Kim, Ji-Young;Lee, Ji-Ho;Kunhikrishnan, Anitha;Kang, Dae-Won;Kim, Min-Ji;Yoo, Ji-Hyock;Kim, Doo Ho;Lee, Young-Ja;Kim, Won Il
Korean Journal of Environmental Agriculture
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v.31
no.4
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pp.300-307
/
2012
BACKGROUND: The Transfer Factor (TF) of heavy metals from soil to plant is important, because TF is an indicator of heavy metal in soils and a factor that quantifies bioavailability of heavy metals to agricultural products. This study was conducted to investigate the transfer ability of Arsenic (As), Cadmium (Cd), and Lead (Pb) from soil to agricultural products. METHODS AND RESULTS: We investigated heavy metals (As, Cd and Pb) concentrations in 9 agricultural products (rice, barely, corn, pulse, lettuce, pumpkin, apple, pear, tangerin) and soil. TF of agricultural products was evaluated based on total and HCl-extractable soil concentration of As, Cd, and Pb. Regression analysis was used to predict the relationship of total and HCl-extractable concentration with agricultural product contents of As, Cd, and Pb. The result showed that TF was investigated average 0.006~0.309 (As), 0.002~6.185 (Cd), 0.003~0.602 (Pb). The mean TF value was the highest as rice 0.309 in As, lettuce 6.185, pear 0.717, rice 0.308 in Cd, lettuce 0.602, pumpkin 0.536 in Pb which were dependent on the vegetable species and cereal is showed higher than fruit-vegetables in As. CONCLUSION(S): Soil HCl-extractable concentration of As, Cd, and Pb had the larger effects on thier contents in agricultural products than total soil concentrations. We suggests that TF are served as influential factor on the prediction of uptake. Further study for uptake and accumulation mechanism of toxic metals by agricultural products will be required to assess the human health risk and need TF of more agricultural products.
This study was conducted to predict number and fresh weight of leaves, and total leaf area of a single-stemmed rose 'Vital' based on the accumulated thermal units, and to develop a model of shoot development for the prediction of the time when the flowering shoot reaches a phenological stage in a plant factory system. The base temperature ($T_b$), optimum temperature ($T_{opt}$), and maximum temperature ($T_{max}$) were estimated by regressing the rate of shoot development against the temperature gradient. The rate of shoot development ($R$, $d^{-1}$) for the phase from cutting to bud break (CT-BB) was best described by a linear model $R_b$ ($d^{-1}$) = -0.0089 + $0.0016{\cdot}temp$. The rate of shoot development for the phase from bud break to harvest (BB-HV) was fitted to the parabolic model $R_h$ ($d^{-1}$) = $-0.0001{\cdot}temp^2$ + $0.0054{\cdot}temp$ - 0.0484. The $T_b$, $T_{opt}$, and $T_{max}$ values were 5.56, 27.0, and $42.7^{\circ}C$, respectively. The $T_b$ value was used in the thermal unit computations for the shoot development. Number of leaves, leaf area (LA), and leaf fresh weight showed sigmoidal curves regardless of the cut time. The shoot development and leaf area model was described as a sigmoidal function using thermal units. Leaf area was described as LA = 578.7 $[1+(thermal units/956.1)^{-8.54}]^{-1}$. Estimated and observed shoot length and leaf fresh weight showed a reasonably good fit with 1.060 ($R^2=0.976^{***}$) and 1.043 ($R^2=0.955^{***}$), respectively. The average thermal units required from cutting to transplant and from transplant to harvest stages were $426{\pm}42^{\circ}C{\cdot}d$ and $783{\pm}24^{\circ}C{\cdot}d$, respectively.
Kang, Ji Ho;Lee, Sang Haak;Kwon, Soon Seog;Kim, Young Kyoon;Kim, Kwan Hyoung;Song, Jeong Sup;Park, Sung Hak;Moon, Hwa Sik;Park, Yong Moon
Tuberculosis and Respiratory Diseases
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v.60
no.1
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pp.76-82
/
2006
Background : The objective of this study was to understand sleep-related problems, and to determine whether the sleep questionnaires is a clinically useful method in patients who need polysomnography. Methods : Subjects were patients who performed polysomnography and who asked to answer a sleep questionnaires at the Sleep Disorders Clinic of St. Paul's Hospital, Catholic University of Korea. Baseline characteristics, past medical illness, behaviors during sleep-wake cycle, snoring, sleep-disordered breathing and symptoms of daytime sleepiness were analyzed to compare with data of polysomnography. Results : The study population included 1081 patients(849 men, 232 female), and their mean age was $44.2{\pm}12.8years$. Among these patients, 38.9% had an apnea-hypopnea index(AHI)<5, 27.9% had $5{\leq}AHI<20$, 13.2% had $20{\leq}AHI<40$, and 20.0% had $40{\leq}AHI$. The main problems for visiting our clinic were snoring(91.7%), sleep apnea(74.5%), excessive daytime sleepiness(8.0%), insomnia(4.3%), bruxism(1.1%) and attention deficit(0.5%). The mean value of frequency of interruptions of sleep was 1.6 and the most common reason was urination(46.3%). Epworth Sleepiness Scale(ESS) had a weak correlation with AHI(r=0.209, p<0.01). When we performed analysis of sleep questionnaires, there were significant differences in the mean values of AHI according to the severity of symptoms including snoring, daytime sleepiness, taking a nap and arousal state after wake(p<0.05). Conclusion : On the basis of statistical analysis of sleep questionnaires, the severity of subjective symptoms such as ESS, snoring, daytime sleepiness and arousal state after wake correlated with the AHI significantly. Therefore the sleep questionnaires can be useful instruments for prediction of the severity of sleep disorder, especially sleep-disordered breathing.
Journal of Korean Society of Environmental Engineers
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v.28
no.3
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pp.308-315
/
2006
Since sewage characteristics are the most important factors that can affect the biological reactions in wastewater treatment plants, a detailed understanding on the characteristics and on-line measurement techniques of the influent sewage would play an important role in determining the appropriate control strategies. In this study, samples were taken at two hour intervals during 51 days from $1^{st}$ October to $21^{st}$ November 2005 from the influent gate of sewage treatment plant. Then the characteristics of sewage were investigated. It was found that the daily values of flow rate and concentrations of sewage components showed a defined profile. The highest and lowest peak values were observed during $11:00{\sim}13:00$ hours and $05:00{\sim}07:00$ hours, respectively. Also, it was shown that the concentrations of sewage components were strongly correlated with the absorbance measured at 300 nm of UV. Therefore, the objective of the paper is to develop on-line estimation technique of the concentration of each component in the sewage using accumulated profiles of sewage, absorbance, and flow rate which can be measured in real time. As a first step, regression analysis was performed using the absorbance and component concentration data. Then a neural network trained with the input of influent flow rate, absorbance, and inflow duration was used. Both methods showed remarkable accuracy in predicting the resulting concentrations of the individual components of the sewage. In case of using the neural network, the predicted value md of the measurement were 19.3 and 14.4 for TSS, 26.7 and 25.1 for TCOD, 5.4 and 4.1 for TN, and for TP, 0.45 to 0.39, respectively.
An empirical model to predict initial disease occurrence and subsequent progress of Alternaria leaf spot was constructed based on the modified degree day temperature and frequency of rainfall in three years field experiments. Climatic factors were analized 10-day bases, beginning April 20 to the end of August, and were used as variables for model construction. Cumulative degree portion (CDP) that is over $10^{\circ}C$ in the daily average temperature was used as a parameter to determine the relationship between temperature and initial disease occurrence. Around one hundred and sixty of CDP was needed to initiate disease incidence. This value was considered as temperature threshhold. After reaching 160 CDP, time of initial occurrence was determined by frequency of rainfall. At least four times of rainfall were necessary to be accumulated for initial occurrence of the disease after passing temperature threshhold. Disease progress after initial incidence generally followed the pattern of frequency of rainfall accumulated in those periods. Apparent infection rate (r) in the general differential equation dx/dt=xr(1-x) for individual epidemics when x is disease proportion and t is time, was a linear function of accumulation rate of rainfall frequency (Rc) and was able to be directly estimated based on the equation r=1.06Rc-0.11($R^2=0.993$). Disease severity (x) after t time could be predicted using exponential equation $[x/(1-x)]=[x_0/(1-x)]e^{(b_0+b_1R_c)t}$ derived from the differential equation, when $x_0$ is initial disease, $b_0\;and\;b_1$ are constants. There was a significant linear relationship between disease progress and cumulative number of air-borne conidia of Alternaria mali. When the cumulative number of air-borne conidia was used as an independent variable to predict disease severity, accuracy of prediction was poor with $R^2=0.3328$.
Park, Hyung-Soo;Lee, Sang-Hoon;Choi, Ki-Choon;Lim, Young-Chul;Kim, Jong-Gun;Jo, Kyu-Chea;Choi, Gi-Jun
Journal of The Korean Society of Grassland and Forage Science
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v.32
no.3
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pp.301-308
/
2012
Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical parameters of Italian ryegrass silages. A population of 267 Italian ryegrass silages representing a wide range in chemical parameters and fermentative characteristics was used in this investigation. Samples of silage were scanned at 2 nm intervals over the wavelength range 680~2,500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of the highest coefficients of determination in cross validation ($R^2$) and the lowest standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The $R^2$ and SECV were 0.98 (SECV 1.27%) for moisture, 0.88 (SECV 1.26%) for ADF, 0.84 (SECV 2.0%), 0.93 (SECV 0.96%) for CP and 0.78 (SECV 0.56), 0.81 (SECV 0.31%), 0.88 (SECV 1.26%) and 0.82 (SECV 4.46) for pH, lactic acid, TDN and RFV on a dry matter (%), respectively. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation quality of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.
A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.
The purpose of this study was to analyze recognition characteristics of science gifted students on the earth system based on their thinking style. The subjects were 24 science gifted students at the Science Institute for Gifted Students of a university located in metropolitan city in Korea. The students' thinking styles were firstly examined on the basis of the Sternberg's theory of mental self-government. And then, the students were divided into two groups: Type I group(legislative, judicial, global, liberal) and Type II group(executive, local, conservative) based on Sternberg's theory. Data was collected from three different type of questionnaires(A, B, C types), interview, word association method, drawing analyses, concept map, hidden dimension inventory, and in-depth interviews. The findings of analysis indicated that their thinking styles were characterized by 'Legislative', 'Executive', 'Anarchic', 'Global', 'External', 'Liberal' styles. Their preference were conducting new projects and using creative problem solving processes. The results of students' recognition characteristics on earth system were as follows: First, though the two groups' quantitative value on 'System Understanding' was very similar, there were considerable distinctions in details. Second, 'Understanding the Relationship in the System' was closely connected to thinking styles. Type I group was more advantageous with multiple, dynamic, and recursive approach. Third, in the relation to 'System Generalization' both of the groups had similar simple interpretational ability of the system, but Type I group was better on generalization when 'hidden dimension inventory' factor was added. On the system prediction factor, however, students' ability was weak regardless of the type. Consequently, more specific development strategies on various objects are needed for the development and application of the system learning program. Furthermore, it is expected that this study could be practically and effectively used on various fields related to system recognition.
This study was carried out to file up using effect and requirement of energy for environmental design data of Pleurotus eryngii growing houses. Heating and cooling Degree-Hour (D-H) were calculated and compared for. some Pleurotus eryngii growing houses of sandwich-panel (permanent) o. arch-roofed(simple) type structures modified and suggested through field survey and analysis. Also thermal resistance (R-value) was calculated for the heat insulating and covering materials of the permanent and simple-type, which were made of polyurethane or polystyrene panel and $7\~8$ layers heat conservation cover wall. The variations of heating and cooling D-H simulated for Jinju area was nearly linearly proportional to the setting inside temperatures. The variations of cooling D-H was much more sensitive than those of heating D-H. Therefore, it was expected that the variations of required energy in accordance with setting temperature or actual temperature maintained inside of the cultivation house could be estimated and also the estimated results of heating and cooling D-H could be effectively used far the verification of environmental simulation as well as for the calculation of required energy amounts. When the cultivation floor areas are all equal, panel type houses to be constructed by various combinations of materials were found to by far more effective than simple type pipe house in the aspect of energy conservation maintenance except some additional cost invested initially. And also the energy effectiveness of multi-span house compared to single span together with the prediction of energy requirement depending on the level insulated for the wall and roof area could be estimated. Additionally, structural as well as environmental optimizations are expected to be possible by calculating periodical and/or seasonal energy requirements for those various combinations of insulation level and different climate conditions, etc.
Park, Mincheol;Kwon, Oh-Kyun;Kim, Chae Min;Yun, Do Kyun;Choi, Yongkyu
Journal of the Korean Geotechnical Society
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v.35
no.10
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pp.47-66
/
2019
A parametric numerical analysis according to diameter, length, and N values of soil was conducted for the PHC pile socketed into weathered rock through sandy soil layers. In the numerical analysis, the Mohr-Coulomb model was applied to PHC pile and soils, and the contacted phases among the pile-soil-cement paste were modeled as interfaces with a virtual thickness. The parametric numerical analyses for 10 kinds of pile diameters were executed to obtain the load-settlement relationship and the axial load distribution according to N-values. The load-settlement curves were obtained for each load such as total load, total skin friction, skin friction of the sandy soil layer, skin friction of the weathered rock layer and end bearing resistance of the weathered rock. As a result of analysis of various load levels from the load-settlement curves, the settlements corresponding to the inflection point of each curve were appeared as about 5~7% of each pile diameter and were estimated conservatively as 5% of each pile diameter. The load at the inflection point was defined as the mobilized bearing capacity ($Q_m$) and it was used in analyses of pile bearing capacity. And SRF was appeared above average 70%, irrespective of diameter, embedment length of pile and N value of sandy soil layer. Also, skin frictional resistance of sandy soil layers was evaluated above average 80% of total skin frictional resistance. These results can be used in calculating the bearing capacity of prebored PHC pile, and also be utilized in developing the bearing capacity prediction method and chart for the prebored PHC pile socketed into weathered rock through sandy soil layers.
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