice husk generated in 2009 were 6.5 and 1.1 million tons, respectively, which consist 75% of the total agricultural based wastes, while the total biomass of pepper shoots and apple pruning twigs were 1.0 and 0.6 million tons, respectively. Despite the high amount of rice-based biomass, their applicability for bio-energy production is low due to conventional utilization of these materials for animal feeds and beds for animal husbandry. In addition to exact estimation of the total biomass, temporal variations in both generated amount and the type of agricultural biomass materials are also important for efficient utilization; fruit pruning twigs (January to March); barley-, been-, and mustard-related waste materials (April to June); rice-related waste (September to October). CONCLUSION(s): Such information provided in this study can be used to establish a master plan for efficient utilization of the agricultural wastes on purpose of bio-energy production.

• The Korean Journal of Community Living Science
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• v.28 no.3
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• pp.377-390
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• 2017

This study identified technological trends through an analysis of patents for the industrialization of personal protection and convenience equipment using information and communication technology (ICT) as a part of efforts to prevent farm work-related disasters. The analysis was conducted on patents registered and published between January 1974 and May 2016 by the world's five largest intellectual property offices, including the KIPO, USPTO, JPO, EPO, and SIPO. The results of the analysis indicate that the US (36.8%) and South Korea (30.9%) led technological research and development (R&D) with frequent patent applications. An analysis of the technological market revealed that these countries are in the growth and maturity stages, in which the number of patents and number of patent applicants grow rapidly. In terms of the technological market shares of major countries, the US recorded the highest market shares in the field of sensing systems for workers' dangerous conditions and convenience protection equipment based on the internet of things (IoT) convergence. South Korea marked the highest share of 41.8% in the field of sensing devices for dangerous conditions in the working environment. An analysis of the trend of patent applications by specific technologies disclosed the following results: sensing systems for workers' dangerous conditions accounted for the highest share (49.2%), followed by IoT convergence-based convenience protection equipment (26.3%) and sensing devices for dangerous conditions in the working environment (24.6%). Based on this study, ICT-based personal protection and convenience equipment technologies are expected to be actively developed in the future. It will be necessary to secure national competitiveness through R&D investments and commercialization in personal protection and convenience equipment appropriate for farm work as well as through the acquisition of patent technologies and intellectual property rights.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.