Seung-Ji Yang;Young-june Park;Sung-Eun Kim;Jun-Geol Ahn;Hyun-Ik Yang
Composites Research
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v.37
no.1
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pp.7-14
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2024
Due to the structural characteristic of a double roller, the double roller can have various deformation behaviors depending on a gap block design, even if dimensions and loading conditions for the double roller are the same. Based on this feature, we propose a strategy for designing the gap block of the carbon-fiber reinforced plastic (CFRP) double roller to minimize defects (e.g., sagging and wrinkling), which can be raised during the product conveying process, with the pursue of the lightweight design. In the suggested strategy, analysis cases are first selected by considering main design parameters and engineering tolerances of the gap block, and then deformation behaviors of these selected cases are extracted using the finite element method (FEM). Here, to obtain the optimal gap block parameters that satisfy the purpose of this study, deformation deviations in the contact area are calculated and compared using the extracted deformation behaviors. Note that the contact area in this work is located between the product and the roller. As a result, through the design method of the gap block proposed in this work, it is possible to construct the CFRP double roller that can significantly decrease the defects without changing the overall sizes of the roller. A detailed method is suggested herein, and the results are evaluated in a numerical way.
Ryu, Yong Min;Kim, Young Nam;Lee, Dae Won;Lee, Eui Hoon
Journal of Korea Water Resources Association
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v.57
no.2
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pp.73-85
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2024
Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R2 for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.
Dong-Joo Kim;Yong Sung Kwon;Na-Yeon Han;Do-Hun Lee
Korean Journal of Environmental Biology
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v.41
no.4
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pp.413-426
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2023
Species distribution model (SDM) is used to preserve biodiversity and climate change impact. To evaluate biodiversity, various studies are being conducted to utilize and apply SDM. However, there is insufficient research to provide useful information by identifying the current status and recent trends of SDM research and discussing implications for future research. This study analyzed the trends and flow of academic papers, in the use of SDM, published in academic journals in South Korea and provides basic information that can be used for related research in the future. The current state and trends of SDM research were presented using philological methods and text-mining. The papers on SDM have been published 148 times between 1998 and 2023 with 115 (77.7%) papers published since 2015. MaxEnt model was the most widely used, and plant was the main target species. Most of the publications were related to species distribution and evaluation, and climate change. In text mining, the term 'Climate change' emerged as the most frequent keyword and most studies seem to consider biodiversity changes caused by climate change as a topic. In the future, the use of SDM requires several considerations such as selecting the models that are most suitable for various conditions, ensemble models, development of quantitative input variables, and improving the collection system of field survey data. Promoting these methods could help SDM serve as valuable scientific tools for addressing national policy issues like biodiversity conservation and climate change.
LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.
TOPMODEL, semi-distributed hydrological model, is frequently applied to predict the amount of discharge, main flow pathways and water quality in a forested catchment, especially in a spatial dimension. TOPMODEL is a kind of conceptual model, not physical one. The main concept of TOPMODEL is constituted by the topographic index and soil transmissivity. Two components can be used for predicting the surface and subsurface contributing area. This study is conducted for the validation of applicability of TOPMODEL at small forested catchments in Korea. The experimental area is located at Gwangneung forest operated by Korea Forest Research Institute, Gyeonggi-do near Seoul metropolitan. Two study catchments in this area have been working since 1979 ; one is the natural mature deciduous forest(22.0 ha) about 80 years old and the other is the planted young coniferous forest(13.6 ha) about 22 years old. The data collected during the two events in July 1995 and June 2000 at the mature deciduous forest and the three events in July 1995 and 1999, August 2000 at the young coniferous forest were used as the observed data set, respectively. The topographic index was calculated using $10m{\times}10m$ resolution raster digital elevation map(DEM). The distribution of the topographic index ranged from 2.6 to 11.1 at the deciduous and 2.7 to 16.0 at the coniferous catchment. The result of the optimization using the forecasting efficiency as the objective function showed that the model parameter, m and the mean catchment value of surface saturated transmissivity, $lnT_0$ had a high sensitivity. The values of the optimized parameters for m and InT_0 were 0.034 and 0.038; 8.672 and 9.475 at the deciduous and 0.031, 0.032 and 0.033; 5.969, 7.129 and 7.575 at the coniferous catchment, respectively. The forecasting efficiencies resulted from the simulation using the optimized parameter were comparatively high ; 0.958 and 0.909 at the deciduous and 0.825, 0.922 and 0.961 at the coniferous catchment. The observed and simulated hyeto-hydrograph shoed that the time of lag to peak coincided well. Though the total runoff and peakflow of some events showed a discrepancy between the observed and simulated output, TOPMODEL could overall predict a hydrologic output at the estimation error less than 10 %. Therefore, TOPMODEL is useful tool for the prediction of runoff at an ungaged forested catchment in Korea.
The purpose of this study is to establish a method of estimating the daily urban water demand using statistical model. This method will be used for the development of the efficient management and operation of the water supply facilities. The data used were the daily urban water use, the population, the year lapse and the weather conditions such as temperature, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. The raw data used in this study were rearranged either by month or by season for the purpose of analysis, and the statistical analysis was applied to the data to obtain the regression model. As a result, the multiple linear regression model was developed to estimate the daily urban water use based on the seather condition. The regression constant and the model coefficients were determined for each month of a year. The accuracy of the model was within 3% of average error and within 10% of maximum error. The developed model was found to be useful to the practical operation and management of the water supply facilities.
The 2001 Leonid meteor storm has been observed all over the world, and its most intense flux since the last few decades has caused great interest among both laymen and experts. Especially, its maximum hours occurred at dawn hours of Nov. 19 in the east Asia, during which moonless clear night at the Mt. Bohyun allowed us near perfect condition of observation. Observation was carried out in the period of 01:00∼05:40(KST), which include the predicted maximum hours, with all-sky camera installed for upper atmospheric airglow research. Tn this paper we analyze 68 all-sky images obtained in this period, which contain records of 172 meteors. Utilizing the zenith hourly rate(ZHR) of 3000 and magnitude distribution index of 2, which were reported to International Meteor Organization by visible observers in the east Asia, we estimate the limiting magnitude of about 3 for meteors detected in our all-sky images. We then derive magnitudes of 83 meteors with clear pixel brightness outlines among the initially detected 172 meteors by comparing with neighbor standard stars. Angular velocities of meteors needed for computing their passing times over an all-sky image are expressed with a simple formula of an angle between a meteor head and the Leonid radiant point. The derived magnitudes of 83 meteors are in the range of -6∼-1 magnitude, and its distribution shows a maximum new -3mag. The derived magnitudes are much smaller than the limiting magnitude inferred from the comparison with the result of naked-eye observations. The difference may be due to the characteristic difference between nearly instantaneuous naked-eye observations and CCD observations with a long exposure. We redetermine magnitudes of the meteors by adjusting a meteor lasting time to be consistent with the naked-eye observations. The relative distribution of the redetermined magnitudes, which has a maximum at 0 mag., resembles that of the magnitudes determined with the in-principle method. The relative distribution is quite different from ones that decrease monotonically with decreasing magnitudes for meteors(1∼6) sensitive to naked-eye observations. We conclude from the magnitude distribution of our all-sky observation that meteors brighter than about 0 mag., appeared more frequently during the 2001 Leonid maximum hours. The frequent appearance of bright meteors has significantly important implication for meteor research. We noted, however, considerably large uncertainties in magnitudes determined only by comparing standard stars due to the unknown lasting time of meteors and the non-linear sensitivity of all-sky camera.
Choi Kyoung Sik;Oh Seung Jong;Lee Jeong Woo;Kim Jeung Kee;Suh Tae Suk;Choe Bo Young;Kim Moon Chan;Chung Hyun-Tai
Progress in Medical Physics
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v.16
no.1
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pp.24-31
/
2005
The stereotactic radiosurgery (SRS) describes a method of delivering a high dose of radiation to a small tar-get volume in the brain, generally in a single fraction, while the dose delivered to the surrounding normal tissue should be minimized. To perform automatic plan of the SRS, a new method of multi-isocenter/shot linear accelerator (linac) and gamma knife (GK) radiosurgery treatment plan was developed, based on a physical lattice structure in target. The optimal radiosurgical plan had been constructed by many beam parameters in a linear accelerator or gamma knife-based radiation therapy. In this work, an isocenter/shot was modeled as a sphere, which is equal to the circular collimator/helmet hole size because the dimension of the 50% isodose level in the dose profile is similar to its size. In a computer-aided system, it accomplished first an automatic arrangement of multi-isocenter/shot considering two parameters such as positions and collimator/helmet sizes for each isocenter/shot. Simultaneously, an irregularly shaped target was approximated by cubic structures through computation of voxel units. The treatment planning method by the technique was evaluated as a dose distribution by dose volume histograms, dose conformity, and dose homogeneity to targets. For irregularly shaped targets, the new method performed optimal multi-isocenter packing, and it only took a few seconds in a computer-aided system. The targets were included in a more than 50% isodose curve. The dose conformity was ordinarily acceptable levels and the dose homogeneity was always less than 2.0, satisfying for various targets referred to Radiation Therapy Oncology Group (RTOG) SRS criteria. In conclusion, this approach by physical lattice structure could be a useful radiosurgical plan without restrictions in the various tumor shapes and the different modality techniques such as linac and GK for SRS.
Persimmon powder (PW), which was prepared by pulverizing freeze-dried persimmon with peels, was added to Maejakgwa up to 25% of wheat flour. Maejakgwa samples were prepared by the central composit experimental design for three independent variables: amount of PW, frying time, and frying temperature. The color of Maejakgwa was influenced more by the frying time and temperature than the content of added PW. Crispiness and adhesiveness were highly correlated with overall preference. Although the amount of PW affected the adhesiveness, the adhesiveness could be controlled by the frying temperature and time. Frying temperature was the most effective factor on the crispness and hardness. The addition of high amount of PW obviously increased the sweetness and aftertaste. However, at the low amount of PW, frying for longer time at high temperature also increased the sweetness and aftertaste. Center sample (15% PW, frying for 4 min at 145$\^{C}$) showed the best score at the overall preference. Overall preference was improved as the sample was fried at high temperature/short time or at low temperature/long time. Maejakwa prepared with high amount of PW at 20% showed no significant difference with the center sample for overall preference as prepared by frying for 3 min at 155$\^{C}$. The optimum condition obtained by superimposing color, crispiness and overall preference was frying for 5∼6 min at 131∼140$\^{C}$.
Previously, cellulase and xylanase producing microorganism, Bacillus subtilis NC1, was isolated from soil. Based on the 16S rRNA gene sequence and API 50 CHL test the strain was identified as Bacillus subtilis, and named as B. subtilis NC1. We cloned and sequenced the genes for cellulase and xylanase. Plus, the deduced amino acid sequences from the genes of cellulase and xylanase were determined and were also identified as glycosyl hydrolases family (GH) 5 and 30, respectively. In this study to optimize the medium parameters for cellulase production by B. subtilis NC1 the RSM (response surface methodology) based on CCD (central composite design) model was performed. Three factors, tryptone, yeast extract, and NaCl, for N or C source were investigated. The cellulase activity was measured with a carboxylmethyl cellulose (CMC) plate and the 3,5-dinitrosalicylic acid (DNS) methods. The coefficient of determination (R2) for the model was 0.960, and the probability value (p=0.0001) of the regression model was highly significant. Based on the RSM, the optimum conditions for cellulase production by B. subtilis NC1 were predicted to be tryptone of 2.5%, yeast extract of 0.5%, and NaCl of 1.0%. Through the model verification, cellulase activity of Bacillus subtilis NC1 increased from 0.5 to 0.62 U/ml (24%) compared to the original medium.
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