• Journal of Korean Society of Environmental Engineers
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• v.32 no.8
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• pp.739-746
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• 2010

The purposes of this study are 1) to develop an advanced chamber system within ${\pm}10%$ of air velocity at the particulate matter (PM) collection area, 2) to research theoretical characteristics of PM10 and PM2.5 samplers, 3) to assess the performance characteristics of PM10 and PM2.5 samplers through chamber experiments. The total six one-hour experiments were conducted using the cornstarch with an mass median aerodynamic diameter (MMAD) of $20\;{\mu}m$ and an geometric standard deviation of 2.0 at the two different air velocity conditions of 0.67 m/s and 2.15 m/s in the chamber. The aerosol samplers used in the present study are one APM PM10 and one PM2.5 samplers accordance with the US federal reference methods and specially designed three mini-volume aerosol samplers (two for PM10 and one for PM2.5). The overall results indicate that PM10 and PM2.5 mini-volume samplers need correction factors of 0.25 and 0.39 respectively when APM PM samplers considered as reference samplers and there is significant difference between two mini-volume aerosol samplers when a two-way analysis of variance is tested using the measured PM10 mass concentrations. The PM10 and PM2.5 samplers with the cutpoints and slopes (PM10: $10{\pm}0.5\;{\mu}m$ and $1.5{\pm}0.1$, PM2.5: $2.5{\pm}0.2\;{\mu}m$ and $1.3{\pm}0.03$) theoretically collect the ranges of 86~114% and 64~152% considering the cornstarch characteristics used in this research. Furthermore, the calculated mass concentrations of PM samplers are higher than the ideal mass concentrations when the airborne MMADs for the cornstarch used are smaller than the cutpoints of PM samplers and the PM samplers collected less PM in another case. The chamber experiment also showed that PM10 and PM2.5 samplers had the bigger collection ranges of 37~158% and 55~149% than the theocratical calculated mass concentration ranges and the relatively similar mass concentration ranges were measured at the air velocity of 2.15 m/s comparing with the 0.67 m/s.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.863-874
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• 2018

The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.2
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• pp.127-138
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• 2000

To enable rapid and convenient soil test, new soil analytical methods, which require only one instrument, UV/Vis spectrophotometer, were developed and named "Soiltek KA-P spectrophotometric methods". The Soiltek$^{(R)}$ KA-P spectrophotometric method was compared with standard method of RDA in analytical capability for soil chemical properties. Using the 78 soils collected from upland, paddy, orchard, and vinyl house soils, soil organic matter, exchangeable K, Ca, and Mg. CEC, available $SiO_2$, and nitrate were analyzed by the two methods. The color stability(ratio of the absorbance at elapsed time t to the absorbance at time t=0) of organic matter. Ca, Mg, and available $SiO_2$ decreased to about 2% within one hour. However, that of exchangeable K, CEC, and nitrate remained constant. The results obtained with Soiltek$^{(R)}$ KA-P spectrophotometric method showed highly significant correlation with those measured by the standard method of RDA($R^2$ >0.9501), in which the slopes were near unity of $1.0{\pm}0.05$. The standard deviation values of organic matter, exchangeable K, Ca, and Mg, CEC, available $SiO_2$, and nitrate were apparently lower than ${\pm}1.8gkg^{-1}$, ${\pm}0.05cmol^+kg^{-1}$, ${\pm}0.18cmol^+kg^{-1}$, and ${\pm}0.13cmol^+kg^{-1}$, ${\pm}1.0cmol^+kg^{-1}$, ${\pm}5.0mgkg^{-1}$, and ${\pm}10.0mgkg^{-1}$, respectively. All the measurements showed coefficients of variation of less than 7~17% and were within the confidence level of 95%, which means both the methods are precise. Considering the relative simplicity, low cost, precision and accuracy, the proposed Soiltek$^{(R)}$ KA-P spectrophotometric methods could be recommended as an alternative to standard method.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.845-862
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• 1995

We followed prospectively some hospital-delivered mothers to identify characteristics of those not initiated breast-feeding and predictors of breast-feeding discontinuation in monthly telephone interviews. Recruits were composed of 482 mothers who delivered their babies at one university hospital and one OB/GYN clinic in September to November 1991. Breast-feeding discontinuation was defined as switch to 100% formula lasting more than one week regardless of solid foods. Average age of the study subjects was 27.3 years of age(standard deviation 3.2). Multiple logistic regression analysis indicated native place, occupation, method of delivery and method of feeding considered to be better for maternal health were statistically significant(p<0.1) between initiators and non-initiators of breast feeding. In starting cohort(N=242) of those initiated breast-feeding, that median of breast-feeding discontinuation were 5 months and 25th and 75th percentiles were 3 and 9 months respectively. In Cox's proportional hazard model, mothers with $10\sim13$ years of education were 2.63 times (95% confidence interval, CI $1.50\sim4.60$) more likely to discontinue than those with less than 9 years of education and those with more than 13 years of education were 3.55 time (95% CI $1.99\sim6.33$). Compared with house wife, mothers with part-time jobs were 1.99 times (95% CI $0.86\sim4.57$) more likely to discontinue and those with employed full-time were 1.55 times (95% CI $0.96\sim2.51$). These results suggest that the predictors of initiation and discontinuation of breast-feeding may be different and different target populations should be selected to promote initiation and to prevent discontinuation of breast-feeding according to the period after birth.

• The Korean Journal of Nuclear Medicine
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• v.36 no.4
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• pp.271-276
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• 2002

Purpose: To measure reliable glomerular filtration rate by using the representative values of transplanted renal depths, which are measured with ultrasonography. Materials and Methods: We included 54 patients (26 men, 28 women), with having both renal scintigraphy and ultrasonography after renal transplantation. We measured GFR with Gates' method using the renal depth measured by ultrasonography, and median and mean ones in each patient. We compared GFR derived from ultrasonography-measured renal depth with GFR derived from median and mean renal depths. The correlation coefficients were obtained among GFR derived from ultrasonography-measured renal depths, median and mean renal depths under linear regression analysis. We determined whether GFR derived from median or mean renal depth could substitute GFR derived from ultrasonography-measured renal depth with Bland-Altman method. We analyze the expected errors of the GFR using representative renal depth in terms of age, sex, weight, height, creatinine value, and body surface. Results: The transplanted renal depths range from 3.20 cm to 5.96 cm. The mean value and standard deviation of renal depths measured by ultrasonography are $4.09{\pm}0.65cm$ in men, and $4.24{\pm}0.78cm$ in women. The median value of renal depths measured by ultrasonography is 4.36 cm in men and 4.14 cm in women. The GFR derived from median renal depth is more consistent with GFR derived from ultrasonography-measured renal depth than GFR derived from mean renal depth. Differences of GFR derived from median and ultrasonography-measured renal depth are not significantly different in the groups classified with creatinine value, age, sex, height, weight and body surface. Conclusion: When median value is adapted as a representative renal depth, we could obtain reliable GFR in transplanted kidney simply.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.77-86
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• 1986

The purpose of this study is to estimate an optimum formula of rainfall intensity on basis of the characteristics for short period of rainfall duration in Kyungpook province for the design of urban sewerage and small basin drain system. Results studied are as follows; 1. The optimum method for Taegu and Pohang, Iwai's and Gumbel-Chow's method are recommended respectively. 2. The opotimum type of rainfall intensity for these area, $I=\frac{a}{\sqrt{t}+b}$ (Japanese type), is confirmed with 2.52~4.17 and 1.86~4.54 as a standard deviation for Taegu and Pohang respectively. The optimum formula of rainfall intensity are as follows. Taegu : T : 200 year - $I=\frac{824}{\sqrt{t}+1.5414}$ T : 100 year - $I=\frac{751}{\sqrt{t}+1.4902}$ T : 50 year - $I=\frac{678}{\sqrt{t}+1.4437}$ T : 30 year - $I=\frac{623}{\sqrt{t}+1.4017}$ T : 20 year - $I=\frac{580}{\sqrt{t}+1.3721}$ T : 10 year - $I=\frac{502}{\sqrt{t}+1.3145}$ T : 5 year - $I=\frac{418}{\sqrt{t}+1.2515}$ Pohang : T : 200 year - $I=\frac{468}{\sqrt{t}+1.1468}$ T : 100 year - $I=\frac{429}{\sqrt{t}+1.1605}$ T : 50 year - $I=\frac{391}{\sqrt{t}+1.1852}$ T : 30 year - $I=\frac{362}{\sqrt{t}+1.2033}$ T : 20 year - $I=\frac{339}{\sqrt{t}+1.2229}$ T : 10 year - $I=\frac{299}{\sqrt{t}+1.2578}$ T : 5 year - $I=\frac{257}{\sqrt{t}+1.3026}$ 3. Significant I.D.F. curves derived should be applied to estimate a suitable rainfall intensity and rainfall duration.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.278-286
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• 2021

In this study, based on the Computational Fluid Dynamics (CFD) simulation model developed through previous study, inner environmenct of the modified glass greenhouse was predicted. Also, suggested the optimal shape of the greenhouse and location of the heat exchangers for heat energy management of the greenhouse using the developed model. For efficient heating energy management, the glass greenhouse was modified by changing the cross-section design and the location of the heat exchanger. The optimal cross-section design was selected based on the cross-section design standard of Republic of Korea's glass greenhouse, and the Fan Coil Unit(FCU) and the radiating pipe were re-positioned based on "Standard of greenhouse environment design" to enhance energy saving efficiency. The simulation analysis was performed to predict the inner temperature distribution and heat transfer with the modified greenhouse structure using the developed inner environment prediction model. As a result of simulation, the mean temperature and uniformity of the modified greenhouse were 0.65℃, 0.75%p higher than those of the control greenhouse, respectively. Also, the maximum deviation decreased by an average of 0.25℃. And the mean age of air was 18 sec. lower than that of the control greenhouse. It was confirmed that efficient heating energy management was possible in the modified greenhouse, when considered the temperature uniformity and the ventilation performance.

• Analytical Science and Technology
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• v.31 no.6
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• pp.240-246
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• 2018

The present study analyzed standard samples of three types of aluminum matrix certified reference materials (CRM) using GD-MS. Calibration curves were constructed for 13 elements (Mg, Si, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Sn, and Pb), with the slope representing the relative sensitivity factor (RSF). The x- and y-axes of the calibration curve represented ion beam ratio (IBR) and the authenticated value of the standard sample, respectively. In order to evaluate precision and linearity of the calibration curve, RSD and the coefficient of determination were calculated. Curve RSD for every element reflected high precision (within 10 %). For most elements, the coefficient of determination was ${\geq}0.99$, indicating excellent linearity. However, vanadium, nickel, and gallium curves exhibited relatively low linearity (0.90~0.95), likely due to their narrow concentration ranges. Standard RSF was calculated using the slope of the curve generated for three types of CRM. Despite vanadium, nickel, and gallium exhibiting low coefficients of determination, their standard RSF resembled that of the three types of CRM. Therefore, the RSF method may be used for element quantitation. Standard iron matrix samples were analyzed to verify the applicability of the aluminum matrix standard RSF, as well as to calculate the RSD-estimated error of the measured value relative to the actual standard value. Six elements (Al, Si, V, Cr, Mn, and Ni) exhibited an RSD of approximately 30 %, while the RSD of Cu was 77 %. In general, Cu isotopes are subject to interference: $^{63}Cu$ to $^{54}Fe^{2+}-^{36}Ar$ and $^{65}Cu$ to $^{56}Fe-Al^{3+}$ interference. Thus, the influence of these impurities may have contributed to the high RSD value observed for Cu. To reliably identify copper, the resolution should be set at ${\geq}8000$. However, high resolutions are inappropriate for analyzing trace elements, as it lowers ion permeability. In conclusion, quantitation of even relatively low amounts of six elements (Al, Si, V, Cr, Mn, and Ni) is possible using this method.