Journal of Korean Society of Environmental Engineers
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v.35
no.8
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pp.554-563
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2013
The purpose of this study is to evaluate the possibility of nutrient release at up and downstream of Kangchun weir, upstream of Yuju and Ipo weir in Namhan River. For this survey, we measured basic characteristics of the sediments (water content, ignition loss, TOC, TP, SRP, TN, phosphorus fractionation) and conducted nutrients release experiments under both aerobic and anaerobic condition. The overlying water from the sediment-water column was analyzed for nutrients (i.e. TP, $PO_4$-P, TN, $NO_3$-N, $NH_3$-N) everyday for 18days. Result of soil texture experiment showed that sediments are Sand. SRP concentration before the release experiment was different with the value after the release experiment. According to this result, we can find that there were more activated release processes in anaerobic condition. $PO_4$-P increased from 1 to 8 days and remained at the maximum value (7~8 days) afterward. The rapidly increase of $PO_4$-P was observed from 1 to 2~3 days whereas the TP continuously increase from 1 to 18 days. The $PO_4$-P release rate calculated by up to 7~8 days data highly correlated with initial SRP concentration with $R^2$=0.8502. $NO_3$-N release rate appears constantly decreasing trend as -5.7~-3.08 $mg/m^2{\cdot}day$, otherwise the $NH_3$-N release rate, by-product of a organic matter decomposition using nitrate as electron acceptor, was 0.57~2.41 $mg/m^2{\cdot}day$. Substantial portion in TN can be induced by organic nitrogen which originated from the tributary passing through non-point pollutant source. Compared with other similar researches, phosphorus and nitrogen release rates obtained in this study can be considered as relatively low values. Since this study targeted the sediments accumulated by one time of flooding season, there are limitation to generalize theses results. Therefore, it is necessary to consistently monitor and investigate the accumulation of nutrients in the sediment for understanding the effect of weir construction on the overlying water quality.
The Journal of Korean Institute of Electromagnetic Engineering and Science
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v.13
no.7
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pp.667-678
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2002
In this paper, a new radiating structure with a multi-layered two-dimensional metallic disk array was proposed for shaping the flat-topped element pattern. It is an infinite periodic planar array structure with metallic disks finitely stacked above the radiating circular waveguide apertures. The theoretical analysis was in detail performed using rigid full-wave analysis, and was based on modal representations for the fields in the partial regions of the array structure and for the currents on the metallic disks. The final system of linear algebraic equations was derived using the orthogonal property of vector wave functions, mode-matching method, boundary conditions and Galerkin's method, and also their unknown modal coefficients needed for calculation of the array characteristics were determined by Gauss elimination method. The application of the algorithm was demonstrated in an array design for shaping the flat-topped element patterns of $\pm$20$^{\circ}$ beam width in Ka-band. The optimal design parameters normalized by a wavelength for general applications are presented, which are obtained through optimization process on the basis of simulation and design experience. A Ka-band experimental breadboard with symmetric nineteen elements was fabricated to compare simulation results with experimental results. The metallic disks array structure stacked above the radiating circular waveguide apertures was realized using ion-beam deposition method on thin polymer films. It was shown that the calculated and measured element patterns of the breadboard were in very close agreement within the beam scanning range. The result analysis for side lobe and grating lobe was done, and also a blindness phenomenon was discussed, which may cause by multi-layered metallic disk structure at the broadside. Input VSWR of the breadboard was less than 1.14, and its gains measured at 29.0 GHz. 29.5 GHz and 30 GHz were 10.2 dB, 10.0 dB and 10.7 dB, respectively. The experimental and simulation results showed that the proposed multi-layered metallic disk array structure could shape the efficient flat-topped element pattern.
An arboretum is defined as a collection of facilities that conserve plant species by surveying, collecting, and proliferating and preserving the plants in nature, perform diverse researches on plants and display the plants in exhibition spaces or outdoors as well as provide the public with educational programs and refreshment spaces according to the laws concerned. The public, however, recognizes the exhibition and education functions on plants of arboretum more importantly compared with the roles to survey, collect, and proliferate plants as regulated by the laws. In particular, arboretum plays a role to offer a pivotal educational place in urban area where the public can obtain an hands-on experience and understanding on a wide range of plant species and natural environment. The study aims to estimate the non market environmental values of Daegu Arboretum operated by Daegu Metropolitan City government by using the Contingent Valuation Methods (CVM), which yields the current monetary estimates for the arboretum. The value estimation was undertaken by using the Double-Bound Dichotomous Choice (DBDC) method, and each estimated value was derived from respective functions based on a logit distribution known to include relatively stable estimates according to the shape of the distribution. Considering the statistical fitness test results, the author estimated the amounts of the Willingness To Pay (WTP) such as mean WTP of 12,718 KRW, median WTP of 11,033 KRW, and truncated mean WTP of 11,468 KRW, which represented the annual recreational values per a person visiting Daegu Arboretum respectively. The analysis showed that Daegu Arboretum created the annual environmental values which were estimated to be approximately 16 to 19 billion KRW. The study also has an implication that the valuation method for the environment of Daegu Arboretum may be effectively applied for estimating the values of other types of environmental goods by altering the locations or goods to be analyzed.
Video adaptation in response to dynamic resource conditions and user preferences is required as a key technology to enable universal multimedia access (UMA) through heterogeneous networks by a multitude of devices In a seamless way. Although many adaptation techniques exist, selections of appropriate adaptations among multiple choices that would satisfy given constraints are often ad hoc. To provide a systematic solution, we present a general conceptual framework to model video entity, adaptation, resource, utility, and relations among them. It allows for formulation of various adaptation problems as resource-constrained utility maximization. We apply the framework to a practical case of dynamic bit rate adaptation of MPEG-4 video streams by employing combination of frame dropping and DCT coefficient dropping. Furthermore, we present a descriptor, which has been accepted as a part of MPEG-21 Digital Item Adaptation (DIA), for supporting terminal and network quality of service (QoS) in an interoperable manner. Experiments are presented to demonstrate the feasibility of the presented framework using the descriptor.
There is a lot of method to manage the insanitary landfill but vertical cutoff walls have been widespreadly used and were installed into the subsurface to act as a barrier to horizontal groundwater flow, The stabilized material such as specialized cement or mixed soil with additives has been generally applied for the materials of the deep soil mixing barrier in korea. The amount of the stabilized material is dependent on the field conditions, because the mixing ratio of the material and the field soil should achieve a requirement in the coefficient of permeability, lower than 1.0$\times$$10^{7}$cm/sec. This study determined the quantity and optimized function ratio of the stabilized material in the formation process of the mixed barrier that was added with stabilized material on the field soil classified into SW-SC under USCS (Unified Soil Classification System). After that the fly ash and lime were selected as an additives an that could improve the function of the stabilized material and then the method to improve the functional progress in the usage of putting into the stabilized material as an appropriate ratio was studied and reviewed. The author used the flexible-wall permeameter for measuring the permeability and unconfined compressive strength tester for compressive strength, and in the view of environmental engineering the absorption test of heavy metals and leaching test regulated by Korean Waste Management Act were performed. As the results, the suitable mixing ratio of the stabilized material in the deep soil mixing barrier was determined as 13 percent. To make workability easy, the ratio of stabilized material and water was proven to be 1 : 1.5. With the results, the range of the portion of the additives(fly ash : lime= 70 : 30) was proven to be 20-40% for improving the function of the stabilized material, lowering of permeability. In heavy metal absorption assessment of the mixing barrier system with the additives, the result of heavy metal absorption was proved to be almost same with the case of the original stabilized material; high removal efficiency of heavy metals. In addition, the leaching concentration of heavy metals from the leaching test for the environmental hazard assessment showed lower than the regulated criteria.
Park, Gab Soon;Kim, Yeoung Chil;Ann, Seoung Won;Kang, Hee Kyoung;Choi, Jong Myung
Horticultural Science & Technology
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v.33
no.1
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pp.47-54
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2015
This research was conducted to investigate the changes in moisture retention capacities of expanded rice-hull (ERH)-based root media and their influences on the growth of mother and daughter plants in vegetative propagation of 'Seolhyang' strawberry. The proportion of water at the container capacity of ERH medium was in the range of 20 to 23%. This range was lower than the 60 to 66% of strawberry-specialized medium, the 30 to 34% of soil mother material (SMM) and the 30 to 35% of loamy sand. The moisture content of ERH was reduced to 10 to 12% at 8 hours after irrigation, and there were large variations among replications of ERH medium. Among four kinds of root media formulated to contain ERH, the medium of ERH + coir dust (CD) (55 + 45%, v/v) had 26.5 and 32.5% water contents at 20 and 40 days after irrigation to daughter plants, respectively. The m edia o f ERH + sandy loam (S L) and E RH + S MM showed similar trends i n moisture r etention. The pH and EC i n the all root media tested were in the range of 6.7 to 7.1 and 0.03 to $0.08dS{\cdot}m^{-1}$, respectively. The pHs and ECs measured at 20 and 40 days after irrigation were not significantly different in each root medium. Among the root media formulated to contain ERH, the growth of daughter plants was the highest in the treatment of ERH + SL (55 + 45%, v/v). As the blending rate of coir dust was elevated in the ERH + CD media, moisture retention capacity increased gradually, but the growth of daughter plants became worse even though the medium showed higher moisture retention capacity than other root media tested. The growth of roots and aboveground tissues of daughter plants deteriorated in the root media formulated by blending ERH + perlite (PE) at various ratios. The results of this research suggest the optimum formulations of root media and management of moisture content in raising of strawberry daughter plants when ERH is a component of root media.
Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.
In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.
In temperate zone planting rice at different date subjects the Crop to different climatic condition. The present study aimed at comparison of the change in source-sink relationship of the Japonica(J) and that of IndicaxJaponica(I$\times$J) type rice cultivars caused by shift of heading date. Two J- and two I$\times$J-type cultivars were made to head on August 16, August 26, and September 5. Sink capacity was changed by shift of heading date in different mode between the types of cultivars. In both types major determinant of sink capacity was number of effective tillers, and the number of spikelets per panicle was the minor. In J-type earlier planting/heading was beneficial to increased panicle numbers and this was due mainly to a larger diurnal difference in temperature. I$\times$J-type cultivars favored a higher daily mean temperature to increase the sink capacity. The ability of source at heading, in terms of leaf area per panicle, chlorophyll content per spiklet, photosynthetic ability of leaves per unit area at 25$\^{\circ}C$, carbohydrate and N contents of leaves, was not so different among different heading dates in both types. However, the source activity was governed principally by temperature during grain filling. The J-type cultivars headed on Sept. 5 and I$\times$J-type cultivars headed later than August 16 could not have had sufficient source activity in grain filling due to lower temperature.
In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (108 or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 108. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.
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