• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.297-304
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• 2004

In this paper, a mesh simplification algorithm based on wavelet transform and 2D planar sampling is proposed for efficient handling of 3D objects in computer applications. Since 3D vertices are directly transformed with wavelets in conventional mesh compression and simplification algorithms, it is difficult to solve tiling optimization problems which reconnect vertices into faces in the synthesis stage highly demanding vertex connectivities. However, a 3D mesh is sampled onto 2D planes and 2D polygons on the planes are independently simplified in the proposed algorithm. Accordingly, the transform of 2D polygons is very tractable and their connection information Is replaced with a sequence of vertices. The vertex sequence of the 2D polygons on each plane is analyzed with wavelets and the transformed data are simplified by removing small wavelet coefficients which are not dominant in the subjective quality of its shape. Therefore, the proposed algorithm is able to change the mesh level-of-detail simply by controlling the distance of 2D sampling planes and the selective removal of wavelet coefficients. Experimental results show that the proposed algorithm is a simple and efficient simplification technique with less external distortion.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1179-1192
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• 2018

In order to detect the Antarctic Polar Front (PF) among the main fronts in the Southern Ocean, this study is based on the combinations of satellite-based sea surface temperature (SST) and height (SSH) observations. For accurate PF detection, we classified the signals as front or non-front grids based on the Bayesian decision theory from daily SST and SSH datasets, and then spatio-temporal synthesis has been performed to remove primary noises and to supplement geographical connectivity of the front grids. In addition, sea ice and coastal masking were employed in order to remove the noise that still remains even after performing the processes and morphology operations. Finally, we selected only the southernmost grids, which can be considered as fronts and determined as the monthly PF by a linear smoothing spline optimization method. The mean positions of PF in this study are very similar to those of the PFs reported by the previous studies, and it is likely to be well represents PF formation along the bottom topography known as one of the major influences of the PF maintenance. The seasonal variation in the positions of PF is high in the Ross Sea sector (${\sim}180^{\circ}W$), and Australia sector ($120^{\circ}E-140^{\circ}E$), and these variations are quite similar to the previous studies. Therefore, it is expected that the detection approach for the PF position applied in this study and the final composite have a value that can be used in related research to be carried out on the long term time-scale.

• Membrane Journal
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• v.33 no.6
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• pp.362-368
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• 2023

This research article explores the application of Polymer of Intrinsic Microporosity (PIM-1) as a cutting-edge material for CO₂ gas separation membranes in response to the escalating global concern over climate change and the imperative to reduce greenhouse gas emissions. The study delves into the synthesis, molecular weight control, and fabrication of PIM-1 membranes, providing comprehensive insights through various characterization techniques. The intrinsic microporosity of PIM-1, arising from its unique crosslinked and rigid structure, is harnessed for selective gas permeation, particularly of carbon dioxide. The article emphasizes the tunable chemical properties of PIM-1, allowing for customization and optimization of gas separation membranes. By controlling the molecular weight, higher molecular weight (H-PIM-1) membranes are demonstrated to exhibit superior CO₂ permeability and selectivity compared to lower molecular weight counterparts (L-PIM-1). The study's findings highlight the critical role of molecular weight in tailoring PIM-1 membrane properties, contributing to the advancement of next-generation membrane technologies for efficient and selective CO₂ capture-an essential step in addressing the pressing global challenge of climate change.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.4
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• pp.228-232
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• 2006

Purpose: electrophilic $^{18}F(T_{1/2}=110\;min)$ radionuclide in the form of $[^{18}F]F_2$ gas is of great significance for labeling radiopharmaceuticals for positron omission tomography (PET). However, its production In high yield and with high specific radioactivity is still a challenge to overcome several problems on targetry. The aim of the present study was to develop a method suitable for the routine production of $[^{18}F]F_2$ for the electrophilic substitution reaction. Materials and Methods: The target was designed water-cooled aluminum target chamber system with a conical bore shape. Production of the elemental fluorine was carried out via the $^{18}O(p,n)^{18}F$ reaction using a two-step irradiation protocol. In the first irradiation, the target filled with highly enriched $^{18}O_2$ was irradiated with protons for $^{18}F$ production, which were adsorbed on the inner surface of target body. In the second irradiation, the mixed gas ($1%[^{19}F]F_2/Ar$) was leaded into the target chamber, fellowing a short irradiation of proton for isotopic exchange between the carrier-fluorine and the radiofluorine absorbed in the target chamber. Optimization of production was performed as the function of irradiation time, the beam current and $^{18}O_2$ loading pressure. Results: Production runs was performed under the following optimum conditions: The 1st irradiation for the nuclear reaction (15.0 bar of 97% enriched $^{18}O_2$, 13.2 MeV protons, 30 ${\mu}A$, 60-90 min irradiation), the recovery of enriched oxygen via cryogenic pumping; The 2nd irradiation for the recovery of absorbed radiofluorine (12.0 bar of 1% $[^{19}F]fluorine/argon$ gas, 13.2 MeV protons, 30 ${\mu}A$, 20-30 min irradiation) the recovery of $[^{18}F]fluorine$ for synthesis. The yield of $[^{18}F]fluorine$ at EOB (end of bombardment) was achieved around $34{\pm}6.0$ GBq (n>10). Conclusion: The production of $^{18}F$ electrophilic agent via $^{18}O(p,n)^{18}F$ reaction was much under investigation. Especially, an aluminum gas target was very advantageous for routine production of $[^{18}F]fluorine$. These results suggest the possibility to use $[^{18}F]F_2$ gas as a electrophilic substitution agent.

• Microbiology and Biotechnology Letters
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• v.33 no.2
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• pp.117-122
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• 2005

Beijerinckia indica was cultured in mineral salts medium (MSM) medium with various carbon and nitrogen sources to improve the production yield of heteropolysaccharide-7 (PS-7). At high C/N ratio, the high concentration of PS-7 was produced until 40 h of the culture, whereas most of the glucose as a carbon source was used for the cell growth at low C/N ratio. However, at the high C/N ratio, PS-7 accumulation stopped at 48 h of the culture due to the increasing viscosity of the culture broth would inhibit the cell growth. Therefore, the optimized value of C/N ratio was 33.3 (20 g/L glucose, 7.5 mM $NH_{4}NO_3$) for the high production of PS-7. In the culture with various carbon sources, B. indica effectively used the hexoses or glucose-generating sugars for PS-7 formation. Especially, sucrose was the best carbon source for the high production of PS-7 (6.96 g/L) with a high viscosity (40772 cp). In the culture of B. indica with MSM medium containing 20 g/L glucose and 7.5 mM $NH_{4}NO_3$ in a 51 fermentor, the highest cell concentration was 2.5 g/L and the highest concentration of PS-7 was 7.5 g/L (35174 cp). The additional nitrogen sources of 7.5 mM $NH_{4}NO_3$, glutamine and glutamate at 12 h of the culture after exhaustion of a nitrogen source regulated the metabolism of carbon sources, therefore the nitrogen sources could control PS-7 synthesis.

• Applied Biological Chemistry
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• v.43 no.3
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• pp.218-224
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• 2000

The efforts were made to optimite ethanol extraction from persimmon leaf with the time of extraction$(1.5{\sim}2.5\;hrs)$, the temperature of extraction$(70{\sim}90^{\circ}C)$, and the concentration of ethanol$(0{\sim}40%)$ as three primary variables together with several functional characteristics of persimmon leaf as reaction variables. The conditions of extraction was best fitted by using response surface methodology through the center synthesis plan, and the optimal conditions of extraction were established. The contents of soluble solid and soluble tannin went up as the concentration of ethanol went up and the temperature of extraction went down, and the turbidity went down as the concentration of ethanol went down. Electron donation ability was hardly affected by the extraction temperature and had the tendency to go up as the concentration of ethanol went up. The inhibitory activity of xanthine oxidase(XOase) had the tendency to go up as both the concentration of ethanol and the temperature of extraction went up. The inhibitory activity of angiotensin converting enzyme(ACE), the significance of which still was not recognized, showed the maximum when the concentration of ethanol was 27%. In result, the optimal conditions of extraction was the extraction time of two hours, the extraction temperature of $75{\sim}81^{\circ}C$, and the ethanol concentration of $33{\sim}35%$.