• Journal of Microbiology and Biotechnology
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• v.29 no.7
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• pp.1083-1095
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• 2019

Butyrate is known to play a significant role in energy metabolism and regulating genomic activities that influence rumen nutrition utilization and function. Thus, this study investigated the effects of an isolated butyrate-producing bacteria, Clostridium saccharobutylicum, in rumen butyrate production, fermentation parameters and microbial population in Holstein-Friesian cow. An isolated butyrate-producing bacterium from the ruminal fluid of a Holstein-Friesian cow was identified and characterized as Clostridium saccharobutylicum RNAL841125 using 16S rRNA gene sequencing and phylogenetic analyses. The bacterium was evaluated on its effects as supplement on in vitro rumen fermentation and microbial population. Supplementation with $10^6CFU/ml$ Clostridium saccharobutylicum increased (p < 0.05) microbial crude protein, butyrate and total volatile fatty acids concentration but had no significant effect on $NH_3-N$ at 24 h incubation. Butyrate and total VFA concentrations were higher (p < 0.05) in supplementation with $10^6CFU/ml$ Clostridium saccharobutylicum compared with control, with no differences observed for total gas production, $NH_3-N$ and propionate concentration. However, as the inclusion rate (CFU/ml) of C. saccharobutylicum was increased, reduction of rumen fermentation values was observed. Furthermore, butyrate-producing bacteria and Fibrobacter succinogenes population in the rumen increased in response with supplementation of C. saccharobutylicum, while no differences in the population in total bacteria, protozoa and fungi were observed among treatments. Overall, our study suggests that supplementation with $10^6CFU/ml$ C. saccharobutylicum has the potential to improve ruminal fermentation through increased concentrations of butyrate and total volatile fatty acid, and enhanced population of butyrate-producing bacteria and cellulolytic bacteria F. succinogenes.

• Spatial Information Research
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• v.8 no.2
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• pp.257-274
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• 2000

Recently, natural environment is being forced by the quick increasing of population and industrialization, and especially, capacity and pollution of water resource is being come to the front. It needs to extract the accurate topological and hydrological parameters of watershed in order to manage water resource efficiently. But, these data are processed yet by manual work and simple operation in hydrological fields. In this paper, we presented algorithm that could extract topological any hydrological parameters over Sumjin watershed using GIS and RS and it gives the saving of data processing time and the confidency of data. The extraction procedure of topological characteristics and hydrological parameters is as below. First, watershed and stream are extracted by DEM and curve number is extracted throughout the overlay of landcov map and soil map. Also, we extracted surface parameters like watershed length and the slope of watershed length by Grid computation into watershed and stream. And we gave the method that could extract hydrologic parameters like Muskingum K and sub-basin lag time by executing computation into surface parameters and average SCS curve number being extracted.

• Korea journal of population studies
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• v.28 no.2
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• pp.1-32
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• 2005

The optimum population of a society or country can be defined as 'the population growth path that maximizes the welfare level of the society over the whole generations of both the present and the future, under the paths allowed by its endowments of production factors such as technology, capital and labor'. Thus, the optimum size or growth rate of population depends on: (i) the social welfare function, (ii) the production function, and (iii)demographic economic interrelationship which defines how the national income is disposed into consumption(birth and education of children included) and savings on the one hand and how the demographic and economic change induced thereby, in turn, affect production capacities on the other. The optimum population growth path can, then, be derived in the process of dynamic optimization of (i) under the constraints of (ii) and (iii), which will give us the optimum population growth rate defined as a function of parameters thereof. This paper estimates the optimum population growth rate of Korea by: specifying (i), (ii), and (iii) based on the recent development of economic theories, solving the dynamic optimization problem and inserting empirical estimates in Korea as the parametric values. The result shows that the optimum path of population growth in Korea is around TFR=1.81, which is affected most sensitively, in terms of the size of the partial elasticity around the optimum path, by the cost of children, share of capital income, consumption rate, time preference, population elasticity of utility function, etc. According to a survey implemented as a follow up study, there are quite a significant variations in the perceived cost of children, time preference rate, population elasticity of utility across different socio-economic classes in Korea, which implied that, compared to their counterparts, older generation and more highly educated classes prefer higher growth path for the population of Korea.

• Journal of Korean Society of Water and Wastewater
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• v.13 no.4
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• pp.45-53
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• 1999

The microbial organisms named "Pseudomonas sp. LK-14" were isolated from farm land and shallow river sediment, activated, augmented and identified; which were using 2,4-D (2,4-Dichlorophenoxyacetic acid) as a sole carbon source and energy source. 2,4-D removal efficiency of LK-14 with 2,4-D sole carbon source (reactor S) were higher than that of Activated Sludge with 2,4-D sole carbon source (reactor A). Dynamic bioligical reaction kinetic parameters (sole carbon source was 2,4-D) obtained from batch reactor experiments were ${\mu}_{max}$ $0.105hr^{-1}$, $K_{s,24D}$ 15.64mg/L, $K_{i,24D}$ $1.94h^{r-1}$, $Y_{24D}$ 0.39 for LK-14 and ${\mu}_{max}$ $0.008hr^{-1}$, $K_{s,24D}$ 26.95mg/L, $K_{i,24D}$ $1.75hr^{-1}$, $Y_{24D}$ 0.10 for Activated Sludge. Using these parameters, we could predict the behaviors of 2,4-D substrate utilized by LK-14 and Activated Sludge in batch reactors. The kinetic parameters are enable to predict the 2,4-D substrate and microbial population behavior entering into wastewater treatment plants by using unsteady states dynamic simulation modeling technique.

• Advances in environmental research
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• v.9 no.3
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• pp.151-160
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• 2020

Water quality demonstrates physical, chemical and biological characteristics of water. The quality of surface and groundwater is currently an important concern with population growth and industrialization. Over exploitation of water resources due to demand is causing the deterioration of surface water and ground water. Periodic water quality testing must be carried out to protect our water resources. The present research analyses the spatial variation of surface water and groundwater in and around the lakes of Hyderabad. Twenty-Seven lakes and their neighboring bore water samples are obtained for water quality monitoring. Samples are evaluated for specific physico-chemical parameters such as pH, Total Dissolved Solids (TDS), Cl, SO₄, Na, K, Ca, Mg, and Total Hardness (TH). The spatial variation of water quality parameters for the 27 lakes and groundwater were analysed. Correlation and multiple regression analysis were carried out to determine comparative study of lake and ground water. The study found that most of the lakes were polluted and this had an impact on surrounding ground water.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.91-97
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• 2009

It is undertaken systematization of results of satellite and ground observation parameters characterizing a current condition and climatic variability of two selected geographical areas. One of them covers territory of Azerbaijan and another covers a wide area of Caspian See region. Average values and mean square deviations of following values are investigated: outgoing long wave radiation during a day and night (in nebulosity and cloudless). absorbed within a day of the stream of a sunlight of the system in "a terrestrial surface-atmosphere". degree of a covering by clouds of the selected areas during a day and at night, ground temperature values of air. pressure and speed of a wind. Monthly average values of corresponding parameters create a basis of suggested investigations. It has been presented features of a time course of investigated parameters for each month and year in the whole due to the continuously observations since 1982-2000. The scientific problem consists that there are no existed models which authentically would be cover the main aspects of a realities specified changes: they are identified by economic activities. growth of the population and other features of development of a human society or internal fluctuations of biogeophysical/climatic system. Possibilities of predictability of biosphere and climate changes depend on available timely supervision. adequacy of construction of appropriate models. understanding of mechanisms of direct and feedback influences in such complicated systems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1029-1037
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• 2009

Recently, the technologies of mobile robots have been growing rapidly in the fields such as cleaning robot, explosive ordnance disposal robot, patrol robot, etc. However, the researches about the autonomous underwater robots have not been done so much, and they still remain at the low level of technology. This paper describes a model of 3-joint (4 links) fish robot type. Then we calculate the dynamic motion equation of this fish robot and use Singular Value Decomposition (SVD) method to reduce the divergence of fish robot's motion when it operates in the underwater environment. And also, we analysis response characteristic of fish robot according to the parameters of input torque function and compare characteristic of fish robot with 3 joint and fish robot with 2 joint. Next, fish robot's maximum velocity is optimized by using the combination of Hill Climbing Algorithm (HCA) and Genetic Algorithm (GA). HCA is used to generate the good initial population for GA and then use GA is used to find the optimal parameters set that give maximum propulsion power in order to make fish robot swim at the fastest velocity.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.697-704
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• 2007

This study proposes an integrated technique of Genetic Algorishim (GA) and Geographic Information System (GIS) for designing the water quality monitoring networks. To develop solution scheme of the integrated system, fitness functions are defined by the linear combination of five criteria which stand for the operation objectives of water quality monitoring stations. The criteria include representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness level is obtained through calculations of the fitness functions and input data from GIS. To find the most appropriate parameters for the problems, the sensitivity analysis is performed for four parameters such as number of generations, population sizes, probability of crossover, and probability of mutation. Using the parameters resulted from the sensitivity analysis, the developed system proposed 110 water quality monitoring stations in the Nakdong River. This study demonstrates that the integrated technique of GA and GIS can be utilized as a decision supporting tool in optimized design for a water quality monitoring network.

• ALGAE
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• v.22 no.3
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• pp.185-192
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• 2007

A study was carried out in nine fertilized fish ponds under three treatments (T-I, T-II and T-III) at Bangladesh Agricultural University, Mymensingh to see the bloom of euglenophytes with the intention of observing its impact on the growth of fish in culture condition. Some water quality parameters viz., temperature, dissolved oxygen, pH, PO4-P and NO3-N concentration and some biological parameters viz., phytoplankton population and growth of fish were monitored at fixed intervals. Euglenophytes showed a heavy bloom in late August in the ponds of T-II. The bloom was occurred by the genera, Euglena, Phacus and Trachelomonas of which Euglena was the most dominant genus. In relation of water quality parameters with euglenophytes bloom, it was hypothesized that euglenophytes prefers higher temperature and acidic environment with higher nutrient concentrations. Acidic environment and nutrient enrichment enhanced the bloom of euglenophytes which hampered the growth of other beneficial algal groups (chlorophytes and bacillariophytes) and fish. Due to heavy bloom, the fishes breathed with difficulty at the surface. The fishes in the heavy bloom ponds presented the weight values were lower than verified for those in the ponds where the bloom did not occur. Total production (calculated) of fish in different treatments ranged from 1355.89 to1760.63 kg ha–1 with significantly (p < 0.05) lowest in the ponds of T-II.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.