Journal of the Computational Structural Engineering Institute of Korea
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v.15
no.4
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pp.591-598
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2002
In the ship structural design, the material cost of hull weight and the overall cost of construction processes should be minimized considering safety and reliability. In the past, minimum weight design has been mainly focused on reducing material cost and increasing dead weight reflect the interests of a ship's owner. But, in the past experience, the minimum weight design has been inevitably lead to increasing the construction cost. Therefore, it is necessary that the designer of ship structure should consider both structural weight and construction cost. In this point of view, multi-objective optimization technique is proposed to design the ship structure in this study. According to the proposed algorithm, the results of optimization were compared to the structural design of actual VLCC(Very Large Crude Oil Carrier). Objective functions were weight cost and construction cost of VLCC, and ES(Evolution Strategies), one of the stochastic search methods, was used as an optimization solver. For the scantlings of members and the estimations of objectives, classification rule was adopted for the longitudinal members, and the direct calculation method, GSDM(Generalized Slope Deflection Method), lot the transverse members. To choose the most economical design point among the results of Pareto optimal set, RFR(Required Freight Rate) was evaluated for each Pareto point, and compared to actual ship.
Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.
Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.
This study was conducted to test the green-tide mitigation technique in the lower part of the Sook Stream (Chusori) of Daecheong Reservoir from June 27 to August 24, 2014. And the effects were compared with weekly monitoring result of the watching station of the algae alert system (AAS) as well as test beds reach. The green-tide in a test bed was begun from the upstream, and it was gradually transferred and spread toward the downstream by the hydrological factors. The total amount of algae removed by algae removal device during the test period was 33,920 kg, and solids dewatered by natural gravity was 8,480 kg. Also chlorophyll-a content was 2.83 kg, the number of blue-green algae cells was equivalent to $78.6{\times}10^{14}$ cells. Compared with the results of the watching station of AAS, the pre-concentrate removal work in the outbreak waters was able to suggest the possibility of green-tide mitigation. In addition, an effective management of the green-tide was required spatial and temporal occurrence information and practical device technology. Particularly, the optimal timing of algae removal in the river-reservoir hybrid system was recommended at times before the monsoon rainy season and reached the lowest water level.
Kim, Hyun-cheol;Han, Hyangsun;Hyun, Chang-Uk;Chi, Junhwa;Son, Young-sun;Lee, Sungjae
Korean Journal of Remote Sensing
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v.34
no.6_2
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pp.1283-1298
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2018
KOPRI(Korea Polar Research Institute) have researhed Arctic sea ice by using satellite remote sensing data since 2017 as a mission of KOPRI. The title of the reseach is "Development of Satellite Observation and Analysis for Arctc sea-ice". This project has three major aims; 1) development of prototype satellite data archive/manage system for Arctic sea ice monitoring, 2) development of sea ice remote sensing data processing and analysis technique, and 3) development of international satellite observing network for Arcitc. This reseach will give us that 1) deveolpment of sea ice observing system for northern sea route, 2) development of optimal remote sensing data processing technique for sea ice and selected satelite sensors, 3) development of international satellite onbservation network. I hope that this letter of introducton KOPRI satellite program for Arctic will help to understand Arctic remote sensing and will introduce you to step into the Arctic remote sensing, which Iis like a blue ocean of remote sensing.
Min-Geun, Kim;Seok-Chan, Kim;Jaeseung, Kim;Jai-Kyung, Lee;Geun-Ho, Lee
Journal of the Computational Structural Engineering Institute of Korea
/
v.35
no.6
/
pp.367-374
/
2022
This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.
Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.
The objective of this study was to develop models for the predict of the milk properties (fat, protein, SNF, lactose, MUN) of unhomogenized milk using the visible and near-infrared (NIR) spectroscopic technique. A total of 180 milk samples were collected from dairy farms. To determine optimal measurement temperature, the temperatures of the milk samples were kept at three levels ($5^{\circ}C$, $20^{\circ}C$, and $40^{\circ}C$). A spectrophotometer was used to measure the reflectance spectra of the milk samples. Multilinear-regression (MLR) models with stepwise method were developed for the selection of the optimal wavelength. The preprocessing methods were used to minimize the spectroscopic noise, and the partial-least-square (PLS) models were developed to prediction of the milk properties of the unhomogenized milk. The PLS results showed that there was a good correlation between the predicted and measured milk properties of the samples at $40^{\circ}C$ and at 400~2,500 nm. The optimal-wavelength range of fat and protein were 1,600~1,800 nm, and normalization improved the prediction performance. The SNF and lactose were optimized at 1,600~1,900 nm, and the MUN at 600~800 nm. The best preprocessing method for SNF, lactose, and MUN turned out to be smoothing, MSC, and second derivative. The Correlation coefficients between the predicted and measured fat, protein, SNF, lactose, and MUN were 0.98, 0.90, 0.82, 0.75, and 0.61, respectively. The study results indicate that the models can be used to assess milk quality.
This pot experiment was conducted to find out the optimal fertilization ratio of the cations(K: Ca: Mg) in various soil conditions. Soil samples were collected from uncultivated mountains and hills where development for grass lands is under consideration. The optimum ratios were computed by the Homes systematic variation technique. The results were summarized as follows : 1. The optimum fertilization ratios of the cations (K : Ca : Mg) for the high yields of grass-clover mixed sward at various areas were obtained (Table 4) 2. The relatively high optimum fertilization ratios of K in Daegu and Taegwalryong, Ca in Unbong, and Mg in Cheju district gave the high yields of clover in mixed sward. They were positively related to the low contents of the above cations in the soils or the relatively low content ratio comparing with other cations. 3. The yields of clover in mixed sward were seriously affected by the changes in both the fertilization ratio and total concentration of cations comparing to those of the grass yields. As a consequence, total yields, quality, and botanical composition of the mixed sward were also affected. 4. The antagonis among the cations K, Ca, and Mg was known from the point of mineral contents of grass and clover. 5. The equivalent ratio K/(Ca+Mg) or grass was greatly increased by the range of 2.4 and 3.3 in the K-group treatment, which was higher than the critical level 2.2 of grass tetany, otherwise that. of clover by the range of 0.9 and 1.2. Therfore, it may be concluded that if the botanical composition of grass/legume sward is optimum, the incidence of grass tetany can be eliminated.
Journal of The Korean Society of Grassland and Forage Science
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v.9
no.1
/
pp.26-33
/
1989
This pot experiments were conducted to find out the optimal fertilization ratios of the N:S:P anions and K:Ca:Mg cations of major nutrients in an orchardgrass/ladino clover mixed sward. The optimum ratios in equivalent basis were computed by the Homes systematic variations technique. The soil samples were collected from the newly reclaimed soils, which are located on colluvial hilly area with a good consideration for the hilly pasture development. The results were summarized as follows; 1, the optimum fertilization ratios of major nutrients for the high yields by the forage species in a mixed sward were obtained (Table 4 in detail); N:S:P = 3:l: 1 and K:Ca:Mg = 1:l: 1 for grass and grass plus legume, and N:S:P = 1:6:43 and K:Ca:Mg = 1: 3: 1 for legume in general. 2. The yield increases from the systematic variations in this mixed sward were laid in following order; N > P >S-group and K >Mg >Ca-group for grass and grass plus legume, and P >S >N-group and Ca >Mg > K-group for legume. Especially, the yields were greatly increased at the N-group for grass, and at the Pand Ca-groups for legume. 3. Soil pH-value was descreased at the Sgroup, and somewhat increased at the Ca- and Mg-groups. The content of available $P_2O_5$, CEC and base saturation were greatest with the Ca-group. 4. At the N-group, the N-contents were highest and the P-contents were lowest in grass and grass plus legume, which resulted in the highest Ca/P ratio of 2.15 among the anion groups. Whereas the highest Ca/P ratio of 9.20 in legume was obtained at the Ca-group. Legume showed in general higher Ca/P ratio and lower K/(Ca+Mg) ratio than these in grass. 5 . There were differences in the effects of systematic variations of major nutrients on the dry matter yields and the mineral yields. The optimum fertilization ratios of anions and cations for the high mineral yields were obtained (Table E), which showed differences comparing with the ratios for the high dry matter yields. The antagonis between the cations K and Mg was known from the point of mineral yields of mixed forages.
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