• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Journal of The Korean Society of Grassland and Forage Science
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• v.9 no.1
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• pp.34-42
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• 1989

This pot experiments were conducted to find out the optimal fertilization ratios of ${\Sigma}anion$ : ${\Sigma}cation$, ${\Sigma}A$/${\Sigma}C$, and the optimal application rates of total major nutrients in an orchardgrass/ladino clover mixed sward. The optimum ratios and concentrations in equivalent basis were computed by the Homes systematic variations technique. The results were summarized as follows; 1. The optimum fertilization ratios of ${\Sigma}A$ : ${\Sigma}C$ and the optimum application rates of total nutrients for the high yields by forage species in a mixed sward were obtained (Table 6 in detail); ${\Sigma}A$ : ${\Sigma}C$ = 2 : 1 at 80 and 320 meq/pot, and 3 : 2 at 560 and 800 meq for grass and grass plus legume, and ${\Sigma}A$ : ${\Sigma}C$ = 1 : 2 for legume in general. 2. The optimum application rates of total nutrients for the high yields of grass and grass plus kgum were increased by decreasing the ${\Sigma}A$/ ${\Sigma}C$: ratio, whereas these for legume showed a valible. range without significance. 3. The yields 01 grass and grass plus legume were generally increasing by increasing both the ${\Sigma}A$/ ${\Sigma}C$ ratio and total concentration, but they were significantly higher at the ${\Sigma}A$/ ${\Sigma}C$ = 1.273 than at the 2.125 under the high total ion concentration. The legume yields were proportional to ${\Sigma}C$ ratio and increased by increasing the total ion concentration under the condition of high ${\Sigma}C$ ratio. 4. The efficiencies of ${\Sigma}A$ and ${\Sigma}C$ in relation to the grass and grass plus legume yields were highest with the low ratios of each other and the low rates of total nutrients ${\Sigma}A$ efficiency m the legume yield tended to be similar to that of ${\Sigma}A$ in the grass yield noted above. The ${\Sigma}C$ efficiency in the legume yield, however, was generally proportional to the ${\Sigma}C$ ratio except at the low rate of 80 meqlpot. 5. The yields of grass plus legume, yield components and botanical compositions in a mixed sward were greatly influenced by the ${\Sigma}A$/${\Sigma}C$ ratios, the fertilization rates of total nutrients, and the interaction of ratio and rate noted above. These effects were generally different and opposite accading to grass and legume. In addition, the soil chemical properties and mineral contents of forages were partially influenced by these systematic variations.

• Food Science and Preservation
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• v.23 no.6
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• pp.804-810
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• 2016

This study aimed to compare the quality characteristics of developed rice Jochung (E) with those of commercial-rice Jochung (A, B, C, and D). The total soluble solid, reducing sugar, and dextrose equivalent of developed rice Jochung were $80^{\circ}Brix$, 44.53%, and 56.94%, respectively. The pH and titrable acidity were 6.25 and 0.19%, respectively. The color difference value (${\Delta}E$) of developed rice Jochung was 74.42, which was significantly lower than the other samples investigated. The light transmittance and total polyphenol contents of developed rice Jochung were 56.4%T and 108.23 mg GAE/100 g, respectively. The adhesiveness values of various commercial-rice Jochung products were 29.0~66.0 sec, while that of developed-rice Jochung was 61 sec, showing good textural properties for use in manufacturing Hangwa, a Korean traditional cookie. The electron-donating values of various rice Jochung were 20.4~50.3%, among which the developed-rice Jochung showed the highest value. The reducing powers of various rice Jochung products were 0.44~0.72, while that of the developed product was 0.72, which was significantly higher than the other values. Sensory evaluation revealed that the color scores of developed- and commercial-rice Jochung products were 6.70~6.80. Flavor scores of rice Jochung products ranged from 6.00 to 7.00. Taste and mouth feeling scores of developed-rice Jochung did not significantly differ from those of commercial Jochung products. Compared to commercial-rice Jochung products, developed-rice Jochung made with malt extract exhibited high polyphenols content. However, there were no significant differences in the overall acceptability scores between commercial-rice Jochung products and the developed product. The developed-rice Jochung analyzed in this study may be useful as a traditional sweetener for various Hangwa products as a substitute for corn syrup or Jochung.

• Korean Journal of Food Science and Technology
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• v.50 no.1
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• pp.117-121
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• 2018

Puffing process modifies the chemical and physical properties of the grains. In this study, oats were puffed by subjecting them to pressure of 1.0 and 1.2 MPa, following which the bioactive constituents and antioxidant activities in the oat extracts were investigated. The polyphenol content in puffed oat extracts increased in a pressure-dependent manner (109 and 157 mg gallic acid equivalent/100 g at 1.0 and 1.2 MPa, respectively). In addition, gallic acid was synthesized after puffing ($518{\mu}g/g$ of extract at 1.0 MPa) and was the most abundant phenolic acid in puffed oats. The antioxidant activities, which were determined by 1, 1-diphenyl-2-picrylhydrazyl (DPPH) and 2, 2-azino-bis-3-ethylbenzothiazoline-6-sulphonic acid (ABTS) radical scavenging activities, were improved in oat extracts after puffing (+245 and +184% at 1.2 MPa, respectively). In conclusion, puffing process of oats increased the extractability of polyphenols, including gallic acid, which positively affected its antioxidant activities. These results will provide useful information when using puffed oats for food production.

• 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.

• Journal of Life Science
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• v.29 no.5
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• pp.596-606
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• 2019

The study investigated the physiochemical properties and the antioxidant and anti-inflammatory activities of the sea tangle (Saccharina japonica) in a water extract before (STWE) and after (STFL) fermentation with Lactobacillus brevis. The pH values of STWE and STFL were 6.18 and 4.16, and the sugar contents were $8.50^{\circ}Brix$ and $7.40^{\circ}Brix$, respectively. The main free amino acids of STWE and STFL were glutamic acid, aspartic acid, and alanine, and the ${\gamma}$-amino butyric acid (GABA) content was increased by fermentation. The total polyphenol contents of STWE and STFL were 498.29 and 615.77 mg gallic acid equivalent (GAE)/ml, respectively. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activities of STWE and STFL were markedly increased in a dose-dependent manner, and revealed about 89.89% and 96.94% activities, respectively, at 10% concentration (p<0.05). The superoxide dismutase (SOD) activities of STWE and STFL were also markedly increased in a dose-dependent manner, and the activity of STFL was significantly increased when compared with STWE (p<0.05). The anti-inflammatory activity was examined in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. STWE and STFL decreased the production of reactive oxygen species (ROS), which had levels of about 189.90% and 174.69% at 1% concentration, respectively (p<0.05). The contents of pro-inflammatory cytokines, such as tumor necrosis factor-alpha ($TNF-{\alpha}$) and interleukin-6 (IL-6), were decreased more by addition of STFL than by addition of STWE. The STWE and STFL showed high antioxidant and anti-inflammatory activity, and these activities were increased by fermentation. Therefore, sea tangle extracts can be used as functional food materials.