• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Korean journal of applied entomology
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• v.48 no.2
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• pp.237-243
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• 2009

This study was conducted to develop economic injury level (ElL) and economic threshold (ET) of Cabbage armyworm, Mamestra brassicae L. on cabbage (Brassica oleracea L. var). The changes of cabbage biomass and M. brassicae density were investigated after introduction of larval M. brassicae (2nd instar) at different densities: 0, 1, 2, 4, 8, and 16 larvae per plant at 40 d after planting for an open field experiment, and 0, 2, 5, 8 and 12 larvae per plant at 25 d after planting for a glass house experiment. In the field experiment, the yield loss of cabbage was not significantly different among treated-plots at 30 d after the larval introduction, showing an over-compensatory response of cabbage plants to M. brassicae attack. In the glasshouse experiment, however, the biomass of cabbage at 15 d after the larval introduction significantly decreased with increasing the initial introduced number of M. brassicae, resulting in 38.3, 36.7, 21.7, 23.3 and 16.7g in above treated-plots, respectively. The relationship between cumulative insect days (CID) and yield loss (%) of cabbage was well described by a nonlinear logistic equation. Using the estimated equation, ElL of M. brassicae on cabbage was estimated at 44 CID per plant based on the yield loss 14%, which take into account of an empirical gain threshold 5% and marketable rate 91% of cabbage. Also, ET was calculated at 80% of the EIL: 35 CID per plant. Until a more elaborate EIL-model is developed, the present result may be useful for M. brassicae management at early growth stage of cabbage.

• Journal of Animal Science and Technology
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• v.55 no.3
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• pp.195-202
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• 2013

The present study was undertaken to investigate the effects of increasing pig market weight on the incidence of the 'caky-fatty' belly, carcass grade and carcass quality traits. To this end, 500 (Yorkshire ${\times}$ Landrace) ${\times}$ Duroc market pigs consisting of equal numbers of barrows and gilts were slaughtered at body weights ranging from 85 to 150 kg and their carcasses were analyzed. Backfat thickness (BFT; mm) of the barrows and gilts regressed on live weight (kg) linearly as follows: BFT (y) = 0.1827x + 3.4825 ($r^2$ = 0.4671) and y = 0.2015x-0.6972 ($r^2$ = 0.4736), respectively. The caky-fatty belly, which, by definition of the present study, had = 55% fat by weight in the dorsal-side half of a 5 cm-wide belly strip between the $11^{th}$ and $12^{th}$ ribs, was found in 10 carcasses from barrows. However, no belly was condemned as 'caky-fatty' by the retailers. Total number of carcasses which were down-graded on account of overweight was as many as 101 (20.2%). The $1^+A$-grade carcasses exhibited a superior intramuscular fat score to all other grades, but except for this and the defective quality traits, no visible differences were found in carcass quality among different carcass grades. In conclusion, the current carcass grading system, which is sparingly reflective of the carcass quality and also under-evaluates the larger but otherwise normal carcasses, may as well be revised. Moreover, the incidence of the caky-fatty belly appears not to be a critical factor to be considered when increasing the pig market weight.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.82-90
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• 2010

The ecological characteristics of the Korean Aucha perch, Coreoperca herzi, were determined in order to estimate stock of the mid-upper system of the Seomjin River. The age was determined by counting the otolith annuli. The oldest fish observed in this study was 5 years old. Relationships between body length (BL) and body weight (BW) were $BW=0.0195BL^{3.08}$ ($R^2=0.966$) (p<0.01). Relationships between the otolith radius (R) and body length (BL) were BL=3.882R+1.66 ($R^2=0.944$). The von Bertalanffy growth parameters estimated from a non-linear regression method were $L_{\infty}=19.68\;cm$, $W_{\infty}=188.64\;g$, $K=0.17\;year^{-1}$ and $t_0=-1.46$ year. Therefore, growth in length of the fish was expressed by the von Bertalanffy's growth equation as $L_t=19.68$ ($1-e^{-0.17(t+1.46)}$) ($R^2=0.997$). The annual survival rate (S) was estimated to be $0.666\;year^{-1}$. The instantaneous coefficient of natural mortality (M) of estimated from the Zhang and Megrey method was $0.346\;year^{-1}$, and instantaneous coefficient of fishing mortality (F) was calculated $0.061\;year^{-1}$. From the estimates of survival rate (S), the instantaneous coefficient of total mortality(Z) was estimated to be $0.407\;year^{-1}$.

• Korean journal of applied entomology
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• v.62 no.4
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• pp.315-323
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• 2023

The brassica leaf beetle, Phaedon brassicae Baly (Coleoptera: Chrysomelidae), is one of the important pests infesting cruciferous vegetables. In order to understand the biological characteristics of the insect, we investigated the effects of temperature on development of each life stage, adult longevity and fecundity of P. brassicae at four constant temperatures of 15, 20, 25 and 27.5℃ for immature life stage and five constant different temperatures of 10, 15, 20, 25 and 27.5℃ for adult stage. Eggs and larvae successfully developed next life stage at temperature tested. The development period of egg, larva, and pupa decreased as temperature increased. Lower developmental threshold (LDT) and thermal constant (K) were calculated using linear regression as 8.7℃ and 344.73DD, respectively. Lower and higher threshold temperature (TL and TH) from egg to adult emergence were estimated by Briere function as 5.3℃ and 40.4℃, respectively. Adults produced eggs at the temperature range between 10℃ and 27.5℃, and showed an estimated maximum number, ca. 627.5 eggs at 21.7℃. Adult oviposition models including aging rate, age-specific survival rate, age-specific cumulative oviposition, and temperature-dependent fecundity were constructed. Temperature-dependent development models and adult oviposition models would be useful components to understand the population dynamics of P. brassicae and to establish the strategy of integrated pest management in cruciferous crops.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.17-26
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• 2012

Purpose: This study mainly focuses on the patients treated with chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO (d,l-hexamethylpropylene amine oxime) which yielded reduced image quality due to a decreased brain extraction rate. $^{99m}Tc$-HMPAO will be examined further to determine whether this product may be accounted as a factor for this cause. Material and Methods: From January 2010 until December 2010, out of 272 patients who were all subjected to $^{99m}Tc$-HMPAO brain blood flow SPECT scans resulting from Cerebral Infarction; 23 patients(ages $55.3{\pm}9$, 21 males, 3 females) with decreased tissue extraction rate were examined in detail. The radiopharmaceutical product $^{99m}Tc$-HMPAO was used on patients with normal brain tissue exchange rate as well as those with reduced rate in order to prove its' chemical stability. The patients' age, sex, blood pressure, existence of diabetes, drug use, current health status, known side effects from CT/MRI, examination of the patients' past SPECT before/after images were accounted to determine the factors and correlations affecting the rate of blood tissue extractions. Result: After multiple linear regression analysis, there were no unusual correlations between the 6 factors excluding sex, and before/after examination images. Male subjects showed reduced brain tissue extraction rate than the females ($p$ > 0.05) 91.3% male, 8.7% female. Wilcoxon Matched-Pairs Signed-Ranks Test was used on the before/after images which yielded a value of 0.06, which did not indicate a significant amount of difference on the 2 tests ($p$ > 0.05). As a result, the before/after images indicated similar brain tissue extraction rates, and there were variations depending on the individual patient. Conclusion: The effects of the chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO depended on the patient's personal characteristics and status, therefore was considered to be a factor in reducing brain tissue extraction rate. The related articles of $^{99m}Tc$-HMPAO cerebral blood flow SPECT speculates a cerebrovascular disease and factors resulting from portal veins, and it was not possible to pin point the exact cause of decreasing brain tissue extraction rate. However, the $^{99m}Tc$-HMPAO cerebral blood flow SPECT scan proved to be extremely useful in tracking and inspecting brain diseases, as well as offering accurate results from patients suffering from reduced brain tissue extraction rates.